Influencing this question are Shannon Vallor’s concept of polypotency and the connected concept of stabilities from Don Ihde. These terms are near-synonyms and both point to the aspect of technology that allows it to have many different uses and outcomes even though the technology was designed only in specific ways1. These concepts force me to think about the polypotencies/stabilities present in LLMs, and if there is a possibility present that enables me to flourish.

Every day for the past few weeks, I’ve been working with LLMs to see if I could do just that: bend the technology toward some of my values. I wanted to make sure that my AI use didn’t diminish my curiosity, intellectual humility, and my intellectual integrity2. Even more, I wanted to see if I could grow in these values while using LLMs. After my initial experiments, I’m convinced that even though LLMs might not share my epistemic values, I can still alter their interactions in order to have quality interactions that improve my thinking and my writing. This is what I mean by principled use, learning to incorporate one’s values into their interaction with technology.

The default use of LLMs, the way that I see many non-technical people use them, is to simply ask it a question and then use the AI’s response. They might ask about how something works, or they might ask for an essay on a topic using some simple text as input. These default uses violate my values. In fact, they actively undermine them.

By copy-pasting AI work, I’m actively working against every one of my values3. Copy-pasting work doesn’t help me stay honest to myself about what I know, since it is presenting work as something I know. It also doesn’t keep me grounded in alternative perspectives or help me acknowledge the gaps of my own thinking. This is how LLMs flatten worlds of knowledge; by commoditizing outputs over the actual parts of the experience that lead to change and growth. With the default use being inadequate, we need to move toward principled use, then.

What I noticed first in my experiment is that I already had a skill that would prove critical in the pursuit of principled use of AI: metacognition. Metacognition is thinking about thinking and the understanding of the patterns behind that thinking. If you want to have better interactions with AI you have to be aware of what your interaction goal is, what are the pitfalls of the system, what are your pitfalls as a human-being, and be keenly aware if any of those things are drifting and how. LLMs, especially in extended interactions, have a tendency to drift. As an example, I was using Claude Desktop to think about an AI editing tool I’m developing, and as I was engaging with the system about how paragraph edits should work, the system suddenly, and inexplicably shifted to article-wide edits. Article-wide edits aren’t as important as the paragraph-by-paragraph feature that I was working on, yet the system drifted anyway. Instead, having awareness of what my goal was (to make sure I could understand how I wanted the system to work, and its implications) stopped the drift from being a problem. I simply re-prompted and carried on with the work.

As I applied what I was learning about my LLM interaction preferences, I settled on the term Constraint Engineering4 for how I was approaching this work. The goal of constraint engineering is to use system prompts and prompts more generally to constrain the kinds of behavior you don’t want while also describing the behavior you do want. Explicit in the idea of constraint engineering is metacognition, since to constrain an LLM requires constant evaluation of the interaction, and how the LLM interaction influences one’s thoughts. In my case I was engineering constraints for the system so that principled use was the default. You see examples of constraint engineering all the time in how people prompt; it’s usually in all caps. One of my favorite joke attempts at constraint engineering is “DO NOT HALLUCINATE”. But, prompts for constraint engineering don’t have to be in all caps, they can be instructions that guide behavior: “don’t provide me the answer, but engage in a dialog that helps me understand X topic better”. This is the system equivalent of Odysseus tying himself to the mast to hear the sirens, I admit, but it’s been an effective approach.

Here are some examples of how I constrain my interactions and the thought processes behind them:

1. “Critical engagement: push back on logical gaps, force precision in reasoning.”

   I’d rather deal with an AI that seeks to poke holes in my argument than one that tries to present things as correct when they’re not. Even if the AI ends up highlighting a logical gap that doesn’t exist, it makes me dive deeper into understanding what I’m saying.

2. “Work WITH me through problems, DON’T generate solutions for me”

   The goal in my interactions with AI is to see if I can improve my ability to think clearly and more accurately communicate these abstract ideas that I’m working with. When I have a problem that I present to the LLM, it’s not for it to solve my problem, it’s for me to solve my problem by having constructed questions, responses, etc. that give me more to think about.

3. ”Act as a Socratic tutor”

   This is more of the above. A Socratic tutor doesn’t so much give an answer but help the person being tutored by constructing questions around their current understanding. I got this idea from reading the book “Brave New Words” by Salman Khan, Founder of Khan Academy. The idea is not to be given answers as much as scaffolding out from current understanding to what you want to understand.

A type of feature in LLM systems that makes constraint engineering, and therefore principled use, more effective, is any feature which allows personal preferences across the system. With personal preferences5, I can constrain my interactions from the preferences level instead of per prompt. Effectively, this means that I handle the bulk of the constraint setting at the preferences level, by using the prompts above (and more), and then I only need to fine-tune my constraints per prompt.

The constraint engineering approach is still limited. I still run into problems where it seems like the LLM ignores my preferences and still offers me up an answer. This is more frustrating than a roadblock. It means I have to be on my toes cognitively to make sure I’m having the kind of interactions I want, even after trying to impose significant constraints at a higher level.

That being said, my initial forays into figuring out how to best constrain LLMs in ways that help me align to my values has been successful. I’m having many more interactions with the LLM where I am augmenting my capacity, and learning new skills as I attempt to do so. I think what this kind of technology needs is many people working with it to try and bend it to their values. It’s not going to be successful for everyone, and that’s the point. We need to see polypotencies, the stabilities, that can be expressed with AI technology and that only happens when we have the will to move the technology toward some other end.

The HBR article defined workslop as material that looks right but lacks substance, and this costs companies an invisible tax of $186 per month per person in correction time and ultimately damages how employees think of their coworkers. People who do submit workslop as work are seen as less creative, capable, reliable, trustworthy, and intelligent by their colleagues. The article makes a distinction between “pilots” (high agency and high optimism) and “passengers” (low agency and low optimism, and the perpetrators of workslop) as a way of classifying from whom quality AI-content can come.

The HBR article was done in collaboration with BetterUp, who created a separate report titled “Winning in the Age of AI” (sorry, this is the best link that does get you to use your email to sign up for something), which isn’t about AI really. It’s about human performance. According to the report, human performance across sectors and across the three different kinds of performance (basic performance, collaborative performance, and adaptive performance), has been decreasing since 2019. Basic performance relies on focus as it’s about task execution, collaborative performance relies on teamwork as its about alignment and championing, and adaptive performance comprises creativity, connectivity, and cognitive agility. Each of these kinds of performance have been decreasing since 2019, before AI and before COVID. This has coincided with a decrease in motivation, optimism, and agency. A quote near the end of the report helps quite a bit “We can’t expect adaptive performance if people don’t believe their efforts matter”.

Why do people submit “workslop” as work? Is it because they’re lazy? That might be part of it, but the more likely answer is that workers are alienated increasingly from work that matters. While the BetterUp data doesn’t explicitly answer this, there is a telling pattern.

The issue is the application of industrial measurements of productivity to knowledge work. Metrics designed for factories, for assembly lines, focusing on the number of widgets churned, have successfully been grafted to knowledge work. The difference between industrial work and knowledge work is that the latter work is inherently about insight, connection, and adaptation. With the grafted industrial model, the metric for knowledge work production becomes busyness (PowerPoint slides, reports that no one actually needs) over results. When success, especially in knowledge work, is measured by visible busyness and output volume rather than meaningful outcomes, workers will optimize for appearance. They become disconnected from work that matters because mattering isn’t being measured.

Workslop is the logical endpoint of this shift. Why invest cognitive effort in work that’s evaluated by whether it looks complete rather than whether it accomplishes anything? What better way to be done with the task than to offload it to AI? The same dynamic produces burnout, where sustained effort directed at meaningless performance metrics rather than meaningful outcomes depletes workers while generating nothing of value. This systemic issue then leads to others having to correct or otherwise manage poorly generated work, however it is not the person at fault, but the workplace that makes meaningful effort difficult to access.

To the credit of HBR and BetterUp, they try to get to the core of this. Both of them use leadership as a means to overcome this issue. With HBR, it’s the leader’s responsibility to model deliberate AI adoption. In the BetterUp report, it’s up to leaders to “…express confidence in their employee’s abilities to manage AI” so that they “cultivate a stronger sense of agency”. Both of these miss the mark. They treat employees as if they’re a simple mechanism that will run properly if only a leader will do things the right way, in the right sequence.

I’m left with unsettled questions: What would it look like for mattering to be defined by workers, rather than defined from above? What if employees chose what to work on instead of executing work defined from above? What if employees saw actual outcomes, like user-impact, or problem resolution, rather than optimizing for KPIs? These are the questions we avoid by arguing about AI tools, or leadership instead of work structures.

It’s The Strokes’ debut album, Is This It. I bought it from someone selling tapes in Indonesia on Discogs. I’ve listened to Is This It many times over my decade or two as a fan of The Strokes, but there’s something different about this physical tape from the version I’ve listened to many times. This is the first international release of the album which means the third to last song off the album isn’t When It Started. It’s instead a song called New York City Cops. Why were these releases different?

Julian Casablancas and crew wrote New York City Cops in reaction to plainclothes police officers in New York killing Amadou Diallo in 1999. Is This It was released first in Australia in July of 2001, but the U.S. release of the album was delayed from September to October, with the song New York City Cops not appearing on the tracklist. The song is naturally critical of New York City cops, but considering 23 cops died responding to the 9/11 attacks, it’s no surprise that the song was taken off the tracklist—it would have made for bad publicity1. (This caused people to think of the band as apolitical despite the singer Julian Casablancas’ political leanings, and this took him a while to recover from.)

I love that I can have this bit of music history with me. In digital media, history doesn’t matter. If the same thing were to happen today, the album would be quickly taken down and re-uploaded with the offending song removed or substituted. That data would then be unreachable for regular people; history manipulated, controlled because it’s easy to do so. It is harder to erase the history held within physical things.

This isn’t to say that physical media is perfect, but that history is preserved locally with physical things. No matter how much someone might want to change the tracklist to Is This It now, I will always be able to experience the album as it is on my tape. Looking at the state of affairs in my national politics, where sites that are supposed to be matters of public record are taken down at will, I’m finding this capacity for physical media to preserve history interesting2.

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It’s hard for me to imagine my life without music in it. Music making and listening have been vital for shaping my identity. Yet, I only recently realized that I’ve become much less deliberate in how I listen to music. Spotify and YouTube, while giving me access to the newest albums and songs whenever I want, have also shaped me into a a passive consumer what I was supposed to love. This is why I’ve been switching some of my music listening to cassettes, CDs and vinyl. I’m aware of the pretension when I say this—the quasi-superior stance that this can be motivated from—but I assure you that’s not my argument. I’m not interested in the quality debate between these media. I don’t listen to them because I think they sound better, in fact, some of my tapes sound rough. I listen to them because it’s the only way I’ve found to have the relationship I want with music again.

When I’m on the internet, or adjacent to a device that is always connected to the internet, I have a miserable time staying on task. My focus lasts maybe a minute or two before it gets hijacked. Even when writing this essay, I’ve spent maybe a minute or two writing but then got sucked into something irrelevant like emails or LinkedIn. I’m prone to distraction just by nature, and if you add on top of this the infinite distractions of the internet and it’s lucky that I get any writing done.

In the same vein, music for me has become just a part of a milieu of distraction. When I listen to music, it sits in the background while I try to write, while I check email, while I respond to that one message that’s been sitting in my inbox. But music used to play a significant role in my life. I used to listen for no other reason than to enjoy a song or an album.

In my early twenties, I was more deliberate about listening to music. I used dedicate time solely to listening to music. I’d pick up a vinyl, place it in the player, and let the music fill my dorm room as I sat there focusing on the music. I enjoyed these times thoroughly and there are many albums from this era that I’m still fond of. I distinctly remember sharing the Daft Punk album Random Access Memories with my then-girlfriend-now-wife. We just listened to the album, sitting up against the bed in my little dorm room. We are now amassing a collection of physical music between CDs, vinyl, and cassettes, a testament to both of our love of music and the bond that we share with it.

This immediately brings to mind how important it is to share music with others. , a good friend, colleague, and one of my main creative collaborators, recommended I listen to an album called Dancing While Falling by the artist Quantic. I spent a week listening to that album, and I coupled my listening with a video essay about the roots of disco and electronic dance music. I don’t want to exaggerate, but that experience fundamentally altered what I think my place is in making music. My point is, however, that sharing music, or any kind of art, is deeply personal and heartfelt. The recommender is offering up a slice of something meaningful to themselves so that you might share in that.

Daniel has also been writing about been writing lately about the ways we relate to one another (LINK, and if you don’t already follow him on Substack, you should). His work reminded me that recommendation algorithms have largely replaced the function recommending people things at all. These recommendation algorithms are so pervasive that it’s likely the most recent song you’ve listened to, or the most recent video you’ve watch, was mediated through an algorithm. This has lead to a fundamental change in how we relate to each other. While I can appreciate the music I’ve found because of these algorithms, I also mourn for the increasing inability for us to relate to each other through sharing.

I started this movement toward less distracting media not impelled by a sense of nostalgia for the technology. I wanted to not be so distracted, and that quickly changed to wanting to have a relationship with music again. But the nostalgia has crept in anyways. It’s not for the technology per se, but nostalgia for the ways I used to relate with people. This nostalgia keeps me anchored to something positive: technology can still mediate heartfelt encounters between people, even through there are increasingly few examples.

Another memory. I was maybe sixteen or seventeen and my dad and I were driving someplace. On the way to grab groceries or something. And he turns on some Motown. My dad’s a big fan of Motown, and I, in turn, became a fan of Motown. During this drive, we weren’t just passively listening to the song though. He was asking me to notice something. The guitar? No. The background vocalist? No. It was something that the bass player was doing within that arrangement, and he wanted me to notice it like he was. He wanted to share with me his musical experiences by helping me notice something that he had. He invited me to participate in his listening process. I’ve had similar experiences since with friends, but that singular experience of my dad inviting me to deeper listening still sits with me today.

I’m nostalgic for these moments and they’re happening less and less frequently as music becomes more disposable. Music now isn’t something that is deliberately listened to, it’s something in service of other things like working or studying. As someone who also makes music, it makes me question why I even make music in the first place.

With music as disposable as it is societally, and now with AI generated music, we’ve reached a point where it feels like it doesn’t matter if I can make my own. And this is a shame because I think we’ve forgotten the important part. Effort allows us to make art and therefore to connect with others through the creation and appreciation of art. It reminds me of Derek Muller’s—the science communicator who runs the YouTube channel Veritasium—recent talk on YouTube on AI and learning. In the video Muller makes the argument that effort is what makes for quality learning, something which AI can disincentivize. Extending this argument, what makes quality experiences are the effort we put into them, and with AI removing the need for effort in more and more things there is a sincere risk that we lose out on many quality experience because we yielded them to AI.

So it’s not commercial success that I’m after in making music, and it’s not for being a lauded musical intellectual that I listen to it deeply and deliberately. I don’t create for prospects of fame. I make music to relate to others. I write so that others maybe will see some aspect of themselves, or at least see an aspect of myself. And that insight might spark a conversation, a discussion, deeper relation.

Technology has given me access to some of the coolest music I would ever be able to listen to. I have the entire world of music at my finger tips, but that comes with its downsides which are also enabled by technology. I’m willing to devolve my music listening tech in order to have a relationship with music that I want to have. But that process is deliberate and measured and based on the understanding that music is a high priority for me.

I’ve been on many sides of this equation, listener and producer of music. I think about the AI music that’s Spotify is starting to hock and how impersonal that feels and I lose spirit. It feels like we’ve missed the plot in a lot of our technological making and I’m left exasperated. I try to stay optimistic, knowing that there are a myriad possibilities still unfolding which give us access to more positive experiences. But still, if I’m to assume that everyone is doing the best they can in the technology we make, I’m left with a simple question: is this it?

I used to believe in the idea of making things user-friendly. I could reference specific instances proving the utility of user-friendliness in the development of systems—places like Three Mile Island, specific mechanisms like the aircraft controls of the B-17 bomber during WWII, “small” aesthetic changes like changing the U.S. insignia on military aircraft. I had a noble quest of finding un-navigable applications, dismantling them, and providing ways for it to be more streamlined. Then, doubt crept in. Two things separated in time by years changed how I thought about user-friendliness: a person and a book.

I used to work with a prominent User Experience (UX) designer with significant acclaim and background. This person was there at the inception of the discipline of UX. When they spoke about design though, they kept revealing an uncaring attitude about the user. They couched their uncaring attitude in UX “truisms” such as “the user doesn’t know what they want but they know what the problem is”. They were fundamentally problem-centric as a person. They wanted to understand and solve problems using design, so much so that I think they lost sight of who they were doing it for. It reflected in how they told stories about the problems they solved—denigrating people, glorifying problems. I always had the sense that if they could, they’d abstract people away and just solve problems. And this was unacceptable to me.

A few years later, I read Life in Code by Ellen Ullman, a history of Ullman’s entire career in and around software development. In one section, she writes about how programmers’ move to make software more user-friendly tends toward treating the user as if they were dumb. This tendency toward user-friendliness-as-idiot-proof necessitates cloaking the complicated internals of a system—non-coders are too dumb to understand anyway, so the sentiment goes. Interestingly, this ultimately turned around on software developers as people developed as more specialized, such as programming languages that don’t let the programmer easily manipulate a computer’s memory. Even though Ullman levied this critique to software development, I realized I had been doing the same thing. I’d been solving problems people had while holding a bias that those who have the problem were dumb, and so, my interventions reflected that. I was so encouraged to design for the “lowest common denominator” that I didn’t even see what was happening. Ullman’s book and encounters with a more senior designer turned have turned everything I know about design on its head.

I suggest we replace the idea of “user-friendliness”. Software developers and designers—the entire technological enterprise, really—has avoided significant mishaps under the banner of user-friendliness, but it also places the user in the position where they cannot learn from the system. It places the user as a dumb thing the person developing and/or designing technology must work around. Users are inert dumb things to the technologist. We need now more than ever to provide ways to give users access to the knowledge that gets abstracted away for the sake of a clean interface. We need purposeful, human-centered complexity and dynamic systems that can unveil themselves.

What I’m proposing is similar to the advent of positive psychology. Positive psychology was a response to a narrow lens on mental well-being. Before positive psychology, the goal of the psychiatrist was to remove or minimize mental illness, with wellness at this time being frame as the absence of mental illness. Martin Seligman, pioneered the field of positive psychology by researching happiness and mental flourishing. Thus extending what it means to be mentally well. Similar to this, then, I’m suggesting that the paradigm of user-friendly has given us a perspective which works, but doesn’t give us systems in which promote increasing knowledge and competence of the user.

You’ve seen examples of this in software—even if you haven’t noticed it—but they’re often not fully explored. Any software you’ve used that has both a “simplified view” and a “standard view” exemplifies the positive of how we can develop dynamic systems while still being couched in the language of user-friendly. Some users are “simple,” designers and developers seem to say, while providing a mildly scalable system that fits changing interest and knowledge of the system.

We can do better. We must do better because a better future for all of us is predicated on the knowledge that the public has and has access to. Knowing first hand that clean interfaces disguise a world of complexity, I know that we need the general public, to know how these technologies work; how to reason and conjecture about them. There are other ways to accomplish this goal, but I see it as the system’s—and therefore the designers and developers behind it—responsibility to impart knowledge of its internals to the users, and to give them an adequate ramp to achieve complete knowledge of its systems.

An example is in order. The interfaces generative AI chatbots employ are generally simple: a textbox to write a prompt in, maybe a sidebar with your “conversational history”, maybe a few settings to toggle about which model to use. A user types their prompt into the textbox and a world of complexity gets executed behind the scenes without me having to know what a generative pre-trained transformer (GPT) is, without needing to grapple with the chorus of models that are often now working in tandem to answer my prompt, without having to know that the data the model is trained on will bias results, ultimately without ever understanding how I got the answer that I got. A system designed with human-centered complexity in mind would do things differently. As a dynamic system, an HCC system would have a series of views that enable the user access to ever more of the internals of the system. There would be a beginners view that would look like what we have for ChatGPT, and based on user’s interest—and ultimately the users’ agency—unveil more options to interface with the model such a temperature slider that affects randomness of the output and access to fine tune the model in the system (along with understanding what exactly it means to fine turn a model). The system would dynamically respond to the system and the user would use their own agency to explore and opt-into ever more complex features as they have the appetite.

I’m calling for a paradigm shift in how we think about user interfaces and experiences. Instead of assuming that every user needs everything simplified perfectly, we should focus on designing systems that encourage exploration and learning. This means embedding educational elements and transparency into our designs so that users can gradually uncover and understand the complexities of the technology. Such systems would not only cater to the immediate needs of novice users but also provide a pathway for them to become experts if they choose. Ultimately, I want human-centered complexity to lead to a more informed and engaged user base who is capable of using technology not just to complete tasks, but to innovate and solve increasingly complex problems themselves.

This isn’t a ChatGPT-is-bad post though. Instead, I’m curious about the ways I’ve surrendered my own confidence and competence to digital technology. I realize now that it doesn’t matter how knowledgeable I might be, or how capable I am at thinking critically about technology, many of the digital tools I use undermine my confidence. What is it about technology that enables this to happen?

Technological undermining happens in micro-moments. I think that I know that we went to the moon in 1969, to use another example, but with a quick Google search that I can know definitively. This certainty means that I will go with the Googled answer rather than my own knowledge. At this point, it doesn’t even matter if I was right, what manners is that my smartphone’s access to the internet cultivated enough doubt that I felt compelled to indulge in the sure answer. This is what I mean by a micro-moment. Another example of a micro-moment of technological undermining happened in a recent conversation. I’ve been reading about Gnosticism, and I told one of my friends that I’d been reading about it. When he asked me what Gnosticism was, instead of relying on my own knowledge that I was gaining on the topic, I went to Wikipedia. This happened in a just a few seconds—this is what I mean by a micro-moment. This isn’t some grand conspiracy to undermine human intellect, at least I like to be hopeful in that regard, but there is something in the mechanism of digital technologies that enable this to happen.

Since people like to talk about it so much, let’s talk about the impacts of the invention of the calculator. It’s popular now, with the advent of generative AI, to compare it to the calculator. The argument goes something like this: the invention of the calculator proved that basic arithmetic wasn’t a skill that we all needed, and so the invention of the calculator was a net positive. This is a fine argument when it’s clear what skill is being replaced. With the invention of the calculator, knowing exactly that basic arithmetic was going to be a skill people lost was calculable. It was understandable what we would lose it. This though, is categorically different with generative AI; it’s not clear right now what we have the chance of losing. If we do a one-for-one swap of the argument that people make with the calculator, then we lose out on: our ability to write, to reason, and overall, to communicate. But it feels like it could be more than that too.

While writing this essay, I encountered a scientific paper that’s pursuing exactly this point of cognitive offloading. Michael Gerlich, the head of the Center for Strategic Corporate Foresight and Sustainability, published a paper just a few weeks ago, which investigated our propensity of cognitive offloading and this current iteration of AI tools. Using a mixed-methods approach, both interviewing 665 participants, and quantitative correlation analysis Gerlich found that cognitive offloading to AI negatively impacts our critical thinking skills:

Our research demonstrates a significant negative correlation between the frequent use of AI tools and critical thinking abilities, mediated by the phenomenon of cognitive offloading. This suggests that while AI tools offer undeniable benefits in terms of efficiency and accessibility, they may inadvertently diminish users’ engagement in deep, reflective thinking processes.

This relies on self-reported data, and the fact that there were interviews with individuals means Gerlich could have a sampling bias—both of which Gerlich admits himself—but the research at minimum starts a conversation about how we must critically engage with these technologies.

I’d like to think of this phenomena less as cognitive offloading and more as a function swap. Cognitive offloading is a pretty natural process of doing something to minimize cognitive processing—such writing something down. What I’m calling “function swap” is the replacement of a cognitive function for a technological function for the reason that the technology does it better. If there is a function that I cognitively have rehearsed many times in my life, but then there is a technology that does it better, faster, and more reliably, then what’s going to happen overtime, and this is just conjecture, is that my trust in myself is going to erode as I interact with the digital technology that does that function better which will prompt me fully substituting that function.

Going back to the master’s applied project example, it’s clear that the functions that were being swapped were my own ability to creatively and critically think through the implementation of feedback. Now, my question becomes “do I want to lose this function”? As in do I want to continue to rely on ChatGPT for this function of thinking through implementing feedback? My answer is no. So, I have to do better.

To be better, I have to stop relying on the tool. I have to, through the process of struggling, through the process of learning—learning requires struggle, get better at doing this kind of work. And that requires that I don’t rely on ChatGPT for this function any longer.

Ultimately, I’m worried about my propensity to fall into harmful cognitive shortcuts. Given the path of least resistance, I will take it. And that act of doing the shortest route to solve my problem, impedes my betterment as a person. And so I’m not saying that people who desire to use generative AI as a tool are necessarily wrong. However, if you relegate a function to generative AI you better prepare yourself to be without that cognitive function. To outsource a skill, and at this point I’m not even talking about with digital technology, is to risk its atrophy internally. In the book The Fifth Discipline Peter Senge talks about a feedback loop working between HR consultants, personnel problems in an organization, and internal managers’ capabilities. In it, the company becomes increasingly more reliant on HR experts rather than their internal managers. Senge calls this a “shifting the burden structure” where “well-intended solutions make matters worse in the long term”. In the case of the company, they employed HR experts to address a personnel problem, but gradually shifted the burden away from expecting internal management handling those problems.

In this same regard, only use these tools for what you are prepared to lose; if it matters to you, stay as true as you can to it.

I thought software would be enough. But, I still yearned for a tactile feeling in what I made—yearned for the wisdom of my hands. When I make things with my hands, it’s as if I’m tapping into another sense in my mind. This is important to me because I have aphantasia, I have no ability to visualize things in my head. I can imagine sounds, sensations, and other imaginary sensory experiences but I can’t visualize. Making things with my hands feels to be a replacement for this lack of faculty. I wrote a poem about this experience:

My mind cannot see
the shape
color
event the outline
of any object

My soul is blind
but it hears well
it smells
it feels
and through this,
I know my soul lives

My hands know traces,
moves made in the past;
fists
palms
tools used;
my hands know to move
before my mind can even see it.

So I took up bookbinding again to reclaim a kind of knowing which feels ever more important to me. Books and paper call to me. Since the last time I posted on here, I ‘ve answered this call to paper to the point that I drafted this essay on paper. With paper I’m home; my hands know the feeling well.

When I’m making books, I wonder about the first books ever made. The The first bound book s were made in India around 100 BCE. Religious scholars copied religious sutras on palm leaves, dried them, and split them down the middle and joined them together. Before knowing this though, I thought of the simple act of folding a piece of paper in half. The form of the page, when folded, jumps from 2D to 3D and begs to be proceeded through: cover, page, page, back cover2. A series of words and/or images then populates this sequence to make a book.

To experience what I’m talking about, take a sheet of paper and fold it in half. Seriously, give it a shot, grab any sheet of paper nearby and fold it in half. We can make it a book about yourself, so once you fold it in half, go ahead and write your name on the front. On each page3, write a single word that describes yourself, and in attempting this you immediately encounter the form: one word must precede another. One word must come first and only then the next. One page sets context for the next.

This makes me think about Large Language Models (LLMs) and other text-based Generative AI (GenAI). They are spoken about as stochastic parrots, but humans must too put words in a sequence when we write. One word must have some logical connection to another, and as you write each word in a sentence, the sum total of options becomes progressively diminished. Yet, we still have a great deal of choice in that sequence. This means that each sentence we make is imbued with artisanal possibility. Each sentence, like a craft beer, a handmade journal, a landscape is ours to make and enjoy. We surrender this possibility when we use GenAI to write. We lessen our agency to craft to give more agency to sophisticated algorithms. And it burdens me with worry that most don’t seem to care.

To be clear, I’m not against GenAI. I benefit from mass produced goods constantly: lamps, pencils, desks, computers, papers, beds, the myriad things. But when things matter, people tend toward the bespoke. A journal you buy for your new journaling habit at the start of this year will feel more important when the book is handmade; a card feels more meaningful when your kids make it. Let’s not surrender that agency for the ease of all things. At least where its important to you, make it more like a craft.

Making changes how you think. When I honor the sequential form of the book, it changes my words; changes my thoughts.

I recently finished a book called Craftfulness by Rosemary Davidson and Arzu Tahsin, and it points to fertile ground in this conversation. Davidson and Tahsin approach craft not as professional artisans but as hobbyists, and from this perspective we come to understand craft as a benefit to our mental and physical health. Craft brings mindfulness, peak experience, mental clarity, and a number of other benefits. When I’m making a book, I immediately now what they are arguing for—my focus turns to paper grain, folding, cutting, sewing, and gluing. I’m full of mind of the book and paper art, and they in turn present themselves to me.

Since graduating with my master’s degree, I’ve felt unable to do serious research. I don’t know the origin of the feeling, but I’ve not been drawn to continue the research I’ve wanted to do. Instead, I’ve been drawn to art and craft. These pursuits can’t tell me what meaningful complexity might be in a system—my next research topic—but I’m wondering if they are an example. If they are an example, then when I’m rested and the urge for research again arises, I will be ready in mind and with hands full of wisdom.

The 1987 film RoboCop is not the movie I expected. I expected a typical action movie, the kind where the plot is in service to the action. I love these kinds of films and expected RoboCop to conform to the genre. However, I got an anti-corporate critique that showed me the underlying mechanisms that drive technological solutions.

I was born after RoboCop’s debut in the late 80s. I only knew of the world that RoboCop was responding to through vague references to Detroit being a place to avoid, and how crime was at the time. It felt more like a bygone time that people were responding to rather than something relatively recent, something that still impacts the black community and the region to this day. RoboCop responds to the issues of crime in America and critiques the solutionist perspective that captures our everyday sentiment.

Lyseology

I’m glad I watched RoboCop near the same time I read Robert Braun’s paper “Radical Reflexivity, Experimental Ontology, and RRI”. Without it, I would not have as precise of a term to explain what RoboCop is critiquing, and so I treat it as a great fortune that the paper was published just a week or two before I watched RoboCop. RoboCop is a film that critiques the way technology corporations, and by extension, the larger science enterprise convinces “policymakers and the general public that the present possesses some form of lack that should be addressed with a new technology brought to life and offered as a solution”. I pulled this quote directly from Braun’s article in his creation of the word Lyseology (pronounced Lee-See-ology). In other words, lyseology refers to how the larger science and technology enterprise convinces us that the only way to solve problems is through a technological fix, and through that convincing becomes the only way we can see, blinding us to all other ways of seeing the world.

RoboCop critiques our lyseologic perspective not through grandstanding moral narratives, but through satire far more subtle than I’m used to.

RoboCop

The Omni Consumer Products (OCP) building towers in Detroit. The CEO of OCP discusses his vision of building Detroit anew into Delta City and sees privatization as the path forward to accomplish this. A privatized police force, to address the rampant crime, is the path ahead to achieve this.

This situation is exactly the lyseologic view, where corporate entities see a lack—the poor crime response in Detroit—and seek to address it with a technological fix. The logic that introduces robots into police departments, because the rate of crime outpaced the ability of the policy to respond, makes sense. This common-sense feeling shows how significant lyseology as a worldview has seeped into our being.

Alex Murphy is killed on the job, and based on the contract of the Detroit Police Department, Alex Murphy is pulled into OCP’s RoboCop program where he becomes the first Robocop. In becoming RoboCop, Murphy is stripped of his memories and all his human parts except the lower part of his face (for some reason). We get this fun super cop montage of how effective RoboCop is in responding to crime, and so we see that the product works. OCP has achieved the 24/7 cop.

Contrary Point: Abbott, the graphic novel

The graphic novel Abbot is about the same era of Detroit. The difference between Abbott’s response to crime versus what RoboCop shows can help you understand what other ways of looking at things might mean. The novel Abbott addresses the problem of crime through revelation. The way to solve crime is through the illumination of facts which will then lead to better outcomes. No technological introduction—Abbott isn’t a sci-fi, it’s a fantasy true crime—but instead the ideals of truth and understanding. Where RoboCop says there is a gap to fill with technology, Abbott says people must understand what is happening.

Imagining the otherwise becomes possible first by understanding the lenses we’ve adopted. Lyseology instructs us on our dominant lens that forces us to see a lack that has to be filled by a new fancy gadget.

Final Thoughts

Lyseology can readily promote the “technology can only be bad” narrative. This is not what I want to critique, nor is it Dr. Braun’s. The default world view which makes technological solutions the only sensible solution to a given problem is the culprit here. Dr. Braun wants people, through the lens of lyseology, to imagine other-than-technological solutions. At the core of RoboCop, for all its subtle satire, is the same message. The being fixed to technological solutions is our default stance, this is how we get a privatized police force making 24/7 surveillance robots instead of reducing crime. RoboCop is a call to not imagine the world it has created, but away from it.

What’s in 750 Words?

I joined a month-long journaling challenge feeling pretty certain that I wouldn’t be able to finish it. I’d wanted to journal many times in my life and I would only last a few days of consistent writing. It’s honestly been a sore spot in my life that I couldn’t figure out just the precise conditions that I needed to have a regular journaling practice, and that frustration bore out every time I tried to pick up the habit again. It would create a spiral where I would effectively tell myself, “Well, here we go again, what makes you think that this time is going to be any different?”

But this time was different. Thanks to my friend , I became acquainted with the journaling web app, 750 Words. I started journaling in late March and at the start of April, I signed up for the challenge. 750 Words uses game-like mechanics like badges, progress bars, social functions to encourage one another, and monthly challenges.

When you sign up for a challenge you have the option of setting up a reward/consequence thing. It’s a fill-in-the-blank pledge that says something in the vein of “If I succeed in this challenge, I will…” and “If I don’t succeed in this challenge, I will…”. I felt pretty bold when I made my pledge, I said that I would buy myself a milkshake if I succeeded and would give someone that I particularly didn’t like at the time a milkshake if I failed.

And Duolingo?

I have learned 2 other languages that aren’t my native language of English. A part of my time in the military, which will end in a year and a half, was in learning Turkish and Korean. I went to a place called the Defense Language Institute, which has an intensive approach to language education based on 8 hours a day of instruction followed by some amount of homework that varies based on the language. At the peak time of my learning Korean, I got to a CEFR equivalent of C1 in my ability to read Korean and B2 in my listening and speaking. In other words, I had “professional proficiency” in reading Korean, and “limited working proficiency” or upper-intermediate in listening and speaking. My Turkish was also at the B2 level across the board.

I’ve wanted to learn Spanish all of my life, and you’d think, based on my ability to learn two other languages, that I would have no trouble learning Spanish. After getting over my hang-ups in learning Spanish, I downloaded Duolingo, ready to dive in.

I feel silly introducing Duolingo, it isn’t something that needs an introduction. It’s a gamified platform for language learning. In my conversation with a gamification expert to write this article, the expert repeatedly emphasized how much of a gold standard Duolingo was for gamification. They cited the millions of people who have learned a language thanks to Duolingo. For me though, after a 60-day streak on Duolingo, I finally decided to delete it. The goal to me stopped being the act of learning and practicing language skills and became doing the bare minimum to support keeping the streak alive. I’m still studying Spanish, and so in a sense my language learning streak is alive, but my practice is completely divorced from the application now.

Two Apps, the Same Value, Different Experience

The difference between what I felt about Duolingo and what I feel about 750 Words compelled me to write this essay. I’m passionate about journaling and language learning, and they give me different but equally important perspectives. Journaling gives me intrapersonal knowledge—knowledge of myself—and language learning gives me cultural knowledge. I feel deeply passionate about both of these two practices. But I left one gamified application and continued to use the other. What gives?

It is easy to ascribe a level of domain knowledge as to why I left Duolingo. I’m deeply familiar with the process of learning a language and know what it takes, what it looks and feels like, to become proficient in a language. Even though I didn’t know much Spanish, I had all the meta-skills of language learning such that I could take myself through the process. I struggle with this as the answer. For journaling, there are very few meta-skills one needs to develop to be someone who journals every day. And the skill of writing every day is something that I have cultivated before when I was writing fiction and especially had to cultivate for my novel. It does seem, based on this, that the reason why I stayed on 750 Words and abandoned Duolingo was that I already knew the skills I needed to learn a language and with journaling I did not. There must be something different about them that is causing this to happen. There must be something in the design of these applications that on the one hand is conducive to creating a journaling habit and on the other hand a reduction of my language learning habit. I wanted to see what the existing philosophy of technology had to say about gamification to get after this question.

Introduction to Gamification

Gamification involves using game-based mechanics to achieve certain effects outside the game environment. Duolingo’s game-based mechanics, such as mapping one’s language journey on a map, encouraging feedback, and the system of hearts, are theoretically all in the service of promoting language skills. Or at least it’s supposed to be that way. With Duolingo, the core game loop, the core mechanics that augment one’s desired effects—language learning—fight against the business interest of Duolingo. Advertisements stop us after every lesson, most of which remind us to subscribe to their services so that we can get unlimited hearts you can make as many mistakes as we want, and the like. The business logic gets in the way of the game loop to get us to pay them money for the intended experience.

I will talk about gamification through the lens of game mechanics and game loops because I feel that gives us a useful framing around when gamification is happening optimally or if competing interests are getting in the way. In Duolingo’s case, the business logic of making money stops us from experiencing the core game loop as intended until we subscribe to the service. 750 Words is also a subscription-based service, but even while using the free/trial version of this software there wasn’t a video after every 250 words reminding me to subscribe. Nothing was preventing me from writing the 750 words in the application, the core game loop of 750 Words.

There are core mechanics that illustrate what game-based mechanics are, and they will ultimately describe how ubiquitous they have become. Badges, progress bars, experience points and levels, leaderboards, and likes. This is also where making distinctions between what is gamification and what is not a difficult one. Does Facebook, which employed the gamified element of likes in the mid-2000s, count as gamification in the same way that a flight training simulator does? They surely both used gamified elements.

Note: Duolingo isn’t all bad, I know of people who have learned a language because of it. I just also know people who have a 100 or 200-day streak in the language and they’re no closer to proficiency.

Gamification: Bullshit and other distinctions

Ian Bogost, a philosopher whose work I stumbled onto on accident, wrote a book called “Alien Phenomenology”, and while this wasn’t the first philosophy book I’ve ever read, it was the first one that centered me on a specific line of inquiry about objects. The subtitle of Bogost’s book is “What It’s Like to Be a Thing”, and it wasn’t until this book, and the offshoots that this book caused that I started thinking about what things there are out there and how we as human beings experience them. His work reinvigorated my love for philosophy in a way that hasn’t happened to me since reading Albert Camus about a decade ago. So in doing research for an essay on gamification, I was pleasantly surprised to see something written by Bogost. That is until I saw the title Why Gamification is Bullshit.

He describes gamification as bullshit, but not in the colloquial sense of “lies”, but instead, bullshit as formulated by moral philosopher Harry Frankfurt to mean the means “to conceal, to impress, or coerce" which has “no use for the truth”. I’ll admit that this characterization struck me pretty deeply, I mean how could I call bullshit on something that deeply changed the quality of my life through instilling a love and a regular practice of journaling? It flew in the face of my experience, to be sure. But as I read his article, I understood his response. In the early days of gamification, much like with many technological concepts, various consultant groups made land grabs for “gamifying everything”. In fact, , in a recent post on gamification talks about this era well. Gurwinder writes in the article Why Everything is Becoming a Game that:

In the 21st century, advances in technology made it easy to add game mechanics to almost any activity, and a new term — “gamification” — became a buzzword in Silicon Valley. By 2008, business consultants were giving presentations about leveraging fun to shape behavior, while futurists gave TED Talks speculating on the social implications of a gamified world. Underpinning every speech was a single, momentous question: if gamification could make people buy more stuff and work more hours, what else could it be used to make people do?

The promise of a better world, or at least that captivating story, fueled much of the posturing. Bogost bemoans this posturing, describing it as consultant “bullshit”, and in this way, gamification becomes bullshit, a consulting ploy meant not to solve actual problems but to coerce, conceal, impress, to paraphrase Bogost. What Bogost was rallying against wasn’t game-based mechanics employed to achieve certain ends, but the insertion of kitschy things you put on top of an application that only served the purpose of bringing more people to the application. What Bogost did believe in are games purposefully meant to teach something. See his game studio (and book of the same title) Persuasive Games for more details on that.

Gurwinder’s article above paints an even more grim picture than Bogost does about gamification. The mechanisms that gamification employs from the behavioral to the framing, have led to most of the problems we now face in our digital society. Note: This is a paraphrase of his essay, I do recommend you read it. He spends the last portion of his essay talking about what to do in this situation of gamified everything which feels more hopeful than the rest. I also interviewed an expert in Gamification, and he presented me with a more neutral account of gamification, stating in our conversation that while there are harms and misuses of gamification, it has also been used for good. The Red Cross, he explained, used gamified components to drive people toward the prosocial behavior of donating more blood.

Me, Complaining at a Crossroads

If I leave this essay as it is, I’ll be falling into an ideology I don’t believe in which is the idea that technology is neutral and it depends on how people use it that determines if it will have a positive or negative impact on people. Langdon Winner in his 1986 book, “The Whale and the Reactor”, also rallies against this idea. At the end of the second chapter, Winner summarizes the two ways in which there are “political qualities” in what he calls artifacts:

In the first instance we noticed ways in which specific features in the design or arrangement of a device of system could provide a convenient means of establishing patterns of power and authority in a given setting….In the second instance we examined ways in which the intractable properties of certain kinds of technology are strongly, perhaps unavoidably, linked to particular institutionalize patterns of power and authority.

For me, Winner presents a compelling account in both instances, but somehow gamification is different in analysis. Gamification is not a specific instance, as it is not one product, and neither are its properties fixed enough to state that gamification necessarily leads to institutionalized patterns of power and authority. Thinking back to Gurwinder’s article, we can see very clearly the ways that gamification has led to behavior manipulation at a mass scale, but so too has gamification led to positive outcomes, more blood donation, more people learning about other cultures through languages, more people journaling, the list is pretty long, especially if you take into account games like Habitica, which is set up to help you accomplish any goal one would want to achieve.

Back to technological neutrality, as you can see. But I will not be pleased with myself if I end this essay here, at ideological odds with myself. Sitting at this crossroads, and honestly kind of pitiful, is when I realized that my framing of neutrality is wrong.

Conceptual Multivalence

I will talk about this in two levels, the instance and the concept, and there are middle levels here but I’m not yet equipped to discuss them. The technological instance is the thing that we have direct interaction with, an application, a website, a highway, or a car. The technological concept is the level at which multiple technological instances can become grouped. I look at the instances of 750 Words, Duolingo, and the Red Cross application, and I can synthesize the technological concept of gamification. In the popular, non-academic talk, we tend to talk about concepts as non-acting, ephemeral things. Telling someone that they’re being “too conceptual” is a way to deride someone.

Here, I want to treat the concept as a unit of analysis. Specific applications, social networks, and even the roads we drive on seem to exhibit political qualities by distributing power in particular ways. If these instances can have varied outcomes that arrange power in different ways, then what does this say about the concept?

The word neutral was leading me astray, what technological concepts exhibit is a kind of multivalence. It is not just the human actor that dictates outcomes like the neutrality conversation led me to, but it does account for the different outcomes in specific instances of that technology. Conceptual multivalence, as I’m describing it, is the capacity of an abstract object (a concept) to have within it different and sometimes conflicting potentials for instantiation.

I’d like to illustrate this using Generative AI (GenAI) as an example. The concept of GenAI contains all the notions that you have accumulated in the relevant instances such as DALL-E, ChatGPT, and all those other products and services that you can name. What the idea of conceptual multivalence tells us about GenAI is that it is not just a matter of using it “properly”. This needs to go beyond the AI Ethics perspective. AI Ethics is useful work and it gives us knowledge about how to better use and live with the technologies. Conceptual multivalence work will help us understand the nature of the concept of GenAI and therefore what kinds of products it is capable of creating as it structures power, as all instances do. How to do this, however, is the hanging question of this essay.

Back to Gamification, a Conclusion

Gamification holds the potential for improving oneself and for making one addicted to the system in use, as well as other valences not explored here or not known more generally. I can’t because of this frame though, seek to abolish all gamified platforms nor should I place fault entirely on human involvement. As we interact with the concept and instances of gamification, we come to know it through our experiences, and that interaction encodes in us some degree of the valences possible in the concept.

The harms that gamification has wrought need to be held in tension with the benefits people have gained. These need to be held together with differing views like with those who have no reason to like it or don’t get it, or those who feel it to be infantilizing. All of these are equally true avenues into the concept of gamification, not because of a relative perspective, but because the concept itself holds multitudes that we can only access through our personal experiences and the experiences of others.

What we do with this collective information matters. It influences what kinds of policies we make, the kinds of technology we decide to adopt nationally and personally, and overall the lives we decide to live. I see a profound and exciting opportunity to try to understand technological concepts like gamification, toward improving our collective situations in the digital space. Not toward a utopia, but toward improving our lives which have become increasingly digital.

It’s an encrypted data archive from an ancient-but-advanced civilization. A smuggler named Martouf—who is pictured above—“found” the eye in unclaimed territory. Since then, he has been decrypting and selling parts of the data to the highest bidder.

The Eye is the subject of focus in Shobo and Shof Coker’s graphic novel New Masters. The graphic novel—written by Shobo and illustrated by Shof—tells us a story in six issues about the alien colonization of Earth, Earth’s role in intergalactic relations, and most primarily the price of a large store of data. The story focuses mostly on half-alien half-”Earther”—the alien race in question are called Jovians—Funlola Reis, and her family: her mom Sulesh, her dad Persio and her uncle Denarii.

The story is, to some degree, about the power that this data bestows on the one who possesses it. So, when Martouf, a smuggler, decides to sell the Eye to the highest bidder, there are simultaneous heists planned to steal the eye from the auction house. Funlola’s mom Sulesh is the lead of one of these groups, accompanied by Periso, Denarii, and another. The resulting story plays out much like a heist story would, but it is Funlola who secures the eye and its data, inside her prosthetic arm.

Data is the new gold or the new oil or the new… well you get it. I’ve seen it a number of times over the years. Most recently in this Mathew McConaughey ad in which he quips, “if AI is the wild west, does that make data the new gold?” This supposed fact about data being gold got me thinking about the Californian Gold Rush.

In a mostly-defunct project that I called Public Interest Energy, I wrote about the Gold Rush and compared it to the anticipated Lithium Rush that’s supposed to happen in a region near my hometown.

Public Interest Energy

Lithium Rush or Gold Rush Repeat?

The Lawrence Berkeley National Laboratory recently published a paper that quantifies the lithium content of the Salton Sea, a highly saline body of water that stretches between California’s Riverside and Imperial counties. Current estimates of lithium content, in the form of lithium carbonate equivalent, was reported by the nat…

Read more

3 years ago · Austin Wiggins

So, when anybody compares a development in technology to the gold rush, I think about the harms caused to various groups of people. Economic prosperity comes at a cost, and often those costs are swept under the rug as the more important task is the development of the abstract economy than the lives of further abstracted people.

New Masters forces me to think about the techno-cultural reality of data. The data that’s stored in the Eye is obviously technical, it derives from some process of extrapolating information and storing it in 1s and 0s. Through this manner of storage, other technological products can now interact with this data as relevant. The data in the Eye is deeply cultural. A people ancient to the land currently inhabited by Funlola’s people, lived in harmony with an alien race. Through this symbiotic relationship, both people experienced a kind of techno-cultural advancement that has not been seen since. This data is deeply cultural. I’m not the only one making this claim about data either, when a business makes the claim in their mission statement “when data is culture, data is power” they are saying the same thing. Or here’s an article from a Ben Proctor who writes in Data Orchard:

The same dataset will be interrogated in different ways by different people based on their lived experiences, their interests and their culture. 

Different people would capture data about different aspects of the same environment based on these same issues. The act of capturing data and creating datasets carries with it the influence of our culture. 

This is not bad. What would be bad would be to ignore this fact, to assume that data is in some way culturally neutral. 

The more diversity we can bring to data, to the design of datasets, to the collection and analysis of data and to the application of insights the better. 

We can see from New Masters itself the history of how the data in the came to be:

The structure of the data reflects the divination system of the Ife people, a lost city that grew to prominence because of its access to a resource called Obsidium. So, we learn in the above panels that the Ife cohabited with “a race of alien visitors”.

Data is valuable. Entire technology empires stand because of the data that we willingly or unwilling share with them in using their applications. It would be one thing to say, for example, that YouTube knows that I like long form content about social commentary. It’s another thing to know how this data gets accumulated. My YouTube history coupled with my Google search history is a powerful combination of data that already exists somewhere out there because YouTube and Google are owned by the same company. For now, the purpose of this data is to get closer and closer to approximating me so that they can predict my interests in finer and finer cross-sections, all in an effort to get me to buy things.

This data does not exist in a vacuum. It communicates cultural knowledge. What might it mean that 30-somethings who have progressive politics like to watch YouTube videos about people deeply engaged in social commentary? It’s a socio-cultural question that this “theoretical” data could answer. My point is, despite the currently reality of data being used to get us all to buy more, there are other ways this data could be, and has been used. This is what I mean by techno-cultural data.

A key question that New Masters asks is “to whom does data belong?” The Eye for much of the graphic novel belongs to Martouf the smuggler, but possession of that data became too dangerous, even for a danger-seeking smuggler. Selling the Eye of to the one who bid the most, is a natural way to rid oneself of something valuable and stolen, and so Martouf’s actions here make sense. Rather than buy this data however, we have two major groups rallying to steal the data. These groups are represented by planetary-political interests: Dr. Gideon Ojumah, a powerful/rich man of means whose interests lies with the Jovians, and Governor Tosin Ojumah whose interests lie with improving the conditions of earth. Yes, they are father and daughter, a wealthy family torn apart due to conflicting ends.

It is worth spending a moment to understand what’s driving this rift. Governor Ojumah sees what people have to do to get by in this world. Much like Funlola in the opening sequence of the story, people are going through significant lengths and at risk of great personal harm such as diving as deep as almost 250 meters, to find and sell Obsidium.

We also open the first part of the graphic novel with Funlola scavenging for Obsidium reserves in the city’s exclusion zone. Wildlife has taken over the area leaving it hostile for those who go there. Funlola’s goal is to bring in more money for her family so that they all might one day enjoy a better life on Jupiter.

Obsidium is the resource that keeps Earth relevant in this planetary-political context. Without it, the sentiment feels, Earth is a backwater. According to Cecily Sommers, the founder of The Push Institute, a trend analysis and consulting non-profit, change is dictated by four major forces: governance, demographics, technology, and resources. These forces are in order of fastest moving to slowest moving making resource the slowest moving as they are “affected by gradual processes—such as evolution, mineral formation, climate change, tectonic shifts—and by human activity.” This comes from Cecily Sommer's book Think Like a Futurist. Thinking about Obsidium, it is only through this resource that Earth remains relevant. Because other planetary groups can’t produce it, they must rely on the Earth’s supply.

Here lies the rift between Dr. Gideon Ojumah and Governor Tosin Ojumah. Tosin, as she is called by her partner, desires a better situation for Earth, but Obsidium as a resource cannot provide Earth this prosperity. And under the colonialist conditions brough about by the Jovians, resources are actively being siphoned away from Earth. Dr. Gideon Ojumah is on the side of monetary profit. It does not make sense to fund a backwater, even if it’s his own home planet, when the Jovians are the far superior people.

So, from the perspective of the reader, the question of “who should have possession of the Eye” becomes more a question of “who do we want to have much more power”? The choices are to centralize the power with a governmental elite or her father, until Funlola and her uncle make off with the data. It is only until her involvement, her hesitancy on who to give the Eye to, that we see that there may be another option. And we do get another option, one that Funlola choses for her self, to disseminate the data across the broadcast system so that everyone would have access to it.

Data was to be for the people. And I think that the data we produce on all of these social media sites and the like should equally be for the people. The fact that such rich data rests often in the hands of an untouchable elite corporate class is contrary to the ideals of democracy.

This freeing of data however, requires frameworks of collection, storage, and access that I’m not sure exist at scale. The infrastructure alone, the ownership and the function, presents a rich set of socio-technical challenges that perhaps outside of academia, have yet to be addressed.

Let’s free our data, but then there’s a lot of work to do.

We all need to be thinking about how we’re in a continuous relationship with technology. It is because we take this relationship for granted, whether by viewing it as all-evil or all-good, that we fail to comprehend technology as a phenomena. This is why I write about technology on Multidisciplined as much as I do. Technology spreads across domains and ways of being and so to attempt to understand technology is to attempt to understand the human condition.

But why have I looked at the technology in fiction?

I’ve written two essays—and have plans for more—that look at the technology depicted in fiction: one on Parable of the Sower by Octavia Butler:

And Black Star written by Eric A. Glover, who is coincidentally a writer on the coming TV Series Star Trek: Starfleet Academy:

I have two reasons for this. The first is , a scientist and the director of Arizona State University’s (ASU) Future of Being Human Initiative. He wrote a book called Films from the Future which explores the intersection of technology depicted in film and the real ways similar technology is manifesting in our present and how things might manifest in the future. I took a course derived from Maynard’s book when I was doing my undergraduate at ASU, and I deeply appreciated how it made me think about the relationship between narrative and reality. I see my work as an extension of Maynard’s but instead of limiting my focus to film, I’m using a wide aperture and taking in any medium that conveys a story that captivates me. I’ve started with graphic novels as a convenience, they are what I’m reading a lot of right now when I’m not reading research papers for my graduate work.

I’m not saying anything new when I say that science fiction alters our perception of what is possible in the future. The news website Quartz has an article with the the title “Here are all the technologies Star Trek accurately predicted”. Its a relatively short article written in 2016 that was meant to celebrate Star Trek turning 50, and it’s more a list of gadgets and gizmos, more than it is anything else. Here’s some of the tech the article says Star Trek “predicted”: tablet computers, portable memory, GPS, and Teleconferencing. Star Trek and other Sci-Fi stories have populated our imagination of the possible, which is why Star Trek didn’t so much predict these and other technologies, but provide a clear and convincing narrative that describes their use. Once the narrative was clear, others that were inspired by Star Trek would push to make some version of what they saw a reality.

I also write these essays because I feel that most perspectives on technology, fiction or not, ignore many of the socio-technical concerns. Technology is not a benign thing that just sits by itself and does nothing if no one uses it. Technology shapes our world and we shape our technology. A great example for what I’m getting at is what formalized road systems have done to us socially. If you see a friend walking on the side of the road while you’re driving, are you going to stop in the middle of the road to chat with them? Of course not, the rules of the road are predicated on safety and people following a set of common behavior which are enforced in many ways by laws. So we either mention it some other time when we see that friend, “hey, I saw you walking the other day…”, or we find a place to park and engage them. Our social systems and our technological systems are talking together all of the time. Most analysis I see on technology typically falls on one side of the camp or the other. Technologists will praise or condemn a piece of technology based on a product’s feature-set and cost. Sociologists and other social advocates will do the same thing with a product based on its impact on people and the many tiered follow on effects that technology can have.

Both of these perspectives are right. The technologist views has dominated most of the discourse around technology, but the social lens is just as important. As a civic-minded technologist, I find that my responsibility resides between these camps; understanding both perspectives so that we get technological outcomes that best serve the public interest. These essays provide me a low-threat, but narratively dense means to practice this view point on integrating these perspectives.

By using fiction as a medium for analyzing technology, I also hope that you get involved in the process. Narratives bond humans together; they are the fabric of culture without which not much would be possible. We all have access to fictional narratives, and those narratives will inevitably involve a relationship with technology. Or maybe I’ve said something about your favorite story that you think is incoherent with the larger point. The more we all practice looking at technology as a technological and a social issue, the more thoughtful and informed we become on these matters. That is ultimately my goal here.

The graphic novel Black Star isn’t one of my favorite pieces of Sci-fi, and it’s not one of my favorite cat and mouse stories either, but it details a few key aspects of technology that are currently on my mind. This narrative ended up being a good of a chance as any to talk about them.

Black Star, as I’ve mentioned, is a story of two astronauts competing for a return flight home on a ship that only holds one. Eric A. Glover, TV writer on the upcoming Star Trek: Star Fleet Academy and the cancelled Tom Swift, of which I may look at another time, wrote Black Star initially as a screenplay, but decided to develop it into a graphic novel instead. Arielle Jovellanos, who has done issue covers for Marvel and has illustrated a number of graphic novels such as Just a Spell (2023), illustrated the graphic novel.

The lead of this story is Dr. Harper North and she is being pursued by the ship’s wilderness survival expert Samantha Parrish. Originally on a quest to collect a specific flower specimen on alien planet, the voyage turns from scientific endeavor into a fight of life and death between the two characters mentioned.

My goal here is not to judge the artistic merit of this graphic novel, though I do appreciate the art style, and the narrative as a whole is solid. As with my previous essay, my goal instead is to look at the technology. The theme that comes to mind when I read Black Star is mediation. Though Dr. North is a technical expert, in this narrative we don’t see her employ her expertise. Instead, we see her in nearly constant communication with Guardian, an AI interface. We see technology play the role of a mediator of experience, rather than an actor itself, through this dynamic.

You can see on pages 5 and 6 the interface used to interact with guardian:

Dr. North wears some kind of extended reality (XR) visor which then visualizes map data of the planet they crash landed on. While guardian is capable of responding accurately to time and distance calculations, what is interesting here is that in some ways what we’ve seen in ChatGPT today is more robust than what is on display in the narrative. ChatGPT can act in the world, the digital world, but still the world. Through the Zapier plug in, it can streamline just about every activity under the sun. Guardian is purely for question and answer prompts. In a way it feels like what ChatGPT was when it was first released; a chat bot. Of course Guardian is more than that. Dr. North, has no reason to doubt any of the information that the Guardian provides her, it is presumed to be 100% accurate as opposed to the disinformation (that some would like to call hallucinations) that ChatGPT generates. While I’m this topic of comparing Guardian to ChatGPT, I want to highlight two ways in which Guardian takes to heart its role as a mediator of experience. The first is in way finding. We see on the following page, that Guardian can incorporate wayfinding, directly into the XR headset Dr. North is wearing.

Also in that page is the second function that I do think we’ll see in more advanced forms of ChatGPT based on integrations, or at least within the ballpark. Dr. North is wounded and doesn’t realize it yet, likely because of the adrenaline still pumping through her veins, but Guardian informs Dr. North that she is injured and should tend to those wounds before proceeding.

Guardian is also able to respond to highly sophisticated queries such as to follow a specific subject that was recorded from multiple camera angles. The features embedded within Guardian, or at least the one we see on display, take seriously, whether it was Eric Glover’s intent to, the idea that technology, and even AI, can serve as positive mediator of our experiences. It can augment what we do in ways that may even end up saving our life. Though this story is one of survival, where only one can survive, we see something somewhat remarkable in how Dr. North uses technology for positive (for her) outcomes.

This brings me to another theme that I would like to highlight: the idea of multistability. A stability within the context of technology refers to a singular meaning of an artifact. Any specific stability of a technology is something that can only be realized through the interpretation of the user. Multistability is then the concept that there are a plurality of meanings, and therefore uses of a technology. I am directly borrowing this from Don Ihde in the book “Technology and the Lifeworld: From Garden to Earth” which introduces the topic. Before returning to Black Star, though I want to highlight how Manuel Carabantes in his paper “Towards the End of the Designer Fallacy: How the Internet Empowers Designers over Users” extends this idea. Carabantes makes the claim that technologies such as the internet are resolving to some degree (though it can never be fully resolved) what is called the designer fallacy (also from Ihde’s work): the idea that a technology only is what is inscribed to it by its designers. To Carabantes, the internet makes this possible through patching and other such practices that are enabled through connecting to a device. Carabantes makes a great illustration of this example with the difference between the Nintendo 64 (N64) and the PlayStation 3 (PS3). With the N64, based on technology of the time, Nintendo had minimal power to stop the flow of unlicensed peripherals from going into market, despite legal action taken. Fast forward a few decades with the PS3, and you have an example of Sony patching out a feature that allowed 3rd party operating systems to be installed via internet connection. It later found ways to punish users who “jailbroke” their systems.

What does all this have to do with Black Star? There is a device that’s attached to the suit that both Dr. North and Samantha Parrish wear—the suit itself is a kind of device that can sense the health of the wearer. This device is a small metallic looking ring, and is supposed to help resuscitate the wearer in case of cardiac arrest or other such event via an electric shock. Throughout this story the device is used instead to deliberately harm one another to gain a leg up. In one example depicted in the panel below, Dr. North hacks into Parrish’s device and activates the resuscitation. In another, Dr. North removes the device from her suit and learns to trigger it in the water thus amplifying the shock (and later pays the price for introducing this idea).

What is important to me here is not that they use a technology for an unintended purpose, but rather that the designers of the technology have every means to stop this unintended stability (Carabantes would call this an eccentric stability, one that is outside of the designers intent) but decided for one reason or another not to. They could at a moment’s notice, patch Guardian to not allow overrides on someone’s resuscitation device, they could add in additional fail safes to make sure they were not used in water and et cetera. Rather than think of this as mere plot contrivance, which it may be. I want to treat it instead as a sign of a larger philosophy of technology from those in the story who created these suits.

Carabantes was concerned about how technology can steer behavior through these stabilities, much like those flashing police lights on posted speed limits, to guide behavior toward something morally correct, a nudge. At a large scale, the designers of this technology are making a deliberate choice not to nudge on proper usage of this technology, trusting the human agency to do what is most appropriate for their context. I will not make an argument for or against this point of view here, but this to me seems to be the statement this technology is making.

Technology can and does even in the real life, mediate our experiences. We go to certain food places not because we want to per se, but because reviews on Yelp say it is good. Algorithms on insert social media of choice, or on YouTube, mediate what kinds of things you watch, based on what they think you would want to watch. We are living in the world of technology as the mediator. We are seeing more and more signs of technology the actor, from its early days in industrial robotics to fully automated financial transactions not based on simple rules programmed by humans, but based on rules learned that their creators might not even be aware of in deep learning processes. Yet, how these technologies will end up being used, the multistable quality of these technologies, is something that we need to be conscious of. Black Star shows us a positive (given the circumstances) view of what good AI can do even if it doesn’t act in the world, and in doing so showcases (again for better or worse) the creative ways that human beings can use technology for radically different means that what the designer intended.

And to me, this technological creativity should be celebrated.

For those of you who don’t know, Parable of the Sower is a post-apocalyptic novel that highlights elements of climate change, crisis profiteering, and social unrest/social injustice. Butler does this by detailing the life of Lauren Oya Olamina, who, due to the consequences of her birth developed a hyper-empathy condition. While its not my intent to review the narrative or artistic quality in this series. I do want to take a second to say that this graphic novel was a marvelous read and I would absolutely recommend it to anyone who is looking for well-rounded post-apocalypse narrative.

Characterizing the technology in Parable of the Sower becomes an interesting challenge as instead of any particular technology, we are instead dealing with the absence of technology. The theme for Parable of the Sower, from a technology perspective, is the failure of infrastructure in the face of a brittle social fabric. What I mean in characterizing this theme is that in this world, there hasn’t been any event that has enabled all technology inert, nor has it been so long in this story that people simply don’t remember the technology. Instead, rising inequality, perhaps brought on by climate change, though that wasn’t explicit—so they are more than likely compounding factors than anything—has made accessing the infrastructure of technology untenable. And it is this confluence of factors that has created post-apocalyptic conditions.

It was mentioned many times over that the price for was simply too high and often too dangerous to obtain. You can see it in the following panel from page 12:

And, perhaps because of this rising price of water, or the general inaccessibility of it, we see a new service emerge, the water station (pages 165-166).

Because the quality of water may not be able to be guaranteed by other means, companies developed a service stations for water, for a cost. These stations are generally unsafe, as people who congregate to these stations have money, and with minimal means of protecting the public, lives are at risk at these locations. A friend of mine who I read a draft of this told me that this was much a return to the old danger of the watering hole, where animals such as gazelles and the like would have to be on high alert while drinking water from a lake or river in case a predator is nearby. This is when they can be most vulnerable however.

This factor highlights another service that is less technological and more a byproduct of poor water infrastructure: water peddlers, and as is mentioned in the above panel, their quality was much less certain. This is because of a third curiosity in this narrative, rampant illiteracy.

Illiteracy in this world seems to be much more prevalent. In fact, outside of major settlements, illiteracy seems to be the standard. This too is a failure of another kind of infrastructure: Education infrastructure.

You might think, that given the present set of problems, that scientific progress would be impossible. This is not the case though. Instead, there is a depiction of a more or less successful landing on Mars.

This is a clear example of the scientific capability of the US within the narrative, even as factors worsen. (Note: the astronaut wishing to be buried on Mars is ultimately not allowed to be buried there due to concerns that her remains would somehow contaminate Mars). Infrastructure fails, for some, and meanwhile allows for significant technological and scientific advancement for others. Progress in the face of such abysmal conditions is of course unjust. It highlights a nearly two different worlds that rely on each other to exist. It is the kind of reality that allows communities to be burned down without so much as a timely fire department response. These services, after all, are to be paid by the communities now.

What do we learn in all of this? First, that a failure of infrastructure does not look like a failure of science and technology progress. The science and technology mechanisms that we have built between academia and supposedly public organizations can advance despite social and economic downturn. This should be common sense to us. How many despotic, oppressive regimes can we list off that have made advancements in, say nuclear weapons technology? It might be easy to say that government corruption or some other such boogeyman created this situation. I don’t have evidence within the graphic novel particularly of what caused this situation. Clearly climate change plays a role, but it can’t be the whole story. And rather than attribute this infrastructural failure to actions on an individual, it makes for better analysis and seems more in line with the text to say that it was a number of well meaning (within degrees) decisions and inactions that lead to this scenario.

We can point to governmental failures easy, but as it seems as though many of these functions have become privatized (why else would one pay for firefighting or police services?) we cannot, at the infrastructural level blame the government. The massive privatization of most services in at least America, which is the only country we really get a glimpse of in this narrative, must be indicative of something larger. This is where I have to become speculative, as Butler doesn’t make this statement at all, but this privatization seems to be a response to climate change. I say this because we’re currently see this play out. In response to climate change, we are seeing a rising private intervention in various parts of the climate response. Including, interestingly enough climate risk insurance. The idea underpinning this is the classic refrain that companies would be able to respond faster and with more quality, products and services for the public, for a fee of course.

The further concentration of wealth as a response to this privatization makes sense, and it also makes sense that by privatizing massive portions of the government, that the government would be able to spend more toward science and technology progress to go to Mars, for example.

Parable of the Sower, from the perspective of technology, shows us a few interesting realities. It shows us legitimate concerns of over-privatization, or at least the troubles of having brittle infrastructures. Two, it shows that one person’s apocalypse is another’s trip to Mars even if you do end up dying there. A country does not have to be prosperous to advance science and technology, and the well-being of the public is by no means mandatory for science and technology’s advancement.

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Updates on Multidisciplined

• The Multidisciple

  • I’m still interested in writing and sharing things weekly, but the researched and deep way I was trying to write things wasn’t working. To best meet that intention, I’m introducing The Multidisciple, a proper newsletter in three sections:

    • The first section is what you’re reading currently, the updates of Multidisciplined as a project (currently the best way to frame it).

    • The second section is titled Notes From a Multi-Disciple. Here you can see in real-time the concepts that I’m puzzling at that eventually feed into longer-form content. (It will also be a summary of the “Research Notes” portion of the website [see below])

    • The last section, From the Desk, showcases the newest publication or provides updates on the writing, art, or other work.

• The New Website

  • In a previous post, I expressed a desire to find a new home for Multidisciplined. I thought that meant that Multidisciplined as a Substack site would cease to exist. I was wrong.

  • Introducing: https://www.multidisciplined.dev/

    • The site is still very much a work in progress. As it fills out, I will likely change pages as necessary and change the entire structure of the site. My intent is for it, including all the content, to change its structure as I change as well.

Notes From a Multi-Disciple

Design Research Revisited

In the note, Design Research as Phenomenology, find a sticking point about how Meike van der Bijl-Brouwer and Kees Dorst liken design research as similar to the work that a phenomenologist would do.

Intelligence as Fineness of Discriminations

I revived the following note in my personal knowledge management system to make use of Frederick Ferre’s point in Philosophy of Technology which expresses that intelligence could be defined by one’s ability to make discriminations. This is connected to the next note.

Modeling For Learning

I’m leaning on Khaitov and Samanova’s 2023 work on “The Importance of Modeling in Student Learning” for this note. This note, as the last one, reminds of the Drs. Cabrera’s extensive work on DSRP (Distinctions, Systems, Relationships, and Perspectives, a newer paradigm for systems thinking). Specifically, their work reminds me that the way that models help us learn is through the process of interrogating and interacting with a model, whether that be a mathematical model or a systems thinking-based model that is codified in DSRP.

Sociotechnological Vision (STV) as Decoding Design

I’m pretty excited about this one. Joseph Giacomin shows in his “What is Human Centered Design”, the note on the Multidisciplined website will do a better job at going into detail than I can currently, but in short, Giacomin details a graphical depiction of HCD that mirrors how I imagine what someone who goes through STV would.

The Objectivity Illusion

As depicted in this article, I’m reminded, just as DSRP and John Boyd’s OODA Loop reminds me, that we don’t perceive reality directly. We perceive reality through mental models, through our experiences, etc.

From the Desk

How to Enjoy the Dread of Being a Generalist

This is an older article from my time on Substack as Multidisciplined, but I’ve revived it as a way to help people understand a bit of what the site is about. In it, I talk about how the journey of learning a bunch of different things, in a number of different domains, can make an environment of a special kind of dread. What’s to do about that?

And that’s all for this newsletter. I appreciate the time you took to read this, it means a lot. If there’s anything in it that you like, please share it with the button below.

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From Weekly to Monthly

While the weekly writing has been truly cathartic for me, I would also like to put more time into what I write. For this reason, I’ll be moving from weekly articles to monthly articles. This timeframe will give me some space to refine what I write much more than I’ve been able to in the past. I want to focus on quality rather than quantity, a theme I’ll come back to during this update.

Multidisciplined Can’t Just Be Written

What good is claiming multidisciplinarity if it’s in a format that puts written expression over others? Sure, articles are one way that I’ve expressed myself, but I’ve also been drawing and making music which I wish I could share with you all. Substack for me, is not fit for the multimodal way that I express myself. This leads to my last update.

Making, Not Finding, a New Home

I will slowly transition from Substack. I’ve decided that the ideal home isn’t going to reach out for me. I have to make it myself, in an expression of digital creativity I hope to achieve. I’m a far way from being able to design a website, but Multidisciplined is a project that deserves my concerted effort.

Thanks for reading my updates. There will be more to come as I progress in these thoughts.

With much love and respect,

Austin, Multidisciplined

If you have been tracking the development of the concept, you’ll realize that I have changed the name of sociotechnological imagination, to sociotechnological vision (STV). This was to avoid awkward acronyms and also to provide greater insight into how I want people to use the concept after learning it.

If you aren’t familiar with the concept of sociotechnological imagination (called sociotechnological vision from now on), please check out my previous article before reading this.

My previous article establishing sociotechnological vision (STV) needs a follow-up. While the article constructed the theory of STV, I wasn’t clear enough for you to use the tool. This follow-up will provide a personal case study of STV to give you a better perspective on how to use it. To do this, I’ll be analyzing my relationship with generative AI. In the end, I hope to have a cogent logic that helps me interact with this technology in the future.

The Biographies, Personal and Technological

A little bit about me

I don’t know how to engage with generative AI. On the one hand, I see a clear threat to the artistic class, of which I’m a bastard member. I’ve seen the Reddit thread of the artist who wanted to kill themself because generative AI threatened their aspiration; a life of and off of art. At the same time, I was once a heavy user of ChatGPT. I used it to write short form thoughts on LinkedIn, short stories, and I was even using it to write a book. I was, and to an extent still am, interested in the way that generative AI will shape our relationship with writing. But it turned out I didn’t want my relationship with writing to change. It already changed once and I’m still coping with the loss.

I’ve wanted to write my whole life. I wanted to make writing my primary means of employment while still finding joy in it. I remember large parts of my childhood through filled notebooks of stories and novel starts. Since then, I’ve published short stories, poems, and articles on the web. Over time, I’ve noticed how technology created significant changes in how I write. I was once a deliberate writer. I pondered sentences endlessly to achieve just the right effect that I wanted. I treated writing like art. As I integrated computing into my writing life as a late teen, I became quick, sloppy, and anchored to my first thoughts.

To be clear, this isn’t because of computing per se, but because of the relationship I unwittingly developed with computing. I didn’t realize this then; it took me writing with ChatGPT to discover it. Writing with ChatGPT I was writing faster than I ever had, orders of magnitude faster even. I felt powerful at first, but when the novelty wore off, what remained was mediocre text that I was incapable of feeling proud of, even when I subscribed to the person-in-the-loop style of writing and iterating with AI. This takes me to the history of ChatGPT and its siblings.

A little bit about ChatGPT

Algorithms for generating text have been around since at least the 1960s. These algorithms, categorized into a process called natural language generation (NLG), were originally developed to “explore human-machine communication.” This is a theme we can still see today with ChatGPT. The interface of a chatbot begs the continued exploration of how we communicate with machines. Even in early applications were the desire to automate tedium: reports, customer service, and image captioning. It is also important to know that since the inception of NLG was the hypothesized capability to produce creative work. The way this ties into the other tasks categorized as tedium should not go overlooked. When NLGs went commercial in the 90s they had yet to make their pivot to artificial intelligence as a backbone, this would happen in about the early 2000s, and from then on significant gains in natural language processing (NLP) can be mapped to gains in artificial intelligence.

ChatGPT has only existed as an accessible prototype since November 2022. It is built on the concepts of large language models and generative pre-trained transformers. The specifics of these are important, but I can’t for the sake of the length of this article describe them sufficiently in detail. What it means in the simplest way I can construct, is that ChatGPT is “pre-trained” (feed a bunch of tagged data) from a large corpus of text. In the case of ChatGPT the text includes a slice of available text on the internet and a set of conversations that give it its conversant style. This is by no means a technical treating of ChatGPT, however, and I recommend you read the papers that develop those concepts.

Tying to Social Roots

I can’t claim to know the intent (positive or negative) of any company involved with this tech. Even when intentions are clearly expressed by their CEO or CTO, I can’t take them at face value, as much as I wish I could. Instead, I look at the impacts of the technology and determine what those impacts might mean.

I write this over a week into the Writer’s Guild of America (WGA) strike. Writers and directors are asking for more pay. Considering these are people who are writing for Hollywood, Disney, Netflix, and other movie and TV giants, it is easy to think that these people are already well-paid and are greedy for asking for more pay. Writers for these companies however, struggle to even have stabling housing. It is clear they are not compensated sufficiently for the effort and impact they have for their employees if this is the case. Aside from compensation, there is also a career longevity subtext to the strike; ChatGPT proves that it can be “cheap labor”. It is anchored in the fear that is in various ways being realized at various stages, that it is possible to automate away the creative class. But does it make a difference who (or what) creates a written work (same question can be asked about visual work as well).

This is another point I struggle with. Here’s the extremely rudimentary thought experiment I had: think of two texts, both of them nearly identical in content, there’re some stylistic differences but they largely convey the same information and the same reading experience. In this situation, would it matter if an AI generated one and a human created the other?

I can imagine the multitude of arguments pro and con. Those who say source doesn’t matter will point to your consumption of processed and fast foods and our collective blindness to source, and they will call their opposition hypocrites. Those who will claim that source does matter will point to the DIY movement/maker movement, or the handmade movement, and call their opponents technological shills. Naturally, the true conversation around this point will be a spectrum of which the two sides I mention will be the moderate sides of each pole, there are more extreme arguments and there will be at least some agreement.

As I think at the scale of individuals, I realize that we have to make decisions that align with our own values. Through the striving for and satisfying of these values, a person may achieve some degree of flourishing. This seems to be the crux of the argument for me; maximizing for human flourishing. But, what do you do when one’s flourishing intrudes on another’s? Currently, it is capital which drives the importance of whose flourishing. This leads to the satisfying of the tech CEO, CTO, and computer scientist’s flourishing at the expense of the artist, who has already been historically seen as a pest of an expense by many.

Final Words for a Thing that Makes Words

To me, ChatGPT becomes a decent idea generation tool, an okay sounding board when I feel like I’ve bothered my typical collaborators too much. To the extent that it starts to threaten people’s livelihoods and means of flourishing, we should be much more deliberate. Without this deliberative spirit, we will unnecessarily cause harm in the name of progress; a backward pursuit. We need to understand the view, whether or not we want to believe it, that ChatGPT and their kin are an organizer of political power more than “simply a tool,” where political power flows from the concentration of automating power at the expense of many parts of labor (creative and otherwise) that we take for granted.

I want to be part of a society that values creative labor (and all other kinds of “invisible” labor) this current iteration of generative AI, irrespective of intent, seems to have the opposite effect.

Sociotechnological Vision

Sociotechnological Vision is a foal, awkward in its steps and needing still to learn how to run. This article and the last are the first step toward maturing a concept that I hope can stay with you and become a part of how you think of technological consequences in society. In that capacity, I hope it has been helpful to you. If you try to use it, please tell me about the experience, the good and the bad.

We don’t have many ways to navigate our relationship with technology at the moment. We have ethicists working in technology, but their work is more geared toward how companies should develop technology. Non-academics are left without tools to navigate our connection to technology and are forced to find our own way. I think of how people learned to navigate the crypto-boom that happened a few years ago. There were people who didn’t know what they were investing in when they invested into crypto; people who lost fortunes because they were promised things that never happened. The NFT craze was similar.

For me, as things like ChatGPT started becoming a topic of everyday discussion, I really wanted a tool that gave me a chance to think critically about technology that included not just the technology itself but its potential impacts on society; a tool that leaves the decision to enter into a relationship, and understand the extent of that relationship, with me. This is why I developed the idea of the sociotechnological imagination, and I hope to pass the idea on to you all now.

Origin

C. Wright Mills introduced the idea of the sociological imagination in his 1959 book The Sociological Imagination. Sociological Imagination cemented itself as a concept via the way it deftly highlighted social dynamics and placed the individual within them. It has since become many people’s introduction to sociology. As a framework, the sociological imagination teaches us to connect our personal experiences (biography) with broader sociocultural forces (history), and by doing so we learn to see the ways our experiences relate to larger social forces. This is in service of figuring out just what factors contribute to an issue.

The book Stolen Focus by Johann Hari is an excellent example of the sociological imagination at play. Whether or not Hari intended specifically to employ the concepts of sociological imagination is beside the larger point that the way he describes our dwindling focus, the applications and programs that lend their hand to their contributing focus, and how on a larger view what we need to do as a people, is a work of sociological imagination. He ties his biography, his experiences in recognizing his regressing focus, to the larger forces at play that include different applications and the attention economy (among other things).

Disambiguation Disco

If any of you are hobbyist scholars in science and technology studies (STS) and/or futures studies, then you might be thinking “Sociotechnological Imagination? That sounds kinda like sociotechnical imaginaries.” I’ll lament that they do sound similar and I am concerned about future confounding of the two concepts, if the sociotechnological imagination stays around as a useful concept. I will seek to disambiguate these two concepts now, knowing very well that the problem will rear its head again.

Sociotechnical imaginaries is a concept coined by Sheila Jasanoff and Sang-Hyun Kim, both out of the John F. Kennedy School of Government at Harvard University. What they realized, and described in their 2009 paper “Containing the Atom: Sociotechnical Imaginaries and Nuclear Power in the United States and South Korea”, was that the field of STS had largely ignored “non-scientific actors and institutions”. To this end, Jasanoff and Kim proposed sociotechnical imaginaries as a new analytic tool, and they defined that tool as “collectively imagined forms of social life and social order reflected in the design and fulfillment of nation-specific scientific and/or technological projects.” We will see going forward how sociotechnical imaginaries and sociotechnological imagination are sibling concepts, but do not cover the same territory.

Another concept which needs to be made distinct from my sociotechnological imagination, is the technological imagination. This concept has been harder for me to pin down. I’ve seen it referenced in a few places, but nothing that I’ve yet to have access to (thanks academia). From what I am able to find however, the concept originates from the work of cultural theorist and media designer Anne Marie Balsamo, specifically her book “Designing culture: the Technological Imagination at Work”. Her concept technological imagination is described in the book abstract as “a quality of mind that enables people to think with technology, to transform what is known into what is possible.” Yet another sibling to my term yet something different altogether.

The Sociotechnological Imagination

The sociotechnological imagination helps you explore your relationship with technology in the same way that a map helps sailors navigate the seas. An experienced sailor could travel with just the stars as a guide. For the novice sailor, having a robust map, provides a safe direct journey to the destination. I want the sociotechnological imagination to be a cognitive tool that gets you where you want to go in your relationships with technology “safely”. And we use cognitive tools daily. We use design thinking for problem solving with the human at the center of design research, we use continual process improvement for when we know we can get more juice with less squeeze. These frameworks, and the potentially infinite frameworks like them, serve the role of directing the tool-users attention to achieve certain ends. The sociotechnological imagination is no different.

As I mentioned at the start, the sociotechnological imagination starts where Mills’ sociological imagination leaves off. The sociological imagination gets us to the point where we can connect our biography to history. An example is in order here.

I have attention problems that can often get in the way of parts of my life. One way to interpret this is that I need to take more personal responsibility for my attention. Maybe I need to start using tools proven to help such as the pomodoro technique. Using the sociological imagination would help me realize that I am singularly at fault. I would look for the roots of my attention problem in society. This direction would have me looking to, for example, the attention economy and how companies get more money the more that they are able to extract my attention from my own ends. It would direct me to looking at how our diets have changed over the last decades and how my massive intake of sugar, a byproduct of modern society at this point, plays a role in my attention problems and avoiding those sugars becomes an Sisyphean ordeal. It is in the connections between my personal attention problems and societal roots. It is not getting rid of my own responsibility and saying its a social problem, but instead a recognition of the multiple factors, genetic, personal, and societal, that have gotten me and many others to this point.

So, we can connect our personal experience to societal experience. Now we need to see relate this thinking back to technology. The first way to do that is to limit the focus area to something technology related. In the example I provided above we’re already in a technological lens, which means we are now able to orient with the sociotechnological imagination. But let’s say you were thinking about unemployment, you could connect your own unemployment to various sociocultural roots and realize the multi-fold mechanisms at play in your condition, but it is not inherently a technology problem. The first rule for employing the sociotechnological imagination is to center your analysis on a technological problem.

From this technological centering, you can then connect your personal experience with that technology to the social roots of that technology. With just this framing, we would have a more narrow implementation of the sociological imagination. Again, my hope is to give you a way of thinking that will help you navigate this world of technology better. To do that, you also have to delve into the biography of the technology. This means understanding both the development of the technology, its component parts, and its connection to the other things that make it possible. If we used a printer as an example of analysis, this second rule would entail understanding the development of that particular printer, the components which comprise it, and how it is connected to other technologies such as your phone.

The last rule of the sociotechnological imagination is to situate both personal biography and technological biography into larger social forces. This is best mediated through the answering of questions. My friend and colleague Daniel Hulter and I have come up with questions, the answering of which will get you deeper into understanding how these two biographies tie into a social knot.

Questions to Consider

1. What might the adoption of this technology mean for myself and for society?

2. What new dynamics might this technology unveil for myself and society?

3. Does the technology shorten or eliminate any journey or process? And was there any benefit in engaging with that process or journey that is now being lost?

4. How might this change how I and society relates?

5. How might this technology change what I value and what society values?

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This is the final part of a three part series. Here are parts one and two.

As a part of this project, I curated a playlist. It evolved into a musical exploration of the ways various artists have discussed technology and the other ideas I’ve mentioned in this series.

If you use Reddit and you like this series, I created a subreddit dedicated to the philosophy of technology called PhiloTech. I hope to continue the conversation there.

I’ve been building up to this point. In part one of this series, I framed the necessity of having a pragmatic philosophy of technology. This argument revolved around the inability to responsibly integrate ethics into technology companies, among some other points. Part two went into a primer on both pragmatism and an introduction to philosophy of technology. Each of these sections deserve a much longer and thorough treatment than I can give them now. My immediate goal with this series was to help organize these thoughts I’ve been having about technology in a way that I can come back later and explore them more in-depth academically later.

The last part of this series will give you a way (emphasis on a, as it is not the only one) of looking at technology, and give you some tools that you can use to navigate this way of looking at technology. This first direction we go is maybe the least likely of all… into Amish communities.

The Amish Relationship With Technology

The Amish have been parodied in our media for some time now. They are depicted as plain people who are inherently anti-technology. Even the godfather of parody, “Weird” Al Yankovic has parodied the Amish.

These depictions are a distortion (incidental or purposeful is not the point here) of Amish reality. The Amish (speaking generally, there are different Amish sects who vary in their allowance of technology) are not anti-technology, but instead their relationship to technology is mediated through Amish values which is deliberated on by the community. The adoption of cars, electricity, and even internet to some degree are all part of a Amish religious value-laden deliberation on the technology.

For more on this topic, NPR has a great article on Amish technology.

Understanding a Nature of Technology

This section is the one that confuses me the most. It was the reasons I knew I needed some more time to think about this and so wrote an intermission post instead. The question I’ve been toying with is, “what is the nature of technology such that our conversations about it in the short term are fundamentally different than they should be in the long term?” Let me clarify what I mean by this question.

I’ve been mired in an electric vehicle (EV) charging project as a part of some undergraduate research I’ve been doing. As part of this research, we hosted workshops with experts in various areas relevant to EV charging, from grid infrastructure, to equity. While there is much to take away from this project (and we are slowly working on a paper to communicate quite a bit of it), one of the things the workshop highlighted is that when people talk about technology in the short term, people default to incremental conversations. In the long term however (and using a tool that I will talk about later), requires a fundamentally different way of talking about it. When talking about how EV charging in twenty years, for example, it is not enough to ask where to put the next n charging stations, there are numerous knock on effects that become significantly more important than that. Things like equity, technology transitions and the like.

What is it about technology in the long term is different about it in the short term? For this I have two different potential answers. One of them comes from an interpretation of Ludwig Wittgenstein’s work. Wittgenstein was a philosopher from Austria who, for the purposes of this article, put some significant thought into language. Langdon Winner, who I mentioned in part two, interprets Wittgenstein’s concept of “ways of life”. In this interpretation, there is a point in time of a technology, for Winner’s assessment, where a technology stops being a tool (within some ways of talking about it) and becomes a part of the human experience. Look at how smart phones have reshaped our methods of talking to each other for example. In other words for Winner, and this is the language I’ve adopted, there is a point in time in the adoption of a technology where a technological artifacts starts to lose its “tool-like qualities” and become a part of our humanity.

This is the first reason our conversations around technology must be different. In the short term, we have to talk about technology within the context of its “tool-ness” but in the long term we have to become aware of how the technology becomes embedded into our experiences.

The second potential answer to this question requires us to look at another way of looking at technology. Frederick Ferré in his 1988 book Philosophy of Technology mentions that technology is not simply a product of knowledge. For Ferré, technology is the product of the co-conspirator of knowledge and values. Our primary means of knowledge as a western society is science, and main means of morality and values is religion (note: I do not agree that religion is the primary means by which we learn morality, this is an artifact of me paraphrasing Ferré.) Science and moral valuation exist in parallel and when there is enough synergy between the two, a technology is created.

This is where we learn of the second way to think about how to answer the question of the outset. We talk about technology different in the short term, under this framing, because when we become acquainted with a new technology we are usually not fully aware of the knowledge or values embedded within a technology and as such we are reduced, in a matter of speaking, to only talking about technology by means of its apparent capability. In the long-term we become aware (or at least some part of the population does) of the knowledge and values embedded within a technology and from this standpoint can challenge the implications of those.

So What Do We Do?

If I left you here, I think many could take this and infer what to do. It is apparent that we need to get better at thinking long-term about technology, no matter which way we decide to answer the question: the knowledge-values way or the tool-to-human-expression way. This could arm the inferring reader with the foresight to look at how the embedded knowledge and values of a new technology impact the things that they value the most and make a critical decision. It would enable someone to say, “after the tool-qualities of this technology have shedded, what social, environmental, economic, and political consequences are we left with?” These are both valid inferences. But for the sake of being thorough, I’ll introduce some tools which I believe will get you to the same outcome.

Foresight/Futures Studies

(Note: I am using Foresight and Futures Studies interchangeably, though some make distinctions. While I think it is an important argument for the community to continue to engage in, for the sake of this work I will use them synonymously.)

It will take more space than I currently have to properly define futures studies and foresight, so for the sake of this article I will define it broadly with the more specific contextual nuance of when certain tools are employed or when certain terms are correct over others saved for another time. Roughly understood then, futures studies is a set of tools and methodologies that use the lens of the future to expand perspectives on a given topic. The practice involves looking to some future timeline, say 20 years from now, and using methods like inference, or imagination, or statistics to explore the impacts of the topic at hand. The body of research here is significant and if you’re interested in even part of what I have expressed here, I recommend reading volume one of Foundations of Futures Studies by Wendell Bell.

The recommendation of futures studies itself is too broad for the task of giving you tools that help you navigate your relationship with technology in a way that is consistent with the short- and long-term phenomenological consequences as expressed above. While there are many tools and methodologies in this practice that can facilitate this relationship (a runner-up in this regard was explaining Jane McGonigal’s expression of episodic future thinking (EFT)), the focus will be on any method that uses a participatory foundation.

Participatory futures approaches are a means of engaging in collective imagining about a topic and to consider the possibilities, consequences, and even opportunities within the imagined future. This practice of gathering people from, preferably, different backgrounds to engage in critical and imaginative thinking on a technology at hand gets to the heart of a pragmatic philosophy of technology, being able to explore the consequences, possibilities, and opportunities of a technology as it relates to our long-term experience with it.

FractalVersing

While participatory futures techniques are great for when you can get people together, we also need tools that we can use to explore when we’re on our own. This is where FractalVersing comes in. I discovered FractalVersing by utter accident via one of my long strolls through Reddit, but as soon as I saw it, I knew the value. I’ve also had a quick chat with Fraser Scott, the creator of FractalVersing and am excited to explore these ideas with him further. So what is FractalVersing? I’ll borrow Fraser’s words for description.

FractalVersing is a method of creating little statements called "verses" related to a subject that help you reflect on, understand, and interpret different situations or events. Use them to guide decision-making, problem-solving, brainstorming, or any other meditation on a subject.

I will not go over how to do FractalVersing on this article, Fraser’s site already does that well. Instead, I will talk about what ways to frame your FractalVersing in order to achieve the ends that I’m discussing. The first important step is to make sure that when you are anchoring your ontology to a subject that you ensure that your subject is a technology (that’s very obvious but worth saying). For the later interpretation stage, or in other words, once you have built your verses and are putting the ontology to use, you have to make sure that you are embedding your inquiry in a socio-technological context. The example given is building a mobile app, I’d argue that in order to best explore the dynamics as it relates to the short- and long-term points of consideration for technology that you find something that combines a piece of technology and some part of the human experience.

The outcome of this will be a deeply nuanced exploration of the piece of technology you had in consideration. Those considerations will be rooted in an ontological understanding that would be difficult to get using other exploration methods.

Grammar as a Means of Being Aware

I’ve been giving you tools that work at different levels of application. Participatory futures works with groups of varying sizes, FractalVersing (while it can be used as a group activity) is for individual and deliberate exploration, but there’s one more level “down” that I think is just as important. I’m talk about a tool that you can use as simple lens of viewing. It’s less deliberate than FractalVersing. It’s not something you deliberate get a sheet of paper out for or something, but something you can use as another lens to look at your technological experiences. What I’m talking about is grammar (obviously because you can read those headings up there).

In keeping in tradition of the spirit of philosophy, I have to engage in a bit of definition-making. When I’m talking about grammar, I’m not talking about it in the way that you typically think of, syntax of sentences and all that, though I am talking about something similar. I come to this term as there have been multiple sources that have taken Wittgenstein’s approach to language and sought to apply it to technology. I’ve mentioned some of them in this series and there are yet more that have done so.

In a really quick manner of speaking there are two types of grammar as it relates to technology: there is the syntactical level (and now I’m pulling this directly from the work of Leon Pezzica and his work on Deep Technogrammar) which is about the connections of a piece of technology. It is how one component of a piece of technology is connected to another, such as how the lever/arm of a toaster relates to the electromagnet within it. It is also about how it connects to other parts of a wider system. The other side of syntactical grammar is deep grammar which is the ways that technology becomes embedded within our social systems.

When considering a technology, we usually use a syntactical grammar (albeit a narrow version of it), by having these two kinds of grammars by which to navigate our encounters of technologies, we can be explicit in our awareness of the connections and the transcendental and social dimensions of technology as they become parts of our human experience.

Conclusion

The questions that technologies leave us with are multidimensional and highly complex. Even this three part exploration left out significant philosophical and social questions such as “what even is technology” (which turns out to be an interesting question. It avoids getting into any potential metaphysical considerations, though considering them and considering how they break down would help significantly in developing this idea. This series leaves me with much more work to do. I have set this series out as a stepping stone by which I would force myself to get “more academic” in my exploration. So, while this exploration is admittedly in complete one, it serves to me as a giant step in a direction I’ve felt myself needing to go.

I hope in my exploration of these concepts, that I have left you with something that will get you to critically consider your relationship with technology and the awareness of how technologies embed themselves as ways of life for us. I made sure in this exploration that I didn’t leverage on any value judgements of technology. I didn’t want my embrace or rejection of any specific technology to get in the way of the particular thoughts that are more important than our current relationships with any technology.

Remember when I said part three of Toward a Pragmatic Philosophy of Technology was coming out this week? Turns out I need some more time with it. This article serves as an intermission between the parts.

Here’s, hopefully, a non-contentious statement: reading is learning. This isn’t to say read is the only way to learn, and I’m not saying that it is the best media of learning either. We might have different levels of precedence of learning media than someone else (you might read more than me, who might read more than someone else, for example), but so long as we are capable of rudimentary literacy, some of our learning will come from reading.

We embrace this fact in abstract, when it is divorced from the context of our lives, but our lived experience tells us a different story. As we go about our day, our practice of reading becomes burden. We are bombarded by emails, workplace memos, twitter threads, and comment sections. Under these conditions, reading is no longer a matter of learning, but a matter of getting through, a matter of efficiency. This might be fine if this practice stoped with the mundane parts of our reading lives, but it bleeds into the reading we were supposed to enjoy. Relishing in or exploring the meaning of a sentence becomes a chore, 30 minutes on a paragraph becomes an unacceptable metric. We’re much worse off for this.

What is Learning?

This guiding question is not me looking at learning science, nor will I dive too deep into a philosophy of the idea of learning (as I am want to do lately). Given this self limitation let’s start with simple definitions. Merriam-Webster defines learning as… I’m kidding. The definition from Merriam-Webster is serviceable but not for the ends I am seeking. Instead, a definition expressed by a J. N. Washburne in 1936 is much more serviceable to the point of this article. In the paper “The Definition of Learning”, Washburne characterizes learning as “an increase, through experience, of problem-solving ability”. (He models this dynamic mathematically which might be interesting for some of you, but the specific formulation isn’t necessary here).

I want to stress that Washburne’s definition is not about the accumulation of facts, it is embedded in what one can do as a product of a learning experience. Many definitions you’ll find in dictionaries will dedicate their first definition the fact accumulation view of knowledge, while only some that I’ve seen mention the outcomes of having learned.

Learning Strategies

I’ve been fascinated with learning strategies lately. I don’t know if that’s because the algorithm wants me to be interested in learning strategies because that’s what drives up my watch time, but that’s besides the point, sort of. What fascinates me about learning strategies is how many of them have become mythologized. We have, for example, the idea of learning styles which are entirely false. In fact, let’s take a second just to show how little the idea of learning styles actually stands up to any critical inquiry. Let’s say I wanted to learn to ride a bike, how would I best learn to ride a bike? Or how about geometry? Imagine if you will learning geometry with no visual examples and only spoken words about length of sides and angles. I would have fared much worse in the subject than I would have other wise.

Evolutionarily speaking, our brains are well adapted for learning it makes no sense no matter the metric used (be it efficiency, survivability, or navigating complexity) to have a specific learning style.

There is another reason for my interest, which is that there are still tools that actually work that both extremely beneficial but majorly over looked. I think about this when I think about the idea of free recall. Free recall is a pretty simple practice. What you do is get a blank sheet of paper, and set aside some amount of time, and write down what you know about a topic. You can connect it to other topics, but the idea is to do your best to exhaust what you remember about a given topic that you are trying to learn sometime after reading or a lecture, etc. For instance, here’s what this looks like when applied to the idea of deliberate practice, which I’ll talk about a bit later in this (Note 1: please ignore my misspellings, Note 2: there are different ways to employ free recall. You can do it before YouTube video for example, to activate the contextual knowledge around the topic, and you can also do it after. It is recommended that you do both before and after):

There are the tried and true methods, too, like spaced repetition, interleaving, and contextual variation, which have all been proven to help out in your learning.

Quick Point on Deliberate Practice

To get to the point I am eventually going to make, I have to talk about deliberate practice. Thanks to Malcolm Gladwell, the idea of deliberate practice is forever tied in our cultural psyche to the idea of 10,000 hours to become an expert at a thing. People tons more capable than me will have far more thought out reasons as to why Gladwell’s particular cherry picking of Anders Ericcson’s work has been harmful, but I want to mention it for an adjacent reason. The point of deliberate practice and the idea of getting in 10,000 hours are at ideologically at odds. Deliberate practice is about quality of practice rather than quantity. To see as the measure of deliberate practice to be a certain amount of hours is the performance of a particular kind of self-sabotage. Remember: quality of learning of quantity (for the particulars of how to do deliberate practice, there are great videos, papers, and books on the topic).

Meandering to a Point: Reading as Learning

If learning is about an increase of capacity to solve problems and if learning is about quality over quantity, then how do we return quality to our reading so that what we learn from reading can readily be of service for problem solving?

We have to transform our relationship with reading. Reading for us has become a matter getting through (ex. “I got through Infinite Jest” or “I’ve gone through 52 books this year”). The siren that is efficiency has lured us to our doom, placing quantity metrics over quality metrics. Course correction is our only hope, so long as we can snap out of our mesmerization.

The type of reading you need to do to gain quality back to your reading is going to tug at core of how we’ve been trained at reading. Spend more time thinking or relishing (depending on the genre and subject matter) per sentence. For nonfiction, my primary focus of reading lately, this means pulling out as much as you can from each sentence. This is best illustrated by cognitive scientist Benjamin Keep on his YouTube channel. In a video about active reading, he showcase just how much you can pull out of a paragraph of text (his example was on Queen Victoria) by actively reading and applying critical thinking skills. Then, you can use a technique like free recall to test yourself on the material after some time has passed, ideally just as you’re starting to forget the material (this is called spaced repetition).

Closing Thoughts

Reading is learning. No matter what you read, it can be a portal to new ways of thinking and being that you would have otherwise never experienced. Getting the most of reading means taking the call seriously when you are engaged with material that you want to learn from. It means taking time. It means being “inefficient” for higher quality learning in the long term. It means opening yourself up to the possibility of being changed by engaging with it earnestly.

There is a Spotify playlist that I am making for this series, check it out here. It will develop as I continue to refine this set of ideas.

Click here to see the first part of the series where I start highlighting the reasons why we need a pragmatic philosophy of technology.

Pragmatism, a Reintroduction

Pragmatism suffers from a bad reputation. It has been used to describe utilitarian bad actors and to describe a sort of cold detachment in our media. We confound pragmatic and practical.

Suspend what definitions you have on pragmatism for a second (unless you’re a well-studied person on pragmatism, then please let me know where I err). I was listening to a part of The World of Philosophy series on “William James, Charles Pierce and American Pragmatism”, and this helped me to a better definition of pragmatism. Pragmatism is not about cold-blooded practicality, nor is it an anti-intellectual pursuit based only on “what works”. It is a philosophical theory embedded in critical thinking and validation through testing that emphasizes practical results and experience in determining what is valuable and true. Instead of being stuck in the quandary of a particular metaphysical question, pragmatism beings that back down into the world of consequences and experience.

There is a lot about pragmatism that I can’t cover here, including the ways that Peirce talks about the intersection of pragmatism and science, but more will come into play as I detail the method in the next part.

Philosophy of Technology

In 1986, a man by the name of Langdon Winner wrote a book, and in that book was the story of overpasses in Long Island, New York. Winner, among others, noticed that these overpasses only had a clearance of 9 feet, effectively discouraging buses from entering Long Island. To some, this would look like an urban planning mistake, or otherwise a lack of foresight. But there was another perspective. These bridges and roads were largely designed by a man named Robert Moses, a “master builder of roads, parks, bridges, and other public works” whose work spanned 5 decades of work in New York. Moses’ biographer, Robert Caro explains that the reasoning was a social one: Moses had an explicit bias against both poor people and Black people. This bias was a conscious part of the design actively excluding those who would travel by other-than-automobile means.

The book I’m referencing is Winner’s work "The Whale and the Reactor”. This book was the first I was acquainted with that dared to venture into technology as an object of philosophical analysis. For Winner, technology was any means of human aid. This definition spanned language and writing, to the thing we typically see as technology today such as computers and software. A philosophy of technology would critically analyze both the “nature and the significance” of these human aids.

We are all sleepwalking, according to Winner, not literally sleepwalking but in our dealings with technology. He argued that our pace of technological advancement has far surpassed our ability to cognitively analyze the effects of their consequences. We are stuck in a making and use the paradigm of technology, where the makers of technology (the tech firms, etc.) are responsible for using their expert knowledge to make a thing, and where users are tied to a good use/bad use dichotomy. I’ve heard the argument many times over and it goes something like this, “Did somebody do something bad with this technology? Yes. But it depends on who is using it whether it is bad.” In fact, this is a common refrain when we talk about guns; they say “Guns aren’t bad, it depends on who is using it.” Winner called this theory the “social determination of technology”, and states that it has “obvious wisdom” but also has shortcomings in suggesting that things in themselves don’t matter. A notion that Winner rejected.

We are in-relationship with technology constantly. Even as I type this out, I am expressing a relationship with myriad technologies: computers, keyboards, desks, electric lights, doors, phones, clocks, and the list goes on even down to the invisible bolts and screws that help keep this building that I’m writing in together.

The challenge, which I mentioned at the outset, is not that I have relationships with all of these technologies, but rather that I need to determine as a layperson (potentially) in this technology, whether I should become enrelationed to this technology.

Okay Okay, Now a Pragmatic Philosophy of Technology

So, you should be able to see by now that when I’m talking about a pragmatic philosophy of technology I’m not talking about a new way to characterize the nature of technology, nor am I talking about forming an abstract theory of technology. When I talk about a pragmatic philosophy of technology, I am not talking about creating a framing based on critical thinking and testing that helps us navigate the many ways that we as individuals and as groups enter and continue these relationships with technology.

In the final(?) part of this exploration, I will go into detail about my view of a pragmatic philosophy of technology and give you a couple of practices that will help you navigate your relationship with technology in a critical manner.

There is a Spotify playlist that I am making for this series, check it out here.

Why a Pragmatic Philosophy of Technology

I still remember hearing about Google forcing Timnit Gebru out of the company. Gebru was the co-lead of Google’s ethical AI team at the time. I was on Twitter quite a bit and her ouster forced a lot of people to think about the role that ethics play in technology. The think-pieces died off for a while, only to resurge with large language models (LLMs) entering the zeitgeist with the rise of ChatGPT, Bard, and other like models. There’s an interesting, but obvious, connection here; what resulted in Gebru’s ouster was a paper on the ethical concerns of LLMs (the linked paper details Gebru’s argument).

We now find ourselves in something being called an “AI boom”. This particular era of the AI boom has been spurred on by the companies that harbor the models I mentioned above. At the same time of this boom cycle, we are also seeing, as reported by the Washington Post, a massive increase in the layoffs of their ethicists/ethics teams. So, as companies see the economic benefit of pushing AI, they have also become aware of the economic impact that ethicists play on their bottom line when describing their tech’s downsides.

It is clear then that we can’t rely on tech companies to prioritize ethical considerations over profit maximization. Some of the best, most well-renown ethicists in the field cannot change a tech company from within (which is why, I imagine, Gebru founded the Distributed Artificial Intelligence Research Institute (DAIR)). What we then have to do is one, trust the experts in their fields, but secondly, have a framework by which we can learn to think more critically about technology ourselves and within our own organizations.

Current Default: Cults of Personality

YouTube has driven a new era of, and a new kind of cult of personality. This is best put on display in the paper “Charismatic authority and the YouTuber: Unpacking the new cults of personality”. Of course, this is continued through other social media platforms like TikTok.

The consequences of this are that if a culted figure describes x as the “next big thing” then that automatically drives the behavior of those in the group which has influences beyond. We can see very directly the results of this if you look at something like NFTs. In this case, however, YouTubers (and other social media influencers) catalyzed the cult of personality of another individual, Sam Bankman-Fried, who is currently facing “13 criminal counts, including securities fraud, money laundering, and campaign finance violations”. This article on CoinDesk covers this phenomenon pretty decently.

When we leave the decision of what tech to adopt to cult figures we surrender our decision-making capacity to them. I would like to say the situation in the Department of Defense (DoD is different than in the civilian world, but I feel that it’s worse. We thrive, generally speaking, on a particular kind of hero worship. This doesn’t just include war heroes, but “innovation heroes” (for more, but tangentially related about this topic check out this article about why innovation heroes are a bad sign, check out this article from Steve Blank), and other kinds of hero roles which leave people in a place of reverence. This reverence then translates to the capitulation of the revered figure’s influence.

Final Thoughts

We’re at an interesting/critical point in our history where if we don’t gain a better understanding of how we can critically evaluate and integrate technologies into our lives, then our futures will risk being driven by high-influence tech firms that have historically ignored ethics and public interest.

Next week I’ll be getting into a framing of pragmatism and the philosophy of technology, the final part will discuss the particular practices that embody the idea of a pragmatic philosophy of technology.

Obligatory: Since I’m discussing the DoD, I have to say that none of these thoughts are that of the DoD. These are my opinions and only reflect my hubris.