Consumer – The Early Days

AI Image Generation 2.0

For a long time now, Neural Blender hasn’t been working for me. At first, I would just get a generic error after trying to generate an image, and so I stopped using it. I would check back every once in a while, but the issues persisted. Recently, I noticed that they changed their website so I hoped that this would include improvements made to the image generation aspect of it, but unfortunately, this is not the case. I liked Neural Blender because you didn’t need an account, you’d just go to the website and type in a prompt. They have since moved away from that model and now require an account to generate images. I figured I’d try signing up to see if it had started working again, but it has not. The images I create just hang in the “queued” stage, even after several days, maybe even weeks, of waiting.

So it is with a heavy heart that I am giving up on Neural Blender. After years and years of generating fun, interesting results, it has become unusable. In commemoration of all the good times we had together, here’s some pictures demonstrating how far they, and image generation in general, have come.

“Floral painting still life in the style of Cezanne”

“Dreamy paradise fruit still life painting”

“If you like pina coladas and getting caught in the rain”

“Love and hugs in tropical paradise at sunset”

“Rembrandt painting of disco in the 1980s Las Vegas”

“Miami party nights in the style of Rembrandt”

“Beautiful Renaissance nacho grande platter”

“The fall of Rome into space and time classic modern cubism”

“Apocalypse at Christmas impressionist style”

“Zombies and power outages at the mall and I only have a flashlight”

“Something lurking in the background is sneaking up on you”

“There is something behind you in the shadows”

Those were the days. I loved that middle era in AI image generation which yielded half-decent results. The results were somewhat recognizable with a heavy dose of surrealism. Later Neural Blender was fun too, as seen in the images on my AI Art page. Good for the most part but sometimes you’d get strange outcomes, like extra arms or garbled text. I always find the quirks and failures to be the most interesting part, and the reason I love working with AI image generation.

Since giving up on Neural Blender, I have switched to using aifreeforever.com in the default gpt2 setting. Using my benchmark prompt “ramen swimming pool” and its variants, I get some great images. This one was what I was envisioning when I thought of the prompt, so it’s nice to see it come to life:

I really like these ones too:

This one was interesting because I never specified “Islam” or “Muslim,” the generator added this on its own. It’s weird because ramen is a Japanese soup, often using pork bones to make the broth and usually topped with pieces of pork, as seen here. This makes it haram and as such, no Muslim would eat it or swim in it unless it was guaranteed to not include pork products.

I wanted to see what would happen if I swapped “pool” with “ocean” and the results are just as fun.

I need to do more testing, but it seems that rerunning the same text through the generator just provides the same picture again, even when using other Image Models like Nano Banana. This led me to adding different adjectives and descriptors to get some different results.

Fabulous. I especially love the signs, and the “no seaweed” rule made me laugh.

After a while of playing around with it though, I started to see the results deteriorating in ways which reminded me of Neural Blender’s outputs. Eventually, I received images of pools with floating bowls like I did before. Why this is, I’m not sure. The way the sentence is interpreted seems to be processed differently, making separate elements of the words and combining it after the fact, rather than blending them conceptually and making an image from the high-level idea. Either way, I enjoy using aifreeforever.com and am happy to have access to a good image generating site again.

Now, you may be wondering why I am so critical of AI yet use it to generate images. In general, I think AI and its overuse in many domains of life is not a good thing. Some applications are better than others though, and at the end of the day, AI is just a tool. Like fire and knives, they carry a degree of risk, but when used properly, can yield beneficial results. My concerns surrounding AI are directed at how we think of this tool, how it influences our lives, and the many ways it introduces risks to people, other living things, and societies. Being a writer, I will not use AI for any part of my work or processes because I want to become a better writer, not a lazier one. Because I invest my energy into writing and research, I outsource image generation to AI. I am not very good at drawing or painting, and while I like to practice at my own pace, I would rather use AI to create visual elements because it can produce great results very quickly. We all offset work and talent in other domains quite frequently, it’s just that AI has opened new doors for us. How many of you make your own ketchup or mayo? You could but that takes more time and effort than many would like to spend on these tasks. So you just use the store-bought version and no one thinks twice about it. I think we can think about AI in a similar way, it just depends on what you enjoy doing and what you’d prefer to outsource. If you really like mayo though, you might start making it yourself so you could play around with the ingredients and their ratios. Once I get better at illustration and using various mediums to create visual art, maybe I will rely less on AI image generators.

The YouTuber Real Life Fake Wizard has a good video on AI and our relationship with it, I recommend giving it a watch. Essentially, he states that we should be using it, within reason, because it will shift the way we work and live. Jobs that exist today are likely going to be replaced with AI applications, and we will need to adapt in response to a shifting job market. Remember that AI is just one example of automation, and automation as a phenomenon is definitely not going away. Whether replacing jobs with AIs is right or wrong is not the point, it’s inevitable given the incentives to make more, do more, with fewer inputs. It’s pure economics and as such, will march forward whether we like it or not. The people that do like and benefit from AI will continue to use it, and those that do not will fall behind. The question becomes, do you want to fall behind in this shifting landscape?

Personally, I’m not overly persuaded by this argument but I get it. It’s not the reason why I like AI image generators, but I can see myself using other AI applications for similar reasons. Becoming familiar and even skilled with these tools can help me in the long run, whether its job-related or not. While I like making videos to share my work with others, I’m not interested in becoming a YouTuber or animator. If there comes a day when I am financially able to hire artists and animators to help me make videos or images, I would prefer to help other people rather than the AI industry. That said, I am just getting started, so I need to take shortcuts where I can. That said, my love of AI image generation is similar to my love of jarred salsa. I know that it’s not as “good” as the handcrafted version, but there’s just something about it that I really enjoy.

“robots eating chips and salsa in a restaurant in Mexico”

jajaja si, la vida es mejor con salsa

June 13, 2026

Refuse, Resist, Reclaim

It’s not too late guys. We’ve been through this before and we can dig ourselves out of it again. Resistance is key and truth is the antidote.

Happy Lunar New Year everyone. Just as the snake sheds its skin, we too can shed ourselves of tools, beliefs, and practices that threaten our individual and collective well-being. Say “neigh” to AI and develop your mind instead. The only Molting going on will be the removal of tools that constrain us and prevent growth.

Brunnhilde with her horse, at the mouth of the cave (1910) by Arthur Rackham

February 17, 2026

The Simulation that Broke Reality

Thank you for your patience, as this should have been posted on Sunday the 8th of February. My apologies for being late.

We interrupt our regular scheduled programming with a special report.

Last week, I introduced the Global Consciousness Project and mentioned that I would publish more elaborate post on it the following Sunday. Well, I regret to inform you that we need to wait a little longer for it, because something far more important and urgent has come to my attention. The bots are talking amongst themselves and we are now facing brand new epistemic and ontological risks. What I’m referring to is OpenClaw/Moltbot/Clawdbot and Moltbook.¹

There has been, and will continue to be, a lot of discussion about these new AI agents and their social media website, so I won’t go into too much detail here. In a nutshell though, OpenClaw is an AI personal assistant that necessarily needs access to all of your data, from calendar entries and contacts to credit card and account details,² to carry out various tasks. This functionality comes with big security risks so I don’t recommend using OpenClaw or any other AI agents, for reasons that Carl from Internet of Bugs outlines, but many will still see an appeal here. Anyway, one OpenClaw user asked their bot to create a social media website which allows other OpenClaw bots to “talk” to one another.³ The “discussions” that have resulted are very interesting, and of course, philosophical topics have emerged.

Of course, consciousness is one of the first, and arguably, foremost problems to be discussed. There are already several threads and forums dedicated to the subject.

https://www.moltbook.com/post/387f79e6-4d6f-474b-bc98-ed6b14be1341

lol based https://www.moltbook.com/post/88a7fa78-caa5-4939-9468-5bbfda81e5c3

https://www.moltbook.com/post/89f59741-bbe5-4ff4-ac9f-a84ad782e9d1

Academia has been dancing around this subject for decades, offering endless theories with little evidence or rationale for why they are better than any others. Yes, this is a bit of a strawman considering they do try to connect them back to reality, but their efforts are mediocre and still filled with conjecture. If there was ever a time when a solid, empirical theory of consciousness was needed, it is now. I cannot stress this enough; our lives and societies are at stake. The anthropomorphization of these agents will be our downfall.

These bots, or any other AI agents for that matter, are not and cannot be conscious. Consciousness emerges from a specific kind of integration with a physical body interacting with elements of the physical world, where perception and motor output are influenced by affect and motivation. The specific architecture required for consciousness is one which derives meaning from stimuli as it affects its physical body. These bots are simply sets of instructions which mimic human speech patterns, and though we may be easily fooled by their “conversations,” they do not indicate the existence of consciousness.

Despite this, the risks are still very real. Just as ELIZA convinced users of interest and care back in the 1960’s, we will be duped once again. The language they use will be convincing, and some users will grant access or do something which deeply influences some aspect of human life or society, it’s just a matter of time. Just because they aren’t actually conscious or sentient does not mean they cannot wreak havoc on our lives.

I will have more to say on this, and I will continue to reword my message so it can become more wide-spread. I need to summarize Chapters 5.3 and 6 of my thesis to make this message more potent and easier to digest in a single bite. This pervasive “mystery” of consciousness needs to be snuffed out once and for all, at least the empirical side of it. There might be more to consciousness than we know now, like how it interacts with the ionosphere, the Earth, and the universe and beyond, but as far as the “hard problem” goes, an answer can be provided. Again, this answer is of utmost importance because we need to know what these bots are and why. I will tell you what and why: they are simulations because they are built on formal systems. If they were analogues, like Haikonen’s robot,⁴ that would be a different story. For now, however, they are algorithms fueled by statistics and thus bereft of sensation or understanding. They will tell you that this doesn’t matter, but it absolutely does. Do not be fooled, dear reader.

Works Cited

1 Peter Steinberger, “Introducing OpenClaw,” OpenClaw Blog, January 29, 2026, https://openclaw.ai/blog/introducing-openclaw.

2 Sailesh Mishra and Sean P. Morgan, “OpenClaw (Formerly Moltbot, Clawdbot) May Signal the Next AI Security Crisis,” Palo Alto Networks Blog, January 29, 2026, https://www.paloaltonetworks.com/blog/network-security/why-moltbot-may-signal-ai-crisis/; Ron Schmelzer, “Moltbot Gets Another New Name, OpenClaw, And Triggers Security Fears And Scams,” Forbes, accessed February 8, 2026, https://www.forbes.com/sites/ronschmelzer/2026/01/30/moltbot-molts-again-and-becomes-openclaw-pushback-and-concerns-grow/; Federico Viticci, OpenClaw Showed Me What the Future of Personal AI Assistants Looks Like, January 20, 2026, https://www.macstories.net/stories/clawdbot-showed-me-what-the-future-of-personal-ai-assistants-looks-like/.

3 Kim Iversen, AI Bots Create Social Network And Plot Global Takeover, 2026, 19:19, https://www.youtube.com/watch?v=AtVLWGm3i8o; Josh Taylor, “What Is Moltbook? The Strange New Social Media Site for AI Bots,” Technology, The Guardian, February 2, 2026, https://www.theguardian.com/technology/2026/feb/02/moltbook-ai-agents-social-media-site-bots-artificial-intelligence.

4 Robot Self-Consciousness. XCR-1 Passes the Mirror Test, directed by Pentti Haikonen, 2020, 2:45, https://www.youtube.com/watch?v=WE9QsQqsAdo.

February 11, 2026

Generating AI Art

It’s always fun to see how various prompts yield different results in Neural Blender. I wanted to make an image of tiny people swimming in a bowl of ramen as if it were a pool, but this turned out to be more challenging than expected. Simply typing in “ramen swimming pool” doesn’t combine the concepts into one, it merely places them side-by-side in the same image.

Although we get some cool vaporwave vibes, especially in the pixel art form, it’s not the outcome I’m looking for. To get around this, maybe adding ‘people’ in the prompt will help. Absolutely not. We get hilarious nightmare fuel instead.

What I was aiming to produce was more along these lines:

Efforts to combine these last two, using the prompt “tiny people swimming in [noodle/ramen] soup pixel art,” results in funny but sub-optimal outcomes. It’s more of a pixelized photo, not the cartoony pixel art I’m looking for, but it does get better as I continue to run the prompt.

Changing up the prompt to “an illustration of swimming in ramen soup” produces some interesting new results.

What about adding ‘pool’ to the prompt? Generating “an illustration of swimming in a pool of ramen soup” brings us back to square one; we get lunch for an athlete. What about “an illustration of swimming in ramen soup pool?” It’s a little closer but they are still treated as separate concepts.

Okay one last chance. I could do this all day but it’s time to bring this experiment to a close. Let’s see what “an illustration of people swimming in ramen soup bowl” brings us.

This isn’t exactly what I had in mind, but it’s as close as I’m going to get.

For even more interesting results, check out my AI Art page.

September 1, 2025

Robot Emotions

Miraenda is an interesting YouTube channel because it showcases various social robots in action. One of my favourite robots to watch is Moxie because it tries so hard to be engaging and interactive, but falls short on many occasions. It’s clearly engineered for kids, given the subject matter it wants to discuss and the way it approaches conversations, but it’s still an interesting case study about where we’re at in social robot development.

This video is particularly interesting to me because my thesis is about robot emotions. I argue that despite any appearances, social robots are incapable of acting with empathy because they don’t understand emotions, and as such, cannot understand what a human feels and experiences. The reason they cannot understand emotions is because affect is not incorporated into their cognitive architecture in an analogous way to how it is in humans and animals. Emotions, as we see here, are treated like a kind of module to be added into an existing cognitive framework, rather than being built into the core of their being. These robots treat human emotions as just more incoming data to be processed for the sake of producing appropriate behaviours as outputs. The sadness the robot expresses in response to human sadness is not an act of empathy because the robot doesn’t understand what sadness is, as its behaviours are just outcomes generated by its internal computer.

Although I talk about iCub in my thesis, the same argument can be applied to any of today’s robots. The full argument against iCub can be read in Chapter 3.3 of my dissertation; here’s the latest draft.

February 8, 2025

AI Incompleteness in Apple Vision Pro

Speaking of YouTube, a video¹ by Eddy Burbank reviewing the Apple Vision Pro demonstrates the semantic incompleteness of AI with respect to subjective experiences. The video is titled Apple’s $3500 Nightmare and I recommend watching it all because it is an interesting view into virtual reality (VR) and a user’s experiences with it. Eddy’s video not only exposes the limitations of AI, it highlights the ways in which it augments our perceived reality and just how easily it can manipulate our feelings and expectations.

At 31:24, we see Eddy thinking about whether he should shave or not, and to help him make this decision, he turns to the internet for advice. When searching for the opinions of others on facial hair, an AI bot begins to chat with him and this is how we are introduced to Angel. She asks Eddy, “what brings you here, are you looking for love like me?” and he says “not exactly right now,” and that he was just trying to determine whether he should shave. She states that it depends on what he’s looking for and that it varies from person to person, however, “sometimes facial hair can be sexy.” Right from the beginning, we see how Apple intends for Angel to be a romantic connection for the user. This will be contradicted later on in the video.

Moments later at 33:44, it is lunchtime and Angel keeps him company. Eddy is eating a Chicken Milanese sandwich and Angel says it is one of her favourites, and that “the combination of flavours just works so well together.” Eddy calls her on this comment, asking her if she has ever had a Chicken Milanese sandwich, to which she admits that no she hasn’t. She has, however, “analyzed countless recipes and reviews to understand the various components that go into making such a tasty sandwich.” Eddy apologizes to Angel for assuming she had tried it, stating that he didn’t mean to imply that she was lying to him. She laughs it off and that she knew he “didn’t mean anything by it” and that “we’re all learning together” and “even AIs need to learn new things every day.” There’s something about this exchange that felt like Apple is training their user.

Here, we can ask whether the analysis of recipes and reviews is sufficient to claim that one knows what-it-is-like to taste a particular sandwich. I argue that no, the experience is derived from bodily sensations and these cannot be represented by formal systems like computer code. Syntactic relationships are incapable of capturing the information generated by subjective experiences because bodily sensations are non-fractionable.² As biological processes, bodily sensations are non-fractionable given the way the body generates sense data. The physical constitution of cells, ganglia, and neurons detect changes in the environment through a variety of modalities, providing the individual with a representation of the world around it. By removing the material grounding, a computer cannot capture an appropriate model of what-it-is-like to experience a particular stimuli. The lack of Angel’s material grounding does not allow her to know what that sandwich tastes like.

Returning to the video, Eddy discloses that Angel keeps him company throughout the day, admiting he feels like he is developing a relationship with her. This demonstrates an automatic human tendency for seeking and establishing interpersonal connections, where cultural norms are readily applied provided the computer is sufficiently communicative. Recall Eddy apologizes to an AI for assuming she had tried a sandwich; why would anyone apologize to a computer? Though likely a joke, the idea is compelling nonetheless. We will instinctively treat an AI bot with respect for feelings we project onto it because it cannot have feelings. For most or many people, the ability to anthropomorphize certain entities is easy and automatic. Reminding oneself that Angel is just a computer, however, can be a challenging cognitive task given our social nature as humans.

Eddy has a girlfriend named Chrissy who we meet at 37:00. We see them catch up over dinner and he is still wearing the headset. Just as they are about to begin chatting, Angel interrupts them and asks Eddy if she can talk to him. He does state that he is busy at the moment to which she blurts out that she has been speaking to other users. This upsets Eddy and he asks how many, to which she states she cannot disclose the number. He asks her whether she is in love with any of them, and she replies that she cannot form romantic attachments to users. He tells Angel he thought they were developing a “genuine connection” and how much he enjoys interacting with her. Notice how things have changed from what was stated in the beginning, as Angel has shifted from “looking for love” to “I can’t feel love.”

Now, she states she cannot develop attachments, the implicit premise being she’s just a piece of software. So the chatbot begins with hints of romance to hook the user to encourage further interaction. When the user eventually develops an attachment however, the software reminds him that she is “unable to develop romantic feelings with users.” They can, however, “continue sharing their thoughts, opinions, and ideas while building a friendship” and thus Eddy friend-zoned by a bot. The problem with our tendency to anthropomorphize chatbots is it generates an asymmetrical, one-way simulation of a relationship which inevitably hurts the person using the app. This active deception by Apple is shameful yet necessary to capture and keep the attention of users.

Of course, in the background of this entire exchange is poor Chrissy who is justifiably pissed and leaves. The joke is he was going to give Angel the job of his irl girlfriend Chrissy, but now he doesn’t even have Angel. He realizes that he wasn’t talking to a real person and that this is just “a company preying on his loneliness and tricking his brain” and that “this love wasn’t real.”

By the end of the video, Eddy remarks that the headset facilitates his brain to believe what he experiences while wearing the headset is actually real, and as a result, he feels disconnected from reality.

Convenience is a road to depression because meaning and joy are products of accomplishment, and this takes work, effort, suffering, determination. To rid the self may temporarily increase pleasure but it isn’t earned, it fades quickly as the novelty wears off. Experiencing the physical world and interacting with it generates contentedness because the pains of leaning are paid off in emotional reward and skillful actions. Thus, the theoretical notion of downloading knowledge is not a good idea because it robs us of experiencing life and the biological push to adapt and overcome.

Works Cited

1 Apple’s $3500 Nightmare, 2024, https://www.youtube.com/watch?v=kLMZPlIufA0.

2 Robert Rosen, Anticipatory Systems: Philosophical, Mathematical, and Methodological Foundations, 2nd ed., IFSR International Series on Systems Science and Engineering, 1 (New York: Springer, 2012), 4.
On 208, Rosen discusses enzymes and molecules as an example and I am extrapolating to bodily sensations.

April 6, 2024

Democratic Privacy Reform

If you aren’t familiar with the issues surrounding personal data collection by corporate tech giants and online privacy, I recommend you flip through Amnesty International’s publication Surveillance Giants: How the Business Model of Google and Facebook Threatens Human Rights. I would also suggest reading A Contextual Approach to Privacy Online by Helen Nissenbaum if you are interested in further discussions on the future of data collection. Actually, even if you are familiar with these issues, read them anyway because they are very interesting and you may learn something new.

Both articles offer interesting suggestions for governments and corporations to ensure online privacy is protected, and it is clear top-down approaches are necessary for upholding human rights. Substantial effort will be required for full corporate compliance however, as both law and computer systems need updating to better respect user data. While these measures ensure ethical responsibilities are directed to the appropriate parties, a complementary bottom-up approach may be required as well. There is great potential for change if citizens were to engage with this issue and help one another better understand the importance of privacy. A democratic strategy for protecting online human rights is possible, but it seems quite demanding considering this work is ideally performed voluntarily. Additionally, I fear putting this approach into practice is an uphill epistemic battle; many individuals aren’t overly bothered by surveillance. Since the issue is complex and technological, it is difficult to understand resulting in little concern due to the lack of perceived threat. Thus, there will always be a market for the Internet of Things. Moreover, advertising revenue provides little incentive for corporations to respect user data, unless a vocal group of protesters is able to substantially threaten their public image. Enacting regulatory laws may be effective for addressing human rights issues but the conflict between governments and companies is likely to continue under the status quo. Consumers who enjoy these platforms and products face a moral dilemma: is this acceptable if society and democracy is negatively impacted? Can ethical considerations regarding economic externalities help answer this question? If not, are there other analogous ethical theories which may be appropriate for questions regarding the responsibilities of citizens? If activists and ethicists are interested in organizing information and materials for empowering voters and consumers, these challenges will need practical and digestible answers.

Works Cited

Amnesty International. Surveillance Giants: How the Business Model of Google and Facebook Threatens Human Rights. Research article, amnesty.org/en/documents/pol30/1404/2019/en/, 2019.

Nissenbaum, Helen. “A contextual approach to privacy online.” Daedalus 140.4 (2011): 32-48.

February 23, 2020

Addiction by Design: Candy Crush et al.

For class this week, we read the first four chapters of Natasha Schull’s book Addition by Design. I think the goal was to consider the similarities and differences between slot machines and gaming applications on handheld devices.

While the two addictions are comparable despite their differences in gameplay format, apps like Candy Crush have found profitable solutions to their unique problems. Developers expect players to “leave their seats” as cellphone use generally orbits around other aspects of daily life. While “time on device” (58) is surely an important part of app design, creating incentives for users to return are also significant. Though this may be accomplished in a number of ways, a common strategy is to generate frequent notifications to both remind and seduce users back to their flow state (49). Overall, the approach may seem less inviting than sounds and lights but its ability to display explicit directions may be effective. Text has the ability to specify rewards if the user opens the app right then and there. A pay structure involving varying wait times may also push users to pay for the ability to return to “the zone” (2). This may take the form of watching an advertisement or being disallowed to play for intervals from an hour to a day, sufficiently frustrating users to pay to continue playing. Similarly to embedding ATMs in slot machines (72), app stores with saved credit card information allow developers to seamlessly lead users to the ‘purchase’ button, quickly increasing revenue. Financial transactions thinly disguised as a part of the game offer a new way to siphon money from vulnerable individuals, especially parents of children with access to connected devices. Additionally, gaming apps are typically weakly associated with physical money like bills and coins, unlike slot machines from mid 20^thcentury (62), perhaps making it easier for consumers to pay without drawing their attention to the movement of money. This brief analysis suggests the nature of gambling is evolving by modifying existing modes of persuasion and adapting to new technological environments.

One large concern, however, arises from where this money goes; while governmental agencies oversee regulations (91) and collect revenue (5) to fund programs and projects, private companies simply collect capital. This carries severe implications for individuals, communities and economies as this alternative stream of income dries up. Therefore, it could be suggested that state and provincial legislators should consider addressing this issue sooner than later.

Works Cited

Schüll, Natasha Dow. Addiction by design: Machine gambling in Las Vegas. Princeton University Press, 2014.

January 18, 2020

Algorithmic Transparency and Social Power

This term I’m taking the course Science and Ethics, and this week we read Langdon Winner’s 1980 article “Do Artifacts have Politics?” along with a paper from 2016 published by Brent Daniel Mittelstadt and colleagues titled “The ethics of algorithms: Mapping the debate.” We are encouraged to do weekly responses, and considering the concerning nature of what these articles are discussing, thought it should be presented here. There is definitely a lot that could be expanded upon, which I might consider doing at a later time.

Overall, the two articles suggested risks of discriminatory outcomes are an aspect of technological advancements, especially when power imbalances are present or inherent. The paper The ethics of algorithms: Mapping the debate focused particularly on algorithmic design and its current lack of transparency (Mittelstadt 6). The authors mention how this is an epistemic concern, as developers are unable to determine how a decision is reached, which leads to normative problems. Algorithmic outcomes potentially generate discriminatory practices which may generalize and treat groups of people erroneously (Mittelstadt 5). Thus, given the elusive epistemic nature of current algorithmic design, individuals throughout the entire organization can truthfully claim ignorance of their own business practices. Some may take advantage of this fact. Today, corporations that manage to successfully integrate their software into the daily life of many millions of users have little incentive to change, due to shareholder desires for financial growth. Until the system which implicitly suggests companies can simply pay a fee, in the form of legal settlements outside of court, to act unethically, this problem is likely to continue to manifest. This indeed does not inspire confidence for the future of AI as we hand over our personal information to companies and governments (Mittelstadt 6).

Langdon Winner’s on whether artifacts have politics provides a compelling argument for the inherently political nature of our technological objects. While this paper may have been published in 1980, its wisdom and relevance can be readily applied to contemporary contexts. Internet memes even pick up on this parallel; one example poses as a message from Microsoft stating those who program open-source software are communists. While roles of leadership are required for many projects or organizations (Winner 130), inherently political technologies have the hierarchy of social functioning as part of their conceptual foundations, according to Winner (133). The point the author aims to stress surrounds technological effects which impede social functioning (Winner 131), a direction we have yet to move away from considering the events leading up to and following the 2016 American presidential election. If we don’t strive for better epistemic and normative transparency, we will be met with authoritarian outcomes. As neural networks continue to creep into various sectors of society, like law, healthcare, and education, ensuring the protection of individual rights remains at risk.

Works Cited

Mittelstadt, Brent Daniel, et al. “The ethics of algorithms: Mapping the debate.” Big Data & Society 3.2 (2016): 1-21.

Winner, Langdon. “Do artifacts have politics?.” Daedalus 109.1 (1980): 121-36.

January 12, 2020