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  "description": "As a Black software engineer and leftist in the United States, I contend with the notion that generative artifical intelligence can be used in a materialistic way that moves the needle forward for progress without intrenching the power of capitalists and business folks who are adamant on exacerbating existing calamities within the technology sector.\n",
  "path": "/essays/2025/left-ai",
  "publishedAt": "2025-10-27T16:00:00.000Z",
  "site": "at://did:plc:e2ctbutx6kya6si4if5ngjmm/site.standard.publication/3mniussyp2d2g",
  "tags": "essay",
  "textContent": "I posted a question [on Bluesky][1] about the placement that leftists\ncan occupy when it comes to generative artificial intelligence. Since 2023, I've\npassively explored the use cases of generative AI, specifically in the case of\nsoftware development; my primary field of work. My background has forced me to\ntake a collectivist perspective when looking at the impact of it on balancing\nlabor's power and how the tech industry, despite its brief support of\nprogressive campaigns, has a knack for falling back to its roots of putting the\nlevers of finance over anything else. Putting it more plainly, I'm less\ninterested in the shiny things that come from the industry I'm in and more\nfocused on the immediate and planned impact of what comes from it. I've\nalso taken some time to observe a lot of the opinions and stances of folks who\nhave more sway and influence that I do in this industry as well folks who've\nexisted in my orbit for some time to juxtapose against the position I'm forming\nhere.\n\nFirst things first; if the following things don't click, then I don't think\nmuch can be said going forward that you'd be able to gleam from what I'm\nexpressing here:\n\n- The technology industry, within the United States, has routinely required\n  [extraction of resources][37] and [labor][35] from other parts of the world\n  with very little being given back to those places.\n- The technology industry has reshaped dozens of [social norms][38] &mdash;\n  dramatically in my life (as [a 1990s millennial][39]) from payphones to cellphones\n  and even more so for my younger siblings (of the 2000s Gen-Z contingency).\n- The technology industry has yet to [be held accountable][40] to _any sort_ of\n  power for [any of the (harmful) actions that has happened under its watch][36].\n\nThis also won't be the last thing I write on this topic, unfortunately, because\nit's a complex topic. With that said, let's get into it.\n\nWhen Rich Workers and Executives Walk Post on Hacker News\n\nDespite what [someone who _probably_ makes more][2] than half of Americans\nmentioned about the weakness of tech labor, the scene for the such has been\n[swelling since 2018][7] &mdash; something [I've helped contribute to][41]. Due\nto such a rise, this has me looking at what opportunities management in\nindustry [can, will and have taken][19] with their levers of control. This came\nto be of importance after the sale of Twitter by Jack Dorsey and its board to\nElon Musk, notably when we saw how the company was able to keep running at a\nmoderately okay pace [despite firing 6,000 people][4]. The company dipped in\nmarket valuation for some time but capital management, especially when in\nbalance with the State helped bring it back up, according to the [Wall Street\nJournal][5]. Fortunately, a lot of the workers who _had_ the ability to find\nnew work have ended up in places like Tiktok, Facebook and Google &mdash; all\nplaces (sans Tiktok?) that also have experienced a wave of layoffs. There's a\nneed to keep in mind that as generative AI becomes better at convincing\nmanagement, there's more need to put in levers _against_ hot swapping folks in\nfavor of it. Although Musk didn't declare this with his move, as far as we\nknow; that kind of behavior proved something that Thomas Ptacek of fly.io and\nElon Musk agree on (emphasis mine):\n\n> LLMs really _might displace many software developers_. That’s not a high\n> horse we get to ride. Our [software developers] jobs are just as much in\n> tech’s line of fire as everybody else’s have been for the last 3 decades.\n> We’re not East Coast dockworkers; we won’t stop progress on our own.\n\nDespite being a [statist][20] (which Musk would also considered himself to be),\nThomas seem to be more in favor of [private governance][6] versus public. Their\nlack of depth when it comes to what tech workers have been fighting towards,\nwhich even ChatGPT is able to poorly produce in a query about tech workers\norganizing highlights this disconnect &mdash; even to a point of where tech\nworkers who are in the organizing space _supported_ (fiscally and otherwise)\nthe East Coast dockworkers and their strikes. It's not something you'll find if\nyou find places like Hacker News to be the sole perspective of the tech\nindustry. I invite them to reevaluate this position after reading this in full\n(if they ever do). Statists are conventionally folks who are in favor of big\ngovernance, and to ignore how Musk _relied_ on strong (capitalist-centric)\ngovernance; the same way a _lot of_ American tech companies do seems like an\noversight by Thomas.\n\nSteve Klabnik has written about [their dismay in the generative AI\ndiscourse][26], which reads as a want from \"both sides\" to do better in how\nthey approach conversations around the topic. He linked to another piece, by\nJames Dennis, that takes [a perspective on art and creativity][27] to highlight\nthat humans (people?) will continue to create and produce novel things _in\nspite of_ generative works. Another one is more specific to software\nengineering, about the eventual decay of the \"craft\" of software engineering\nthat [books][28] and [conferences][29] have formed around peoples' cleverness,\nthrough the lens of [the software engineer's identity crisis][30]. These sit\ncloser to the \"center-right\" (bear with me) position on how one can look at\nthis technology and how it impacts the craft. Unfortunately, it ends in a way\nthat reinforces the notion of forced evolution of a field as necessary to\ngrowth. As someone who's worked in public consulting for a short period of\ntime; the last thing you want to do is _rush ahead_ with a trend or sense of\nprogress because Hacker News prescribes it. In fact, it's always wiser to give\nit time to iron out. However, there's more positions that lean towards\nsomething you'd expect Ptacek to agree with in a piece by Campos on the notion\n[that AI criticism has become lazy][31]. These stances tend to lean toward what\nyou'd find as you read [_The Network State_][32]; a book that over indexes\ntowards techno-solutionism as the end-all-be-all and a means of saving us from\nourselves. Notably, this piece would fit in around the third chapter in\nBalaji's book, around [tripolarality in power][33] since points are declared\ntowards succumbing education towards technology despite the strongest\nproponents for \"ethical AI in education\" tend to [be the biggest\nbullshitters][34]. It does end with this a semi-honest point that capitalism\ncurrently dictates the direction of this industry but with no real\ncall-to-action despite demanding more from the space of criticism, which is\ndisappointing because it gives AI proponents _more of an excuse_ to do nothing\nabout most of the issues Campos outlined.\n\nLeveraging Generative AI for the Public?\n\nThe thing that folks do like to mention, especially in my left-leaning circles,\nwhen it comes to generative AI, is China's introduction of smaller, cheaper and\nefficient LLMs that can, at times, outperform the American made ones. This\nseems to be a habit with Eastern technology &amp; from cars to computer\nmanufacturing. The most notable one is the ones produced by its namesake,\n[DeepSeek][8]. As mentioned, I've been testing some use cases with these\nsolutions at home, most recently with [ollama][9] and [aider][21], allowing\nme to flip between different downloaded models when working with them. The\noutput is moderately okay &mdash; if I give it a \"solved\" problem, it can get\nto a particular distance (~40% to 60%) before I need to intervene and correct\nthings. I struggle to replicate the level of performance that [Harper's company\nproduced with his journey into social \"agentic\" coding][11]. Despite it\nbeing described as not comparable to that of the output of an actual software\nengineer, folks are comfortable doing the software engineering equivalent\nof what they're [doing with OpenAI's Sora][23] (emphasis mine):\n\n> What’s also happening here is a massive _outsourcing of labor_. OpenAI has\n> cleverly packaged what would otherwise be expensive training and evaluation\n> work as a \"fun social experience.\" Every video prompt, every video tweak,\n> every video that gets shared or discarded, what goes viral, what doesn’t, is\n> training their video generation model. That’s all free labor _that would cost\n> millions_ to replicate in a controlled environment with paid testers. They’re\n> essentially getting millions of people to volunteer as unpaid quality\n> assurance testers, prompt engineers, and data labellers. They have gamified\n> reinforcement learning at scale.\n\nThe focus here is what I see mirrored in public sector work: a want to\n\"increase response times\" (or efficiency or whichever business-centric term\nyou'd like to improve) while not taking into consideration what _human_\ndecisions (almost always policy) that cause slowdowns and the like. What's\nhappening &mdash; as it tends to and was even noted by Thomas Ptacek in his\ncompany's blog and ignored in Campos' &mdash; is that folks who champion these\ntechnologies _rarely_ stop to consider how other people can use their tools for\nmalice. The Wright brothers didn't (couldn't?) and look how that turned out for\nthe future of war and invasion. A particular United States Marine Corps colonel,\nhowever, was already operating from a position of violence, on behalf of the\nstate and its interests, and had no issue asking for even _more_ efficiency in\nhow the M45 MEUSOC semi-auto pistol can be used &mdash; especially in places\nlike Iraq or by the Los Angeles Police Department.\n\nIn none of the pieces mentioned above was there any strong considerations\naround how generative artificial intelligence has increased the difficulty of\nfolks finding work due to the (now speculative but not improbable) case of\nlower ranking software engineering positions being made redundant. In fact, in\nAnnie's aforementioned post, they needed to rewrite history just a bit in order\nto justify a transformation in labor (emphasis mine):\n\n> The pendulum metaphor offers us wisdom here. Just as many of us have swung\n> between engineering and management roles, we can embrace a similar fluidity\n> with AI. Some periods we’ll dive deep into the code, experiencing that thrill\n> of crafting elegant solutions. Other times we’ll step back to guide AI\n> systems - not as overseers, but as master builders who understand every part\n> of their craft. Like the Industrial Revolution’s workers who became experts\n> at optimising the machines that transformed their craft, we can master these\n> AI systems - making them instruments of our creativity, not replacements for\n> it.\n\nIronically, [the term \"overseer\"][42] _is more apt_ since what an AI engineer\nis doing is \"guiding\" the outputs of a machine without a requirement of\nunderstanding the depth of the craft &mdash; that's the whole premise of [vibe\ncoding][43]. This rephrasing also helps to ignore what many workers of the\nIndustrial Revolution were against: hyper-specialized machinery that _directly_\nthreatened their ability _to work_ and _negotiate the terms of work_. This is\ndiscussed at length in Brian Merchant's latest book, [Blood in the\nMachine][44], in the brief chapter, \"The Machinery Question\" that discussed how\nthis perspective on the impact of machines on work depended on one's\nposition (and interest in placement) of class. In short, did one want to\nbe a worker of merit or an entrepreneur of control? Software engineering, post\nthe dot-com boom, has enjoyed a comfortable place in pay, especially in the\nUnited States, that has warped people's understanding of how [that loyalty is\nbought][45] (and can be easily retracted). Digging into the folks that helped\ncraft the _concept_ of modern overseers, or the professional managerial class,\nwe can see how [that also leaned on a system][46] that mimicked what Aristotelian\nphilosophy on the need for human exploitation towards automation (warning for\nthose uncomfortable with the linkage of technology and plantations due to their\nidentity and nationality):\n\n> To understand the link between Babbage’s engines and his theories of labor\n> control, we can first look to his view on automation itself. During Babbage’s\n> time, the term “engine” was a synonym for “machine” and was applied to the\n> swell of industrial machinery that was used to transform traditional labor\n> practices. His engines take their place alongside other mechanical tools for\n> labor automation, distinguished by their purposive automation of mental\n> (rather than manual) labor. Babbage understood automation generally—including\n> his engines—as dependent on the division of labor. He observed that “[t]he\n> division of labour suggests the contrivance of tools and machinery to execute\n> its processes,” reasoning that “[w]hen each process has been reduced to the\n> use of some simple tool, the union of all these tools, actuated by one moving\n> power, constitutes a machine.” Division and rationalization of\n> labor—specification of each piece of a given job in order to render the work\n> process (and the people doing it) observable, quantifiable, and controllable\n> “from above”—was, for Babbage, the enabling condition for automation. Thus,\n> in order to design engines to automate mental labor, Babbage first needed to\n> borrow (or develop) systems of labor division and control.\n\nYou can't divorce these notions without _actively_ ignoring history and present\nday impacts of technological innovation. Doing so is tremendously easy because\nit's not a requirement to download Microsoft's Visual Studio Code or to install\nWindsurf &mdash; the same way we see no lapse in a sense of judgement between\n[faciliating genocide for profit &mdash; in the form of state interest][47].\nThe _point_ here is that by choosing to narrow the scope of production and\nimpact to a point of comfort for one's discourse, folks are doing the work of\nthe alt-right in technology in the left spaces. This has to be something folks\nacknowledge lest we slide more and more developmental progress in their favor.\n\nCountermeasures in genAI\n\nI opened up this mentioning a collectivist perspective. It's a novel one for\nme, frankly, because I once did see technology as a means of giving folks more power\nin a world that has it held and hoarded by a few. It took me moving to\nCalifornia, closer to the American crux of technology worship to come to terms\nthat it is largely an extension of the means in which American capitalism\noperates. In fact, [Ruha Benjamin][13]'s book, [Race After Technology][14] makes\n_many_ cases &mdash; new to many, old to some &mdash; about how the most\nimmediate deployments of technology tend to have racial underpinnings to\noperate on behalf of a larger agenda of integrating what she calls [The New Jim\nCode][18]. Before we can begin to talk about democratizing AI, making it fit\nsome definition of open; we have to be honest about who it's being made open\nfor and what we're defining as accessible. Routinely, this is not for the folks\nwho could benefit from having more control over their indirectly leased\ntechnologies but for the folks who can afford thousand-dollar machines and\nphones _off_-lease. To this day, technology is made and optimized in the\nperspective of a white man. We have small efforts towards changing this but\nthey're not just far and few &mdash; they're intentionally underfunded and\ndriven out of sight. Relying on the mimicry of capital to drive a new direction\nwill result in its trend of burnout or worse for the founders and workers\ninvolved.\n\nThere's quite a few folks working on this from a perspective that recenter\npeople over the outputs of the machine. One of note is [_AI as Normal\nTechnology_][48]; a longer read that yoyos between wanting a (neo-)industrial\nagenda to push us towards allowing AI to be more deeply integrated into society\nand development such that it's not necessarily controlled by a few industry\ntitans. They're more honest about the progression of AI than more advocates:\n\n> According to the normal technology view, such sudden economic impacts are\n> implausible. In the previous sections, we discussed one reason: Sudden\n> improvements in AI methods are certainly possible but do not directly\n> translate to economic impacts, which require innovation (in the sense of\n> application development) and diffusion.\n>\n> Innovation and diffusion happen in a feedback loop. In safety-critical\n> applications, this feedback loop is always slow, but even beyond safety,\n> there are many reasons why it is likely to be slow. With past general-purpose\n> technologies such as electricity, computers, and the internet, the respective\n> feedback loops unfolded over several decades, and we should expect the same to\n> happen with AI as well.\n>\n> Another argument for gradual economic impacts: Once we automate something,\n> its of production, and its value, tend to drop drastically over time compared\n> to the cost of human labor. As automation increases, humans will adapt, and\n> will focus on tasks that are not yet automated, perhaps tasks that do not\n> exist today (in Part II we describe what those might look like).\n\nThey highlight a forecasting of what job closure and restructuring will\neventually look like given how generative artificial intelligence operates as a\n\"labor maximizer\" towards the end of Part II:\n\n> In addition to AI control, task specification is likely to become a bigger\n> part of what human jobs entail (depending on how broadly we conceive of\n> control, specification could be considered part of control). As anyone who\n> has tried to outsource software or product development knows, unambiguously\n> specifying what is desired turns out to be a surprisingly big part of the\n> overall effort. Thus, human labor—specification and oversight—will operate at\n> the boundary between AI systems performing different tasks. Eliminating some\n> of these efficiency bottlenecks and having AI systems autonomously accomplish\n> larger tasks “end-to-end” will be an ever-present temptation, but this will\n> increase safety risks since it will decrease legibility and control. These\n> risks will act as a natural check against ceding too much control.\n\nIt links [to one paper][49] that I've shared while working on a LLM\nproject to highlight my concern about the echo chamber of technology and\ngovernment:\n\n> What’s most notable is that McDermott’s warning is from 1984, when, like\n> today, the field of AI was awash with confident optimism about the near\n> future of machine intelligence. McDermott was writing about a cyclical\n> pattern in the field. New, apparent breakthroughs would lead AI practitioners\n> to predict rapid progress, successful commercialization, and the near-term\n> prospects of \"true AI.\" Governments and companies would get caught up in the\n> enthusiasm, and would shower the field with research and development funding.\n> AI Spring would be in bloom. When progress stalled, the enthusiasm, funding,\n> and jobs would dry up. AI Winter would arrive. Indeed, about five years after\n> McDermott’s warning, a new AI winter set in.\n\nAnil Dash [wrote on their blog that][50] runs counter to the above mentioned of\nartifical intelligence criticism being lazy: more on the point that a\n\"moderate\" position is nearly not possible/available in most spaces. I\ndisagree with this for a number of reasons made clear by [the number of\nconferences][51], product launches if one scrolls on LinkedIn and capital\nraised _in favor_ of promoting generative artificial intelligence. They've\nwritten themselves in enthusiasm of retrofitting a API standard for models to\ncommunicate _as groundbreaking_ as Web 2.0 itself &mdash; disrespectful to the\nactual gains of that space since it was something done collectively (despite\ncorporate capture) whereas the Model Context Protocol was an amplifying tool\nfor Amazon's Antrophic to enable what Doctorow describes as the flywheel effect\nof platform capitalism in [his book, Chokepoint Capitalism][52]. He's also\nwritten what _I think_ is the clearest definition of the MIT-license equivalent\nof [what good generative artificial intelligence model development][53] could\nlook like but this would require what China's doing &mdash; some level of state\nintervention or a wealthy benefactor to fund the basis of this research and\nwork. This wouldn't happen in a capitalist society, especially in the United\nStates, without some sort of nationalistic agenda to ramp up domestic talent.\n\nWait, so can there be a leftist position on AI?\n\nI actually don't think so &mdash; at least, not in a completely puritanical\nway. As I've mentioned, I've worked on providing generative AI solutions\nto government at work and I experiment with its efficacy largely to prevent the\nhype outputs to cloud my perspective, at least from an individual perspective.\nThe individual perspective also tends to be the limiting scope of most of the\nfolks I've mentioned above are approaching it. There's been little mention of\nhow we can reshape policy to handle this transition. Relying on executives\ndown to middle management to take a firmer stance yoyos between being beholden\nto investors to executives that lean into that Aristotelian stance mentioned\nearlier. So how does it move from that to one of a collectivist, people-centric\nposition?\n\nFrom a Labor Organizing Perspective\n\nIt is disappointing that [_AI As a Normal Technology_][48] danced around labor\nand softly ignored the impact of said productivity gains in relation to the\nsociopolitical [evolution of the landscape][54] as well as what regions of the\nworld [had to operate as the battery and labor][55]. This tends to result\nin the inherent utopian perspective of trusting industry leaders (or\ndevelopers) to do The Right Thing. This doesn't tend to work out in favor\nof the people who need it the most: folks who don't have a fleet of lawyers at\ntheir disposal or like me, folks who live in a state whose legislature down to\nthe local level are against any sort of progressive stances. So that returns us\nback to what we can do together as workers. I would love to see a sectoral\nbargaining unit across engineers, designers, lower management, product\nmanagers, researchers &mdash; the whole plethora of folks so we can stand\nshoulder to shoulder like the folks who keep your smartphone's network running,\nthe power that fuels your home and hobbies and the construction of the data\ncenters where you can run your instance of [Headscale][57] to get back to your\nhomelab from wherever you are in the worker-built world. This would push back\non what Ptacek initially mentioned about our inability of approach with\ndockworkers but it requires political education and a commitment to folks you\ndon't know as well. That's why events like [_Circuit Breakers_][58] are important\nso folks _can_ bond, learn about what steps we need to take to get here and\nlearn about meaningful tech labor history.\n\nFrom a Community Perspective\n\nI don't expect much to shift here, especially since the soft decline of\npeople-centric community events has been overtaken by corporate cosplay of the\nsuch. By cosplay, I mean the developer relations community spearheading, with\ncorporate funding, the moves to \"reboot\" community spaces that went dormant\nduring the (still ongoing) COVID-19 pandemic. Events like [WaffleJs][59] have\nbeen usurped by Google Developer communities and the like. And with the advent\nof generative AI, sidecar events are all about what folks are spending money on\nto make that they could have spent 30 more minutes developing themselves\n&mdash; or with a bit more curiosity.\n\nInstead, more work and effort needs to be spent on countering the systems that\nrely on the inputs of generative AI. This enters a level of \"black-hat\" work\nsince this would also pollute public datasets that folks would be using but\nunfortunately, until the larger actors that fund companies like\n<https://brightdata.com/> or even Google's own search proxying infrastructure,\nthis is necessary. More efforts in making things like [Glaze][60] and\n[Nightshade][61] more integrated in tools that folks use on a regular basis and\na means of submitting content for extending the efficacy of said tools.\nSocial media networks can allow folks to opt-in into such protections as\nthey're a hot target for non-consensual scraping. It's weird; these projects\ntechnically fall under generative AI since it also modifies images but since\nit's in the adverse position to prevent _further_ modifications, you'll rarely\nfind any advocates pushing in favor of it. That highlights how the advent of\nsuch production isn't necessarily around making the act of \"generating art\"\nmore accessible but mirrors the plantation-like behavior mentioned before\n(though coded with race &mdash; as technology inherently is):\n\n> The specter of the plantation that hangs over computation and industrial\n> labor regimes also speaks to the need to revisit the terms of \"free\"\n> industrial labor, and to recognize the contested process through which this\n> particular category of \"freedom\" was created and guaranteed. To do so, we\n> must directly confront the unmarked presence of Black unfreedom that haunts\n> \"free\" labor and reweave links that have been strategically severed between\n> race, labor, and computational technologies.\n\nPut differently, the production and training of this work is non-zero and the\nneed to move with the veneer of the such helps justifies further extraction of\nthe work of people for the sake of \"scratching a visual itch\".\n\n---\n\nIf you've read this all the way through, I appreciate any feedback and\ncorrections. As I started, my politics lead my stances and that means taking a\ncritical lens at the industry, its impact and the players within in. If I had\nto propose a \"critical\" reading list on AI that's balanced on its development\nand denigration; the following would be a start:\n\n- [Race After Technology][14] by Dr. Ruha Benjamin\n- [Empire of AI][book:1] by Karen Hao\n- [The Alignment Problem][book:2] by Brian Christian\n- [The AI Con][book:3] by Dr. Emily Bender and Dr. Alex Hanna\n- [Weapons of Math Destruction][book:4] by Cathy O'Neil\n- [AI Engineering: Building Applications with Foundation Models][book:5] by\n  Chip Huyen\n\nI hope this'll help advocates understand the contentions and history behind the\npush against this work. I also hope this helps anti-use proponents a sense of\nunderstanding of the scope of the space and avoid repetition of things that\nhave either debunked or made non-relevant. I don't think criticism or advocacy\nhas gotten lazy in its delivery but I do think that we need to consider more\n&mdash; not just the economic impact but the sociopolitical, cultural and\nsocietal impacts of this technology. We missed this opportunity with cellphones\nand the Internet - to a degree, so let's try now.\n\n[book:1]: https://en.wikipedia.org/wiki/Empire_of_AI\n[book:2]: https://brianchristian.org/the-alignment-problem/\n[book:3]: https://thecon.ai/\n[book:4]: https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction\n[book:5]: https://www.oreilly.com/library/view/ai-engineering/9781098166298/\n[1]: https://blacksky.community/profile/did:plc:e2ctbutx6kya6si4if5ngjmm/post/3m3y5pecnpc2z\n[2]: https://fly.io/blog/youre-all-nuts/\n[3]: https://jacobin.com/2025/05/south-african-unionists-international-solidarity\n[4]: https://www.cnn.com/2025/02/05/tech/musk-x-twitter-takeover-us-government-employee-advice/\n[5]: https://www.wsj.com/finance/banks-sell-5-5-billion-of-x-loans-after-investor-interest-surges-4b84f89c\n[6]: https://press.princeton.edu/books/hardcover/9780691176512/private-government\n[7]: https://collectiveaction.tech/data/\n[8]: https://en.wikipedia.org/wiki/DeepSeek#Overview_of_models\n[9]: https://ollama.com/\n[10]: https://www.nvidia.com/en-us/geforce/graphics-cards/geforce-gtx-760/specifications/\n[11]: https://harper.blog/2025/09/30/ai-agents-social-media-performance-lambo-doomscrolling/\n[12]: https://2389.ai/#team\n[13]: https://www.ruhabenjamin.com/\n[14]: https://www.ruhabenjamin.com/race-after-technology\n[18]: https://hyperallergic.com/593074/how-racial-bias-in-tech-has-developed-the-new-jim-code/\n[19]: https://www.ailayofftracker.com/\n[20]: https://en.wikipedia.org/wiki/State_capitalism\n[21]: https://aider.chat/\n[22]: https://antirez.com/news/153\n[23]: https://sineadbovell.substack.com/p/openais-endgame-starts-with-your\n[24]: https://antirez.com/news/155\n[25]: https://logicmag.io/supa-dupa-skies/origin-stories-plantations-computers-and-industrial-control/\n[26]: https://steveklabnik.com/writing/i-am-disappointed-in-the-ai-discourse/\n[27]: https://jmsdnns.com/tech/algo-underground/\n[28]: https://pragprog.com/titles/tpp20/the-pragmatic-programmer-20th-anniversary-edition/\n[29]: https://bangbangcon.com/\n[30]: https://annievella.com/posts/the-software-engineering-identity-crisis/\n[31]: https://redeem-tomorrow.com/the-average-ai-criticism-has-gotten-lazy-and-thats-dangerous#real-activists-ship\n[32]: https://thenetworkstate.com\n[33]: https://thenetworkstate.com/moral-power-martial-power-money-power\n[34]: https://arstechnica.com/ai/2025/09/education-report-calling-for-ethical-ai-use-contains-over-15-fake-sources/\n[35]: https://dyingforaniphone.com/\n[36]: https://www.hachettebookgroup.com/titles/malcolm-harris/palo-alto/9780316592031/?lens=little-brown\n[37]: https://us.macmillan.com/books/9781250284297/cobaltred/\n[38]: https://gretchenmcculloch.com/book/\n[39]: https://us.macmillan.com/books/9781250785756/lurking/\n[40]: https://en.wikipedia.org/wiki/Careless_People\n[41]: https://local1101.org/glitch\n[42]: https://www.wordnik.com/words/overseer\n[43]: https://blog.google/technology/developers/introducing-vibe-coding-in-google-ai-studio/\n[44]: https://www.hachettebookgroup.com/titles/brian-merchant/blood-in-the-machine/9780316487740/\n[45]: https://en.wikipedia.org/wiki/Golden_handcuffs\n[46]: https://logicmag.io/supa-dupa-skies/origin-stories-plantations-computers-and-industrial-control/\n[47]: https://en.wikipedia.org/wiki/Rohingya_genocide\n[48]: https://knightcolumbia.org/content/ai-as-normal-technology\n[49]: https://arxiv.org/pdf/2104.12871\n[50]: https://www.anildash.com/2025/10/17/the-majority-ai-view/\n[51]: https://www.digitalocean.com/resources/articles/best-ai-conferences\n[52]: https://pluralistic.net/2022/08/21/what-is-chokepoint-capitalism/\n[53]: https://www.anildash.com/2025/05/02/what-would-good-ai-look-like/\n[54]: https://shapingwork.mit.edu/wp-content/uploads/2023/08/PandP_Acemoglu-Johnson_July2023.pdf\n[55]: https://en.wikipedia.org/wiki/How_Europe_Underdeveloped_Africa\n[56]: https://www.backstage.com/magazine/article/sag-aftra-ai-deal-explained-76821/\n[57]: https://headscale.net/stable/\n[58]: https://techworkerscoalition.org/circuit-breakers/\n[59]: https://wafflejs.com/\n[60]: https://glaze.cs.uchicago.edu/\n[61]: https://nightshade.cs.uchicago.edu/",
  "title": "An exploration on what could be a leftist position on generative AI"
}