Lately I've been thinking of the much-hyped generative AI products of the last 2 years as anti-technology.

That may sound odd, since these are clearly technological artifacts in the way we've come to understand technology, and they're being produced by what's commonly called the tech sector. However, there are at least two ways in which these artifacts differ markedly from what we usually (used to?) think of as "technology":

(1) They tend to have a deskilling effect. The English word "technology" ultimately derives from the Greek word "tekhnē", which can be interpreted as meaning skill or craft. It's very much about a human being's ability to perform a task. Yet much of generative AI is aimed at removing human beings from a task, or minimizing our involvement. In that sense generative AI is very much anti-tekhnē

(2) They tend to lie squarely in what Albert Borgmann called "the device paradigm". L.M. Sacasas has several nice takes on Borgmann's distinction between devices and focal things. See https://theconvivialsociety.substack.com/p/why-an-easier-life-is-not-necessarily and also https://theconvivialsociety.substack.com/p/the-stuff-of-a-well-lived-life (and of course, read Borgmann himself!). Simply put, devices tend to hide their inner workings under a simplified "interface"; a device is a device “if it has been rendered instantaneous, ubiquitous, safe, and easy”, if it hides the means in favor of the ends. By contrast, focal objects tend to invite you into fully experiencing the focal practices they enable, to experience the means and the ends. In particular, they tend not to be easy: you have to engage with and learn to use them. Guitars are an interesting example of focal objects. To be (I hope not overly) simplistic, devices dumb you down while focal objects train you up. Devices are anti-tekhnē, and to the extent that current generative AI is created and deployed in the device paradigm, it is too.

None of this means generative AI has to be anti-tekhnē. I do admit though that I struggle to see how to make it less device-y, at least as it's currently made and used (I do have a few half-formed thoughts along these lines but nothing worth sharing).

#tech #dev #GPT #Gemini #Claude #LLaMa #LLM #Copilot #Midjourney #DallE #StableDiffusion #AI #GenAI #GenerativeAI

If I had the time, energy, and education to pull it off, I'd do some scholarship and writing elaborating on this juxtaposition:

- Statistics, as a field of study, gained significant energy and support from eugenicists with the purpose of "scientizing" their prejudices. Some of the major early thinkers in modern statistics, like Galton, Pearson, and Fisher, were eugenicists out loud; see https://nautil.us/how-eugenics-shaped-statistics-238014/
- Large language models and diffusion models rely on certain kinds of statistical methods, but discard any notion of confidence interval or validation that's grounded in reality. For instance, the LLM inside GPT outputs a probability distribution over the tokens (words) that could follow the input prompt. However, there is no way to even make sense of a probability distribution like this in real-world terms, let alone measure anything about how well it matches reality. See for instance https://aclanthology.org/2020.acl-main.463.pdf and Michael Reddy's The conduit metaphor: A case of frame conflict in our language about language

Early on in this latest AI hype cycle I wrote a note to myself that this style of AI is necessarily biased. In other words, the bias coming out isn't primarily a function of biased input data (though of course that's a problem too). That'd be a kind of contingent bias that could be addressed. Rather, the bias these systems exhibit is a function of how the things are structured at their core, and no amount of data curating can overcome it. I can't prove this, so let's call it a hypothesis, but I believe it.

#AI #GenAI #GenerativeAI #ChatGPT #GPT #Gemini #Claude #Llama #StableDiffusion #Midjourney #DallE #LLM #DiffusionModel #linguistics #NLP

I guess the #AI hype has been wearing off long enough that thoughtful critique can be published:

Participants who used AI produced fewer ideas, with less variety and lower originality compared to a baseline.

From https://dl.acm.org/doi/full/10.1145/3613904.3642919 , titled The Effects of Generative AI on Design Fixation and Divergent Thinking

This is something I'd expect because of anchoring. I'd expect a similar phenomenon when using generative AI to help with other kinds of ideation like writing or coding. Basically, your creative process gets stuck--anchored--on the first couple ideas. If you're generating those ideas with AI without taking account of this phenomenon, your overall process will tend to be less creative than if you hadn't used the AI. Surely there are ways to mitigate this effect but you have to be aware of it and practiced in those ways.

#GenAI #GenerativeAI #Midjourney #DALLE #StableDiffusion #art #ChatGPT #GPT #Copilot

Lately I've been thinking of recent generative AI as the equivalent of fast food for the mind.

#AI #GenAI #GenerativeAI #LLM #GPT #ChatGPT #Gemini #Llama #Copilot #Midjourney #StableDiffusion #DALLE

“Self-checkout could have been better integrated into supermarkets in ways that augmented and better-facilitated interactions between frontline workers and shoppers, but that design goal goes against the very reason they were adopted by retailers in the first place—to cut labor costs,” Mateescu says. “So the tool has a self-defeating logic to it from the get-go.”

From https://gizmodo.com/why-self-checkout-is-and-has-always-been-the-worst-1833106695 ; see also https://www.bloodinthemachine.com/p/understanding-the-real-threat-generative .

Generative AI could be an instance of what self-checkout or automated customer service phone trees are: what Brian Merchant ( @brianmerchant@mastodon.social ) dubs "shitty automation" in the first link, with a similar kind of self-defeating logic built into it from the start. If the only purpose of a technology is to cut labor costs for corporations, then there's a decent chance everyone, including the corporations deploying the technology, eventually suffers from it. One of the weirdest things to witness in this latest AI hype cycle is the enthusiastic deployment of a technology that may end up producing worse products and services at greater expense than the laid-off people who used to produce those products and services. It also threatens to leave behind a kind of technological detritus: even companies that recognize the cost and poor quality won't be able to remove it once it's entrenched. Why all the enthusiasm?

Obviously I have no way of knowing whether that's what comes to pass, but a lot of signs are pointing that way. I've already had a few conversations with people, including a CEO, who told me they felt like they had no choice but to deploy generative AI somehow, because all their customers were doing so. But like the most-photographed barn--which is the most-photographed barn because it's famous for being the most-photographed barn--this kind of justification is ephemeral white noise. You are putting yourself into a dangerous position by following it: this ouroboros will eat your business once it's done swallowing its own tail. Very strange to witness.

#AI #GenerativeAI #ChatGPT #GPT #Copilot #Midjourney #DALLE #WhiteNoise

I think A.I. is a poison to the creative process. I think it makes your work worse and makes you less interesting and less employable.

From: https://www.muddycolors.com/2024/04/the-a-i-lie/ by David Palumbo . I strongly recommend reading the whole post if this topic is of interest. I think it's absolutely spot on. This writer is coming from the perspective of a creative professional, but I'd expand this statement to include both scientific research and software development, two areas in which I've worked myself. By using the current generation of AI tools you are trading short-term convenience for long-term degradation, something I've analogized here before as eating your seed corn.

It has become standard to describe A.I. as a tool. I argue that this framing is incorrect. It does not aid in the completion of a task. It completes the task for you. A.I. is a service. You cede control and decisions to an A.I. in the way you might to an independent contractor hired to do a job that you do not want to or are unable to do. This is important to how using A.I. in a creative workflow will influence your end result. You are, at best, taking on a collaborator. And this collaborator happens to be a mindless average aggregate of data.

Another excellent point among many. I've called AI a tool in the past but I'm convinced by this framing of it as a service and would-be collaborator. Calling the current generation of AI a set of tools is providing cover for its more degrading effects.

Given all of this, I can not personally see anything attractive about using these programs in any capacity. Though they might dramatically speed up or replace parts of a workflow, the short and long term costs are appalling to me. It is removing my own hand, the single most valuable asset I possess, from the creation of my work.

Absolutely. If you do knowledge work, it's removing your own brain and mind from your work. If you've spent years and money educating yourself in a subject, why would you choose to throw that away and give over part of your work to a computer program?

#AI #GenerativeAI #ChatGPT #GPT #Midjourney #StableDiffusion #DALLE #Copilot #GithubCopilot

For all the surrealism of these tools’ outputs, there’s a banal uniformity to the results. When people’s imaginative energy is replaced by the drop-down menu “creativity” of big tech platforms, on a mass scale, we are facing a particularly dire form of immiseration.

From https://thebulletin.org/2022/10/ai-is-plundering-the-imagination-and-replacing-it-with-a-slot-machine/

#AI #Midjourney #DALLE #StableDiffusion #GenAI

Among the many reasons we should resist the widespread application of generative #AI an important, if less concrete, one is to preserve the freedom to change. This class of method crystallizes the past and present and re-generates it over and over again. The net result, if it's used en masse, is foreclosing the future.

If you're stats-poisoned: human flourishing requires the joint distribution of the future to be different from that of the past and present. We, collectively, form a non-stationary system, and forcing the human system to be stationary is a kind of violence.

#StableDiffusion #Midjourney #DALLE #GPT #ChatGPT #GenAI #AI

Nightshade 1.0 is out: https://nightshade.cs.uchicago.edu/index.html

From their "What is Nightshade?" page:

Since their arrival, generative AI models and their trainers have demonstrated their ability to download any online content for model training. For content owners and creators, few tools can prevent their content from being fed into a generative AI model against their will. Opt-out lists have been disregarded by model trainers in the past, and can be easily ignored with zero consequences. They are unverifiable and unenforceable, and those who violate opt-out lists and do-not-scrape directives can not be identified with high confidence.

In an effort to address this power asymmetry, we have designed and implemented Nightshade, a tool that turns any image into a data sample that is unsuitable for model training. More precisely, Nightshade transforms images into "poison" samples, so that models training on them without consent will see their models learn unpredictable behaviors that deviate from expected norms, e.g. a prompt that asks for an image of a cow flying in space might instead get an image of a handbag floating in space.

#Nightshade #Glaze #Midjourney #StableDiffusion #DALLE #DALL-E #AI #GenAI #generativeAI #art

To put it differently, these tools and techniques are drawing out the value of works created by creative people without replenishing the originators of that value. That's a horribly dehumanizing way of looking at it, as if people were value spigots, but that's the problem isn't it? This is a dehumanzing arrangement. We don't need to be doing this.

#ChatGPT #GPT #Midjourney #StableDiffusion #DALLE #AI

Regarding that last boost, I'm starting to conceive of LLMs and image generators as a phenomenon of (American) society eating its seed corn. If you're not familiar with the phrase, "seed corn" is the corn you set aside to plant next year, as opposed to the corn you eat this year. If you eat your seed corn this year, you have no seeds to plant next year, and thus create a crisis for all future years, a crisis that could have been avoided with better management.

LLMs and image generators mass ingest human-created texts and images. Since the human creators of the ingested texts and images are not compensated and not even credited, this ingestion puts negative pressure on the sharing of such things. Creative acts functioning as seed for future creative acts becomes depressed. Creative people will have little choice but to lock down, charge for, or hide their works. Otherwise, they'll be ingested by innumerable computer programs and replicated ad infinitum without so much as a credit attached. Seed corn that had been freely given forward will become difficult to get. Eaten.

Eating your seed corn is meant to be a last ditch act you take out of desperation after exhausting all other options. It's not meant to be standard operating procedure. What a bleak society that does this, consuming itself in essence.

#ChatGPT #GPT #Midjourney #StableDiffusion #DALLE #AI