On Fri, Dec 23, 2022, Luke Munn wrote: > At the core of all this, I think, is the instinct that there's something > unique about 'human' cultural production. [snip...] Terms like 'meaning', > or 'intention', or 'autonomy' gesture to this desire, this hunch that > something will be lost, that some ground will be ceded with the move to AI > image models, large language models, and so on. >
These are old (maybe antiquated?) problems that were central to Continental philosophy from Heiddeger to Gadamer, Levinas, Baudrillard and many others. Basically the questions are, Who am I and how do I guide my action amid a flood of normalizing or coercive cultural contents? How do I know and recognize the Other in his/her/their full otherness? As time goes by I have got more interested in Gadamer's focus on interpretation as the process whereby an individual or community sets their ethical/political course with respect to the expressions and actions of others. That will always be necessary in any society - exactly because there is no reliable benchmark, no fully original expression, no pre-given authentic self - so the process of interpretation becomes a creative and always provisional act. However, with statistically generated images you are in a sense alone in the room, there is no one to evaluate or answer to. Baudrillard has a great quote on this, which I used in my work on Guattari's Schizoanalytic Cartographies: "This is our destiny, subjected to opinion polls, information, publicity, statistics: constantly confronted with the anticipated statistical verification of our behavior, absorbed by this permanent refraction of our least movements, we are no longer confronted with our own will. We are no longer even alienated, because for that it is necessary for the subject to be divided in itself, confronted with the other, contradictory. Now, where there is no other, the scene of the other, like that of politics and of society, has disappeared. Each individual is forced despite himself into the undivided coherency of statistics. There is in this a positive absorption into the transparency of computers, which is something worse than alienation." Now, AI brings a new twist to all this: computers are no longer transparent, we don't exactly know how neural networks function. Like Harun Farocki in his explorations of machine vision, some people are now interpreting the expressions of the inscrutable AIs. There's a chance that humans will learn something fundamental about the potentials of their own intelligence through this process. However, it is equally or far more likely that entire populations will be massively confronted with statistical transforms of previous generations of statistically generated images, in the scenario that Francis outlines. What's more, it's exceedingly likely that the whole process of statistical image production will be carried on coercively by states and corporations, whose intentions will be masked by the statistical operations. The Baudrillardean worst-case is getting a lot closer to fulfillment. I would be glad to learn different perspectives on all this. It's why I joined this thread. All the best, Brian >> >> On Fri, Dec 23, 2022 at 8:54 AM Francis Hunger < >> francis.hun...@irmielin.org> wrote: >> >>> Dear Luke, dear All >>> >>> Interesting essay Francis, and always appreciate Brian's thoughtful >>> comments. I think the historical angle Brian is pointing towards is >>> important as a way to push against the claims of AI models as somehow >>> entirely new or revolutionary. >>> >>> In particular, I want to push back against this idea that this is the >>> last 'pure' cultural snapshot available to AI models, that future >>> harvesting will be 'tainted' by automated content. >>> >>> At no point did I allude to the 'pureness' of a cultural snapshot, as >>> you suggest. Why should I? I was discussing this from a material >>> perspective, where data for training diffusion models becomes the >>> statistical material to inform these models. This data has never been >>> 'pure'. I used the distinction of uncontaminated/contaminated to show the >>> difference between a training process for machine learning which builds on >>> an snapshot, that is still uncontaminated by the outputs of CLIP or GPT and >>> one which includes generated text and images using this techique on a large >>> scale. >>> >>> It is obvious, but maybe I should have made it more clear, that the >>> training data in itself is already far from pure. Honestly I'm a bit >>> shocked, you would suggest I'd come up with a nostalgic argument about >>> purity. >>> >>> Francis' examples of hip hop and dnb culture, with sampling at their >>> heart, already starts to point to the problems with this statement. Culture >>> has always been a project of cutting and splicing, appropriating, >>> transforming, and remaking existing material. It's funny that AI >>> commentators like Gary Marcus talk about GPT-3 as the 'king of pastiche'. >>> Pastiche is what culture does. Indeed, we have whole genres (the romance >>> novel, the murder mystery, etc) that are about reproducing certain elements >>> in slightly different permutations, over and over again. >>> >>> Maybe it is no coincidence that I included exactly this example. >>> >>> Unspoken in this claim of machines 'tainting' or 'corrupting' culture is >>> the idea of authenticity. >>> >>> I didn't claim 'tainting' or 'corrupting' culture, not even unspoken. >>> Who am I to argue against the productive forces? >>> >>> It really reminds me of the moral panic surrounding algorithmic news and >>> platform-driven disinformation, where pundits lamented the shift from truth >>> to 'post-truth.' This is not to suggest that misinformation is not an >>> issue, nor that veracity doesn't matter (i.e. Rohingya and Facebook). But >>> the premise of some halcyon age of truth prior to the digital needs to get >>> wrecked. >>> >>> I agree. Only, I never equaled 'uncontaminated' to a "truth prior to the >>> digital", I equaled it to a snapshot that doesn't contain material created >>> by transformer models. >>> >>> Yes, Large language models and other AI technologies do introduce new >>> conditions, generating truth claims rapidly and at scale. But rather than >>> hand-wringing about 'fake news,' it's more productive to see how they >>> splice together several truth theories (coherence, consensus, social >>> construction, etc) into new formations. >>> >>> I was more interested in two points: >>> >>> 1.) Subversion: What I called in my original text the 'data space' >>> (created through cultural snapshots as suggested by Eva Cetinic) is an >>> already biased, largely uncurated information space where image data and >>> language data are scaped and then mathemtically-statistically merged >>> together. The focus point here is the sheer scale on which this happens. >>> GPT-3 and CLIP are techniques that both build on massive datascraping >>> (compared for instance to GANs) so that it is only possible for well funded >>> organizations such as Open-AI or LAION to build these datasets. This >>> dataspace could be spammed a) if you want to subvert it and b) if you'd >>> want to advertise. The spam would need to be on a large scale in order to >>> influence the next (contaminated) iteration of a cultural snapshot. In that >>> sense only I used the un/contaminated distinction. >>> >>> 2). In response to Brian I evoked a scenario that builds on what we >>> already experience when it comes to information spamming. We all know, that >>> mis-information is a social and _not_ a machinic function. Maybe I should >>> have made this more clear (I simply assumed it). I ignored Brians comment >>> on the decline of culture, whatever this would mean, and could have been >>> more precise in this regards. I don't assume culture declines. Beyond this, >>> there have been discussions about deepfakes for instance and we saw that >>> deepfakes are not needed at all to create mis-information, when one can >>> just cut any video using standard video editing practices towards >>> 'make-believe'. I wasn't 'hand-wringing' about fake news, in my comment to >>> Brian, instead I was quoting Langlois with the concept of 'real fakes'. >>> Further I'm suggesting that CLIP and GPT make it more easy to automate >>> large scale spamming, making online communities uninhabitable or moderation >>> more difficult. Maybe I'm overestimating the effect. We can already observe >>> GPT-3 automated comments appearing on twitter or the ban of GPTChat posts >>> on Stackoverflow ( >>> https://meta.stackoverflow.com/questions/421831/temporary-policy-chatgpt-is-banned), >>> the latter already being a Berghain-no-photo-policy. >>> >>> Finally, I'm interested in the question of bias and representation, and >>> how a cultural snapshot, that builds on a biased dataset (and no, I'm not >>> saying there are unbiased datasets at all), can further deepen these biases >>> with each future interation, when these bias get statistically reproduced >>> through 'AI' and the become basis for the next dataset. >>> >>> best >>> >>> Francis >>> >>> >>> nga mihi / best, >>> Luke >>> >>> >>> On Tue, 20 Dec 2022 at 22:20, Francis Hunger < >>> francis.hun...@irmielin.org> wrote: >>> >>>> Hi Brian, >>>> >>>> On Mon, Dec 19, 2022 at 3:55 AM Francis Hunger < >>>> francis.hun...@irmielin.org> wrote: >>>> >>>>> While some may argue that generated text and images will save time and >>>>> money for businesses, a data ecological view immediately recognizes a >>>>> major >>>>> problem: AI feeds into AI. To rephrase it: statistical computing feeds >>>>> into >>>>> statistical computing. In using these models and publishing the results >>>>> online we are beginning to create a loop of prompts and results, with the >>>>> results being fed into the next iteration of the cultural snapshots. >>>>> That’s >>>>> why I call the early cultural snapshots still uncontaminated, and I expect >>>>> the next iterations of cultural snapshots will be contaminated. >>>>> >>>> >>>> Francis, thanks for your work, it's always totally interesting. >>>> >>>> Your argumentation is impeccable and one can easily see how positive >>>> feedback loops will form around elements of AI-generated (or perhaps >>>> "recombined") images. I agree, this will become untenable, though I'd be >>>> interested in your ideas as to why. What kind of effects do you foresee, >>>> both on the level of the images themselves and their reception? >>>> >>>> Foresight is a difficult field, as most estimates can extrapolate >>>> maximum 7 year into the future and there are a lot of independent factors >>>> (such as e.g. OpenAI, the producer of CLIP could go bankrupt etc.). >>>> >>>> It's worth considering that similar loops have been in place for >>>> decades, in the area of market research, product design and advertising. >>>> Now, all of neoclassical economics is based on the concept of "consumer >>>> preferences," and discovering what consumers prefer is the official >>>> justification for market research; but it's clear that advertising has >>>> attempted, and in many cases succeeded, in shaping those preferences over >>>> generations. The preferences that people express today are, at least in >>>> part, artifacts of past advertising campaigns. Product design in the >>>> present reflects the influence of earlier products and associated >>>> advertising. >>>> >>>> That's an great and interesting argument. Because it plays into the >>>> cultural snapshot idea. >>>> >>>> Obviously Language wise, people already use translation tools, such as >>>> Deepl and translate Text from German to English and back to German in order >>>> to profit off the "clarity" and "orthographic correction" brought by the >>>> statistical analysis that feeds into the translator and seems to straighten >>>> the German text. We see the same stuff appearing for products like text >>>> editors and thus widely employed for cultural production. That's one >>>> example. Automated forum posts using GPT-3, for instance on Reddit are >>>> another, because we know that the CLIP Model also partly build on Reddit >>>> posts. >>>> >>>> Another example is images generated using diffusion models and prompts >>>> building on cultural snapshots and being used as _cheap_ illustrations for >>>> editorial products, feeding off stock photography and to a certain extend >>>> replacing stock photography. This is more or less an economic motivation >>>> with cultural consequences. The question is what changes, when there is not >>>> sufficiently 'original' stock photography circulating, but the majority is >>>> syntheticly generated? Maybe others want to join in, to speculate about it. >>>> >>>> We could further look into 1980s HipHop or 1990s Drum'n Bass sample >>>> culture, which for instance took (and some argue: stole) one particular >>>> sound break, the Amen Break, from an obscure 1969 Soul music record by The >>>> Winston Brothers and build a whole cultural genre from it. Cf. >>>> https://en.wikipedia.org/wiki/Amen_break Here the sample was refined >>>> over time, with generations of musicians cleaning the sample (compression, >>>> frequencies, deverbing, etc.) and providing many variations of it, then >>>> reusing it, because later generation did not build on the original sample, >>>> but on the published versions of it. >>>> >>>> We can maybe distinguish two modi operandi where a) "the cultural >>>> snapshot" is understood as an automated feedback loop, operating on a large >>>> scale, mainly through automated scraping and publication of the derivates >>>> of data, amplifying the already most visible representations of culture and >>>> b) "the cultural snapshot" is a feedback loop with many creative human >>>> interventions, be it through curatorial selection, prompt engineering or >>>> intended data manipulation. >>>> >>>> Blade Runner vividly demonstrated this cultural condition in the early >>>> 1980s, through the figure of the replicants with their implanted memories. >>>> >>>> I dont know if I get your point. I'd always say that Blade Runner is a >>>> cultural imaginary, one of the many phantasms about the machinisation of >>>> humans since at least 1900 if not earlier, and that's an entirely different >>>> discussion then. I would avoid this as an metaphor. >>>> >>>> The intensely targeted production of postmodern culture ensued, and has >>>> been carried on since then with the increasingly granular market research >>>> of surveillance capitalism, where the calculation of statistically probable >>>> behavior becomes a good deal more precise. The effect across the neoliberal >>>> period has been, not increasing standardization or authoritarian control, >>>> but instead, the rationalized proliferation of customizable products, whose >>>> patterns of use and modification, however divergent or "deviant" they may >>>> be, are then fed back into the design process. Not only the "quality of the >>>> image" seems to degrade in this process. Instead, culture in general seems >>>> to degrade, even though it also becomes more inclusive and more diverse at >>>> the same time. >>>> >>>> When looking for a plausible scenario regarding synthetic text and >>>> synthetic images, Steve Bannons “The real opposition is the media. And the >>>> way to deal with them is to flood the zone with shit.” is sadly a good >>>> candidate. This ties in with what Ganaele Langlois posits: >>>> >>>> „Therefore: communicative fascism posts that what is real is the >>>> opposite of social justice, and we now see the armies of ‚Social Injustice >>>> Warriors‘ as Sarah Sharma (2019) calls them, busy typing away at their >>>> keyboards to defend the rights to keep their fear of Others unchallenged >>>> and to protect their bigotry, misogyny, and racism from being debunked as >>>> inept constructions of themselves“ Langlois 2021:3 >>>> >>>> „The first aspect of this new communicative fascism is related to what >>>> can be called ‚real fakes_ that is to say, the construction of a fictional >>>> and alternative reality where the paranoid position of fear and rage can >>>> find some validation … Real fakes are about what reality ought to be: they >>>> are virtual backgrounds on which fascists can find their validity and >>>> raising’être.“ Langlois 2021:3f >>>> >>>> So this is to be expected both for political or consumer marketing >>>> purposes. >>>> >>>> AI is poised to do a lot of things - but one of them is to further >>>> accelerate the continual remaking of generational preferences for the needs >>>> of capitalist marketing. Do you think that's right, Francis? >>>> >>>> That's one possible reading. I would insist, to not use an active verb >>>> with AI however, rephrasing your point towards "AI may be used for a lot of >>>> things". Better even replace 'AI' with the term 'statistical computation'. >>>> >>>> Currently I would read 'AI' as a mixture of imaginations and phantasms >>>> about automation, of which some may become true – just in another way from >>>> what was expected or promoted. For certain, the inner logics of capital >>>> circulation command to deploy statistical computation to replace living, >>>> human labor. We already see how the job description of translators changes >>>> towards an human–statistical_computation entanglement and how the >>>> repetetive parts of the illustrator job, like coloring get automated away >>>> and put people out of jobs and it is plausible to expect the consolidation >>>> of jobs like photo editor, news editor, author with prompt-engineering. >>>> Since we are concentrating on the cultural sphere here, I'll limit the >>>> examples to this field. Human Labor in production, logistics, care labor >>>> would need their own thoughts. >>>> >>>> What other consequences do you see? And above all, what to do in the >>>> face of a seemingly inevitable trend? >>>> >>>> We are going to create separate data ecologies, which prohibit spamming >>>> the data space. These would be spaces, comparable to the no-photo-policy in >>>> clubs like Berghain or IFZ with a no-synthetics policy. While vast areas of >>>> the information space may be indeed flooded, these would be valuable zones >>>> of cultural exchange. (The answer would be much longer indeed, but we're >>>> not writing a book here). >>>> >>>> >>>> >>>> best, Brian >>>> >>>> -- >>>> Researcher at Training The Archive, HMKV Dortmund >>>> >>>> Artistic Practice http://www.irmielin.org >>>> Ph.D. at Bauhaus University Weimar http://databasecultures.irmielin.org >>>> >>>> Daily Tweets https://twitter.com/databaseculture >>>> >>>> >>>> Peter and Irene Ludwig guest professorship at the Hungarian University of >>>> Fine Arts in Budapest 2022/23 >>>> >>>> # distributed via <nettime>: no commercial use without permission >>>> # <nettime> is a moderated mailing list for net criticism, >>>> # collaborative text filtering and cultural politics of the nets >>>> # more info: http://mx.kein.org/mailman/listinfo/nettime-l >>>> # archive: http://www.nettime.org contact: nett...@kein.org >>>> # @nettime_bot tweets mail w/ sender unless #ANON is in Subject: >>> >>> -- >>> Researcher at Training The Archive, HMKV Dortmund >>> >>> Artistic Practice http://www.irmielin.org >>> Ph.D. at Bauhaus University Weimar http://databasecultures.irmielin.org >>> >>> Daily Tweets https://twitter.com/databaseculture >>> >>> >>> Peter and Irene Ludwig guest professorship at the Hungarian University of >>> Fine Arts in Budapest 2022/23 >>> >>> # distributed via <nettime>: no commercial use without permission >>> # <nettime> is a moderated mailing list for net criticism, >>> # collaborative text filtering and cultural politics of the nets >>> # more info: http://mx.kein.org/mailman/listinfo/nettime-l >>> # archive: http://www.nettime.org contact: nett...@kein.org >>> # @nettime_bot tweets mail w/ sender unless #ANON is in Subject: >> >> # distributed via <nettime>: no commercial use without permission >> # <nettime> is a moderated mailing list for net criticism, >> # collaborative text filtering and cultural politics of the nets >> # more info: http://mx.kein.org/mailman/listinfo/nettime-l >> # archive: http://www.nettime.org contact: nett...@kein.org >> # @nettime_bot tweets mail w/ sender unless #ANON is in Subject: > >
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