I attended a small event this week. When entering the room they asked for everyone to leave their phone in a box, to be claimed on exit. “So that people would talk more.”
At the end of the event, the embargo being lifted and everyone still being encouraged to talk, most people lined-up to get their phone… so they could walk back in the room and all dive into the matrix, silent.
Would asking people to show self-control and not use their phones have worked better? In this case they were confiscated and people just grabbed them again as fast as they could.
This week: AI Can Thrive in Open Societies / The Past, Present, and Future of AI Art / Save Our Food. Free the Seed. / Rethinking Technological Positivism / Feminist cyborg scholar Donna Haraway.
Bruce Schneier and James Waldo take aim at the “China is an unrestrained surveillance state, thus has more data, thus will kick everyone’s ass in AI” trope. They don’t look that much at US and Chinese societies but give a number of reasons why AI doesn’t / shouldn’t / won’t always require massive amounts of data to work, and argue that the way research in the field is done is not something you can just throw military money at, like nuclear. In issue No.80, commenting on A new way to build tiny neural networks could create powerful AI on your phone, I wrote the following, which seems to align quite well with the Schneier-Waldo piece: “The smaller networks possibility, paired with the advances in synthetic data, and the fact that some AIs can be based on much smaller data sets for training, points the way (I reckon) to AIs which would require smaller investments and be possible in more places / companies.”
Current machine learning techniques aren’t all that sophisticated. All modern AI systems follow the same basic methods. Using lots of computing power, different machine learning models are tried, altered, and tried again. … The different layers will try different features and will be compared by the evaluation function until the one that is able to give the best results is found, in a process that is only slightly more refined than trial and error. […]
All data isn’t created equal, and for effective machine learning, data has to be both relevant and diverse in the right ways. […]
Just adding more data may help, but not nearly as much as added research into what to do with the data once we have it. […]
AI is a science that can be conducted by many different groups with a variety of different resources, making it closer to computer design than the space race or nuclear competition.
No.85 Asides ⊕ See Note
- Rethinking Technological Positivism with Cory Doctorow. 🎙 Interview on the CoRecursive podcast. Doctorow sometimes takes shortcuts in his explanations but he’s always very entertaining and all the issues he talks about are important and usually worrying. Very much worth a listen, especially on monopolies and why software has power.
- ⌨️ Ian Bogost on What It’s Like to Work on a 30-Year-Old Macintosh and Game of Thrones author George R.R. Martin explains why he writes on a DOS machine.
- 🥵 Zeke Hausfather 🧵on Twitter “This is an amazing visualizations by @alxrdk showing global temperatures from 1850 to today, and different pathways we might take in the future. This definitely wins the award for best warming stripes in my book!” (Supposedly the emissions peak for the best case scenario actually needs to be even earlier.)
- Medieval Indonesia 🧵 on Twitter: “One of the most persistent tropes about Indonesia in the Middle Ages is the one about “Arab traders”.It’s a common assertion: The spice trade was in the hands of the Arabs before the Portuguese arrived. Arab sailors. Arab ships. 1001 Nights.”. “Is it really so hard for people nowadays to conceive of a multipolar pre-colonial world in which no single region holds all the cards? Apparently it is. But that’s what the medieval world was like.” (Keep reading to the replies for some sources.)
- 🎙 The Time Sensitive podcast. “[F]eatures candid, revealing portraits of curious and courageous people in business, the arts, and beyond who have a distinct perspective on time.” It’s the first project by The Slowdown, who do “[s]hort-form content with a long view. Focused on culture, nature, and the future.” Quite interesting.
- 🚆 Once Threatened, Europe’s Night Trains Rebound. ““Public opinion is changing compared to a few years ago, when night trains were considered old-fashioned and nostalgic, something from the past, [n]ow it’s considered a serious alternative to flying which should be redeveloped.”
- 🚲 Why the soft machine will dominate urban transport. “The rise of this apparently old-fashioned technology suggests to many observers that, despite the widespread excitement about the prospects for self-driving cars and air taxis, the future of mobility in old and crowded cities is likely to be powered by human muscle.”
- 👽 What We Know About the Navy’s UFO Problem. “The craft sighted in 2014-2015 also reportedly performed aerial acrobatics that known aircraft are unable to perform—and that would turn a human pilot into a red goo due to the tremendous g-forces involved. The craft moved at “hypersonic” speeds—hypersonic defined as being at speeds of Mach 5 (3,836 miles an hour) or greater.”
- 🚰🇮🇳😱 Chennai water crisis: City’s reservoirs run dry. “Residents have had to stand in line for hours to get water from government tanks, and restaurants have closed due to the lack of water.”
Restauranteur and seed entrepreneur Dan Barber with an interesting overview and history of the seed oligopoly. Only four giants dominate the business of patented seeds, including the Bayer-Monsanto juggernaut, giving them way too much power as they constantly reduce the number of varietals and the liberty of farmers. The latter are stuck in what amounts to an industrial production chain where they have to buy seeds every year, a “type of seed [which] also dictates the fertilizer, pesticide and fungicide regimen, sold by the same company as part of the package, requiring a particular planter and sprayer.” An unhealthy situation for producers, unhealthy for soil, less choice for consumers, and in many cases less flavour and nourishment.
Have a listen to Doctorow below, the monopoly / legislators combo he talks about for software is very similar to what agribusiness is doing.
And note the patent “moves” detailed by Barber, the same kind of land grab is happening right now (early stages) with DNA patents.
Just 50 years ago, some 1,000 small and family-owned seed companies were producing and distributing seeds in the United States; by 2009, there were fewer than 100. Thanks to a series of mergers and acquisitions over the last few years, four multinational agrochemical firms — Corteva, ChemChina, Bayer and BASF — now control over 60 percent of global seed sales. […]
Organic growing reduces the use of harmful chemicals, improves the soil’s ability to sequester carbon and retain water, and strengthens biodiversity. As the climate grows more severe and unpredictable, we will need seeds adapted to this kind of farming, and to their environments — precisely what a centralized, chemical-driven industry is not built to provide. […]
More than 90 percent of the 178 million acres of corn and soybeans planted last year in the United States were sown with genetically engineered seeds. […]
“Patents are completely unethical. We all need access to traits. My varieties are probably being used to create new varieties right now. I love that.”
Not the best Haraway interview, the longer form to appear in Logic magazine will likely be better but sharing it for the quote below. I’ve often said I “translate” between disciplines, this is a good framing for something similar.
It’s related to [what the postcolonial theorist Gayatri Chakravorty Spivak has called] “strategic essentialism”. There is a strategic use to speaking the same idiom as the people that you are sharing the room with. You craft a good-enough idiom so you can work on something together. I go with what we can make happen in the room together. And then we go further tomorrow.
TL;DR instead of comparing AI to “normal” art or looking at it purely as software, we miss the better way to critique it; as a continuation of computer generated art / aesthetics, which have been happening since the 1950s. Also takes us through some of the history of the field. Connects to previous issues where I included pieces on centaurs, hybrids, and AI as medium.
Finally, photography and film have long settled the issue of machine authorship (that I will discuss in detail below): “the owner or operator of the machine owns” the work created with it. […]
Nake’s argument is simple: there are no masterpieces in computer art because computer art is not about the production of “pieces”. It is about the production of system designs, and about the beauty and coherence of these designs. In other words, it is the method, not the artifact, that is relevant for the aesthetic judgement of a work. […]
In contrast, AI art, in the limited scope discussed here, has the problem that it is always essentially mimetic. After all, all of a neural network’s knowledge about the world comes from the data it processes.
Pure mimesis, it turns out, is impressive, but has no lasting aesthetic value. It provides immediate gratification in the easy recognition of similitude, but this quickly wears off. In other words, purely mimetic AI art becomes kitsch fast. […]
It is often overlooked that (non-trivial) art progresses much like science does - by building on a history of invention and discovery, sometimes taking incremental steps, sometimes questioning and overthrowing paradigms.
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