Everything looks like a nail by Ed Zitron
However, the real thing that Andreessen wants to hide is that he doesn’t actually want progress. The world that existed before 2020 was one that supported the growth-at-all-costs model that enriched him — a systemic inequity that fattens up private companies to be dumped onto the public markets with no regard for how poorly they’ll perform, meaning that investing in tech is inherently rigged to enrich the few and exploit the many. Andreessen fears any cause – (de-growth, regulation, equity, socialism, and so on) – that threatens A16Z’s core business model, which requires the future to arrive at exactly the speed that’s most profitable.
+
The Market for Lemons by Alex Russell
The baroque and insular terminology of the in-group is a clue. It’s functional purpose (outside of signaling) is to obscure furious plate spinning. This tech isn’t working for most adopters, but admitting as much would shrink the market for lemons.
+
How AI reduces the world to stereotypes by Victoria Turk (Rest of World)
Bias in AI image generators is a tough problem to fix. After all, the uniformity in their output is largely down to the fundamental way in which these tools work. The AI systems look for patterns in the data on which they’re trained, often discarding outliers in favor of producing a result that stays closer to dominant trends. They’re designed to mimic what has come before, not create diversity.
“My personal worry is that for a long time, we sought to diversify the voices — you know, who is telling the stories? And we tried to give agency to people from different parts of the world,“ [said Valeria Piaggio, global head of diversity, equity, and inclusion at marketing consultancy Kantar]. “Now we’re giving a voice to machines.”
+
SEC Head: Financial Crash Caused by AI ‘Nearly Unavoidable’ by Jules Roscoe (VICE)
Gary Gensler, the chairperson of the Securities and Exchange Commission, told the Financial Times that the lack of diversity in AI models used by companies could one day pose a significant threat to U.S. financial stability. While various open-source AI models exist, most entities today rely on a small number of tools developed by a select group of players, such as OpenAI’s ChatGPT.
+
Monopoly Power Is the Elephant in the Room in the AI Debate by Max von Thun (Tech Policy Press)
Unlike the previous wave of technological disruption, in which plucky upstarts rose from obscurity to create and dominate entirely new markets, when it comes to generative AI, the incumbents have a head start.
There is plenty of evidence to show that market concentration undermines innovation, reduces investment, and harms consumers and workers. This is especially true in digital markets – from search engines and app stores to e-commerce and digital advertising – where a few corporations have gained so much power that they are able to extract value from and impose terms on everyone in their orbit, while having a disproportionate say over the information we consume and the ways in which we communicate.
+
Microincentives and Enshittification by Cory Doctorow
Google Search is as big as it could possibly be. The sub-ten-percent of the search market that Google doesn’t own isn’t ever going to voluntarily come into the Google fold…
That means that Google Search can’t grow by adding new customers. It can only grow by squeezing its existing customers harder.
For Google Search to increase its profits, it must shift value from web publishers, advertisers and/or users to itself.
The only way for Google Search to grow is to make itself worse.
But it’s not just tech that faces the curse of bigness: your bank, your insurer, your beer company, the companies that make your eyeglasses and your athletic shoes — they’ve all run out of lands to conquer, but instead of weeping, they’re taking it out on you, with worse products that cost more.
Enshittification follows monopoly as sure as night follows day.
