onfocus

Trust in AI technology and the companies that develop it is dropping, in both the U.S. and around the world, according to new data from Edelman shared first with Axios.

Not much to this summary, but interesting to hear AI skepticism is on the rise even as it's being built into every technology product.

Pitch work is basically when a director, writer, producer, or any combination of those get together with an artist and say, “We want to pitch to studios and we need imagery.” All of that has now been given to generative AI.

Fascinating interview with concept artist Karla Ortiz about the impact of generative AI on her industry.

To even entertain the idea of building AI-powered search engines means, in some sense, that you are comfortable with eventually being the reason those creators no longer exist. It is an undeniably apocalyptic project, but not just for the web as we know it, but also your own product. Unless you plan on subsidizing an entire internet’s worth of constantly new content with the revenue from your AI chatbot, the information it’s spitting out will get worse as people stop contributing to the network.

Speaking of newsletters that recently moved away from Substack, Garbage Day made the jump to Beehiiv. Go read about AI search nihilism and a bunch of other stuff.

In this 5 minute video linguistics professor Emily M. Bender talks about AI as a marketing term. She proposes replacing the term AI with automation to avoid making mistakes about responsibility.

AIs are not people; they don’t have agency. They are built by, trained by, and controlled by people. Mostly for-profit corporations. Any AI regulations should place restrictions on those people and corporations. Otherwise the regulations are making the same category error I’ve been talking about. At the end of the day, there is always a human responsible for whatever the AI’s behavior is. And it’s the human who needs to be responsible for what they do—and what their companies do.

This talk is exactly how we should be thinking about AI, algorithms, technology in general. Technology doesn’t spring from the Earth fully formed, it’s the result of people designing it and making decisions that they should be responsible for.

This overview of the historic origins of these Artificial General Intelligence boom or doom cults by Timnit Gebru should be required viewing. We have a real world with existing needs that these ideologies ignore. The result of these scifi inspired beliefs is promoting authoritarian politics. As mentioned in this video, the main question to ask: who benefits now?

See also: The Wide Angle: Understanding TESCREAL — the Weird Ideologies Behind Silicon Valley’s Rightward Turn.

UnitedHealthcare, the largest health insurance company in the US, is allegedly using a deeply flawed AI algorithm to override doctors' judgments and wrongfully deny critical health coverage to elderly patients. This has resulted in patients being kicked out of rehabilitation programs and care facilities far too early, forcing them to drain their life savings to obtain needed care that should be covered under their government-funded Medicare Advantage Plan.

A current "benefit" of AI: providing cover for inhumane policies. Policy creators can blame the algorithm.

Instead of responding to search queries by linking to the web pages we’ve made, Google is instead generating dodgy summaries rife with hallucina… lies (a psychic hotline, basically). Google still benefits from us publishing web pages. We no longer benefit from Google slurping up those web pages.

Cutting ties with Google is an interesting idea. I've definitely been trying to minimize my interactions with Google. I don't use Google Analytics here. I use DuckDuckGo for most of my searching. I use Firefox for browsing on a desktop and Safari on iOS. Hard to see a shift from Google happening on a big scale without some other shift in the way people discover new things online though.

Our findings reveal that these detectors consistently misclassify non-native English writing samples as AI-generated, whereas native writing samples are accurately identified. Furthermore, we demonstrate that simple prompting strategies can not only mitigate this bias but also effectively bypass GPT detectors, suggesting that GPT detectors may unintentionally penalize writers with constrained linguistic expressions.

Interesting look at the effectiveness of GPT detectors universities are using to find cheating. Especially this bit:

While detectors were initially effective, a second-round self-edit prompt (“Elevate the provided text by employing literary language”) applied to ChatGPT-3.5 significantly reduced detection rates from 100% to 13%...

Ouch, not sure how these services can get away with charging money for AI detection if it's that easy to bypass.

Rather than needing tens of thousands of machines and millions of dollars to train a new model, an existing model can now be customized on a mid-priced laptop in a few hours. This fosters rapid innovation.

Nice summary of how innovation in AI might move out of the largest few companies.

Coupled with the Writers Guild strike and the arguably reckless pace at which companies are willing to adopt a mostly unproven, experimental, and demonstrably harmful technology, the world seems to be falling headfirst into a labor struggle the likes of which it hasn’t seen in quite a while.

The answers here are to vote for labor-friendly politicians and unionize. Good evergreen advice but also frustratingly vague for a specific looming threat.

That’s because there is no actual precedent for saying that scraping data to train an AI is fair use; all of these companies are relying on ancient internet law cases that allowed search engines and social media platforms to exist in the first place. It’s messy, and it feels like all of those decisions are up for grabs in what promises to be a decade of litigation.

The current round of language and image model speculation is based on the premise that using any public data for training is fair use not a massive copyright violation.