"AI 2027 and AI as Normal Technology were both published in April of this year. Both were read much more widely than we, their authors, expected.

Some of us (Eli, Thomas, Daniel, the authors of AI 2027) expect AI to radically transform the world within the next decade, up to and including such sci-fi-sounding possibilities as superintelligence, nanofactories, and Dyson swarms. Progress will be continuous, but it will accelerate rapidly around the time that AIs automate AI research.

Others (Sayash and Arvind, the authors of AI as Normal Technology) think that the effects of AI will be much more, well, normal. Yes, we can expect economic growth, but it will be the gradual, year-on-year improvement that accompanied technological innovations like electricity or the internet, not a radical break in the arc of human history.

These are substantial disagreements, which have been partially hashed out here and here.

Nevertheless, we’ve found that all of us have more in common than you might expect.

In this essay, we’ve come together to discuss the ways in which we agree with each other on how AI progress is likely to proceed (or fail to proceed) over the next few years."

https://asteriskmag.substack.com/p/common-ground-between-ai-2027-and

#AI #GenerativeAI #AI2027 #AGI #AIAsNormalTechnology #NormalTechnology

"We think we see the world as it is, but in fact we see it through a thick fog of received knowledge and ideas, some of which are right and some of which are wrong. Like maps, ideas and beliefs shape our experience of the world. The notion that AI is somehow unprecedented, that artificial general intelligence is just around the corner and leads to a singularity beyond which everything is different, is one such map. It has shaped not just technology investment but government policy and economic expectations. But what if it’s wrong?

The best ideas help us see the world more clearly, cutting through the fog of hype. That’s why I was so excited to read Arvind Narayanan and Sayash Kapoor’s essay “AI as Normal Technology.” They make the case that while AI is indeed transformational, it is far from unprecedented. Instead, it is likely to follow much the same patterns as other profound technology revolutions, such as electrification, the automobile, and the internet. That is, the tempo of technological change isn’t set by the pace of innovation but rather by the pace of adoption, which is gated by economic, social, and infrastructure factors, and by the need of humans to adapt to the changes. (In some ways, this idea echoes Stewart Brand’s notion of “pace layers.”)"

https://www.oreilly.com/radar/is-ai-a-normal-technology/

#AI #GenerativeAI #NormalTechnology #AGI

"[F]ar from marking a break with the widely hated platform giants that precede it, the A.I. of this most recent hype cycle is a “normal technology” in the strong sense that its development as both a product and a business is more a story of continuity than of change. “Instead of measuring success by time spent or clicks,” a recent OpenAI announcement reads, “we care more about whether you leave the product having done what you came for”--a pointed rebuke of the Meta, Inc. business model. But as Kelly Hayes has written recently, “fostering dependence” is the core underlying practice of both OpenAI and Meta, regardless of whether the ultimate aim is to increase “time spent” for the purpose of selling captured and surveilled users to advertisers, or to increase emotional-intellectual enervation for the purpose of selling sexy know-it-all chat program subscriptions to the lonely, vulnerable, and exploitable:"

https://maxread.substack.com/p/ai-as-normal-technology-derogatory

#AI #GenerativeAI #OpenAI #ChatGPT #Chatbots #LLMs #NormalTechnology #SocialMedia #Meta