Artificial Intelligence, Scientific Discovery, and Product I...

Artificial Intelligence, Scientific Discovery, and Product Innovation

The study examines AI's effects on materials discovery, revealing increased innovation, productivity disparities among scientists, and diminished job satisfaction due to reduced creativity and skill utilization.

aidantr.github.io

RelatedHighlights

Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality

SSRN papers.ssrn.com

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To me, the most natural fit here for both art and science is the "innovation-as-mining" hypothesis. In that hypothesis:The basic dynamic is that innovation in a given area is mostly a function of how many people are trying to innovate, but "ideas get harder to find" over time.

Holden Karnofsky • Where's Today's Beethoven?

Lillian Sheng added

AI tools have shown their value in speeding up software development and discovering pharmaceuticals

Russell Brandom • OpenAI cuts its last and most important link to China

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For now, at least, innovation is a uniquely human ability—one that would be critical to a system that could recursively imagine and create better versions of itself.

Alice Albrecht • The Case for Cyborgs

Britt Gage added

In the most practical sense, we are now much less limited by ideas than ever before. Even people who don’t consider themselves creative now have access to a machine that will generate innovative concepts that beat those of most humans (though not the most creative ones). Where previously, there were only a few people who had the ability to come up ... See more

Ethan Mollick • Automating Creativity

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This is a common error, which existed long before AI. In fact, generating (or selecting) good ideas is a key challenge. LLMs so far seem to be about as good as the internet at generating lots of quite generic ideas - those who can select the ones that match their context (and yes, then, execute on them) are the ones who will have a chance to succeed.

No one knows, of course, but we suspect that AI is far more likely to complement and empower human workers than to impoverish them or displace them onto the welfare rolls. This doesn’t mean we’re starry-eyed Panglossians; we realize that this optimistic perspective is a tough sell, and even if our vision comes true, there will certainly be some pe

Noah Smith • Generative AI: autocomplete for everything

sari and added

Generative AI is quite good at certain parts of the value chain of knowledge work, but thinks quite differently from humans. Anthropic, a company that focuses on understanding how AI works, has found that humans working side-by-side with expert AI assistants to perform various tasks produce superior performance compared to either the AI or a human

Noah Smith • Generative AI: autocomplete for everything

sari added

First, many productivity-increasing AI products are just digital algorithms: infinitely replicable and instantly distributable around the world. This makes for a stark contrast to the hardware-intensive revolutions of steam power, electricity, and even large parts of ICT.

Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality

Holden Karnofsky • Where's Today's Beethoven?

Russell Brandom • OpenAI cuts its last and most important link to China

Alice Albrecht • The Case for Cyborgs

Ethan Mollick • Automating Creativity

Noah Smith • Generative AI: autocomplete for everything

Noah Smith • Generative AI: autocomplete for everything

Kai-Fu Lee • AI Superpowers: China, Silicon Valley, and the New World Order