Hello. Today, I’m writing from Deer Valley, Utah, where Fortune is holding its Brainstorm Tech conference. AI has, unsurprisingly, been a major theme of the event. Here’s a recap of some of the key AI tidbits so far:
On Monday, my colleague Emma Hinchliffe interviewed San Francisco Federal Reserve President Mary Daly, who said generative AI’s impact on the labor market will depend on what we do with the technology. Daly said we should expect generative AI to contribute to at least average productivity growth, which is currently 1.5% annually.
But she also said that if AI helps us to invent new products and new processes, rather than simply automating existing ones, then its potential impact on productivity growth would be much greater. “If we say in a decade, [AI] was disappointing that is because of us,” Daly said. She also noted that all previous new technologies have, in the long term, created more jobs than they’ve eliminated, and she suspects AI will be no different.
Picking up these ideas, Stanford University economist Erik Brynjolfsson urged companies to view AI as complementary to human labor. Acknowledging that many companies have struggled to figure out how to derive a reasonable return on investment from generative AI, Brynjolfsson said the key was to stop thinking about jobs and start thinking about tasks. AI can automate some tasks within an organization, but it can’t automate entire jobs (at least not yet). In fact, as automation helps lower the cost associated with some roles, demand for those roles could actually increase, leading to the hiring of more people for those jobs. (This is called Jevons Paradox.) Brynjolfsson has cofounded a company called Workhelix that helps companies do this kind of task-based analysis and come up with strategic plans for implementing AI in the most impactful way within their organization. Among the tasks best suited to AI automation today include many in software development and within customer contact centers, he said.
Robinhood CEO Vladimir Tenev told Fortune editor-in-chief Alyson Shontell that he sees AI democratizing access to wealth management services. While very high net-worth individuals will continue to be served by human financial advisors, AI will be able to give many other people access to good financial advice who could never have afforded a financial advisor before.
Agility Robotics CEO Peggy Johnson showed off the company’s Digit humanoid robot, which is already working inside warehouses as part of a multi-year deal with GXO Logistics. Johnson said Agility is now integrating Digit with large language models (LLMs) so that people can give Digit instructions in natural language. Johnson says she sees Digit and humanoid robots like it as necessary for helping to meet a shortfall of some 1.1 million warehouse workers in the U.S.
Clara Shih, Salesforce’s AI chief, talked about how to build trust in AI within large organizations. She touted Salesforce’s own Einstein AI trust layer, which includes features such as data security and guardrails to prevent toxic language from being generated and techniques to defend against prompt injection attacks. That's when an adversary crafts a prompt that is designed to trick an LLM into jumping its guardrails.
She also said the company will begin rolling out AI software with more “agentic” qualities soon. These are AI models that will be able to perform tasks within workflows, not simply generate emails, letters, or customer service dialogues. More broadly, Shih said, one way organizations could develop more trust in AI was to make sure they were using the right AI model for the problem at hand. Just throwing a general-purpose large language model at every business dilemma was unlikely to result in the value companies are hoping to see from AI.
This morning, I interviewed Google’s chief scientist Jeff Dean, who said increasingly long context windows, such as those Google has pushed with Gemini, will help tame AI hallucinations. But he also agreed with recent comments from Microsoft’s Bill Gates that LLMs alone will not deliver AGI even if we continue to scale them up. Dean concurred that some other innovation would be necessary algorithmically.
There’ll be plenty of more discussion of AI over the next few days at Brainstorm Tech—it wraps up Wednesday around lunchtime. You can tune in to the livestream here, watch archived sessions here, and catch up on coverage of many of the sessions on fortune.com.
With that, here’s more AI news.
Jeremy Kahn
jeremy.kahn@fortune.com
@jeremyakahn
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