Person
1 episodes · 24 quoted claims
In 2012, Erik Brynjolfsson and Andrew McAfee rode in a Google self-driving car from Mountain View to San Francisco, after writing Race Against the Machine.
“Actually, it was 2012, right after we wrote Race Against the Machine, we rode from Mountain View up to San Francisco.”
Erik Brynjolfsson states that the accident rate of the self-driving cars he rides is 90% lower than that of human drivers.
“The accident rate is 90% lower than with humans.”
Erik Brynjolfsson reports that his earlier research found investment in intangible complementary assets was about ten times larger than direct investment in computer technology.
“we found that the investments in those intangible assets are about ten times bigger than the direct investments in the computer technology.”
ADP, described as the world's largest payroll processor, shared its payroll data with the Stanford Digital Economy Lab for the Canaries in the Coal Mine study.
“ADP, which is the world's largest payroll processor, they shared the data with us here at the Digital Economy Lab”
Daniel Rock and colleagues created a taxonomy ranking about 18,000 distinct tasks by their exposure to large language models.
“have created a taxonomy where they rank all of the tasks in the economy, you know, 18,000 distinct tasks by how much they're exposed to LLMs”
The Canaries in the Coal Mine researchers examined about 750 occupations and divided them into quintiles by AI exposure.
“So we looked at about 750 occupations, we divided them into quintiles.”
Erik Brynjolfsson says the youngest workers in the most AI-exposed quintile of occupations show an employment decline of about 16 to 17 percent relative to other occupations.
“now it's more like a sixteen to 17% employment decline relative to the other occupations”
In the study, workers using AI mainly to automate work had falling employment, while those using it to augment and learn new skills had growing employment.
“The automating group had falling employment, and the augmenting group, the ones who were learning new skills, had growing employment.”
Geoffrey Hinton predicted that AI would replace radiologists because they read medical images.
“Jeff Hinton famously said, Hey, you know, reading medical images, that's what radiologists do, that's going to be replaced by AI.”
Erik Brynjolfsson says that as AI made image reading cheaper and better, radiologists became more valuable for their other tasks and net radiologist employment grew.
“as reading images got cheaper and better because of AI, it actually increased the value of radiologists for doing those other tasks, and net employment grew for radiologists”
Jevons paradox describes cases where making something cheaper increases demand enough that employment rises even as efficiency improves.
“some people call it Jevons paradox, where making something cheaper increases the demand for it, and you end up having more employment rather than less, even as it gets more efficient.”
Erik Brynjolfsson says at least half of goods and services in the economy have elastic demand, where small price drops produce large increases in quantity demanded.
“And at least half the goods and services in the economy are on that side of the curve.”
Paul David and others documented that factories saw essentially no productivity gain for up to thirty years while electrifying.
“Paul David and others documented this very carefully that for literally up to thirty years, there was essentially no productivity gain in factories as they were electrifying”
Factories eventually redesigned around separate electric motors for each machine and laid out by the flow of materials, rather than clustering around one central steam engine motor, after which productivity rose sharply.
“Instead of being clustered around a central motor like a steam engine, they had separate motors for each piece of equipment, and they distributed the work and they laid out the arrangement based on the flow of materials.”
Erik Brynjolfsson's company WorkHelix helps companies identify opportunities for value creation with AI.
“My company, WorkHelix, is very involved in showing companies how to identify the opportunities for value creation.”
Erik Brynjolfsson recounts that a CFO told him she required every division to report headcount reduction from AI as its return on investment.
“that's why I'm demanding that every division tell me how much headcount reduction they're getting from AI”
Erik Brynjolfsson calls the focus on using AI only to replace or imitate workers the 'Turing trap', after Alan Turing's imitation test.
“I call it the Turing trap because I think that it's a trap to only focus on using AI to replace or imitate workers.”
Scaling laws for large language models mean that more data, compute and parameters produce predictable performance gains, which has driven training costs into the billions.
“there are these scaling laws for LLMs where as you make a model bigger, if you have a model have more data, more compute, more parameters, you get a predictable improvement in performance.”
Erik Brynjolfsson says Anthropic and OpenAI are filing to go public at the time of the recording.
“Anthropic and OpenAI are filing to go public”
When asked what hardware he uses for his discoveries, Geoffrey Hinton reportedly pointed to his laptop.
“he pointed to his laptop and tapped it and said, This is this is the hardware I use”
Erik Brynjolfsson started his first AI company, an expert systems firm, in the late 1980s.
“the first AI company I started, I started back, believe it or not, in the late nineteen eighties.”
Erik Brynjolfsson has a long bet with economist Robert Gordon on how fast productivity will grow because of technology.
“I have a bet, a long bet on that with Bob Gordon, and I've written about, you know, how I expect productivity to grow”
Erik Brynjolfsson says productivity growth is no faster than at the start of the AI revolution, perhaps slightly higher.
“productivity is not growing any faster than it was at the beginning of this AI revolution, maybe a smidge if you kind of squint”
Erik Brynjolfsson spent over twenty-five years at MIT before moving to Stanford in Silicon Valley.
“I loved my time at MIT. I was there for over twenty five years, but now I'm out here in Silicon Valley”