Véliz: HBR study shows AI makes workers less productive
Carissa Véliz · Are We Too Obsessed With AI Predictions? — With Carissa Véliz · Apr 22, 2026 · at 37:07
Oxford philosopher Carissa Véliz questions whether generative AI delivers real net economic value when debating host Alex Kantrowitz.
0:00 / 0:14exact quote · 14.7s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“There was a paper recently at the Harvard Business Review that suggested that even when people think they're being more productive with AI, when you have researchers look at it, they're being less productive because they're spending a lot of time fixing what the AI gets wrong.”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Carissa Véliz
Véliz: Academia faces a serious problem with data fraud
“In my world, in academia, I think we have a serious problem of fraud. Of people who are very well known, and who have been very successful, and who have fudged their data, or who have committed other kinds of academic fraud.”
Véliz: Large language models have no regard for truth
“And that's essentially what a large language model is. It has no regard for the truth. It wants to please you. If what pleases you happens to be true, great. But if it's not true, then it doesn't care one way or another.”
Véliz: Predictive AI creates self-fulfilling prophecies with zero error signals
“Self-fulfilling prophecies are like the perfect crime. Because it's like a murder weapon that disappears upon striking. It leaves no record. It creates no error signals. We will never know how that person would have fared, because they will never get the job, …”
Véliz: Algorithmic bias audits are limited by a lack of counterfactual data
“When you say, well, let's investigate for bias or investigate for inaccuracy, there is a limit to what we can do, because we will never have the counterfactual. This is not a randomized control trial, right? And you still have the problem that without clear cr…”
Véliz: Opaque algorithmic systems induce alienation and magical thinking
“We are building systems that are very Kafkaesque, that are impossible to navigate, and I don't know if you've had this experience in which they are becoming so alienating and so Kafkaesque That people start having, like, magical thinking about the algorithm, a…”
Véliz: Anonymous Wallets Made $1.2M Betting on Iran Attack
“Six anonymous accounts earned 1.2 million dollars on a prediction market betting for the attack on Iran, and some of those wallets were funded hours before, which suggests that they might have had insider information, and if they had insider information, did t…”