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Pew Research Center short read, 18 August 2026, on a survey of US adults conducted 22-28 June 2026. 52% now say they are more concerned than excited about AI in daily life, up from 37% in 2021. Among adults aged 18-29, 55% are more concerned than excited and 11% more excited than concerned, and 73% think AI will mean fewer US jobs over the next 20 years, up from 61% in 2024.
Why I recommend it: Useful when a client says the worry is just in their head — it is not, and the numbers are free to download as a spreadsheet. Read it as what people expect, not as what has happened to employment: it measures opinion, not job counts.
Stanford Digital Economy Lab working paper by Bharat Chandar and Bouke Klein Teeselink, separating what happens to jobs after a firm adopts generative AI into a company-wide productivity effect and changes in what specific kinds of workers are asked to do.
Why I recommend it: Free, with the full PDF on the page. It is a working paper dated 21 September 2026, meaning it has not been through peer review yet, so read it as early evidence. Useful because it does not answer 'will AI take jobs' — it asks which workers get asked to do more and which get asked to do less.
Chapter 3 of Pew's April 2025 report comparing US adults with AI experts on what AI will do over the next two decades. 56% of the experts surveyed expect AI's impact on the US to be positive, against 17% of the public; 35% of adults expect a negative impact, against 15% of experts. The gap is widest on work and money: 73% of experts think AI will positively affect how people do their jobs versus 23% of the public, and 69% versus 21% on the economy, with a 40-point gap on medical care (84% versus 44%). Experts and the public broadly agree on the risks to democracy and journalism: only 11% of experts and 9% of the public expect AI to help elections, while 61% of experts and 50% of the public expect harm. Gender splits are large among experts — 63% of male experts predict a positive impact versus 36% of female experts. Free to read, with methodology and appendix tables.
Why I recommend it: Use this when someone tells you 'the experts say AI will be fine at work' — the numbers show experts and the public are describing two different futures, and the widest gap of all is about jobs. Read it with two limits in mind: the fieldwork was in 2024 and published 3 April 2025, so it predates a lot of what has happened since, and Pew's 'AI experts' are people who published or presented at AI conferences, many of them employed by companies building AI, which is exactly the group the optimism gap belongs to.
Interdisciplinary Stanford research institute studying how digital technology and AI change work, productivity and shared prosperity, with public papers and data.
From the site: The Stanford Digital Economy Lab is an interdisciplinary research institute shaping a future where technology drives human well-being and shared prosperity.
Why I recommend it: Free to read. Useful when you want measured research on AI and jobs instead of headline claims — check the publication date on each paper, the field is moving fast.
IEEE Spectrum article on how AI is shifting entry-level engineering work toward higher-order thinking, review and collaboration skills, and what recent graduates can do about it.
From the site: How can recent grads navigate a job market transformed by AI? Learn how to make AI work for you, not against you.
Why I recommend it: Free to read on IEEE Spectrum. Practical if you are early-career: it describes what junior work is turning into rather than predicting job counts.
