Results suggest: high-skilled benefit, lesser-skilled not so much ➡️ Implications for Inequality?

Estimates vary sharply across earnings distribution:

• Bottom deciles: -8 days, earnings −3.9%
• Top decile: +5 days, earnings +2.5%

👉 Suggestive evidence: AI could widen existing inequalities

10/N

AI exposure expands analytic + interactive tasks, and reduces manual ones.

These task expansions translate into measurable earnings gains, especially through analytic work.

👉 Early AI technologies seem to induce task shifts, consistent with reinstatement effects.

9/N

Clear pattern: expert workers gain modestly, others not.

• Experts: +0.7% earnings (~400€), small gains in days worked in response to doubling in local AI demand

• Lesser-skilled workers: small declines

👉 Job-specific expertise matters (more than formal education or other skill proxies).

8/N

AI Exposure rises with skill levels:

👉 Experts face more AI vacancies than helpers, professionals, or specialists

👉 Similar insights by formal education and occupational task structures

Sets the stage for distinct insights by skill groups (more on that later).

5/N

AI demand across local labor markets: occupations × regions

Most local labor markets show little AI skill demand, others experienced notable increases.

(e.g.: in 2017 only 9% of local labor markets displayed AI demand, by 2023 ca. 16%)

👉 Key variation: changes in AI skill demand over time.

4/N

Stylized Facts on AI Skill Demand (2017–23, Germany)

• Modest in aggregate terms, fluctuates between 1 – 1.5% of all job postings.

• Most demand on unspecified AI skills, #machinelearning, and other technologies popularized prior to the emergence of #GenAI.

3/N

How does AI skill demand affect individual workers?

#AI can:

1. displace tasks
2. boost productivity
3. create new tasks

👉 Explore channels in context of longer-term dynamics of the early AI wave (2017-2023).

Data: Online Job Postings + German worker-level admin data (@iabnews.bsky.social)

2/N

It was a pleasure to host Oliver Schlenker (ifo & @iabnews.bsky.social ) today @ihs.ac.at Vienna.

Oliver presented "The Deadly Consequences of Labor Scarcity: Evidence from Hospitals".

Setting: DE–CH border region, but w/ many lessons beyond. Very timely paper!

👉 Check it out: lnkd.in/eNyxXHNS

How do people use ChatGPT?

A new NBER WP by researchers from OpenAI, Harvard & Duke analyzes millions of ChatGPT conversations since its launch, showing how usage patterns have shifted across work & personal contexts.

There are many interesting insights in here, but two findings stood out to me:

EDIT:

The sky is (still) blue,
and (at times) we were too! 😉

Was a pleasure to be back in Esch. Thanks to all presenters for insightful presentations and the organizers for putting up a wonderful program ✌

See you soon!

Hello Luxembourg!

The sky is blue and, tomorrow, the regressions too!

Looking forward to the TASKS conference at @liser-lm.bsky.social with vibrant discussions at day and a fun time at night 😉

Especially looking forward to reconnecting with many great friends & colleagues in the biz! 😀

Puh... only Tuesday but I could use some weekend again. I guess I'm not the only one.

For my first post here a fitting scenery. Arrived to Luxembourg earlier today, nice colors, nice view. A bit of sightseeing as well.

Now looking forward to ELMI conference starting tmrw at LISER.

Will be great to see old and new friends & colleagues again!