Guy Lichtinger

Guy Lichtinger is an academic researcher and co-author, with Hosseini Maasoum, of the August 2025 SSRN working paper on seniority-biased technological change in AI-adopting firms. The paper, drawn from a dataset of 62 million US worker resumes across 285,000 firms over 2015 to 2025, found that generative AI adoption is associated with a 15% decline in entry-level job postings and a 3% decline in senior-level postings within the same adopting firms. The study was presented at the Stanford Digital Economy Lab and circulated as a pre-publication working paper on SSRN.

Lichtinger's contribution to the research sits within a body of work examining how technology adoption differentially affects workers by experience level. The paper's methodological strength is its use of revealed hiring behaviour (actual postings and resume flows) rather than survey data, making its findings harder to dismiss as measurement artefacts. The entry-level decline is attributed to slower hiring rather than increased firing, a nuance that matters for policy: it means the displacement is largely invisible to unemployment statistics, which track separations but not non-hiring.

The broader significance of the Lichtinger and Hosseini Maasoum research is that it provides an empirical baseline for the 'career ladder' argument against AI displacement. The conventional rebuttal to AI job-loss fears has been that workers adapt by moving up the value chain. This study shows that the bottom of the chain is being removed before workers on it have anywhere to move to, creating a cohort of graduates and early-career professionals who may never accumulate the experience that future employers will require.