12 citations · 18 across the 6 of their papers we have counts for
6 papers
Monocultural Biases: Correlated biases in large language models lead to unequal systemic exclusion rates in hiring
Matthew Bone, Fabian Stephany, Maria del Rio-Chanona
Employers are increasingly using large language models (LLMs) to automate their hiring process. This paper investigates the risk of monocultural biases, in which the widespread dep…
AI Skills Improve Job Prospects: Causal Evidence from a Hiring Experiment
Fabian Stephany, Ole Teutloff, Angelo Leone
The growing adoption of artificial intelligence (AI) technologies has heightened interest in the labor market value of AI related skills, yet causal evidence on their role in hirin…
Beyond pay: AI skills reward more job benefits
Alejandra Castaneda, Matthew Bone, Fabian Stephany
This study investigates the non-monetary rewards associated with artificial intelligence (AI) skills in the U.S. labour market. Using a dataset of approximately ten million online…
Complement or substitute? How AI increases the demand for human skills
Elina Mäkelä, Matthew Bone, Mareike Sehrer +2
Artificial Intelligence (AI) is transforming the nature of work, yet there is limited empirical evidence on how it affects demand for human skills. This paper examines whether AI a…
Improving Task Instructions for Data Annotators: How Clear Rules and Higher Pay Increase Performance in Data Annotation in the AI Economy
Johann Laux, Fabian Stephany, Alice Liefgreen
The global surge in AI applications is transforming industries, leading to displacement and complementation of existing jobs, while also giving rise to new employment opportunities…
Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs
Matthew Bone, Eugenia Ehlinger, Fabian Stephany
Emerging professions in fields like Artificial Intelligence (AI) and sustainability (green jobs) are experiencing labour shortages as industry demand outpaces labour supply. In thi…