Working Paper No. 378: Returns to AI skills
Hellsten, M. (2024). Returns to AI skills. Ratio Working Paper No. 378.
Hellsten, M. (2024). Returns to AI skills. Ratio Working Paper No. 378.
This paper assesses whether workers who develop and apply artificial intelligence experience an earnings premium. I link skill requirements specified in job vacancies to the individuals ultimately hired to fill those positions using a combination of Swedish job vacancy and matched employer-employee register data. By identifying positions that explicitly necessitate AI skills, this paper seeks to determine if an earnings premium is associated with these skills while controlling for other individual attributes. Findings suggest a significant earnings premium for individuals hired to positions requiring AI skills. Discerning between AI developers and AI users, the results indicate that the former group experiences a stronger earnings premium. The premium is partly driven by workers being hired into high-wage industries. However, transitioning into roles requiring AI skills does not result in additional earnings increases, indicating that firms do not engage in wage competition for these workers.
Hellsten, M.
2024
Ratio Working Paper series.
2024
Ratio.
Andra upplagan av boken finns tillgänglig i bokhandeln, exempelvis här.
Artificiell intelligens (AI) väcker oro och nyfikenhet. Kommer AI att ta våra jobb? I denna tankeväckande bok tar sig forskaren Magnus Lodefalk an denna fråga – och de många delfrågor som frågan egentligen består utav.
Med hjälp av historiska exempel och dagsaktuell forskning diskuterar Lodefalk vilka jobb som kan försvinna med AI:s intåg, men också vilka typer av jobb som kan uppstå. Vad som skiljer AI från andra teknikers intåg är att den kan användas för att utföra kognitiva arbetsuppgifter. I boken diskuteras därför hur AI generellt sett kan förmodas påverka nästan alla jobb i termer av löneutveckling, produktivitet, kompetenskrav och innehåll.
Det görs genom att dissekera vad AI, och vad jobb, faktiskt är. Redan här kan konstateras att AI kan användas för att ersätta mänskliga förmågor eller för att förstärka desamma – det beror på hur man väljer att utveckla och använda tekniken. Och det, skriver Lodefalk, är i sin tur upp till oss.
I denna bok görs en pedagogisk översyn av forskningsläget gällande AI och arbetsmarknaden. Dessutom innehåller boken konkreta verktyg till dig som vill ha svar på hur AI-exponerat ditt yrke egentligen är.
2022
Bjuggren, P.O. & Long, V.
This paper decomposes the factors that govern the access and sharing of machine-generated industrial data in the artificial intelligence era. Through a mapping of the key technological, institutional, and firm-level factors that affect the choice of governance structures, this study provides a synthesised view of AI data-sharing and coordination mechanisms. The question to be asked here is whether the hitherto de facto control—bilateral contracts and technical solution-dominating industrial practices in data sharing—can handle the long-run exchange needs or not.
2021
Taking three recent business books on artificial intelligence (AI) as a starting point, we explore the automation and augmentation concepts in the management domain. Whereas automation implies that machines take over a human task, augmentation means that humans collaborate closely with machines to perform a task. Taking a normative stance, the three books advise organizations to prioritize augmentation, which they relate to superior performance. Using a more comprehensive paradox perspective, we argue that, in the management domain, augmentation cannot be neatly separated from automation. These dual AI applications are interdependent across time and space, creating a paradoxical tension. Over-emphasizing either augmentation or automation fuels reinforcing cycles with negative organizational and societal outcomes. However, if organizations adopt a broader perspective comprising both automation and augmentation, they could deal with the tension and achieve complementarities that benefit business and society. Drawing on our insights, we conclude that management scholars need to be involved in research on the use of AI in organizations. We also argue that a substantial change is required in how AI research is currently conducted in order to develop meaningful theory and to provide practice with sound advice.