What jobs are affected by AI? Better-paid, better-educated workers face the most exposure.

Autor/inn/en	Muro, Mark; Whiton, Jacob; Maxim, Robert
Institution	Brookings Institution / Metropolitan Policy Program
Titel	What jobs are affected by AI? Better-paid, better-educated workers face the most exposure. Gefälligkeitsübersetzung: Welche Arbeitsplätze sind von KI betroffen? Besser bezahlte, besser ausgebildete Arbeitnehmer sind am stärksten gefährdet.
Quelle	Washington, DC (2019), 45 S. PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Monographie
Schlagwörter	Künstliche Intelligenz; Substitution; Beschäftigungseffekt; Patent; Arbeit; Berufsgruppe; Mittlere Berufsausbildung; Niedrig Qualifizierter; Qualifikation; Tätigkeitsmerkmal; Auswirkung; Zukunft; Hoch Qualifizierter; USA
Abstract	"Artificial intelligence (AI) has generated increasing interest in 'future of work' discussions in recent years as the technology has achieved superhuman performance in a range of valuable tasks, ranging from manufacturing to radiology to legal contracts. With that said, though, it has been difficult to get a specific read on AI's implications on the labor market. In part because the technologies have not yet been widely adopted, previous analyses have had to rely either on case studies or subjective assessments by experts to determine which occupations might be susceptible to a takeover by AI algorithms. What's more, most research has concentrated on an undifferentiated array of 'automation' technologies including robotics, software, and AI all at once. The result has been a lot of discussion -- but not a lot of clarity -- about AI, with prognostications that range from the utopian to the apocalyptic. Given that, the analysis presented here demonstrates a new way to identify the kinds of tasks and occupations likely to be affected by AI's machine learning capabilities, rather than automation's robotics and software impacts on the economy. By employing a novel technique developed by Stanford University Ph.D. candidate Michael Webb, the new report establishes job exposure levels by analyzing the overlap between AI-related patents and job descriptions. In this way, the following paper homes in on the impacts of AI specifically and does it by studying empirical statistical associations as opposed to expert forecasting." (Author's abstract, IAB-Doku).
Erfasst von	Institut für Arbeitsmarkt- und Berufsforschung, Nürnberg
Update	2020/3