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Impact of Basic Human Values on Alcohol Use as a Coping Strategy During Chronic Stress Tovább olvasom

Bakucs Zoltán, Benedek Zsófia, Fertő Imre és Fogarasi József tanulmánya Tovább olvasom

From fork to farm, locally: social acceptance pathways for human excreta-derived fertilisers across three European regions - Varjú Viktor cikke Tovább olvasom

Megjelent a Socio-Ecological Practice Research folyóiratban Tovább olvasom

The Kitchen-Work of Collaborative Research: Recipes for Transformative Methodologies - Bródy Luca Sára és szerzőtársai cikke megjelent az Antipode folyóiratban Tovább olvasom

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Who is still in line? How bank beliefs drive fragility under runs - Csóka Péter és Kiss Hubert János cikke megjelent a Finance Research Letters folyóiratban Tovább olvasom

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Dynamics of two-sided platforms in public administration - Somogyi Róbert és szerzőtársai cikke megjelent az Operational Research folyóiratban Tovább olvasom

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Budapest így kerüli meg a kormányt a nemzetközi színtéren - Brucker Balázs írása a KRTK blogban a Portfolion Tovább olvasom

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KTI szeminárium: Rosario Crinò – Artificial Intelligence and Jobs: Evidence from US Commuting Zones (with Alessandra Bonfiglioli, Gino Gancia and Ioannis Papadakis)

Az előadásra hibrid formában kerül sor Zoom felületen, illetve személyesen a K13-14-es földszinti előadóban 2024.09.26-án, 13.00 órától.

Előadó: Rosario Crinò

BIO: Rosario Crinò is a Professor of Economics at the University of Bergamo and a Research Fellow of CEPR and CESifo. His research focuses on the effects of automation, artificial intelligence, and globalization on labor markets, productivity, and welfare.

Cím: Artificial Intelligence and Jobs: Evidence from US Commuting Zones (with Alessandra Bonfiglioli, Gino Gancia and Ioannis Papadakis)

Abstract: We study the effect of Artificial Intelligence (AI) on employment across US commuting zones over the period 2000-2020. A simple model shows that AI can automate jobs or complement workers, and illustrates how to estimate its effect by exploiting variation in a novel measure of local exposure to AI: job growth in AI-related professions built from detailed occupational data. Using a shift-share instrument that combines industry-level AI adoption with local industry employment, we estimate robust negative effects of AI exposure on employment across commuting zones and time. We find that AI’s impact is different from other capital and technologies, and that it works through services more than manufacturing. Moreover, the employment effect is especially negative for low-skill and production workers, while it turns positive for workers at the top of the wage distribution and for those in STEM occupations. These results are consistent with the view that AI has contributed to the automation of jobs and to widen inequality.

2024.09.26. - 2024.09.26. | MTA HTK (1097 Budapest, Tóth Kálmán u. 4.) K13-14-es földszinti előadóban és Zoom felületen