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Report NEP-AIN-2023-11-20
This is the archive for NEP-AIN, a report on new working papers in the area of Artificial Intelligence. Ben Greiner issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-AIN
The following items were announced in this report:
- Bansak, Kirk & Paulson, Elisabeth, 2023, "Public Opinion on Fairness and Efficiency for Algorithmic and Human Decision-Makers," OSF Preprints, Center for Open Science, number pghmx, Oct, DOI: 10.31219/osf.io/pghmx.
- Christian Peukert & Margaritha Windisch, 2023, "The Economics of Copyright in the Digital Age," CESifo Working Paper Series, CESifo, number 10687.
- Gaetan de Rassenfosse & Adam Jaffe & Melissa Wasserman, 2023, "AI-Generated Inventions: Implications for the Patent System," Working Papers, Chair of Science, Technology, and Innovation Policy, number 22, May.
- Philip Trammell & Anton Korinek, 2023, "Economic Growth under Transformative AI," NBER Working Papers, National Bureau of Economic Research, Inc, number 31815, Oct.
- Giulio Cornelli & Jon Frost & Saurabh Mishra, 2023, "Artificial intelligence, services globalisation and income inequality," BIS Working Papers, Bank for International Settlements, number 1135, Oct.
- Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia S. Foster & Nikolas Zolas, 2023, "AI Adoption in America: Who, What, and Where," NBER Working Papers, National Bureau of Economic Research, Inc, number 31788, Oct.
- Alessandra Bonfiglioli & Rosario Crinò & Gino Gancia & Ioannis Papadakis, 2023, "Artificial Intelligence and Jobs: Evidence from US Commuting Zones," CESifo Working Paper Series, CESifo, number 10685.
- Carlo Pizzinelli & Augustus J Panton & Ms. Marina Mendes Tavares & Mauro Cazzaniga & Longji Li, 2023, "Labor Market Exposure to AI: Cross-country Differences and Distributional Implications," IMF Working Papers, International Monetary Fund, number 2023/216, Oct.
- Hanson, Gordon H., 2023, "Immigration and Regional Specialization in AI," SocArXiv, Center for Open Science, number 9a45d, Oct, DOI: 10.31219/osf.io/9a45d.
- Xu Yang & Xiao Yang & Weiqing Liu & Jinhui Li & Peng Yu & Zeqi Ye & Jiang Bian, 2023, "Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle," Papers, arXiv.org, number 2310.11249, Oct.
- Sebastian Heinrich, 2023, "Deriving Technology Indicators from Corporate Websites: A Comparative Assessment Using Patents," KOF Working papers, KOF Swiss Economic Institute, ETH Zurich, number 22-512, Jul, DOI: 10.3929/ethz-b-000623739.
- Alex Kim & Maximilian Muhn & Valeri Nikolaev, 2023, "From Transcripts to Insights: Uncovering Corporate Risks Using Generative AI," Papers, arXiv.org, number 2310.17721, Oct, revised Mar 2025.
- Bhaskarjit Sarmah & Tianjie Zhu & Dhagash Mehta & Stefano Pasquali, 2023, "Towards reducing hallucination in extracting information from financial reports using Large Language Models," Papers, arXiv.org, number 2310.10760, Oct.
- Jean-Marie John-Mathews, 2022, "Some critical and ethical perspectives on the empirical turn of AI interpretability," Post-Print, HAL, number hal-03395823, Jan, DOI: 10.1016/j.techfore.2021.121209.