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Training with AI: Evidence from chess computers
Abstract: We suggest that AI can help decision-makers learn; specifically, that it can help them learn strategic interactions by serving as artificial training partners and thus help them to overcome a bottleneck of scarce human training partners. We present evidence from chess computers, the first widespread incarnation of AI. Leveraging the staggered diffusion of chess computers, we find that they did indeed help chess players improve by serving as a substitute for scarce human training partners. We also illustrate that chess computers were not a perfect substitute, as players training with them were not exposed to and thus did not learn to exploit idiosyncratic (“human”) mistakes. We discuss implications for research on learning, on AI in management and strategy, and on competitive advantage.
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| PSB lt.2 - Karya Akhir (Majalah) | 1 |
| Penerbit | USA: Strategic Management Society 2023 |
|---|---|
| Edisi | Vol. 44 Issue 11, Nov 2023 |
| Subjek | Artificial intelligence Learning Difference-in-differences Chess Strategic interaction |
| ISBN/ISSN | 1097-0266 |
| Klasifikasi | NONE |
| Deskripsi Fisik | 235 p. |
| Info Detail Spesifik | Strategic Management Journal |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas |