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Generative AI tools hold promise to increase human productivity.
Inequality and growth: What can the data say?
Banerjee, A. V. and Duflo, E. (2003) · 2003
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Estimating marginal returns to education
Carneiro, P., Heckman, J. J., and Vytlacil, E. J. (2011) · 2011
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Machine learning methods for estimating heterogeneous causal effects
Athey, S. and Imbens, G. W. (2015) · 2015
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Artificial intelligence, labor, productivity, and the need for firm-level data
Raj, M. and Seamans, R. (2018) · 2018
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Artificial intelligence: the ambiguous labor market impact of automating prediction
Agrawal, A., Gans, J. S., and Goldfarb, A. (2019) · 2019
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Evaluating large language models trained on code
Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. d. O., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., et al. (2021) · 2021
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Ai and shared prosperity
Klinova, K. and Korinek, A. (2021) · 2021
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Grounded copilot: How programmers interact with code-generating models
Barke, S., James, M. B., and Polikarpova, N. (2022) · 2022
Cited alongside, same era.
The robots are coming: Exploring the implications of openai codex on introductory programming
Finnie-Ansley, J., Denny, P., Becker, B. A., Luxton-Reilly, A., and Prather, J. (2022) · 2022
Cited alongside, same era.
A research agenda for assessing the economic impacts of code generation models
Manning, S., Mishkin, P., Hadfield, G., Eloundou, T., and Eisner, E. (2022) · 2022
Cited alongside, same era.
Reading between the lines: Modeling user behavior and costs in ai-assisted programming
Mozannar, H., Bansal, G., Fourney, A., and Horvitz, E. (2022) · 2022
Cited alongside, same era.
An empirical evaluation of github copilot’s code suggestions
Nguyen, N. and Nadi, S. (2022) · 2022
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Security implications of large language model code assistants: A user study
Sandoval, G., Pearce, H., Nys, T., Karri, R., Dolan-Gavitt, B., and Garg, S. (2022) · 2022
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Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models
Vaithilingam, P., Zhang, T., and Glassman, E. L. (2022) · 2022
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The ai index 2022 annual report
Zhang, D., Maslej, N., Brynjolfsson, E., Etchemendy, J., Lyons, T., Manyika, J., Ngo, H., Niebles, J. C., Sellitto, M., Sakhaee, E., et al. (2022) · 2022
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Productivity assessment of neural code completion
Ziegler, A., Kalliamvakou, E., Li, X. A., Rice, A., Rifkin, D., Simister, S., Sittampalam, G., and Aftandilian, E. (2022) · 2022
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