Kausik, B.N. (2023): Long Tails & the Impact of GPT on Labor.
Preview |
PDF
MPRA_paper_117063.pdf Download (500kB) | Preview |
Abstract
Recent advances in AI technologies renew urgency to the question whether automation will cause mass unemployment and reduction in standards of living. While prior work analyzes historical economic data for the impact of automation on labor, we seek a test to predict the impact of emerging automation technologies such as Generative Pre-trained Transformers (GPT). Towards that goal, we observe that human needs favor long tail distributions, i.e., a long list of niche items that are substantial in aggregate popularity. In turn, the long tails are reflected in the products and services that fulfill those needs. Technologies that address a small portion of the distribution, typically the head, free up human labor to focus on more complex tasks in the long tail, thereby improving productivity and potentially lifting wages. In contrast, technologies that cover substantial portions of the long tail can squeeze wages or displace humans entirely. With this in mind, we propose a long tail test for automation technologies to predict their impact on labor. We find that popular GPTs perform poorly on such tests in that they are erratic on straightforward long tail tasks, hence absent breakthroughs, will augment human productivity rather than cause mass displacement of human labor. Going forward, we believe that to have a broad impact on displacing or devaluing human labor, AI must at least be capable of long-tail tasks that humans perform with ease.
Item Type: | MPRA Paper |
---|---|
Original Title: | Long Tails & the Impact of GPT on Labor |
English Title: | Long Tails & the Impact of GPT on Labor |
Language: | English |
Keywords: | AI, labor |
Subjects: | J - Labor and Demographic Economics > J2 - Demand and Supply of Labor > J21 - Labor Force and Employment, Size, and Structure J - Labor and Demographic Economics > J3 - Wages, Compensation, and Labor Costs > J30 - General O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes |
Item ID: | 117063 |
Depositing User: | B.N. Kausik |
Date Deposited: | 14 Apr 2023 07:03 |
Last Modified: | 14 Apr 2023 07:04 |
References: | Fowler, Gregory, A. (2023): “Say what, Bard? What Google’s new AI gets right, wrong and weird” https://www.washingtonpost.com/technology/2023/03/21/google-bard/ Roose, Kevin, (2023): “A Conversation With Bing’s Chatbot Left Me Deeply Unsettled” https://www.nytimes.com/2023/02/16/technology/bing-chatbot-microsoft-chatgpt.html Korinek, Anton and Stiglitz, Joseph, (2020): “Steering Technological Progress,” https://conference.nber.org/conf_papers/f143989.pdf Brynjolfsson, Erik, (2022): “The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence,”https://digitaleconomy.stanford.edu/news/the-turing-trap-the-promise-peril-of-human-like-artificial-intelligence/ Acemoglu, Daron, (2022): “The Harms of AI,” https://economics.mit.edu/files/21848 Autor, D., Mindell, D., and Reynolds, E. (2020). “The Work of the Future: Building Better Jobs in an Age of Intelligent Machines” Cambridge: MIT Press. https://workofthefuture.mit.edu/wp-content/uploads/2021/01/2020-Final-Report4.pdf Basu, Kaushik, (2022), “An inclusive future? Technology, New Dynamics and Policy Challenges” Brookings Institute, https://www.brookings.edu/wp-content/uploads/2022/05/Inclusive-future_Technology-new-dynamics-policy-challenges.pdf Acemoglu, D., and Restrepo, P., “Automation and New Tasks: How Technology Displaces and Reinstates Labor.” Journal of Economic Perspectives—Volume 33, Number 2. Eloundou, T., Manning, M., Mishkin, P., and Rock, D. (2023). “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models,” https://arxiv.org/pdf/2303.10130.pdf Anderson, C., (2004) “The long tail.” Wired Magazine, 12(10):170–177, 2004. Anderson, C., (2006) “The Long Tail: Why the Future of Business is Selling Less of More.” Hyperion. Brynjolfsson, E., Hu, Y.J., and Smith, M.D., (2007)“Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers.” MIT Center for Digital Business Working Paper. Goel, S., Broder, A, Gabrilovich, E., Pang, B., (2010). “Anatomy of the long tail: ordinary people with extraordinary tastes.” Proceedings of the third ACM international conference on Web search and data mining. Bubeck, S., Chandrasekharan, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y-T., Li, Y., Lundberg, S., Nori, H., Palangi, H., Ribiero, M.T., Zhang, Y., (2023). “Sparks of Artificial General Intelligence: Early experiments with GPT-4.” https://arxiv.org/pdf/2303.12712.pdf Noy, S. and Zhang, W., (2023). “Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence,” https://economics.mit.edu/sites/default/files/inline-files/Noy_Zhang_1.pdf Chafkin, (2022), “Even After $100 Billion, Self-Driving Cars Are Going Nowhere” https://www.bloomberg.com/news/features/2022-10-06/even-after-100-billion-self-driving-cars-are-going-nowhere |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/117063 |
Available Versions of this Item
- Long Tails & the Impact of GPT on Labor. (deposited 14 Apr 2023 07:03) [Currently Displayed]