What Occupations Will ChatGPT Most Likely Impact?
Publication Date: March 24, 2023 5 minute readfrom “How Will Language Modelers Like ChatGPT Affect Occupations and Industries?” by Ed Felten, Manav Raj, and Rob Seamans“Trying to understand how AI will affect work is like trying to hit a moving target because the capabilities of AI are still advancing.”
The impact of artificial intelligence technologies (AI) on industries and jobs is anticipated to be multi-faceted. In some cases, AI may substitute for work previously done by humans, and in other cases AI may complement work done by humans. A recent Washington Post article (“AI isn’t yet going to take your job — but you may have to work with it”) explored how “Artificial intelligence is increasingly making its way across industries, changing jobs from retail to medicine to marketing.” The article goes on to say, “AI won’t entirely replace humans any time soon, industry experts and companies investing in the technology say. But jobs are transforming as AI becomes more accessible.”
Given the recent dramatic increases in AI language modeling capabilities, Professors Ed Felten (Princeton), Rob Seamans (New York University), and Manav Raj (University of Pennsylvania) collaborated to explore how ChatGPT and other AI language modelers will affect jobs, industries, and geographies. The resulting working paper, “How Will Language Modelers Like ChatGPT Affect Occupations and Industries?” shares their findings:
We find that the top occupations exposed to language modeling include telemarketers and a variety of post-secondary teachers such as English language and literature, foreign language and literature, and history teachers. We find the top industries exposed to advances in language modeling are legal services and securities, commodities, and investments.
Below are key takeaways from “How Will Language Modelers Like ChatGPT Affect Occupations and Industries?” by Ed Felten, Manav Raj, and Robert Seamans. (available at SSRN, March 6, 2023).
Methodology to Determine Occupational Exposure to AI
The authors used a framework they had previously developed, the AI Occupational Exposure (AIOE) measure, and extended the methodology to account for recent advances in language modeling.
This methodology “links advances in AI to occupational abilities.”
The AIOE measure was constructed by linking 10 AI applications (abstract strategy games, real-time video games, image recognition, visual question answering, image generation, reading comprehension, language modeling, translation, speech recognition, and instrumental track recognition) to 52 human abilities (e.g., oral comprehension, oral expression, inductive reasoning, arm-hand steadiness, etc.) using a crowd-sourced matrix that indicates the level of relatedness between each AI application and human ability.
The term “exposure” is used so as to be agnostic as to the effects of AI on the occupation, which could involve substitution or augmentation depending on various factors associated with the occupation itself.
Note: for more information about the AI Occupational Exposure (AIOE) measure, see “A Method to Link Advances in Artificial Intelligence to Occupational Abilities” (AEA Papers and Proceedings, 2018) and “Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses” (Strategic Management Journal, 2021) –both written by Professors Felten, Raj, and Seamans.
Findings: Occupations and Industries Exposed to AI-Enabled Advances in Language Modeling Capabilities
Notably, [the findings] includes more education-related occupations, indicating that occupations in the field of education are likely to be relatively more impacted by advances in language modeling than other occupations. This accords well with the recent spate of articles around how ChatGPT and other language modeling tools affect the way teachers assign work and detect cheating or could use language modeling tools to develop teaching materials.
Also of interest, the top occupation in the language modeling list is “telemarketer.” One might imagine that human telemarketers could benefit from language modeling being used to augment their work. For example, customer responses can be fed into a language modeling engine in real time and relevant, customer-specific prompts quickly fed to the telemarketer. Or, one might imagine that human telemarketers are substituted with language modeling enabled bots. The potential for language modeling to augment or substitute for human telemarketers work highlights one aspect of the AIOE measure: it measures “exposure” to AI, but whether that exposure leads to augmentation or substitution will depend on specifics of any given occupation.
The top 5 occupations most exposed to advances in language modeling:
- Telemarketers
- English Language and Literature Teachers, Postsecondary
- Foreign Language and Literature Teachers, Postsecondary
- History Teachers, Postsecondary
- Law Teachers, Postsecondary
The top 5 industries most exposed to advances in language modeling:
- Legal Services
- Securities, Commodity Contracts, and Other Financial Investments
- Agencies, Brokerages, and Other Insurance Activities
- Insurance and Employee Benefit Funds
- Nondepository Credit Intermediation
Read the full article, “How Will Language Modelers Like ChatGPT Affect Occupations and Industries?” by Ed Felten, Manav Raj, and Robert Seamans. (Available at SSRN, March 6, 2023).
Read More
- “A Method to Link Advances in Artificial Intelligence to Occupational Abilities” by Ed Felten, Manav Raj, and Robert Seamans. (AEA Papers and Proceedings, vol. 108, pp. 54-57, May 2018)
- “Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses” by Ed Felten, Manav Raj, and Robert Seamans. (Strategic Management Journal, vol. 42(12), pp. 2195-2217, December 2021)
About Edward Felten
Professor Edward Felten's research interests include computer security and privacy, and public policy issues relating to information technology. Specific topics include software security, Internet security, electronic voting, cybersecurity policy, technology for government transparency, network neutrality and Internet policy.
See more with Edward Felten
About Rob Seamans
Robert Seamans is an Associate Professor at New York University’s Stern School of Business where he teaches courses in game theory and strategy. Professor Seamans’ research focuses on how firms use technology in their strategic interactions with each other, and also focuses on the economic consequences of AI, robotics and other advanced technologies.