Forecasting extreme labor displacement: A survey of AI practitioners

Gruetzemacher, Ross; Paradice, David; Lee, Kang Bok

doi:10.1016/j.techfore.2020.120323

Cited by 47 publications

(30 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is a small but growing literature that surveys the AI/ML community. Most existing surveys focus on eliciting researcher forecasts on AI progress, such as when specific milestones will be reached or when AI will surpass human performance at nearly all tasks (Sandberg & Bostrom, 2011;Baum et al, 2011;Müller & Bostrom, 2016;Grace et al, 2018;Walsh, 2018;Gruetzemacher et al, 2020). Others have focused on how computer scientists define AI (Krafft et al, 2020) or the impact of AI on society (Anderson et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers

Baobao¹,

Anderljung²,

Kahn

et al. 2021

jair

View full text Add to dashboard Cite

Machine learning (ML) and artificial intelligence (AI) researchers play an important role in the ethics and governance of AI, including through their work, advocacy, and choice of employment. Nevertheless, this influential group's attitudes are not well understood, undermining our ability to discern consensuses or disagreements between AI/ML researchers. To examine these researchers' views, we conducted a survey of those who published in two top AI/ML conferences (N = 524). We compare these results with those from a 2016 survey of AI/ML researchers (Grace et al., 2018) and a 2018 survey of the US public (Zhang & Dafoe, 2020). We find that AI/ML researchers place high levels of trust in international organizations and scientific organizations to shape the development and use of AI in the public interest; moderate trust in most Western tech companies; and low trust in national militaries, Chinese tech companies, and Facebook. While the respondents were overwhelmingly opposed to AI/ML researchers working on lethal autonomous weapons, they are less opposed to researchers working on other military applications of AI, particularly logistics algorithms. A strong majority of respondents think that AI safety research should be prioritized and that ML institutions should conduct pre-publication review to assess potential harms. Being closer to the technology itself, AI/ML researchers are well placed to highlight new risks and develop technical solutions, so this novel attempt to measure their attitudes has broad relevance. The findings should help to improve how researchers, private sector executives, and policymakers think about regulations, governance frameworks, guiding principles, and national and international governance strategies for AI. This article appears in the special track on AI & Society.

show abstract

Section: Introductionmentioning

confidence: 99%

Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers

Baobao¹,

Anderljung²,

Kahn

et al. 2021

jair

View full text Add to dashboard Cite

show abstract

“…However, similar to Delphi and focused group interview techniques, the expert-based approach is limited because the experts' views on future jobs can be largely different even though they share a similar background. For example, Gruetzemacher, et al [17] surveyed attendees of AI conferences and found that their forecasts on labordisplacing AI scenarios were significantly different depending on what conferences they attended. This suggests that the forecast of future jobs should be based on quantitative data that objectively shows the change of technology.…”

Section: A Job Forecastingmentioning

confidence: 99%

Job Forecasting Based on the Patent Information: A Word Embedding-Based Approach

Lee

Yun

et al. 2022

IEEE Access

View full text Add to dashboard Cite

The rapid change in technology makes it challenging to forecast the future of jobs. Previous studies have analyzed economics and employment data or employed expert-based methods to forecast the future of jobs, but these approaches were not able to reflect the latest technology trends in an objective way. To overcome the issue, this study matches jobs with patents and forecasts the future of jobs based on changes in the number of patents with time. A word embedding model is trained by patent classification code and job description data and used to find similar patent classification codes of jobs. For an illustration purpose, we identify information technology-related jobs listed in O*NET and discover similar patent classification codes of the jobs. Based on the change in the number of patents, we find promising jobs presenting high technical demands. Several implications of our approach are also discussed.

show abstract

“…There is a growing academic literature that surveys the AI researcher community. Still, most of these surveys have focused on eliciting forecasts on AI, how they define AI, or the perceived impact of AI [3,8,27,28,39,42,48,62,65].…”

Section: Existing Research On Ai Researchers' Immigration Preferencesmentioning

confidence: 99%

Skilled and Mobile: Survey Evidence of AI Researchers' Immigration Preferences

Zwetsloot

Zhang

Dreksler

et al. 2021

Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society

View full text Add to dashboard Cite

Countries, companies, and universities are increasingly competing over top-tier artificial intelligence (AI) researchers. Where are these researchers likely to immigrate and what affects their immigration decisions? We conducted a survey ( = 524) of the immigration preferences and motivations of researchers that had papers accepted at one of two prestigious AI conferences: the Conference on Neural Information Processing Systems (NeurIPS) and the International Conference on Machine Learning (ICML). We find that the U.S. is the most popular destination for AI researchers, followed by the U.K., Canada, Switzerland, and France. A country's professional opportunities stood out as the most common factor that influences immigration decisions of AI researchers, followed by lifestyle and culture, the political climate, and personal relations. The destination country's immigration policies were important to just under half of the researchers surveyed, while around a quarter noted current immigration difficulties to be a deciding factor. Visa and immigration difficulties were perceived to be a particular impediment to conducting AI research in the U.S., the U.K., and Canada. Implications of the findings for the future of AI talent policies and governance are discussed. * Author order was randomized using the American Economic Association Author Randomization Tool (Confirmation ID: KiIBo0vkY2Vk).

show abstract

Forecasting extreme labor displacement: A survey of AI practitioners

Cited by 47 publications

References 46 publications

Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers

Ethics and Governance of Artificial Intelligence: Evidence from a Survey of Machine Learning Researchers

Job Forecasting Based on the Patent Information: A Word Embedding-Based Approach

Skilled and Mobile: Survey Evidence of AI Researchers' Immigration Preferences

Contact Info

Product

Resources

About