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An International Consortium for Evaluations of Societal-Scale Risks from Advanced AI
Given rapid progress toward advanced AI and risks from frontier AI systems (advanced AI systems pushing the boundaries of the AI capabilities frontier), the creation and implementation of AI governance and regulatory schemes deserves prioritization and substantial investment.
Deep Transfer Learning & Beyond: Transformer Language Models in Information Systems Research
Recent progress in natural language processing involving transformer language models (TLMs) offers a potential avenue for AI-driven business and societal transformation that is beyond the scope of what most currently foresee.
Forecasting AI Progress: A Research Agenda
This paper describes the development of a research agenda for forecasting AI progress which utilized the Delphi technique to elicit and aggregate experts' opinions on what questions and methods to prioritize.
Exploring AI Futures Through Role Play
We present an innovative methodology for studying and teaching the impacts of AI through a role play game.
The Transformative Potential of Artificial Intelligence
We suggest that the term 'transformative AI' is a helpful alternative, reflecting the possibility that advanced AI systems could have very large impacts on society without reaching human-level cognitive abilities.
Alternative Techniques for Mapping Paths to HLAI
To address these limitations we propose the use of alternative techniques for an updated systematic mapping of the paths to HLAI.
Forecasting Transformative AI: An Expert Survey
Respondents indicated a median of 21. 5% of human tasks (i. e., all tasks that humans are currently paid to do) can be feasibly automated now, and that this figure would rise to 40% in 5 years and 60% in 10 years.
