AI Risk Skepticism, A Comprehensive Survey
Not on the map. Why?
Abstract (arXiv)
In this thorough study, we took a closer look at the skepticism that has arisen with respect to potential dangers associated with artificial intelligence, denoted as AI Risk Skepticism. Our study takes into account different points of view on the topic and draws parallels with other forms of skepticism that have shown up in science. We categorize the various skepticisms regarding the dangers of AI by the type of mistaken thinking involved. We hope this will be of interest and value to AI researchers concerned about the future of AI and the risks that it may pose. The issues of skepticism and risk in AI are decidedly important and require serious consideration. By addressing these issues with the rigor and precision of scientific research, we hope to better understand the objections we face and to find satisfactory ways to resolve them.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 4 of its 128 references that are in the map. First posted on arXiv 16 Feb 2023.
Builds on
4 of 128 references.
References · 4
- 2016Concrete Problems in AI Safetycited by 1,642
- 2017When Will AI Exceed Human Performance? Evidence from AI Expertscited by 41
- 2021Why AI is Harder Than We Thinkcited by 41
- 2020On Controllability of AIcited by 5
Built on by
Citing papers per year: 2023: 3; 2024: 3.
6 papers.
- 2023Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generationcited by 148
- 2024Benchmarks as Microscopes: A Call for Model Metrologycited by 35
- 2024Exploring Vulnerabilities and Protections in Large Language Models: A Surveycited by 11
- 2023ChatGPT in the Age of Generative AI and Large Language Models: A Concise Surveycited by 10
- 2023Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanitiescited by 9
- 2024On Formally Undecidable Traits of Intelligent Machinescited by 0
- 2024Benchmarks as Microscopes: A Call for Model Metrology22 Jul 2024
- 2024Exploring Vulnerabilities and Protections in Large Language Models: A Survey1 Jun 2024
- 2024On Formally Undecidable Traits of Intelligent Machines14 Feb 2024
- 2023Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities30 Oct 2023
- 2023Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation3 Oct 2023
- 2023ChatGPT in the Age of Generative AI and Large Language Models: A Concise Survey9 Jul 2023