# AI Risk Skepticism, A Comprehensive Survey

arXiv: https://arxiv.org/abs/2303.03885 · HTML: https://mlsanity.com/paper/2303.03885/

## 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 (most cited first, 4 of 4)

- [Concrete Problems in AI Safety](https://mlsanity.com/paper/1606.06565/) (2016)
- [When Will AI Exceed Human Performance? Evidence from AI Experts](https://mlsanity.com/paper/1705.08807/) (2017)
- [Why AI is Harder Than We Think](https://mlsanity.com/paper/2104.12871/) (2021)
- [On Controllability of AI](https://mlsanity.com/paper/2008.04071/) (2020)

## Built on by (most cited first, 6 of 6)

- [Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation](https://mlsanity.com/paper/2310.02304/) (2023)
- [Benchmarks as Microscopes: A Call for Model Metrology](https://mlsanity.com/paper/2407.16711/) (2024)
- [Exploring Vulnerabilities and Protections in Large Language Models: A Survey](https://mlsanity.com/paper/2406.00240/) (2024)
- [ChatGPT in the Age of Generative AI and Large Language Models: A Concise Survey](https://mlsanity.com/paper/2307.04251/) (2023)
- [Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities](https://mlsanity.com/paper/2310.19626/) (2023)
- [On Formally Undecidable Traits of Intelligent Machines](https://mlsanity.com/paper/2402.09500/) (2024)

## 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.