Sætra, H.S., Danaher, J.
AI Ethics (2023).
Abstract
AI poses both short- and long-term risks, but the AI ethics and regulatory communities are struggling to agree on how to think two thoughts at the same time. While disagreements over the exact probabilities and impacts of risks will remain, fostering a more productive dialogue will be important. This entails, for example, distinguishing between evaluations of particular risks and the politics of risk. Without proper discussions of AI risk, it will be difficult to properly manage them, and we could end up in a situation where neither short- nor long-term risks are managed and mitigated.
Here is my summary:
Artificial intelligence (AI) poses both short- and long-term risks, but the AI ethics and regulatory communities are struggling to agree on how to prioritize these risks. Some argue that short-term risks, such as bias and discrimination, are more pressing and should be addressed first, while others argue that long-term risks, such as the possibility of AI surpassing human intelligence and becoming uncontrollable, are more serious and should be prioritized.
Sætra and Danaher argue that it is important to consider both short- and long-term risks when developing AI policies and regulations. They point out that short-term risks can have long-term consequences, and that long-term risks can have short-term impacts. For example, if AI is biased against certain groups of people, this could lead to long-term inequality and injustice. Conversely, if we take steps to mitigate long-term risks, such as by developing safety standards for AI systems, this could also reduce short-term risks.
Sætra and Danaher offer a number of suggestions for how to better balance short- and long-term AI risks. One suggestion is to develop a risk matrix that categorizes risks by their impact and likelihood. This could help policymakers to identify and prioritize the most important risks. Another suggestion is to create a research agenda that addresses both short- and long-term risks. This would help to ensure that we are investing in the research that is most needed to keep AI safe and beneficial.
