The Challenge of Value Alignment: from Fairer Algorithms to AI Safety
By Iason Gabriel, Vafa Ghazavi. 2021
71 citations recorded by the source corpus.
This paper addresses the question of how to align AI systems with human values and situates it within a wider body of thought regarding technology and value. Far from existing in a vacuum, there has long been an interest in the ability of technology to 'lock-in' different value systems. There has also been considerable thought about how to align technologies with specific social values, including through participatory design-processes. In this paper we look more closely at the question of AI value alignment and suggest that the power and autonomy of AI systems gives rise to opportunities and challenges in the domain of value that have not been encountered before. Drawing important continuities between the work of the fairness, accountability, transparency and ethics community, and work being done by technical AI safety researchers, we suggest that more attention needs to be paid to the question of 'social value alignment' - that is, how to align AI systems with the plurality of values endorsed by groups of people, especially on the global level.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Po-Sen Huang
- Jonathan Uesato
- Amelia Glaese
- Laura Weidinger
- Maribeth Rauh
- Iason Gabriel
- Zachary Kenton
- John F. J. Mellor
Citations in the corpus
- Taxonomy of Risks posed by Language Models (2022, background): “The risk, in this case, is that LMs come to represent language from a particular community and point in time, so that the norms, values, categories from that moment get “locked in” [15, 59].”