Using the Veil of Ignorance to align AI systems with principles of justice
By Laura Weidinger, Kevin R. McKee, Richard Everett, Saffron Huang, Tina Zhu, Martin Chadwick, Christopher Summerfield, Iason Gabriel. 2023
47 citations recorded by the source corpus.
Significance The growing integration of Artificial Intelligence (AI) into society raises a critical question: How can principles be fairly selected to govern these systems? Across five studies, with a total of 2,508 participants, we use the Veil of Ignorance to select principles to align AI systems. Compared to participants who know their position, participants behind the veil more frequently choose, and endorse upon reflection, principles for AI that prioritize the worst-off. This pattern is driven by increased consideration of fairness, rather than by political orientation or attitudes to risk. Our findings suggest that the Veil of Ignorance may be a suitable process for selecting principles to govern real-world applications of AI.
Subfields: Cognitive Neuroscience, Safety Research, Safety, Robustness & Interpretability
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
In Safety Research
- Irene Solaiman
- Marie-Therese Png
- Zeerak Talat
- Yacine Jernite
- Alexandra Sasha Luccioni
- Su Lin Blodgett
- Margaret Mitchell
- Sara Hooker
In Safety, Robustness & Interpretability
- Irene Solaiman
- Su Lin Blodgett
- Dylan Baker
- Zeerak Talat
- Marie-Therese Png
- Yacine Jernite
- William Agnew
- Alexandra Sasha Luccioni
Citations in the corpus
- Evaluating the Social Impact of Generative AI Systems in Systems and Society (2023, background): “Novel alignment techniques [259, 25] by modality can determine preferable principles and values for generative AI systems.”