When AI prediction substantially resolves trial uncertainty, a party purchasing AI prediction will disclose it if it is in their favour and not otherwise, signalling the outcome to the other party. Thus, the trial outcome becomes common knowledge. However, this implies that the parties will settle rather than purchase the AI prediction. When parties have differing prior beliefs regarding trial outcomes, these differences are only resolved if the AI prediction is purchased and utilised. In this case, AI will be purchased in equilibrium. Different trial cost allocation rules awarding all costs to the losing party (the English Rule) or having each party bear their own costs (the American Rule) can impact the demand for AI for settlement negotiations, but how this occurs interacts with the expectations regarding whether a settlement will occur or not in AI's absence.
Authors
- Acknowledgements & Disclosure
- Joshua Gans has drawn on the findings of his research for both compensated speaking engagements and consulting engagements. He has written the books Prediction Machines, Power & Prediction, and Innovation + Equality on the economics of AI for which he receives royalties. He is also chief economist of the Creative Destruction Lab, a University of Toronto-based program that helps seed stage companies, from which he receives compensation. He conducts consulting on anti-trust and intellectual property matters. He also has equity and advisory relationships with a number of startup firms. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research.
- DOI
- https://doi.org/10.3386/w32685
- Pages
- 15
- Published in
- United States of America
