Alirezaie, Marjan, Hossein Rahnama, and Alex Pentland. "Structural Learning in the design of Perspective-Aware AI Systems using Knowledge Graphs." Proceedings of the AAAI. 2024.

Abstract

We define perspective-aware computing as an emerging area of computational innovation in which users of the system can view and interact through each other’s points of view without the need for a centralized recommendation system. To achieve this, we propose a multi-modal neurosymbolic graph generation approach to construct personalized models known as “borrowable identities” from a user’s digital footprint, comprehending an individual’s cognitive and behavioral tendencies in diverse and contexts. Applications of our approach enable users of a trusted social network to view and interact with information through each other’s perspective. In summary, we allow individuals to lend their expertise to each other, and advance classic digital personalization techniques toward more participatory systems. This approach has potential in the design of less-biased recommendation systems in areas such as Digital Immortality, peer-to-peer learning, and in general, decentralized computational social systems.