AI Can Be a Powerful Social Innovation for Public Health if Community Engagement Is at the Core.

There is a critical need for community engagement in the process of adopting artificial intelligence (AI) technologies in public health. Public health practitioners and researchers have historically innovated in areas like vaccination and sanitation but have been slower in adopting emerging technologies such as generative AI. However, with increasingly complex funding, programming, and research requirements, the field now faces a pivotal moment to enhance its agility and responsiveness to evolving health challenges.

Stable Matching with Uncertain Linear Preferences.

We consider the two-sided stable matching setting in which there may be uncertainty about the agents' preferences due to limited information or communication. We consider three models of uncertainty: (1) lottery model-for each agent, there is a probability distribution over linear preferences, (2) compact indifference model-for each agent, a weak preference order is specified and each linear order compatible with the weak order is equally likely and (3) joint probability model-there is a lottery over preference profiles. For each of the models, we study the computational complexity of computing the stability probability of a given matching as well as finding a matching with the highest probability of being stable.