AI and Big Data

Machines are sorting, scoring, and judging us with consequences big and small. They also help each of us sort and select our options on how to spend our time, money, or effort. AI and machine learning algorithms can often improve accuracy and efficiency, but they open big philosophical questions about how to prioritize competing values. Ideally, decisions should be made based on accurate assessments that are fair, transparent, and free from bias, but these goals are sometimes in conflict. Moreover, making improvements on any of them may compromise efficiency and privacy. And if AI outperforms human decision-makers along all of these dimensions, it is still possible that people have a preference for human systems that should not, or cannot, be ignored.

TechLaw faculty have been at the forefront of public discourse to help identify and illuminate the competing societal interests that must be taken into account when AI is deployed responsibly.