"Good" isn't good enough

Despite widespread enthusiasm among computer scientists to contribute to “social good,” the field's efforts to promote good lack a rigorous foundation in politics or social change. There is limited discourse regarding what “good” actually entails, and instead a reliance on vague notions of what aspects of society are good or bad. Moreover, the field rarely considers the types of social change that result from algorithmic interventions, instead following a “greedy algorithm” approach of pursuing technology-centric incremental reform at all points. In order to reason well about doing good, computer scientists must adopt language and practices to reason reflexively about political commitments, a praxis that considers the long-term impacts of technological interventions, and an interdisciplinary focus that no longer prioritizes technical considerations as superior to other forms of knowledge.

Speaker bio: Ben Green is a PhD Candidate in Applied Math at Harvard, an Affiliate at the Berkman Klein Center for Internet & Society at Harvard, and a Research Fellow at the AI Now Institute at NYU. He studies the social and policy impacts of data science, with a focus on algorithmic fairness, municipal governments, and the criminal justice system. His book, The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future, was published in 2019 by MIT Press.