Image by Peshkova

The Center for Research in Computation and Society (CRCS) was founded to develop a new generation of ideas and technologies designed to address some of society’s most vexing problems. CRCS brings computer scientists together with community partners and academic colleagues from across the University and throughout the world, to address fundamental computational problems that cross disciplines, and to create new technologies informed by societal constraints to address those problems. 


Research initiatives that have been launched throughout industry and academia study the intersection of technology and society in two distinct manners: They investigate the effects of information technology on society, or they study ways to use existing technologies to solve societal problems. The approach of Harvard CRCS is unique in its forward-looking scope and integrative approach, supporting research on innovative computer science and technology informed by societal effects, not merely examining the effects of existing technology on society.

Research Interests

Areas of specific research interest for the 2020-2021 academic year include conservation and public health. Research in this arena may involve, among myriad other possibilities, the use of AI for protecting endangered wildlife, fisheries, and forests; the use of technology to detect and prevent the spread of disease; and public health challenges in populations who are not typically served by AI and computing solutions. Other topics that continue to remain of interest to CRCS include privacy and security; social computing; economics and computation; and ethics and fairness in the application of technological innovation to societal problems.


Wild giraffes in Uganda

AI for Conservation refers to the application of artificial intelligence to conservation, such as wildlife protection and the protection of natural resources. For example, in the green security domain, the repeated and strategic interaction between those who protect these resources and those who seek to attack or exploit these resources can be modeled using game theory as a repeated game. While our predictive analytics effort focuses on predicting where adversaries (e.g., poachers) will strike, our prescriptive analytics work provides recommendations to defenders (e.g., rangers) to conduct strategic, randomized patrols. These analytics can be supported using machine learning, for example by detecting poachers or animals in unmanned aerial vehicle (UAV) imagery automatically.

To read more on CRCS activity in Conservation research, visit Conservation.

Public Health

public health


Public health topics of current interest include mobile health delivery, tuberculosis medication adherence, COVID 19 spread, suicidality and metal health topics. To read more on CRCS activities related to Public Health, visit Public Health.