Responsible Data Science Community of Practice

What we are doing:

The Responsible Data Science CoP brings together Ohio State University researchers from many fields to conduct collaborative research on data science’s negative externalities and the mechanisms by which society can reduce these harms. In so doing, it supports the development of responsible data science. The CoP’s research teams produce knowledge that policymakers, businesses, educators and others can use to promote and practice responsible data science.  Their research spans three, related subject areas:

  • Externalities: Our research teams examine, and seek to understand better, the negative externalities that advanced analytics and artificial intelligence (data science, for short) can produce. These include privacy invasion, bias, inequality, manipulation, opacity and other such harms.
  • Solutions: Our researchers [Note: not all will be faculty] identify and evaluate the various means by which society can act to reduce these externalities. These include laws and policies, ethics and social norms, business management, and technological solutions.
  • Education: Our research teams draw on their knowledge about externalities and solutions to design curricula on how to practice responsible data science.

Why we are doing it:

Data science can produce many benefits. Used incorrectly, it can also invade privacy, perpetuate bias, manipulate the vulnerable, exacerbate inequalities, and produce other harms. These negative externalities endanger individuals and the broader society, and threaten to undermine trust in, and public support of, data science itself. If society is to reap data science’s many benefits, it must squarely face these harmful impacts and implement effective strategies for reducing them. Advanced analytics and artificial intelligence have far outpaced the mechanisms by which society normally brings technology into line with its values. We do not yet know how to design the laws, technologies, ethical and business management frameworks, and educational curricula, required to “socialize” data science. To produce this new knowledge, we will need research that spans the humanities, social sciences and hard sciences.  The Responsible Data Science CoP will marshal The Ohio State University’s considerable talent and resources to produce this research.  It will also partner with the other TDAI Communities of Practice to conduct research on responsible data science in their respective fields of expertise.

Why at Ohio State:

The Ohio State University possesses world-class faculty not only in advanced analytics, but also in the fields required to assess data science’s social and ethical impacts. This includes a number of nationally recognized centers and initiatives –spanning topics such as ethics, race and ethnicity, technology law and policy, data mining, and risk management — whose work can contribute directly to the advancement of responsible data science.  OSU is well-positioned to investigate responsible data science.

The Columbus, Ohio region, meanwhile, has emerged as a leading location for the data science industry.  It is home to state government and the civil society organizations that grow up around it, and so to many policy discussions and initiatives. The Responsible Data Science CoP constitutes a hub through which Ohio State researchers, the data science industry, government and civil society can connect, learn about each other’s efforts,  and work together to achieve responsible data science. We hope that you will join our community by clicking here.

Faculty Leads:

Dennis Hirsch


Interested in joining this community of practice?