Data science to make our society better

How do we get people to understand how data influences their lives?

Data science has infiltrated our everyday lives and, although a powerful tool, with it come cases of bias, injustice, and discrimination. Consider the emerging discourse around the metaverse, within which people only exist as data. These data provide opportunities for research and innovation, but also commodification and surveillance. 

So how do we conduct data science responsibly?

That’s exactly what the new DSI@UTM initiative is tackling. The DSI at the University of Toronto Mississauga is leading a tri-campus initiative to encourage research activity in Responsible Data Science that includes community-building, workshops and seed funding for research.

Data science will continue to restructure aspects of our world and it is important to maintain a commitment to questions of power, inequity, responsibility, surveillance, justice, and harm. Especially, to ensure that collecting, manipulating, storing, visualizing, learning from, and extracting useful information from data is done in a reproducible, fair, and ethical way.

Why is UTM the right place for this initiative?

UTM has a cluster of faculty working across questions of responsible data science. One example is the Institute of Communication, Culture, Information and Technology (ICCIT), which looks at technology, media, and society and considers how algorithms affect the world. The campus is also comprised of  researchers working on sustainability, management, and geography along with  initiatives focused on giving back to the Mississauga community, including working with Indigenous community leaders. 

During an interview about this initiative, Associate Director of the DSI@UTM, Professor Bree McEwan, highlighted the revised UTM Strategic Framework. The Framework expresses core priorities and commitments that will strengthen consensus, inspire action, and guide investment. It includes priorities such as embracing place and encouraging collaboration.

“Responsible data science is about how we do data science, not just for the purpose of doing data science, but doing data science in a way that is making our society, our environment, etc. better for everyone. Therefore, the idea of responsible data science fits hand in glove with the other pieces of the Framework at UTM. How do we get lots of people to understand how data influences their lives, the idea of responsible data science? At UTM, we already have some strengths in how what we do here at the University influences the community around us,” says McEwan.

“The University of Toronto Mississauga is brimming with world-class researchers, focused on changing the world. UTM is a great place for this initiative, and we are thrilled to be building this within the DSI, as responsible data science needs to be a key part of both our research at UTM and our daily lives,” says Elspeth Brown, Associate Vice-Principal Research (AVPR) in the Office of the Vice-Principal, Research (OVPR). 

Events to look out for

A big focus of this initiative is bringing researchers working with data science at the UTM campus, and beyond, together. On December 7, DSI@UTM will be hosting its first Data Digest, Data & Sustainability. These networking events feature UTM data science researchers and provide attendees with the opportunity to engage in Responsible Data Science. Each month will feature a selection of short interdisciplinary research-based talks on a topic and explore challenges and opportunities related to data science. 

In February 2023, DSI@UTM will be hosting a Data in the Metaverse workshop. This event seeks to imagine future possibilities, challenges, and implications of data creation, collection, analysis, and deployment in the metaverse. Current discussions of the metaverse and the increase in VR adoption make this an opportune time to consider how data can, is, and could be employed in virtual reality and immersive environments.

Critical Investigation of Data Science Grant

The DSI@UTM Critical Investigation of Data Science (CIDS) grant is designed to provide seed funding for scholars. Projects can vary in scope from the analysis of specific data science projects and approaches to the articulation of potential harms in data science from a broader perspective.

“It’s about putting our money where our mouth is, in that we should be inviting critique of the data sciences in order to improve the data sciences. These grants will allow people to have some support for exactly those kinds of projects. Building in this critical angle, this self-reflection, into the data sciences is also important to make sure that we are doing data science responsibly,” says McEwan.

By Sara Elhawash, DSI

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