By Amy S. Evans, AICP

As our profession’s ability to collect, share, and analyze data grows by leaps and bounds, planners have an opportunity to think about data with an equity lens. This viewpoint is especially important when we use data to allocate community resources or predict future behavior or community characteristics.

Predictive analytics rooted in machine learning and artificial intelligence offer new opportunities to communities but come with new challenges as well. The Annie E. Casey Foundation identifies a primary concern in its “Four Principles to Make Advanced Data Analytics Work for Children & Families” report:

Algorithms implemented by systems (private or public) will tend to automate decision-making criteria already in place, learning from data that capture how these systems have historically allocated resources … . The problem for civil rights advocates isn’t chiefly bias or naivety on the parts of those building these models – it’s the racism built into the policy and historical practice of many institutions.”

Sharing of decision-making power with community members is one best practice, especially as distrust in private and public sector use of data grows nationally. Transparency before, during, and after development of advanced analytical tools is critical.

Another best practice is to search for opportunity in data as often as you look for challenges. Analytics tools often have a tremendous capacity to identify opportunity, whether that’s a community that’s doing well despite disadvantages, or locating untapped community resources, or sequencing improved processes, routes, and networks.

Remember also that advanced analytical tools assess specific data points. Parameters that lay outside the data– things like local policy decisions and individual actions and judgement – are not considered even when they play an important role in producing the data being analyzed. At its worst, this gap hides and perpetuates disparities by giving a false understanding of the factors affecting communities.

From the same report, a good example of a community using advanced analytics to increase opportunity comes from New York City, NY:

“New York City has used advanced analytics to identify landlords who discriminate against potential tenants because of their source of income, in violation of the city’s Human Rights Law. The Mayor’s Office of Data Analytics ‘pinpointed areas with available housing, high-performing schools, and little crime, but suspiciously low use of housing vouchers,’ writes Chris Bousquet for Data Smart Cities at the Harvard Kennedy School of Government’s Ash Center. Using this model to target 24 neighborhoods for increased investigation by the Fair Housing Justice Center, New York City lodged 120 income discrimination complaints against landlords from the Council on Human Rights and levied a record-high $100,000 civil penalty.”

As planners, we have access to a large volume and variety of data. We also have a choice in using it to maintain the status quo or embracing it as an opportunity to build a shared understanding of local conditions and needs, an understanding that can target longstanding systemic barriers and inequities.