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Statistics Used in the Session:

• Cities across the world are relying on an increasing number of data sets as cities become smarter and adopt advanced technologies.
• A ProPublica report from 2016 showed that data and predictive “Risk Assessment” algorithms from Coral Springs Florida consistently rated African-Americans as being a greater public risk than Caucasians despite having all the same data inputs.
• A broader analysis of Risk Assesment algorithms showed that only 20% of defendants who were identified at a high risk of committing a violent crime in the future actually did; and it mis-labeled black people at almost twice the rate as whites.
• A Google-Developed smart community in Toronto, Canada has come under heavy public criticism for its data privacy issues, despite promising to put all public data in a first-of-its-kind Data Trust

Facilitator Questions Asked in the Session:

• What is the role of data in shaping how we build our community?
• Who gathers this data? Where does it come from?
• Is it possible for this data to carry the same biases of the people that create it?
• How does an inability to access data sets impact how citizens can make their voices heard?
• What can we do to impact data systems to build a more equitable community?

Resources & Sources:

• ProPublica Report on Algorithmic Bias in Coral Gables Florida
• Towards Data Science - Big Data will be biased, if we let it
• A Public Response from the Quayside Civic Data Trust
• Data-Smart City Solutions - Algorithmic Fairness: Tackling Bias in City Algorithms

Notes:

Is it possible for the data to not carry the same biases of the people that create it?