THE TYRANNY OF DATA?
THE BRIGHT AND DARK SIDES OF
DATA-DRIVEN ALGORITHMIC DECISION
MAKING FOR PUBLIC POLICY
The unprecedented availability of large-scale human behavioral data is profoundly changing the world we live in. Researchers, companies, governments, financial institutions, non-governmental organizations and also citizen groups are actively experimenting, innovating and adapting algorithmic decision-making tools to understand global patterns of human behavior and provide decision support to tackle problems of societal importance. In my talk, I will focus on social good decision-making algorithms, i.e. algorithms strongly influencing decision-making and resource optimization of public goods, such as public health, safety, access to finance and fair employment. Through an analysis of specific use cases and approaches, I will highlight both the positive opportunities that are created through data driven algorithmic decision-making and the potential negative consequences that practitioners should be aware of and address in order to truly realize the potential of this emergent field. I will elaborate on the need for these algorithms to provide transparency and accountability, preserve privacy and be tested and evaluated in context, i.e. by means of living lab approaches involving citizens. I will discuss the requirements which would make it possible to leverage the predictive power of data-driven human behavior analysis while ensuring transparency, accountability, and civic participation with the goal to have positive social impact.
Publications related to my talk can be found here:
- "Fair, transparent and accountable algorithmic decision-making processes" Lepri, B., Oliver, N., Letouze, E., Pentland, A. and Vinck, P. Springer Journal of Philosophy and Technology, 2017
- "The Tyranny of Data?: The Bright and Dark Sides of Data-driven Decision-making for Social Good" in "Transparent data mining for Big and Small data" Springer, 2016