Designing AI for All: Addressing Polarization and Political Anger

By Jennifer Aaker, Fei Fei Li, Pecvin Pui Wan Yong, Matthew Cruickshank, Thomas Higginbotham, Zoe Weinberg, Wendy De La Rosa
2020 | Case No. ETH30 | Length 6 pgs.

Could artificial intelligence become a tool to help resolve political discord in an increasingly polarized world? This case draws on research that looks at Hong Kong’s 2019 unrest, when a controversial extradition proposal split the community into pro- and anti-government factions, and the protests and social discord resulted in the contraction of GDP. Would an AI-focused solution, using Natural Processing Language, help clarify what the real issues at stake were, as well as highlight how much the two sides actually had in common and encourage engagement between those with opposing views?

The case prompts students to consider that AI and machine learning might have broader applications beyond the known applications in health care, transportation, and online security.

Learning Objective

The case is designed to invite further discussion of out-of-the-box thinking on major societal challenges, by focusing on one such challenge: increased polarization and the resulting anger, violence, and social unrest.
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