NVIDIA AI Podcast
Ep. 44: Forget Polls, Here's What Street View, and AI, Can Tell You About How People Will Vote
Dec 20, 2017
Timnit Gebru, a postdoctoral researcher at Microsoft and a Stanford AI Lab PhD graduate, dives into the intriguing intersection of AI and voting behaviors. She discusses how Google Street View data can predict demographic trends by analyzing vehicle types in neighborhoods. With a focus on the challenges of fine-grained image recognition and the ethics of AI, she emphasizes the need for fairness and accountability in algorithms. Gebru also shares fascinating insights from her research, underscoring the biases that can influence societal outcomes.
30:32
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Quick takeaways
- Using deep learning on Google Street View images enables insights into neighborhood demographics that traditional polling methods cannot provide.
- The correlation between vehicle types and voting behavior highlights the potential of visual data to predict political leanings based on socio-economic status.
Deep dives
Innovative Use of AI for Demographic Insights
Using deep learning in conjunction with Google Street View images provides valuable insights into the demographic makeup of neighborhoods across the United States. By analyzing 15 million images from 200 populous cities, researchers were able to classify over 2,600 distinct car types to infer the socio-economic characteristics of surrounding areas. The methodology involved correlating data on these cars with ground truth information from census data and voting records, allowing the team to draw meaningful conclusions. This innovative approach differs from traditional polling by relying on visual data rather than direct voter feedback, potentially offering a more nuanced view of community demographics.
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