Q&A with Andy Oram: How Can We Tell Whether Predictive Analytics Are Biased?
The fear of reproducing society's prejudices through computer algorithms is being hotly discussed in both academic publications and the popular press. Just a few of the publications warning about bias in predictive analytics include the New York Times, the Guardian, the Harvard Business Review, and particularly a famous and hotly contested article by Propublica on predictions of recidivism among criminal defendants.
In this Q&A, Zoomdata asks Andy Oram, co-author of its recent book collaboration withO'Reilly Media, Delivering Embedded Analytics in Modern Applications, what the fuss is about and what data scientists currently know about bias in algorithms.
Why are algorithms and predictive analytics used in sensitive decisions affecting human lives in the first place?
Many organizations in both commerce and government have come to appreciate the almost magical-seeming achievements of data analysis. Google's Alphabet corporation would not trade at record highs without its comprehensive analysis of user input, nor would Walmart earn nearly $500,000,000 a year without analyzing customer behavior. On the government side, data analysis contributes to many critical initiatives, such as tracing the spread of the Zika virus...
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- AdSense
- Andy Oram
- Barack Obama
- bias in algorithms
- bias in predictive analytics
- big data
- Cathy O'Neil
- civil rights
- cybersecurity
- Cynthia Dwork
- data privacy
- data science
- EU's General Data Protection Regulation
- European Union (EU)
- Frank Pasquale
- Google's Alphabet
- Harvard
- human coding
- Instant Checkmate
- Latanya Sweeney
- machine learning
- Massachusetts Institute of Technology (MIT)
- Northpointe
- predictive analytics
- privacy
- ProPublica
- recidivism among criminal defendants
- transparency
- Zika Virus
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