by Christopher S Penn | Sep 21, 2020 | AI, Artificial Intelligence, Bias, Data Science, Machine Learning, Marketing, Marketing Data Science, Marketing Technology
Jessica asks, “When it comes to training data for marketing AI models, do you think vendors will anonymize/share data sources in the future? Will it be required?” It depends on the vendor and the model. The raw data for public models, even de-identified,...
by Christopher S Penn | Sep 18, 2020 | AI, Artificial Intelligence, Bias, Data Science, Machine Learning, Marketing, Marketing Data Science
Jessica asks, “Who’s liable for violations in marketing AI models, the company that hires the vendor, or the vendor? Anything in service agreements to look for?” Who’s liable when someone uses a tool improperly or illegally? Companies have some...
by Christopher S Penn | Sep 17, 2020 | AI, Artificial Intelligence, Bias, Data Science, Machine Learning, Marketing, Marketing Data Science
Tracy asks, “What are some questions you should ask vendors to better understand what data they use in their algorithms to make sure it’s not biased?” It’s not just questions we need to ask. Consider checking for bias to be like any other audit...
by Christopher S Penn | Sep 16, 2020 | AI, Artificial Intelligence, Bias, Data Science, Machine Learning, Marketing, Marketing Data Science
Gianna asks, “What’s the difference between fair and unfair bias? What’s the fine line?” Fair and unfair comes down to two simple things: laws and values. Statistical bias is when your sample deviates from the population you’re sampling...
by Christopher S Penn | Jun 26, 2020 | AI, Artificial Intelligence, Bias, Data Science, Machine Learning, Marketing, Marketing Data Science, Marketing Technology
Jim asks, “Are there any resources that evaluate marketing platforms on the basis of how much racial and gender bias is inherent in digital ad platforms?” Not that I know of, mostly because in order to make that determination, you’d need access to...
by Christopher S Penn | Apr 1, 2019 | AI, Artificial Intelligence, Bias, IBM, Machine Learning, Strategy
Tammy asks, “There was a talk this week about AI and ML and I was disturbed by a claim a speaker made at the CXL conference. He basically asserted that we should not be concerned about bias being trained into AI because we can just ‘remove the variable...