Category: Bias
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You Ask, I Answer: Fairness and Mitigating Bias in AI?
In today’s episode, I tackle the big question of mitigating bias in AI. I explain the differences between statistical bias and human bias, and equality of outcome versus opportunity. There are no easy answers, but understanding these concepts is key to documenting and implementing fairness policies for your models. Tune in for an in-depth look…
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You Ask, I Answer: Third Party Data and Model Audits?
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, probably will not be publicly available, but should be made available to…
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You Ask, I Answer: Liability for Marketing AI Models?
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 responsibility, as we see with product warnings, but the ultimate responsibility – and who gets sued/arrested…
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You Ask, I Answer: Vetting Marketing AI Vendors for Bias?
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 or due diligence. We will want to investigate the 6 main…
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You Ask, I Answer: Difference Between Fair and Unfair Bias?
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 from. Bias isn’t inherently bad unless it crosses one of those two lines. Can’t see anything? Watch…
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You Ask, I Answer: Detecting Bias in Third Party Datasets?
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 the underlying data. What you can do is validate whether your particular…
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You Ask, I Answer: Removing AI Bias by Removing Data?
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 from the model that causes the bias.’…
