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,...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...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...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...You Ask, I Answer: Third Party Data and Trustworthiness?
Ashley asks, “If you choose to use public datasets for your ML models, like from Amazon or Google, can you trust that those are free of bias?” Can you trust a nutrition label on a food product? The analogy is the same. What’s in the box is important,...AI for Marketers Book
In this all-new, completely-rewritten 2nd Edition of AI for Marketers, learn:
- What AI is and isn't
- 5 practical applications of AI in marketing
- Key questions to ask of any vendor claims about AI
- How to prepare your company and your career for AI
