Surely, we all know ethical from unethical conduct! Would that it were so. Have you ever heard the expression “just because it’s legal doesn’t make it right”? Even a set of values derived from applicable law (for instance, avoid discimination in hiring because it’s illegal) isn’t going to protect your organization from consumer outrage or employee defections if your values don’t live up to their expectations. If your organization has a vision and/or values statement, start with that. If you don’t, you’ll have something similar when you’re done here.
With your knowledge of data and AI ethics issues (see Educate, above), and your stakeholder experts (see Recruit a Task Force, above) your next objective is to create a map of potential data and AI trouble spots overlaid with the issues that may arise there. Try to look at every point where data and AI enter your organization (in particular, when vendors supply these, or when internal teams build these) and exit your organization (in particular, when customers engage with your data and AI such as on a website, or when data and AI are released for use by partners or the public). A few examples:
- HR—are recruiters inadvertently targeting job ads in a way that discourages women, minorities, or older potential applicants?
- Marketing—does your recommendation engine rely on data that customers didn’t (and wouldn’t, if they knew about it) give you permission to use?
- Application processing—are approvals dependent on features like zip codes which could be a proxy for race?
From the 4 part series How to Start Your Organization’s Data and AI Ethics Program
Next – Part 4: Test Your Data and AI Ethics Program
If the process described in this series is challenging for your organization, reach out! We’ll set up a call to talk about your organization’s goals and how I can help.