Ethics are about translating values into action. Data and AI in the abstract don’t contain any values except those we humans imbue them with. More importantly, we make value choices about how we use data and AI—including, sometimes, the decision not to use them. So unless all you are looking to accomplish with your data and AI ethics program is publishing a statement of platitudes that no one is going to take seriously, you need to figure out what values your organization wants to rally around, and how honoring those values will look in practice in the day-to-day work of all of the various people you employ and partner with in their specialized roles.
Ultimately you want input and buy-in of representatives from many different stakeholder groups to formulate and implement your organization’s data and AI ethics policies.
If you already have a Chief Data Officer, a business ethics committee, or some other entity in place, they may be the logical starting place for putting together your group. Having said that, a mistake some organizations make is to treat data and AI ethics as a technical problem, entirely within the realm of data science. The truth is:
- Reputation. Data and AI ethics touches your organization’s brand/reputation—how will the organization be perceived because of its choices (or lack thereof) about ethics?—so you need participation from senior leadership, marketing and PR.
- Regulation. It touches regulatory issues, including legal scenarios that are just emerging. For example, we will soon be seeing enforcement actions giving context to the California Consumer Privacy Act, which goes into affect less than 30 days from when this is being written. So you need to get your legal and compliance people involved.
- Employees. Your approach to data and AI ethics affects hiring and retention—what resonates with the people you want to attract to your organization?—so you need HR in the mix.
- Partners. It affects the ways in which your data and AI can be used, so you need clear communication with whoever is responsible for your sales, licensing, and/or partnerships.
- Technologists. In addition to all of these, of course you need the people who build and deploy your actual data systems (developers and data scientists).
Can’t get representatives from all of these constituencies on board at the onset? Work with who you’ve got. Start with a prototype—maybe one product, one department, or one scenario. As you go forward, promote the value proposition of your work throughout your organization, and solicit input from whoever is interested but unable to formally participate, while building momentum towards an expanded role down the road.
From the 4 part series How to Start Your Organization’s Data and AI Ethics Program
Next – Part 2: Educate Your Organization About Data and AI Ethics
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.