Tim DaviesCEO Projekt Rising - The expert AI partner for SMEs

The Importance of Leadership in Addressing AI Bias

11 Apr 2025

Watch on YouTube

A short talk (uploaded by Tim Davies) arguing that responsibility for preventing bias in AI extends beyond engineers and data scientists to organizational leaders (marketing, finance, executives). Using the Amazon hiring-tool example, the speaker stresses leaders must ask who approved biased systems and whether training data included all groups.

I remember sharing with them one of those examples about Amazon and the tool they had that was discriminating against women. And one of them asked a very important question was like, let's leave the fact that, you know, it did that, it's fine. But who approved that? And that was a good question. Like even if the guys in the engineering rooms or whoever was building that missed it, yeah, who approved that to go out? You know, so it shows that as leaders we need as well to be in there. We can't just leave everything to those that are building and say, oh, we want an inclusive room of engineers or data analysts or data scientists. How about those that are in leadership, who are marketers, who are financial leaders, Whoever you are in the place of leadership, you should be able to ask the question and say, how did we train this data? Did you have everyone included in it.