Why Data Bias In AI Will Keep Board Directors And CEOs Awake At Night?

In my prior Forbes blogs, I outlined key reasons for board directors and CEOs to advance their AI governance practices and reinforced the imperative to recognize AI is a top ten security risks, as reported by EY in their Global Risk Survey. In my blog last week, Cathy Cobey, EY Global Trusted AI Lead, and I discussed the maturity of AI third party audits or certifications of AI models or systems, and concluded the industry was still in a very immature state, as organizations like IEEE and ISO are working on standards for AI, but won't be available until 2021. This blog discusses the acceleration of data bias in AI models, introduces five types of AI bias, and identifies key governance questions for board directors and CEO's to ask their organizations in order to mitigate data bias risks. Well first, we have already experienced a tenfold increase of data between 2013 and 2020. According to IDC in their Data Age 2025 report, data creation will grow to 163 Zettabytes by 2025, which is about ten times the amount of data produced in 2017.