One of the biggest technological advances that we're about now is artificial intelligence,

Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. Reid Blackman, PhD, is the author of Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI (Harvard Business Review Press), Founder and CEO of Virtue, an AI ethical risk consultancy, and he volunteers as the Chief Ethics Officer for the non-profit Government Blockchain Association. He has also been a Senior Advisor to the Deloitte AI Institute, a Founding Member of Ernst & Young's AI Advisory Board, and sits on the advisory boards of several start-ups. His work has been profiled in The Wall Street Journal and Forbes and he has presented his work to dozens of organizations including Citibank, the FBI, the World Economic Forum, and AWS. Reid's expertise is relied upon by Fortune 500 companies to educate and train their people and to guide them as they create and scale AI ethical risk programs.

In part one, I examined some noted ethicists' opinions about fairness measurement - and found some reasonable, and some incomplete (Can we measure fairness? In this article, I will begin with an example that was in dire need of fairness assessment. I will also introduce another method for fairness assessment. And finally, I'll try to resolve some different opinions between Reid Blackman, myself, and some Oxford scholars. I want to start with an example where the fairness measurement described in Part 1 could have avoided nearly catastrophic results.

As I've written in my "On AI Ethics," series, machine learning models that aim to mirror and predict real-life as closely as possible are not without their challenges. Household name brands like Amazon, Apple, Facebook, Google have been accused of algorithmic bias that have negatively affected society at large. While some organizations are investing in teams to ensure algorithmic accountability and ethics, Reid Blackman, CEO of Virtue and former professor of philosophy at Colgate University and the University of North Carolina, Chapel Hill, says most are still falling short in ensuring their products perform ethically in the real world. "Despite reputational, regulatory, and legal risks, it's surprising how many companies that rely on AI/ML still lack the ability to identify, evaluate, and mitigate the associated ethical risks," says Blackman. "Teams end up either overlooking risks, scrambling to solve issues as they come up, or crossing their fingers in the hope that the problem will resolve itself."