Consider using a portfolio of … Artificial intelligence (AI), which represents the largest economic opportunity of our lifetime, is increasingly employed to make decisions affecting most aspects of our lives. Yet human decision making in these and other domains can also be flawed, shaped by individual and societal biases that are often unconscious. Olga Russakovsky. Second, when your business or organization is deploying AI, establish responsible processes that can mitigate bias. John Villasenor discusses the sources of bias in artificial intelligence, how to identify instances of bias, and what can be done to mitigate it. The first one is bias in the data. “Bias” occurs when AI systems produce results that are prejudiced due to unintended, erroneous assumptions in the machine learning process. Though Artificial Intelligence is used more and more in the financial services industry, it can actually become biased. The growing use of artificial intelligence in sensitive areas, including for hiring, criminal justice, and healthcare, has stirred a debate about bias and fairness. Bias in AI is looming as a significant issue for Australian businesses, according to Human Rights Commissioner Edward Santow, who has launched a new … I believe there are three root causes of bias in artificial intelligence systems. As the federal government increasingly adopts AI strategies and technologies, understanding how to identify and mitigate potential bias becomes more critical. In a paper at the Artificial Intelligence Ethics and Society Conference (AIES) 2018, we presented a composable bias and fairness ratings system and architecture for API-based AI services (including all of the commercial classifiers studied by Buolamwini and Gebru) and demonstrate its applicability in the domain of language translation [3]. More than 8 in 10 federal executives acknowledge that collaboration between humans and machine through artificial intelligence will be critical to innovation in the future. <<< Start >>>