IBM launches bias-detection tool in AI decision making

IBM is launching a new tool which will check biases in algorithms and try to understand how and why they crept in, and how to mitigate them. Explanations show which factors weighted the decision in one direction vs. another, the confidence in the recommendation, and the factors behind that confidence.

Reportedly, this initial release of the AIF360 Python package contains nine different algorithms, developed by the broader algorithmic fairness research community, to mitigate that unwanted bias. "It's time to translate principles into practice".

In an IBM blog post, IBM developers Animesh Singh and Michael Hind stated: "As AI becomes more common, powerful, and able to make critical decisions in areas such as criminal justice and hiring, there's a growing demand for AI to be fair, transparent, and accountable for everyone". This means organizations can take advantage of these new controls for most of the popular AI frameworks used by enterprises. The software will feature visual dashboards for providing the breakdown of automated decisions.

The Kit is supposed to analyze how the machine-learning algorithms make their decisions in real-time and work out if and how they are being biased on accident, by, for example, not identifying correctly people who are not white in photographs. A final check will be carried out too, but the systems will be tracked for accuracy, performance and overall fairness, over time.

Technology giant IBM said it is introducing a new solution that aims to provide increased transparency and "bias-detection" capabilities related to artificial intelligence processes deployed by companies. It is an open-source library to assist in targeting and removing bias within data sets and machine-learning models.

Study reveals priorities and hurdles for mainstream AI deploymentAccording to IBM's just-released study of 5,000 C-Suite executives, the IBM Institute for Business Value AI 2018 Report, there is a significant shift underway in how business leaders look at AI's potential to drive business value and revenue growth.

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