Artificial intelligence (AI) governance is the idea that there should be a legal framework for ensuring that machine learning technologies are well researched and developed with the goal of helping humanity navigate the adoption of AI systems fairly. This interesting information came to us from Fortune in their article, “Investors are pouring billions into artificial intelligence. It’s time for a commensurate investment in A.I. governance.”

In these days of AI explosion, organizations are sinking billions into AI development. For all the money invested in capabilities, however, there has not been nearly as much investment in AI governance. Dealing with issues surrounding the right to be informed and the potential for costly litigation, AI governance aims to close the gap between accountability and ethics in technological advancement. Due to the widespread implementation of AI across sectors everywhere, including healthcare, transportation, economics, business, education, and public safety, the need for a clear definition of AI governance has become a top priority.

Where machine learning algorithms are involved in making decisions, AI governance is a necessity. Machine learning biases have been observed to racially profile, unfairly deny individuals for loans, and incorrectly identify basic information about users. The development of AI governance will help determine how best to handle scenarios where AI-based decisions are costly, unjust, or undermine human rights.

The most important thing is for organizations to understand how the technology makes decisions. AI and machine learning can seem like opaque monoliths. Explainable AI allows users to comprehend and trust the results created by machine learning algorithms.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

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