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 pouring billions of dollars 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 costly violations that may occur, AI governance aims to close the gap that exists between accountability and ethics in technological advancement. Due to the rise of the implementation of AI across sectors everywhere, including healthcare, transportation, economics, business, education, and public safety, the concern of definitively outlining AI governance is becoming greater.

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 contradict human rights.

The most important thing is for organizations to understand how the technology makes the decisions it does, and as a result, how the results are being applied in the various fields that AI and machine learning are being applied. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.

Melody K. Smith

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

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