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Artifical Intelligence: How Much Can It Be Trusted?
Many businesses and organizations are accelerating their drive to adopt artificial intelligence to improve process, decisions, and design. In many cases the ability for AI to perform tasks is nothing short of astounding. But at what point can an AI algorithm be trusted, especially for critical processes and when lives are at risk? At what point can we trust AI enough to let it pilot airplanes or make medical decisions?
Ron Poznansky, former IBM Researcher, said that “there are some very good reasons why people don’t trust AI tools just yet. For starters, there’s the hot-button issue of bias. Recent high-profile incidents have justifiably garnered significant media attention, helping to give the concept of machine learning bias a household name. Organizations are justifiably hesitant to implement systems that might end up producing racist, sexist or otherwise biased outputs down the line.”
Consider IBM’s experience in collaboration with MD Anderson using IBM WATSON AI technology as a tool for diagnosing cancer. If the diagnosis from WATSON matched the oncologist’s recommendation, they often thought that it isn’t providing anything beyond what they already know or expected; and when the diagnose deviate from the oncologist, and because it did not match what was expected, there was considerable skepticism and a belief that the diagnosis and recommended treatment was flawed.
The results of the WATSON experiment made researchers go back to see what they could do to develop more trust from users. They came up with three areas that need to be addressed in order to increase user trust in AI:
- Need to demonstrate that the technology is safe, built correctly, and performs well.
- Needs to perform as expected with outcomes that are positive.
- Needs to adhere to ethical standards and be fair.
Charles Towers-Clark wrote in a piece for Forbes that “trust is not an easy thing to inspire in people, especially on a wide scale and with such a transformative technology as AI. Blind faith in AI’s ability to do good has already led to serious mistakes, and a more logical, measured, and humble approach to such a powerful technology can only help AI to do more good in the world, and help humanity further as a result.”
