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How Can We Trust Machine Learning and AI? Posted on : Nov 17 - 2017

During the 2008 financial crisis, the banking industry realized that their machine learning algorithms were based on flawed assumptions. So financial system regulators decided that additional controls were needed, and regulatory requirements for “model risk” management on banks and insurers were introduced.

Banks also had to prove that they understood the models they were using, so, regrettably but understandably, they deliberately limited the complexity of their technology, resorting to generalized linear models that offered simplicity and interpretability above all else.

In the past several years, machine learning and AI have made enormous strides in accuracy. Yet regulated industries (like banking) remain hesitant, often prioritizing regulatory compliance and algorithm interpretability over accuracy and efficiency. Some businesses even consider the technology untrustworthy, or dangerous.

In order to trust the recommendations AI and machine learning provide, businesses from all industries need to work to better understand it. Data scientists and PhDs shouldn’t be the only ones capable of clearly explaining machine learning models, because as AI theorist Eliezer Yudkowsky states, “By far, the greatest danger of AI is that people conclude too early that they understand it.”

Trust requires a human approach

When data scientists are asked how a machine learning model makes decisions, they tend to rattle off complex mathematical equations, leaving laymen dumbfounded and the question of how one can trust the model unanswered. Wouldn’t it be more productive to approach machine learning decision-making in the same way one would approach human decision-making? As Udacity co-founder Sebastian Thrun once said, “…artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition.”

So, rather than using complex mathematical equations to determine how, say, a human loan officer makes their decisions, one would simply ask, "Which information on the loan application form is the most important to your decision?" Or, "What values indicate good or bad risks, and how did you decide to accept or reject some specific examples of loan applications?" View More