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It is no secret that our artificial intelligence (AI) technology is grappling with a Frankenstein’s monster problem: The software can often inherit and amplify all the biases of its creators. Racial and gender bias in AI has reared its ugly head in applications such as hiring, financial services and policing.
But the sheer size of the AI market — the technology could contribute up to $15 trillion to the global economy in 2030 — means that this high-profile problem is also a huge opportunity. The companies and entrepreneurs who can nail ethical, bias-free AI can win the trust and dollars of consumers, while the market punishes less scrupulous firms.
The world is getting wiser about the prevalence of AI bias, and the many ways it can creep into software.
Bias can infiltrate AI software when companies are training their models with data. The infamous example is facial recognition: If an algorithm is mainly fed photos of light-skinned people, then it will not learn how to recognize dark-skinned faces as well. Given that dark-skinned people are in fact the global majority, such biases are both lousy business and ethics.
AI bias could cause problems for people applying for jobs and mortgages or even, parole. It’s easy to see the economic and societal risk in these kinds of algorithms being given more and more power. But trying to repress AI would also be a mistake. In addition to the economic growth we could see from AI, the technology has the potential to eliminate meaningless tasks and move people to better jobs; help radiologists make faster and better cancer diagnoses; and get people on the financial margins access to credit.
It is not easy for companies to rectify bias in AI software, mainly because of a simple psychological barrier: It is usually difficult to see the error of your ways if you believe you have acted honestly. Companies will struggle to pinpoint the source and nature of flaws if they have built their AI models in good faith. It is even harder when the data and attributes that companies use to test an AI model very often contain exactly the same biases as the model used to train the software.
Even if the bias is successfully tracked down, it may have already caused some damage. For example, Amazon discovered that a hiring tool was overlooking female applicants and reprogrammed its software to ignore obviously gendered language. However, the corrected software had already learned to pick up on less-obvious gendered words and was making decisions on that basis.
Companies may also find that working to snuff out bias can lead them into a moral and sociological maze. Their AI models need to survive in several different social contexts, as well as weather philosophical and mathematical scrutiny about what constitutes justice and fairness. For example, the definition of fairness in a town in New York or California might be very different from that in Wyoming or West Virginia.
This does not mean that entrepreneurs and companies should be disheartened and abandon their efforts to root out bias in their AI. There are practical steps they can take to minimize bias, such as deploying software that explains the inner workings — and exposes the possible flaws — of a machine learning (ML) model. Underwriters could also feed their AI with relevant alternative data to paint a more detailed and accurate picture of an individual’s creditworthiness.
But correcting flaws in the digital world is just like fighting bias and prejudice in the real world: It is an ongoing process that never ends. The approach of companies to minimizing bias in their AI should reflect this. They should constantly re-evaluate the attributes and datasets of their ML model. Companies also need to continually scrutinize the outcomes of their model for signs that something is awry under the hood. It also helps if AI-focused entrepreneurs and companies make sure they are the loudest voices in conversations about fairness.
In the end, the success of entrepreneurs and companies in building ethical AI may depend on something more fundamental: moral fiber. The winners will be anyone with a strong sense of fairness and a desire to see things improve.
July 3, 2019 at 08:34PM
Forbes – Entrepreneurs