Artificial intelligence poses a lot of ethical risks to businesses: It may promote bias, lead to invasions of privacy, and in the case of self-driving cars, even cause deadly accidents. Because AI is built to operate at scale, when a problem occurs, the impact is huge. Consider the AI that many health systems were using to spot high-risk patients in need of follow-up care. Researchers found that only 18% of the patients identified by the AI were Black—even though Black people accounted for 46% of the sickest patients. And the discriminatory AI was applied to at least 100 million patients. The sources of problems in AI are many. For starters, the data used to train it may reflect historical bias. The health systems’ AI was trained with data showing that Black people received fewer health care resources, leading the algorithm to infer that they needed less help. The data may undersample certain subpopulations. Or the wrong goal may be set for the AI. Such issues aren’t easy to address, and they can’t be remedied with a technical fix. You need a committee—comprising ethicists, lawyers, technologists, business strategists, and bias scouts—to review any AI your firm develops or buys to identify the ethical risks it presents and address how to mitigate them. This article describes how to set up such a committee effectively.

The field of artificial intelligence is detonating with products like IBM Watson, DeepMind's AlphaZero, and voice recognition used in virtual assistants including Amazon's Alexa, Apple's Siri, and Google's Home Assistant. Due to the massive impact of AI on humans' lives, the concern is growing about how to adopt a sound ethical AI strategy to shape future developments. Building ethical AI requires both an ethical way for building AI systems and a strategy for making AI systems themselves moral. For instance, engineers of self-driving vehicles should consider their social results including guaranteeing that the vehicles are fit for making moral decisions. Subsequently, building ethical use of artificial intelligence that we can trust should be at the core of its plan and development. The process of building ethical AI, in any case, is definitely not straightforward.

Male business professionals are discussing ... [ ] during meeting. They are sitting in office. While artificial intelligence is the trend du jour across enterprises of all types, there's still scant attention being paid to its ethical ramifications. Perhaps it's time for people to step up and ask the hard questions. For enterprises, it's time to bring together -- or recruit -- people who can ask the hard questions.

Male business professionals are discussing ... [ ] during meeting. They are sitting in office. While artificial intelligence is the trend du jour across enterprises of all types, there's still scant attention being paid to its ethical ramifications. Perhaps it's time for people to step up and ask the hard questions. For enterprises, it's time to bring together -- or recruit -- people who can ask the hard questions.

Consumer faith in businesses in most markets worldwide is wallowing in "stagnant distrust" – according to the Edelman Trust Barometer – and Australia is no exception. The recent Banking Royal Commission exposed some shocking misdemeanors across the financial services sector, Facebook appears to be trapped in an endless cycle of data misuse scandals, while breaches of customer data held by Australia's biggest businesses are now depressingly frequent. According to a recent CA Technologies commissioned report by analyst firm Frost & Sullivan, Australian consumers had the lowest overall level of'digital trust' – their confidence in brands to appropriately collect, store and use their digital information – in the world. Across nearly all sectors consumer trust is low and in decline, ranking only slightly higher than citizens' trust in politicians and the media. At first appraisal, an organisation's use of artificial intelligence related technologies would appear to put those pitifully low trust stocks at risk.