AI ethics in the spotlight
Fei-Fei Lee, co-director of Stanford University’s Institute for Human-Centred AI
Photography: Drew Kelly/Stanford HAI
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AI ethics in the spotlight

Jim Mortleman — April 2019

Concerns about AI’s negative impact have prompted a surge of pledges, guidelines and research initiatives aimed at ensuring the technology delivers human-centric outcomes. We look at the momentum gathering behind a vision for a more people-focused AI.

AI has been implicated in all manner of social ills in recent years. It has allegedly helped to subvert elections, promote dangerous conspiracy theories and even steer vulnerable teenagers towards suicide, for instance. The upshot is a consensus among academics, policymakers, businesses and the public that the implications of AI are so profound that its development can neither go unchecked nor be left in the hands of the technologists.

Yet, without greater interdisciplinary collaboration and understanding, there is a danger that ill-conceived policy decisions concerning the technology may damage its potential to deliver incredible social benefits.

Fortunately, Klaus Schwab, executive chair of the World Economic Forum, did not go unheeded when he said of AI in 2016: “Let us together shape a future that works for all by putting people first.” Many initiatives around the world are now working towards that goal, including Stanford University’s Institute for Human-Centered Artificial Intelligence (HAI), which opened in March. It aims to assemble people from a range of disciplines to ensure that AI’s development is guided by a concern for its impact on society; that AI augments human skills rather than replacing them; and that it incorporates more of the versatility, nuance and depth of human intelligence.

Stanford HAI’s co-director, Fei-Fei Li, says: “AI is transitioning into a field that extends far beyond computer science. In order to train AI to benefit humanity, the creators of AI need to represent humanity. This requires true diversity of thought across gender, age, ethnicity and cultural backgrounds, as well as different disciplines — from engineering, robotics and statistics to philosophy, anthropology and law. It’s time to build a complete AI feedback loop.” 

“To train AI to benefit humanity, its creators  need to represent humanity.”

While Li paints a vivid picture of how AI can bring life-enriching benefits in fields as diverse as healthcare, search and rescue, and education, she stresses that its pitfalls need to be addressed urgently. This has to start with eliminating algorithmic bias, mitigating the impact of job losses and devising new legal frameworks to define accountability in an age where machines such as self-driving cars may be making ethical choices on our behalf.

Stanford HAI is by no means the first initiative aiming to channel AI towards better outcomes for humankind. Fujitsu has led the field since 2015 with Human Centric AI Zinrai — an framework designed to “focus on areas of AI that are complementary to people’s lives.” Like Microsoft, SAP and many others in its field, Fujitsu has also formulated a set of value principles around a commitment to AI. Elsewhere, the Partnership on AI to Benefit People and Society is a consortium that includes Amazon, Facebook, Google and Apple, while the University of Montreal’s Declaration for a Responsible Development of AI has attracted more than 1,000 signatories.

The goal is well worth fighting for, according to Li, who says: “AI is a story about the human values we want our technology to embody. I have colleagues training deep neural networks to help stroke patients and using AI to understand world poverty and deliver training to people with no access to education. This is what human-centered AI is all about: a better world for everyone.”

First published April 2019
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  • AI ethics in the spotlight

    Human Centric Innovation

    AI ethics in the spotlight

    Concerns about AI’s negative impact have prompted a surge of pledges, guidelines and research initiatives aimed at ensuring the technology delivers human-centric outcomes. We look at the momentum gathering behind a vision for a more people-focused AI.

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