People First AI Strategy

Considerable article that is a transcript of a conversation with  Soumitra Dutta, professor of operations, technology, and information management at the Cornell SC Johnson College of Business on how decisions need to be made when including people and machines.   Agree in principle, but how do we place people first?   Which and how many people?   Can we  crowdsource the agreement of people.  And how transparent do we need to be to make sure that this is actually happening?

Why We Need a People-first AI Strategy  in K@W

With more access to data and growing computing power, artificial intelligence (AI) is becoming increasingly powerful. But for it to be effective and meaningful, we must embrace people-first artificial intelligence strategies, according to Soumitra Dutta, professor of operations, technology, and information management at the Cornell SC Johnson College of Business. “There has to be a human agency-first kind of principle that lets people feel empowered about how to make decisions and how to use AI systems to support their decision-making,” notes Dutta. Knowledge@Wharton interviewed him at a recent conference on artificial intelligence and machine learning in the financial industry, organized in New York City by the SWIFT Institute in collaboration with Cornell’s SC Johnson College of Business.

In this conversation, Dutta discusses some myths around AI, what it means to have a people-first artificial intelligence strategy, why it is important, and how we can overcome the challenges in realizing this vision.

An edited transcript of the conversation follows: 

Knowledge@Wharton: What are some of the biggest myths about AI, especially as they relate to financial services?

Soumitra Dutta: AI, as we all know, is not new per se. It has been there for as long as modern computing has been around, and it has gone through ups and downs. What we are seeing right now is an increased sense of excitement or hype. Some people would argue it’s over-hyped. I think the key issue is distinguishing between hope and fear. Today, what you read about AI is largely focused around fear — fear of job losses, fear of what it means in terms of privacy, fear of what it means for the way humans exist in society. The challenge for us is to navigate the fear space and move into the hope space. By “hope,” I mean that AI, like any other technology, has negative side effects – but it also presents enormous positive benefits. Our collective challenge is to be able to move into the positive space and look at how AI can help empower people, help them become better individuals, better human beings, and how that can lead to a better society.

Knowledge@Wharton: How do you get to the “hope” space in a way that is based on reality and away from the myths and hype?

Dutta: We need to have what I term as a “people-first” AI strategy. We have to use technology, not because technology exists, but because it helps us to become better individuals. When organizations deploy AI inside their work processes or systems, we have to explicitly focus on putting people first.

This could mean a number of things. There will be some instances of jobs getting automated, so we have to make sure that we provide adequate support for re-skilling, for helping people transition across jobs, and making sure they don’t lose their livelihoods. That’s a very important basic condition. But more importantly, AI provides tools for predicting outcomes of various kinds, but the actual implementation is a combination of the outcome prediction plus judgment about the outcome prediction. The judgment component should largely be a human decision. We have to design processes and organizations such that this combination of people and AI lets people be in charge as much as possible.

There has to be a human agency-first kind of principle that lets people feel empowered about how to make decisions, how to use AI systems to make better decisions. They must not feel that their abilities are being questioned or undercut. It’s the combination of putting people and technology together effectively that will lead to good AI use in organizations.

“The key issue is distinguishing between hope and fear…. The big challenge for us is to navigate the fear space and move into the hope space.”  ..... "