Artificial Intelligence

IBM Watson CTO: The 3 ethical principles AI needs to embrace

TechRepublic spoke to IBM's Rob High about the ethical, privacy, and security obstacles that artificial intelligence has to overcome.

IBM Watson CTO Rob High has done a lot of thinking about the privacy, security, and ethical implications of artificial intelligence. He presented some of those ideas at Mobile World Congress 2018, and we talked to him about some of his key findings.

You can watch the interview above or read the transcript below.

High said, "One of the things we have to realize about AI—it's relatively new to all of us. There's a lot about it that we don't all fully understand. Even as a technologist, we know where we're trying to bring the technology, but on the other side there's lots of people for which this technology is new. The experiences around that are going to be different. As with any new technology, it's really important that we be thinking now about how we do that ethically and responsibly. For us, that comes down to three basic principles. Trust, respect, and privacy.

"What that basically means is that when you're using an AI technology, you have to trust that it's going to be doing the right thing. Or you focus on things like, can we create transparency in the AI algorithms? Can we get the algorithms to actually identify your level of confidence (in them), for example."

SEE: IT leader's guide to the future of artificial intelligence (Tech Pro Research)

"Transparency comes down to can we identify what sources of information are being used? Have we established the right properties, the right principles in place when we train these systems to use data that is representative of who we are, and the information that we're using?" said High.

"Of course, privacy comes down to recognizing that your data is our data. It should be your choice as to what data you're going to provide in order to gain the benefits these AIs offer. That goes from everything from the privacy of enterprise data, and the data that enterprises bring to the table when they use AIs, maintain separation between each of the enterprises all the way through, to how those enterprises protect the privacy of the data of their clients."

High added, "The journey for adopting AI and delivering that for value to clients begins with one very basic proposition, which is, is the AI going to augment and amplify the intelligence of the people using it? Because if it's not doing that, it's probably not going to be very useful. You're going to lose this utility very quickly. First of all, identify what that is. How do you help people do what they do better?

SEE: How to implement AI and machine learning (ZDNet special feature) | Download the report as a PDF (TechRepublic)

"If you get that out of the way then you can begin to look at how to apply the technology, but all through that we really encourage our clients to think about two things. One is, how they're going to protect and preserve the privacy of their institutions, of their clients. But also how do they convey the responsibility of their clients to be aware of what data they're getting across and to challenge those cases where, perhaps they don't want to give up the data they're offering. Or at least to make sure the value they're getting from that data is also very supportive of this idea that's augmented their intelligence."

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Image: CNET/Sarah Tew

About Jason Hiner

Jason Hiner is Global Editor in Chief of TechRepublic and Global Long Form Editor of ZDNet. He's co-author of the book, Follow the Geeks.

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