Industry Address

Jonas is chief scientist of the IBM Entity Analytics group and an IBM Distinguished Engineer. The IBM Entity Analytics group was formed based on technologies developed by Systems Research & Development (SRD), founded by Jonas in 1984 and acquired by IBM in January 2005. Prior to IBM’s acquisition, he led SRD through the design and development of a number of extraordinary systems, including technology used by the surveillance intelligence arm of the gaming industry. Leveraging facial recognition, this technology enabled the gaming industry to protect itself from aggressive card count teams, the most notable known as the MIT team and the subject of the book “Bringing Down the House” and recent movie “21.” Today, possibly half the casinos in the world use technology created by Jonas and his SRD team. His work frequently is featured on the Discovery Channel, Learning Channel and the Travel Channel. And it has a significant bearing on how service providers might start thinking about their customer databases. Read more about Jonas and his work at http://jeffjonas.typepad.com.

Today, Jeff Jonas charts the big vision for the IBM Entity Analytic Solutions group, but through his career he has charted a course across the information management and identity analytics landscape that this industry would be well served to follow. He will share his vision in a keynote address at the Billing & OSS World Conference & Expo in April in Las Vegas.

Jeff Jonas is a distinguished engineer and chief scientist at IBM (IBM), but it only starts there. He also is a member of the Markle Foundation Task Force on National Security in the Information Age. He’s a senior associate for the Center for Strategic and International Studies and a contributor to leading think tanks, advocacy groups and policy research organizations on matters of privacy, technology and homeland security.

These are his credentials, but his ideas are here on his blog where you may find yourself sharing what he calls his absolute fascination with this space. Only someone who is so fascinated can build systems as diverse as an inventory system for fish in the Mirage Casino aquarium or a genealogy system for the North American Llama Society and as businesslike as the order fulfillment distribution system for Netscape and the 150 to 200 other systems his company, Systems Research & Development (SRD), built before it was acquired by IBM in 2005. He got famous for helping casinos catch cheaters, but today he’s all about information management and promoting the responsible use of this amazing yet potentially invasive technology.

Here, he speaks to B/OSS editor Tim McElligott on privacy, civil liberties and the imperative for companies to achieve sense making in real time.

How did you become so fascinated with data analytics?

It was an accident. My company, SRD, was a custom software company. Organizations would come to us and ask us to build systems for all kinds of things. So the position I have been in for most of my life is [figuring out] how to take the information an organization has and harness it to make it more useful. It is not so much analytics as it is information management. Within information management there are a lot of pieces, one of which is analytics.

What is your role with IBM today?

I play a number of roles. I chart the big vision about where to take the technology. I also help determine how to solve certain problems. We have a highly competent group, but sometimes I get involved in deciding should we turn right or left. That is 10 percent of what I do.

I am quite active in the privacy and civil liberties conversation. I am a technologist, so I don’t pretend to be a privacy advocate, but I have come to realize that if people like myself and my team build powerful systems that are smart, [it’s important] to make sure they get implemented with the correct level of privacy and civil liberties protection. I find myself in a lot of conversations with people in the privacy community and I actively encourage more technologists to spend more time with people in the privacy advocacy field. I think that is good for America. I think it is good for the world.

I also think transparency is good. Certainly there are elements of transparency that exist today like with the Freedom of Information Act, and I think things like Facebook allow people to show more transparency. I can’t speak to absolute transparency, but more transparency is good.

There is a lot of room for abuse with information technology. How can you set limits on how someone might use it?

A couple of things are essential. I testified in the Department of Homeland Security Data Privacy and Integrity Advisory Committee and there I laid out five or six things we can build into the technology to give it higher levels of responsibility. (Editor’s note: You can see them and more in his blog: Macro Trends: The Privacy and Civil Liberties Consequences...and Comments on Responsible Innovation.)

There are notions like data tethering that help you keep your data current across an ecosystem by ensuring that if the custodian of data makes a change, that change is received by the recipient. And there’s full attribution, a core piece of data tethering that means every piece of data knows from whence it came. You never want to be holding a piece of data that you don’t know who gave it to you or why.

Why are service providers having such a hard time making the best use of their data?

It isn’t just them. This happens to be a common problem just about everywhere. But I think the agenda is switching to be all about the information. And the key point about that is organizations are only as smart as the net sum of their perceptions. If organizations have no access to data, they can’t use it, but they have collected enormous piles of data that lie as an unharnessed asset. I think it is of the absolute highest importance to better recognize like things, to know if [you’re looking at] three customers with one account or one customer with three accounts.

It’s called identity resolution. It lets you know if you’re dealing with one customer and not three. The more broad technical term would be semantic reconciliation which recognizes like things despite their having been described differently. Being able to count like things is essential if you want to have any kind of accurate analytics.

But let’s go to a higher level. The way to compete is not just to make more sense of the data. Everyone is working on figuring that out. You really want to make more sense of more data, but you want to make sense of it first. You need to be able to act and move faster than your competition. You want, at the moment a piece of data is arriving at your organization, to make sense of it and in that split second take the very best action while the transaction is occurring. Not 10 minutes after someone hangs up, not next week after you missed the obvious. It’s really about sense making in real time, to know — based on the net sum of your perceptions — the moment someone is subscribing whether they have been a customer before, if so how many times, if they were a good customer or bad, which way to steer them or if this the person that has been ripping you off every six weeks.

Other thoughts on privacy?

What is driving the surveillance society is not government. I have come to the conclusion that a surveillance society is not only inevitable and irreversible, but the oddest thing is that it is irresistible. And you and I are doing it. You want a phone with GPS so you can locate Starbucks and find your kid. You’re going to want RFID in your glasses so you don’t lose them again. This is really what is driving the surveillance society. As soon as you give consumers a more convenient way to do something, they just throw away their privacy and control.

And if I were to synthesize what I have learned from all the time I spent in the privacy community, the number one thing is avoiding consumer surprise, and that is all about educating the consumer. It is the real hard part and has nothing to do with technology.