Interview: Dave Marvit, Innovation Strategy Consultant, Fujitsu on Privacy and Sentiment Analysis challenges

We discuss the modern sentiment analysis challenges, how to address privacy concerns, Big Data predictions and more.

Dave MarvitDave Marvit is Innovation Strategy Consultant for Fujitsu Laboratories of America. There he has led projects ranging from digital negotiation systems to sensor-based healthcare, from automated ontology generation to novel interface methodologies.

Dave has worked as a writer and producer with WGBH’s Nova Science Team, served as a Mellon Visiting Professor at Caltech, and been involved with many Silicon Valley Startups. This includes his role as a founder, VP Production, and lead creative at Worlds Inc., and founder and VP Marketing at Disappearing Inc.

Dave is a Fellow of the Internet Archive. He was selected as one of Time Magazine’s 2001 “Digital Dozen” – one of the 12 most influential people in the digital world. He has over 70 patents granted and pending.

First part of this interview.

Here is the second part of my interview with him:

Anmol Rajpurohit: Q5. What do you consider as the biggest challenges in the progress towards this futuristic Sentiment Analysis?

ChallengesDave Marvit: I’d say that the biggest challenge is getting the sensors small enough and usable enough. The second biggest challenge will be developing a business model that drives deployment. I only list business model second because plenty of people will try plenty of ideas and something will succeed. There aren’t any fundamental physical barriers that need to be overcome – as there are with sensor development.

There are still plenty of issues to consider – privacy being high on the list. Finding the appropriate limits of self-knowledge will likely become another question we will all have to grapple with. But these changes will come.

AR: Q6. Even with the current technology solutions such as personalization, users are concerned about Privacy. So, would the "ubiquitous continuous sensing" not take privacy concerns to a whole another level? Do we have the right environment (technology, regulations, law enforcement) to address users' concerns about Privacy?

DM: Excellent question. A key to improving efficiency across many kinds of systems is information capture and sharing. This is true for everything from scheduling maintenance on big machines in factories to reducing demand on the electric grid. Efficiencies in our daily life and healthcare / wellness are no exception. The challenge unique to social and health issues, as compared to say, equipment maintenance, is finding a way to get those efficiencies without compromising people’s privacy.

I’m enough of a technologist to believe that there are technical solutions to this problem. I think there will inevitably be issues along the way as we move into this new world, but we will get there.

Data PrivacyThere are a few challenges along the way. One is to be collectively committed to learning from the issues. Another is to recognize that, however much we value privacy, we can’t foresee all of the new problems that will emerge as the technical and business landscapes change. We don’t know, and can’t know, many of the questions we need to ask.

As a distantly related example, look at the struggles around bitcoin and crypto-currencies. They are creating sets of questions that nobody had to think about before. The questions would have been impossible even to ask. Now regulators and enforcers are struggling to catch up. In the same way, ubiquitous continuous sensing will surface new questions that were previously impossible even to ask – let alone answer.

I believe that ubiquitous sensing is one of those areas where the technologists need to build in the appropriate systems to help us manage and maintain enough control over our personal data to protect our individual privacy – and by extension everyone else’s. I don’t think it is socially responsible to pass the responsibility along to the regulators or law enforcement. Sure, they have their role. But we technologists have our role too. We need to do our best from the outset, with enough humility to know that we won’t predict everything and enough commitment to jump on problems as soon as they surface.

AR: Q7. What do you personally think about the future of Big Data? Your predictions?

DM: I’m betting that the term ‘Big Data’ will seem quaint pretty soon. The technology community is already starting to move to a recognition that lots of data may be just lots of data. It will not necessarily translate into wisdom or even understanding. The big challenge ahead of us is figuring out what are right questions to ask, and how to ask them. The data alone isn’t nearly enough.

That said, I think we will come to take for granted the sea of data we will be awash in. We will come to expect to be able to review any aspect of our lives. ‘Where was I on that day?’ ‘How fast was I traveling?’ ‘What did I eat?’ ‘Who did I talk to?’ ‘What did I say?’ ‘How did I feel?’

All of that information will be at our fingertips – just as the web has made so much other information instantly available. All of this will be potentially interesting data. But the lessons we learn by looking at that data in new ways will be more interesting. There will be questions we haven’t even thought to ask yet that can suddenly shed light on how we live our lives and what it means to be human.

AR: Q8. What was the last book that you read and liked? What do you like to do when you are not working? The Alchemy of Air

DM: The Alchemy of Air: A Jewish Genius, a Doomed Tycoon, and the Scientific Discovery That Fed the World but Fueled the Rise of Hitler by Thomas Hager. I found it and incredibly dramatic example of the moral ambiguity and unpredictability of scientific discovery.

When not working I enjoy playing the Asian board game ‘Go’ and riding my recumbent bike (though generally not at the same time).