Editor’s Note: Viktor Mayer-Schönberger is Professor of Internet Governance and Regulation at the Oxford Internet Institute of Oxford University. He is also a faculty affiliate of the Belfer Center of Science and International Affairs at Harvard University. He has published nine books (most recently Big Data: A Revolution That Transforms How we Work, Live, and Think with Kenneth Cukier) and is the author of over a hundred articles and book chapters on the governance of information. He is a frequent public speaker, and sought expert for print and broadcast media worldwide. He and his work have been featured in (among others) New York Times, Wall Street Journal, Financial Times, The Economist, Nature, Science, NPR, BBC, The Guardian, Le Monde, El Pais, Die Zeit, Süddeutsche Zeitung, Der Spiegel, Boston Globe, Los Angeles Tribune, WIRED, Ars Technica, Daily Kos. You can read his full bio from here.
eTalk’s Niaz Uddin has interviewed Viktor Mayer-Schönberger recently to gain insights about his ideas, research and works in the field of Big Data which is given below.
Niaz: Dear Viktor, thank you so much for joining us. We are very delighted to have you at eTalks
Viktor: My pleasure.
Niaz: Big Data has become a talked topic in these days. A very tight hype about Big Data is going on over tech industry. Big Data means ‘Making sense of the New World’ to many people. Can you please tell us about this ‘New World’? What has actually changed? And what does ‘Making Sense of New World’ mean?
Viktor: What’s changed is that in the past, we weren’t able to apply to data to help our decision-making since the cost of collection, storage and analysis was so high. But as those barriers have fallen, we are not able to harness lots of data — and when we do, we can unlock new insights from it. Take predictive maintenance. We didn’t know when an engine part would break before it did in the past. Now, looking at lots of sensor data like sound, heat and vibrations – from tens of thousands of vehicles, through big data analysis companies can spot that a part is likely going to break in the near future, and change it before it actually breaks. That’s new. It’s a new way of interacting with the world in a more empirical, quantified way. And it’s because of the data.
Niaz: How do you define the term Big Data?
Viktor: We resist giving a concrete definition since that would limit it. But basically, it refers to the idea that we have so much more information these days that we can apply new techniques to it, to spot useful insights or unlock new forms of economic value. There are things we can do with a large body of data that we simply couldn’t when it was in smaller amounts. In our book, we identify three features: more, messy and correlations.
Niaz: What is Data Science?
Viktor: The idea is that a new profession that has emerged in recent years, that combines the skills of the statistician, software developer, infographics designer and storyteller. Instead of peering into a microscope to discover the mysteries of the world, the data scientist looks into massive databases to uncover a finding. That said, since it’s a new job title, what it means will surely change over time.
Niaz: What is more important: Big Data vs. Data Science?
Viktor: The two are not at all at odds with each other. Big data is when there is vastly more data available relative to the phenomenon or question to be investigated than before; when we are accepting of some level of messiness of the data; and when we are using big data correlations to tease out the “what” rather than aiming to understand the “why”. The data scientists work with data, sometimes but not necessarily always “big data,” to analyze the information and extract meaning from it.
Niaz: Who is a Data Scientist?
Viktor: These are people who serve a useful interface between the hard-to-understand data, and the people who need to understand and make decisions from it.
Niaz: Do you think Data Scientists Job is the sexiest job in 21st Century?
Viktor: There are lots of sexy jobs in the 21st century. A data scientist is just one. Statisticians, machine-learning expert are others.
Niaz: What are the educational backgrounds, trainings, skills and expertise that someone needs to become a Data Scientist?
Viktor: The data scientist will need a multidisciplinary background that spans math and statistics, to computer science, design and the humanities. This is because one needs to be fluent in the language of data — how to run regression models and double-tailed T tests. But also possess coding skills to write programs to scrap data, clean data, or simply collect data. Then, one needs to eye of a designer to present the data visually. And storytelling skills to have the data reveal a narrative. Finally, one needs a deep sense of humanity — to ensure we are not beguiled by data’s false charms, and we keep our common sense amid the spreadsheets.
Niaz: You along with Kenneth Cukier have published a book ‘Big Data: A Revolution That Will Transform How We Live, Work, and Think’ which has already become a best seller. Can you please give us a brief on your impressive book?
Viktor: In “Big Data” we aim to go beyond the big data hype, and explain why big data represents a paradigmatic shift in how we understand and make sense of the world. We suggest that three qualities characterize big data: more, messy and correlations (see above), and that big data analysis is founded on our ability to datafy the world – that is to render more and more aspects of the world into data format that then can be calculated and analyzed. We look at the value of data – and the importance of secondary uses, as well as the emerging big data value chain. We explain who will be winning and who will be losing in the big data era. But not everything is rosy. We talk in detail about big data’s dark sides – from its challenge to privacy to the threat of punishment by propensity. We suggest concrete safeguards to ensure that the dark sides of big data remain contained, including suggesting the need for a new cadre of professionals – the “algorithmists” – that will help protect us against big data abuse. We end with a cautionary chapter about the importance of the human element in a world of big data.
Niaz: After publishing the book, Big Data: A Revolution That Will Transform How We Live, Work, and Think, you have been speaking, engaging with readers and getting feedback. Now what are your new findings?
Viktor: It’s still the first inning — it’s still round one for big data. So before we think about what’s next, we need to get the word out about how transformational this will be. That said, every day brings new case studies of how companies and organizations are unlocking new value by harnessing information in new ways.
Niaz: Now Big Data is becoming an integral part of the organizations. Organization has started to hire Data Scientists having a strong belief that Big Data means Big Opportunity. Do you think Big Data means Big Opportunity?
Viktor: Absolutely. For those with the right mindset, data offers huge opportunities. There is a gold rush under way – as people, companies and society realize that most of data’s value remains to be uncovered.
Niaz: What is the dark side of Big Data?
Viktor: In the book we look multiple dark sides. In addition to privacy, we are particularly concerned about propensity – the use of big data analysis to hold individuals responsible for acts they are only predicted to commit. That we fear negates human volition – our ability to decide freely whether and when to act. Punishing people for predicted rather than actual behavior is undoing the notion of justice in our society.
Niaz: How to overcome this dark side?
Viktor: On privacy we suggest we need a significant adjustment in the way we protect it from big data surveillance, so that big data benefits can be reaped without making a mockery of individuals’ justified privacy concerns. But we also suggest that in the era of big data we need to broaden our understanding of justice – and what it entails.
Niaz: As you know Poverty has been ruling the world for centuries. Billions of people have been living hand to mouth and suffering from lack of nutrition, lack of education, lack of sanitation, lack of food etc.. There are hundreds of social organizations those who have been working with poverty and social problems. At the end of the day, these social organizations are unable to measure the changes they have made. Or we could say, they might fail to bring sustainable changes though billions of dollars have been invested by donors and other sources. But these poor people have been suffering and living almost the same life for decades after decades. Now can you please tell us how Big Data can be a help to analyze, map, measure and formulate the problems of poor people?
Viktor: Yes. There are two problems with measuring the plight of the poor in a small data age: it costs a lot of time and money to collect data about them, and it is hard and costly to analyze that data. In the big data age, we can use data that is collected for other purposes – say micropayments through mobile phones – and reuse it to better understand the economy of poverty. And because big data analysis is relatively cheap, and no longer requires huge upfront investments in processing and storage infrastructure, sophisticated big data analysis can be undertaken by a handful of people working for instance for a civil society organization.
Niaz: Do you think we can design and program solutions of our social problems with the help of Big Data analysis?
Viktor: Big data can provide us with a much better sense of what policy areas need to be addressed first, and what results our policy decisions might produce. But at the end of the day, machines cannot take decisions, humans do. And so whether or not we find solutions to our social problems depends not on big data, but on human empathy and resolve.
Niaz: Please tell us about how Big Data can be a great help to measure the changes that social organizations bring?
Viktor: Social organizations often do good things, but their impact is hard to measure – in part because in a small data world collecting such information was very costly. In the age of big data that may change, and thus give social organizations perhaps for the first time a chance to analyze and see how well they are doing, and where. That helps these organizations to learn and evolve, and to improve their impact.
Niaz: Can you please suggest us ways of changing this world with the rigorous use of technology and innovation to solve our social problems to make this mother earth a better place to live in?
Viktor: Take medicine: Today we are using medication developed for the average person, rather than customized for a particular individual. This means that today we over- and under-medicate. As a result billions are wasted, and people are suffering. Big data provides us with the ability to change this – so that we can treat illnesses on an individual level, and learn. It increases effectiveness, but more importantly it improves lives. But for that to happen we need to be able to collect and use the data.
Niaz: Viktor, thank you so much for your time and for all of these impressive ideas.
Viktor: You’re most welcome Niaz.
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