'Big data will help us understand the world better' argued Viktor Mayer-Schönberger when he visited the PP Platform

On September 18 the CBS Public-Private Platform and the Big Data Forum proudly presented a seminar with Viktor Mayer-Schönberger – one of the world’s leading experts on big data and co-author of the New York Times and Wall Street Journal best-selling book Big Data: A Revolution That Will Transform How We Live, Work and Think (co-authored with Kenneth Cukier from The Economist).

10/02/2013

150 guests gathered at CBS for a talk about Big Data

On September 18 the CBS Public-Private Platform and the Big Data Forum proudly presented a seminar with Viktor Mayer-Schönberger – one of the world’s leading experts on big data and co-author of the New York Times and Wall Street Journal best-selling book Big Data: A Revolution That Will Transform How We Live, Work and Think (co-authored with Kenneth Cukier from The Economist).

At the seminar, Viktor elaborated on his book by addressing questions about the processes and effects of widespread ‘datafication’ in a wide range of spheres. He started by outlining the process of datafication as: information that were always here, but which we didn’t treated as data before. Now, by encouraging an absolute system embedding the location of data then importing the data to a computer we can set-up new agendas for working and using the data.
 

How Big Data?

‘10 million photos are uploaded at Facebook in one hour’

stated Viktor Mayer-Schönberger at the fully booked seminar. More than 150 people had signed up and joined the PP-Platform and the Big Data Forum for an intense presentation. Represented in the room were private experts, researchers, public servants and students, all keen on learning more on the possibilities of big data, and the current challenges and limitations it carries along.

The photos on Facebook are just an example of the enormous amount of data that exist ‘out there’. Drawing on the term to ‘datafy’ Viktor describes the process of transferring data into more valueable with the aim of shifting the focus of data from collected to actual use.

Viktor argued that by focusing on big data rather than small data we can provide an outline for more qualified choices. Whereas with small data you focus on one thing and the rest is blurry, big data is the opposite, and if you can see it all – then you can choose what you want to focus on. He compared it to a camera, saying:  ‘wouldn’t it be great to have a photo camera where you don’t have to focus on one layer but where you capture every single light and then later on you choose what you want to focus on? Similar with big data, you can choose what you want to focus on after you have collected the data’. According to Viktor the problem with small data is also, that you have to invest time and thoughts on what you want to collect and you are limited to the notion of what is possible to collect. With fewer data points, you need to make them accurate. However, he underlined that we should not give up on other data methods, like small data, just because of the the possibilities now existing within big data.    

Working with big data both requires the right skills but it also calls for a certain mindset.  You need to understand the connections, links and possibilities existing in the data but at the same time, you must also know where and how to find the data. Newspapers write about scarcities these days– the scarcity of big data skills. Now instead, more and messy data put together can help us make correlations of data, linkages, patterns of data. And by that, he explains, we move away, at least partially, from asking ‘why’ to simply asking ‘what’. Knowing why is sometimes illusionary, knowing what might instead be a pragmatic step forward. Amazon uses methods like these to suggest books, and so do Netflix – they focus on what – and not why we are interested in e.g. a certain book he explained and stressed that it doesn’t mean we should give up on causality but correlations tells us a lot – and they do it in time.

Inspirational cases

In his presentation Viktor elaborated on the case of the flu:

‘What Google did was to take the 50 million most common things people search for and compare where and when these search threads has been used related with ‘the flu’. The idea was to predict the spread of the flu with a higher degree of accuracy. It worked!’

Another example from the presentation was the case of Rolls Royce. They have found that their flight engines collect data all the time. But they have never used these 3-5 GB bits of data collected at each flight. However this data can help them predict damages and thereby upholds maintenance in their engines by preparing a part before it breaks. Knowing this predictive maintenance gives a huge opportunity to re-invent products while at the same time drawing on the concept of reusing data.

Also the company Inrix was mentioned as an examble. Inrix sees their users as sensors, in the way that they transport themselves, and GPS data becomes a strategy aiming at collecting data, analyzing it and then providing information to be shared. Inrix maps data to make e.g. urban planning. 

The challenges

In regard to challenges Viktor argued that if big data is going to be the most pressures to own, we might see a challenge in the willingness to share it? Data is now protected by copyright, but having data might going to be the best recipe for success in the future! Viktor underlined in this relation that it can become a challenge to cope with this balance. And it is sad, as e.g. cloud capacity makes you easily access the data which can be of great value for start-up businesses. Therefore releasing data sets by the government in order to stimulate startup business and big data innovation could be great in a future perspective.

Furthermore Viktor explained, that the ‘problem’ with big data is not that privacy is challenged it is the mechanisms we use to protect our privacy that is challenged – that is the key problem and the key challenge when coping with big data in the future. In extension it is not big data analysis that is challenging, it is how we use the analysis capable of being made.
 

What is next?

Big data will help us understand the world better. It will improve medicine, how we educate our children and much more argued Viktor.

We have seen the risk and still more challenges is ahead. Though we should be careful not to focus too much on the dictatorship of data and hereby giving it more meaning and power than it actually deserves explained Viktor. We cannot and shall not forget humility; we need to have a place for the human, for rationality and imagination. Also in relation to all the possibilties big data reveals.

The data in the end of the day is always just a shadow of the reality and will therefore always be incomplete without the understanding and co-existence with the notion of humanity.

 

Viktor Mayer-Schönberger is Professor of Internet Governance and Regulation at the Oxford Internet Institute of Oxford University, and a faculty affiliate at Harvard University. He has published nine books, including the very influential book Delete: The Virtue of Forgetting in the Digital Age (2011), and 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, and WIRED. Learn more about Viktor and his work at the Oxford Internet Institute.

The page was last edited by: Public-Private Platform // 12/17/2017