"Without NRP 75, we would have missed many totally cool projects and important findings."
Reinhard Riedl, member of the Steering Committee, about NRP 75 and Big Data in general.
Can you tell us what Big Data means from your perspective?
For me, Big Data means making information implicitly contained in data sets explicit. This can take many different forms – from preparing data for analysis to extracting content findings and managing real-world systems to presenting data in a way that people can understand. The major challenges lie in processing heterogeneous data and data of dubious quality in a meaningful way, getting extremely large amounts of data under control and classifying the results correctly. Big Data can be used to work wonders and produce great benefits, but it can also be employed in shady business and cause damage.
Where do you expect the greatest impacts?
Big Data is expected to have the greatest positive impact on the average person in health care: On average, people will stay healthy longer thanks to Big Data. Big Data will support medical research, help automate simple tasks, improve diagnosis based on machine learning, support personalized precision medicine, assist physicians in processing complex knowledge and enable patients to better care for their health. The list goes on.
One important question, for example, is how to reduce false positives in warning systems in intensive care units. Too many false warnings lead to high levels of stress for staff and then to errors. This is where Big Data would help to reduce stress and potentially serious errors. One project of NRP 75 is specifically dedicated to this question.
Many people will also experience how Big Data will lead to a change in their field of expertise: Teachers, sports coaches and managers, as well as farmers, civil servants and judges. And of course, all researchers on a very large scale. Anyone who is enthusiastic about their profession and also inquisitive will appreciate it and learn how to use it well. Others will perceive it as a threat or use it carelessly and so senselessly that new checks and balances will have to be introduced. Take, for example, predictive policing, data-based personnel management or the use of data in the insurance industry.
Big Data will also challenge us all with the question of whether we want to consciously and rationally manage our resources or whether we prefer to continue acting on our instincts – from dealing with our talents, our time and our financial assets, to handling our health resources and our emotions, or even to using our circle of friends and relationships.
And what is nonsense?
Firstly, it is nonsense that Big Data makes the world a better place. Big Data can be used in a bizarrely cynical way, for example to selectively exploit the poor and the desperate. Big Data is simply able to help us become much better at what we want to do. This applies to idealists and specialists, as well as to people in power and to criminals.
Secondly, it is nonsense that Big Data can change the world quickly and at short notice. It works in parallel in many areas, but it often takes a very long time before it leads to changes in professional practice. Above all, these changes do not happen automatically.
Thirdly, it is nonsense that Big Data is making specialist disciplines superfluous and that in future only one science will be needed, namely data science. Big Data is an extremely powerful tool; it can potentially even promote transdisciplinarity, but it cannot replace specialist knowledge or creativity.
How has Big Data changed since the launch of NRP 75?
As expected, the development of algorithms has made great strides. Mathematics and statistics are moving more into the forefront. Big Data is no longer just a computer science thing. Equally important is that the use of algorithms in practical applications – in system control, research, specialist practice, administration and corporate management – has led us to a deeper understanding of opportunities, risks and practical challenges. This has resulted, for example, in research questions on "inference uncertainty". However, the first rational concepts for ethical reflection have also been developed. At the same time, the hype has diminished and many now dare to call out Big Data as a bluff. Others trivialize Big Data and reduce it to the use of very simple meshed tools. Actually, the confusion among the general public has become even greater. But that is normal in this phase.
How do you assess Switzerland's position with regard to Big Data research? With NRP 75, for example?
For the economic and political future of Switzerland, it is of absolutely vital importance to be on par with the best in the world in Big Data research. Those who are merely recipients of technological progress cannot act autonomously from a political point of view and have an economic problem. It is foolish to believe that the Americans and Chinese will solve the Big Data problems for us. We must do our own research on algorithms, technology and applications. In addition, we have the opportunity to demonstrate new perspectives based on our values, for example on multidisciplinary and transdisciplinary impact analysis and impact modelling. These are large, as yet scarcely researched fields.
What would be missing if NRP 75 had not been created?
Firstly, the many totally cool projects and the important findings which have resulted from them. We would have really missed something! Then there are the networks that are currently being established among the researchers participating in the programme. And last but not least, there is the political attention being paid to the topic. Political opinion shapers and decision makers are very interested in understanding how to promote the utilisation of Big Data in Switzerland and where regulatory intervention is necessary. NRP 75 will provide important input for political discourse in this area. In view of the reality of the legal paradox that early framework regulations usually lead to more liberal legislation than late regulations, the timely transfer of knowledge into politics is very important. For me personally, the transfer of knowledge to the economy on a broad front is also important. In Switzerland, we are several years behind the USA and other countries in the practical use of data. We can only catch up if normal companies and the administration begin to use Big Data tools effectively.
Reinhard Riedl studied technical mathematics and received his doctorate in pure mathematics. He is currently involved in the digital transformation of companies. He is Co-director of the Institute Digital Enabling (IDEA) at the Bern University of Applied Sciences (BFH), Director of the BFH Center for the Digital Society and Editor of www.societybyte.swiss.