Dirk Helbing is convinced that data ethics and combinatorial innovation are the basic prerequisites for the economy of the future. In an interview, the ETH Professor of Computational Social Science explains why this change is essential – and why companies need to assume greater responsibility for our society than ever before.
Text: Christoph Widmer, Images: Herbert Zimmermann,
We can see that digitisation is drastically changing all our institutions, and in some cases completely reinventing them. For example, more than 70% of all share trading is now conducted using algorithms. In connection with blockchain, the “code is law” principle is gaining significance because the program code of a smart contract contains all the contractual information while all the execution and transactions remain unchanged. Digitisation is thus also affecting our legal system. Meanwhile in business, money is being reinvented: we have Bitcoin and Ethereum and data is being heralded as the new oil.
Companies are developing strongly into data-driven businesses. Every company collects, evaluates and exploits data to either optimise its processes or develop new business models and ultimately generate added value from the data. This approach has far-reaching consequences.
Data use requires a framework that takes human rights into perspective. It must have a value-oriented approach. In this context, the issues of privacy and informational self-determination are more relevant than ever. A few years ago, it was claimed that privacy was dead and we should get used to it. But now Facebook, for example, has chosen “The future is private” as the new guiding principle for its business. This shows that digitisation is setting new priorities. Data ethics and ethical AI are complementing today’s business fields and this in turn is creating opportunities for companies to position themselves accordingly on the market. After all, these approaches seem to be the most promising for both today and the future – especially in Europe.
Prof. Dr. Dirk Helbing: Professor of Computer-Aided Social Sciences, ETH Zurich
It was once believed that you could control not only companies but our entire society using a data-driven approach. The first models for smart cities were very strongly data-driven. Everything was recorded and many processes were automated. But it turned out that these concepts did not work very well, either as business models or politically. After all, a data-driven society ultimately implies mass surveillance and totalitarianism, of which China and its social credit system is the best example. I do not think this is a good idea, especially in Europe, which has such a deep-seated understanding of democracy. Technologies should serve us, not the other way around.
We must include those people who are considered to be disrupting factors by a purely data-driven society. What is important for people often cannot be measured – or only with difficulty – and is therefore not adequately represented by data: human dignity, love, freedom, creativity and so on. In the past, privacy served as a protected place in which these values could flourish. And yet now, our smartphones, computers, televisions and even kitchen appliances are constantly collecting data about our personal lives. We need digital upgrades which create a social system that takes account of those values that are enormously important to us as human beings. At the same time, this system must be able to compete economically with other systems, such as the Chinese one. In this respect, we can perhaps learn a lot from Taiwan’s digital democracy.
For the economy, I recommend the concept of combinatorial innovation: Innovations in different technological fields can increasingly be combined to form new applications. This requires more openness and cooperation between companies and leads in part to more open data, more open innovation and a more open source approach. It is conceivable that knowledge gained from data could be made available to the general public in anonymised form after a certain time in a similar way to how patents are disclosed. Companies could also support a platform for informational self-determination. In this, the data of individual citizens would be sent to personal data mailboxes and they could then decide for themselves which companies were permitted use which data for their purposes. Ultimately, it would constitute competition based on trust, in which even SMEs, spin-offs, NGOs and research establishments were given an opportunity to gain access to extensive data.
That’s true. Today’s economy is characterised by the “everyone vs. everyone else” principle. However, we mustn’t assume that our economy and society will always function in the same way as they do today. Our current economy is not sustainable, and this lack of sustainability means it is not sufficiently future-proof. Companies are partly responsible for helping tackle the challenges that we face as humans today – and thus also the problem of the scarcity of resources. What we need is a new social contract in which the roles of the state, of companies and of civil society are recalibrated. Only then can we use resources responsibly, be they raw materials or data. A sharing economy and a circular economy are the keys to this. That is why we need underlying conditions which ensure that digitisation strengthens everyone and leaves nobody behind. Neither the state, nor the economy nor the civil society.
If Switzerland and its digital business models want to be able to compete with markets such as China or Silicon Valley, we will have to do things a little differently. In some ways, Switzerland has the best prerequisites to promote combinatorial innovation on a large scale: People know one another. Switzerland is manageable in terms of its size and population. The idea of the collective intelligence that we need for innovation and information ecosystems is to some extent anchored in the grassroots democracy that forms Switzerland’s “DNA.” The conditions in Switzerland are therefore ideal for bringing about this transformation.
Dirk Helbing has been the Professor of Computational Social Science at the Department of Humanities, Social and Political Science and the Department of Computer Science at the ETH Zurich since 2007. He studied physics and mathematics and now works on the modelling of social systems and complexity research. He also coordinates the FuturICT initiative, which aims to solve global problems through new approaches to a digital society.
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