Fear of Technology
A critical look can lead to more caution
In Germany there is less investment in innovative technological start-ups than in, for example, the United States. Is this a sign of greater scepticism about technology? Check out this interview with the philosopher of technology, Christian Vater.
By Arne Cypionka
The process involved in machine learning is unspectacular when it comes to the details – but at the same time it is an impressive technique that our forefathers would not have believed possible 80 years ago. This spawns all kinds of myths, both in terms of tales of fear and in terms of formulating hope. For example – artificial intelligence will be able to steer our planet through the climate catastrophe better than any human being. Or – artificial intelligence will take on a life all of its own and wipe us all off the planet. If we look at the books and films in the realm of science fiction, then it is all there and has been for quite some time. These stories have been around at least since the age of romanticism with Frankenstein and most definitely since the early history of cinema with Metropolis.
How justified are these concerns? Will Frankenstein soon become reality?
We are already surrounded by machines that can be reconfigured independently. Did that lead to us suddenly having to deal with intelligent, anthropomorphic androids? No. We now have devices that do not need an assistant standing by who constantly has to plug and unplug things. And we have devices that can perform measurement series, for example, without any experts monitoring them. Our technology has become adaptive. No more and no less.
Nevertheless, these machines are increasingly turning into black boxes for laypeople – they can no longer understand how they exactly work. Doesn’t the use of such technologies potentially result in a loss of social control? Here I am thinking, for example, of predictive policing, in which algorithms based on data are used to predict future crimes and justify preventive police operations.
Predictive policing is an attempt to build forecasting tools that are heavily data-driven. Behind it are models of how people commit crimes, or in which districts these people live and which crimes they commit and in which ways. These findings are intended to help the machine designers make and validate their assumptions. These assumptions, if they are presented transparently, can then be listed and checked individually, for example, with the help of sociological tools, However, this is a lot of work.
Christian Vater worked in the collaborative research centre “Material Text Cultures” of the German Research Foundation and has worked as a scientific consultant in various start-ups. He is doing a PhD in Heidelberg on Alan Turing and Artificial Intelligence in Philosophy. | Photo: © Ute von Figura, Heidelberg What is happening in Germany in this regard? Is anybody doing this work?
In Germany we have a conspicuously active association that deals with these questions and is taken very seriously – the Chaos Computer Club (CCC). It is represented in every relevant expert committee of the Federal Government and is now also consulted at Bundestag hearings.
But isn’t it the CCC in particular that frequently warns of misuse and the risks of new technologies?
A critical look does not necessarily have to be destructive or pessimistic – it can also lead to more caution.
These days start-up companies are considered to be a guarantee for innovative technology development. Compared to Silicon Valley, however, the German start-up scene seems to be more cautious. Are people more sceptical about new technologies in Germany?
The financing structures are different for us. There are not many hedge funds in Germany that specialise in seed investment. They speculate on the fact that if they finance ten small start-ups, one of them will generate enough profit that all the other investments will pay for themselves. In Germany, savings banks and Volksbanks (cooperative banks) are typically the first to invest in a new business. Since they manage community money to a greater or lesser extent, they are cautious business partners who invest less eagerly in projects.
So it’s more of a structural problem.
And one, too, that may change. Universities, for example, have identified this deficiency and are now making their own investments through the university’s own incubators, which provide support in the first phase from the initial idea to the planning. This funding is very low-threshold: the incubators offer office space, an internet connection, a mailbox. In Germany, there are also many hacker spaces in which state-of-the-art technology is available to all interested laypersons thanks to public funding or sponsorship, for example, in the form of drones or 3D printers. And, as an extension to the hacker spaces, there are more and more special coworking spaces. In Darmstadt, for example, office space has been created around the Hacker Spaces Lab3 and Hub31 for the first phase of the start-up.