At TDL, our role is to translate science. This article is part of a series on cutting edge research that has the potential to create positive social impact. While the research is inherently specific, we believe that the insights gleaned from each piece in this series are relevant to behavioral science practitioners in many different fields. At TDL, we are always looking for ways to translate science into impact. If you would like to chat with us about a potential collaboration, feel free to contact us.
As a socially-conscious applied research firm, TDL is interested in connecting cutting-edge research with real-world applications. To further this interest, The Decision Lab reached out to Michał Klincewicz, an assistant professor in Tilburg University in the Department of Cognitive Science, to learn more about his work on using video games to explore moral cognition and stimulate moral insight, as well as his use of machine learning to spot conspiratorial online videos.
In his research, Professor Klincewicz combines insights from social epistemology, data science, computational linguistics, psychology, neuroscience, and philosophy to learn about what can make individuals better decision-makers. With the aforementioned disciplines, he combines a mix of empirical and theoretical thinking to create transformative technologies.
A full version of some of Michał’s studies are available here:
- Robotic Nudges for Moral Improvement through Stoic Practice
- Drugs and Hugs: Stimulating Moral Dispositions as a Method of Moral Enhancement
- Artificial Intelligence as a Means to Moral Enhancement
Julian: How would you describe the focus of your research?
Michał: Recently, I’ve been focusing on two things: First, on video games in which players are faced with moral dilemmas. These simulations are a great way to stimulate moral insight, develop moral sensitivity, and are a versatile environment that can help us understand the psychological mechanisms behind complex decisions under uncertainty. Second, I’ve been focusing on developing machine learning algorithms that can spot conspiratorial YouTube content. A variety of insights from social epistemology, data science, and computational linguistics can be used to make these algorithms perform better. There is also a pressing need to counter the spread of misinformation.
Julian: What was your research question, broadly speaking?
Michał: I want to know what makes individuals better decision-makers. To find out, I use insights from across the cognitive sciences: psychology, neuroscience, linguistics, and philosophy. This is a mix of empirical and theoretical work, where it isn’t always clear which discipline may turn out to be relevant. I then use this knowledge to design technologies that can facilitate decision-making or improve individuals in the long-term.
Julian: What insights did you think you’d find out from your research, and why?
Michał: Put plainly, I’m interested in finding ways to make people better. There has been a lot of discussion across disciplines about how the psychology we inherited from our ancestors has left us unprepared for rapid technological change and globalization.
I look to identify which particular aspect of that inheritance is the main culprit and then find a way to either limit its impact or a way to counteract it with something else. There were some relatively good candidates to look at first: tribalism, biases, negative emotions, and general intelligence.
I thought one of these or a combination of them would be a good place to start and then that most of the work would be in designing an appropriate intervention to deal with it. Artificial intelligence techniques seemed like a very promising avenue at that point, given how well they do in classifying things and in finding patterns where none are immediately apparent.
Once the main problematic psychological mechanism is identified, we can use artificial intelligence techniques to identify when it is active and design an intervention to deal with it.
Julian: What is your general research process?
Michał: I work with a number of researchers across disciplines that have similar research agendas. In short, I like to work with people that aim to understand how technology shapes individuals and their environment for better and for worse. Their work and community is an important source of inspiration and direction to my own work.
I have also been fortunate to have dozens of talented students over the years. Together, we have designed and carried out controlled experiments, designed nudges and tested them, and developed methods for studying decision-making in video games. Overall, I would characterize my research process as being both vertical and horizontal collaboration. It is dialogue that is bound together by a common commitment to serious theory and science that serves the public good.