Max Planck Institute for Human Development

Longitudinal study examines organ donation rates in five countries that have changed their organ donation default policy from opt-in to opt-out.
 

Mega-study investigates how the right wording can lead to more honesty

Cooperative project of scientists from 25 institutions and universities

The "Spook the Machine" experiment begins

New article outlines the ways large language models can help and hurt collective intelligence and proposes recommendations for action

The first self-driving cars are already on the road. Yet the technology is not yet fully developed, and certain ethical issues remain unsolved. It is also high time to think about how the new technology can promote sustainable transportation in the future.

Studies show that the louder political minorities shout on social networks, the quieter the democratic majority becomes. Hate, hate speech, and propaganda thrive in echo chambers and distort perceptions in political discourse. Researchers investigate this phenomenon from the perspective of social science, law, and mathematics.

Cognitive scientist Ralph Hertwig and his team at the Max Planck Institute for Human Development in Berlin are investigating why people consciously choose not to take note of certain information – and why this can sometimes be advantageous for orientation in our complex world.

According to traditional dogma, political decisions should be rational and sensible. Under no circumstances should they be emotional. However, the reality has always looked somewhat different. What importance did feelings have for political events?

We are increasingly encountering artificial intelligence (AI) in our everyday lives, from bots in call centers and robotic colleagues on assembly lines, to electronically controlled players in computer games. At the Max Planck Institute for Human Development in Berlin, Iyad Rahwan and his team are investigating how people behave when they interact with intelligent machines and what they expect from their artificial counterparts.

For the Communist Party, work was the “first necessity of life” and at the same time duty, it was fulfilment and the path to communism. But what did the people who had to do the work, day after day, actually think of it?

The Lise Meitner Group for Environmental Neuroscience at the Max Planck Institute for Human Development investigates how our environment influences our behaviour and our brain. It has been known for some time that our behaviour, and especially factors such as sport, diet and hobbies like video games, can alter our brains. Until now, however, the question of whether the environment that surrounds us on a daily basis also influences the human brain has remained largely unanswered. 

Machines powered by artificial intelligence take on ever more social roles. To study this new class of actors, their behavioral patterns, and ecology, Researchers of the Center for Humans and Machines at the Max Planck Institute for Human Development in Berlin describe Machine Behavior—an emerging approach that applies concepts and methodologies from across the behavioral sciences to intelligent machines. They review available empirical evidence on how machine behavior can corrupt human morals and evaluate the risks of AI agents acting as bad role models and AI advisors.

It is essential to carefully plan a scientific study to maximize the chance of its success. The planning phase typically includes considerations of statistical power, which is the probability that the study will show a hypothesized effect if it exists. Often, sample size is considered as the primary parameter. Particularly in longitudinal studies, however, there are numerous other parameters, such as the number of measurements and their distribution over time, which have a significant impact on the success and also the budget of a study.

Consumers need independent health information to evaluate health care services. Fast-and-frugal decision trees can reduce complexity and help consumers identify useful health information. Together with experts and laypeople and based on machine learning methods, we developed a fast-and-frugal tree that warns consumers about unreliable health information. Integrated learning methods, we developed a fast-and-frugal tree that warns consumers about unreliable health information. Integrated into the RisikoKompass-App (RiskCompass-App), the decision tree enhances consumer’s risk literacy.