In 2007, the Swedish gambling agency ran a simple gambling game called LIMBO. Gamblers were invited to stake 10 kronor on a number of their choice between 1 and 99,999. The person choosing the smalles

Noûs 53 (1), 3-22 Abstract How do we get out knowledge of the natural numbers? Various philosophical accounts exist, but there has been comparatively little attention to psychological data on how the lea

Erik Mohlin, Oxford University We exploit a unique opportunity to study how a large population of players in the field learn to play a novel game which has a complicated and non-intuitive mixed strateg

Synthese, 1-18. Abstract Game theory is a formal approach to behavior that focuses on the strategic aspect of situations. The game theoretic approach originates in economics but has been embraced by sch

Machine learning and social science with Måns Magnusson

Presentation from the workshop "AI and autonomous decision making" at the Institute for Futures Studies in Stockholm, October 2017.

Machine learning, norms and data collection with Pontus Strimling

Presentation from the workshop "AI and automated decision making" at the Institute for Futures Studies in Stockholm, October 2017.

This paper estimates cohort size effects on earning profiles and whether these are affected by an individual’s position in the Swedish Baby Boom and Baby Busts. Amongst other, it is found that higher

Journal of Health Organisation and Management. DOI:10.1108/JHOM-05-2019-0130 AbstractThe purpose of this paper is to analyse ethical competence related to healthcare governance and management tasks at t

in: Technology in Society. 63, 101396 Abstract:Artificial Intelligence (AI) in the form of Deep Learning (DL) technology has diffused in the consumer domain in a unique way as compared to previous gene, i.e., by being added to preexisting technologies that are already in use. We find that DL-algorithms for recommendations or ranking have been infused into all the 15 most popular mobile applications (apps) in the U.S. (as of May 2019). DL-infusion enables fast and vast diffusion. For example, when a DL-system was infused into YouTube, it almost immediately reached a third of the world's population. We argue that existing theories of innovation diffusion and adoption have limited relevance for DL-infusion, because it is a process that is driven by enterprises rather than individuals. We also discuss its social and ethical implications. First, consumers have a limited ability to detect and evaluate an infused technology. DL-infusion may thus help to explain why AI's presence in society has not been challenged by many. Second, the DL-providers are likely to face conflicts of interest, since consumer and supplier goals are not always aligned. Third, infusion is likely to be a particularly important diffusion process for DL-technologies as compared to other innovations, because they need large data sets to function well, which can be drawn from preexisting users. Related, it seems that larger technology companies comparatively benefit more from DL-infusion, because they already have many users. This suggests that the value drawn from DL is likely to follow a Matthew Effect of accumulated advantage online: many preexisting users provide a lot of behavioral data, which bring about better DL-driven features, which attract even more users, etc. Such a self-reinforcing process could limit the possibilities for new companies to compete. This way, the notion of DL-infusion may put light on the power shift that comes with the presence of AI in society.

Swedish preparedness for silent health crises and organizational learning after the swine flu, the heatwave, and the COVID-19 pandemic

This project aims to identify organizational conditions for efficient crisis management within intensive care units and special accommodations. It will also give recommendations on how the regions can strengthen their preparedness for silent health crises.