Synthese, doi.org/10.1007/s11229-018-01929-5 Abstract A moderately risk averse person may turn down a 50/50 gamble that either results in her winning $200 or losing $100. Such behaviour seems rational i

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.

Olle Häggström: Large Language Models, AI Risk and AI Alignment

Research seminar with Olle Häggström, a professor of mathematical statistics at Chalmers University of Technology, an affiliated researcher at the Institute for Futures Studies, and a member of the Ro

Venue: Institutet för framtidsstudier, Holländargatan 13 in Stockholm, and onlineResearch seminar with Olle Häggström, a professor of mathematical statistics at Chalmers University of Technology, an affi

Global Environmental Politics Abstract Much existing empirical research on polycentric climate governance (PCG) systems examines small-Nexamples. In response, we aim to advance studies of PCG by explori

2010. Pp. 183-205, European Journal of Population, vol. 26 (2).

An important mechanism in low fertility countries is social interactions and its effects on ideal family size; as this is hard to capture in formal models, this paper uses an agent based simulation mo

Delmi Policy Brief 2022:3. Abstract Three weeks after the Russian invasion of Ukraine more than three million people have fled the war. Knowledge and predictions on the flow of migrants are important for

This paper examines the Nordic Social Democratic parties’ own efforts to manage the inner and outer challenges of the so-called Nordic welfare model, i.e. how it is described, legitimized, and what ro

Big Data & Society Abstract In recent years, both private and public organizations across contexts have begun implementing AI technologies in their recruitment processes. This transition is typicall