This paper outlines recent developments in private provision of elder care services and examines arguments and actors for increasing private financing, both supportive and dissenting. The purpose is t

Population Research and Policy Review 41, p. 1619–1639 Abstract Modern fertility techniques allow parents to carry out preimplantation sex selection. Sex selection for non-medical purposes is legal in m

Journal of Family Issues, doi:10.1177/0192513X14522244. Abstract Couples generally move to accommodate men’s, rather than women’s, career opportunities. Using Swedish panel data including 1,039 married o

Journal of Cross-Cultural Psychology, 0022022115605387. Abstract Cialdini has argued that whereas injunctive norms motivate behavior by their promise of social sanctions, descriptive norms motivate beha

Educational and Psychological Measurement, Vol. 77 (2017), 4, p. 616-630. Abstract Null hypothesis significance testing (NHST) provides an important statistical toolbox, but there are a number of ways i

Oskar Nordström Skans och Lena Hensvik, Institutet för arbetsmarknads- och utbildningspolitisk utvärdering The Montgomery (1991) model of employee referrals suggests that it is optimal for firms to sel

Lorne L. Dawson: Reconceptualizing Lone-Actor Terrorists as Solo Public Mass Murders

Lorne L. Dawson, Professor Emeritus, University of Waterloo, Canada. In public and expert judgements of whether an incident of mass violence by a lone actor is an instance of terrorism or simply mass m

Completed: Predicting the diffusion of artificial intelligence

A framework for predicting the spread of AI applications.

Delmi Report 2024:11 Summary This report investigates how migration aspirations within the Russian population have evolved following the full-scale invasion of Ukraine by Russia in 2022. It primarily fo

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.