Emma Engström

I defended my PhD thesis on predictive modeling of groundwater contamination at the Department of Sustainable Development, Environmental Science and Engineering (SEED), KTH, Royal Institute of Technol

Karim Jebari & Emma Engström: Sustainable Agriculture - How Far Can Technology Take Us?

What would it take to have a sustainable world by the year 2100? In their research, philosopher Karim Jebari, and Emma Engström, PhD in technology, have analyzed a large set of potentially disruptive

Transportation Research Part D: Transport and Environment 69, pp. 276-292, doi: 10.1016/j.trd.2019.02.008 Abstract Dedicated to show climate leadership, Sweden has committed to cut 70% of greenhouse-gas

Hydrogeology Journal 25(4) pp. 1077-1091, doi: 10.1007/s10040-016-1504-x Abstract This study developed methodology for statistically assessing groundwater contamination mechanisms. It focused on microbiahumanitarian aid organisation Médecins Sans Frontières in 2010. The factors included hydrogeological settings, land use and socio-economic characteristics. The results showed that the residuals of a conventional probit regression model had a significant positive spatial autocorrelation (Moran’s I =3.05, I-stat = 9.28); therefore, a spatial model was developed that had better goodness-of-fit to the observations. The mostsignificant factor in this model (p-value 0.005) was the distance from a water source to the nearest Tukul area, an area with informal settlements that lack sanitation services. It is thus recommended that future remediation and monitoring efforts in the city be concentrated in such low-income regions. The spatial model differed from the conventional approach: in contrast with the latter case, lowland topography was not significant at the 5% level, as the p-value was 0.074 in the spatial model and 0.040 in the traditional model. This study showed that statistical risk-factor assessments of groundwater contamination need to consider spatial interactions when the water sources are located close to each other. Future studies might further investigate the cut-off distance that reflects spatial autocorrelation. Particularly, these results advise research on urban groundwater quality.

Environmental Earth Sciences 74(6), pp. 4827-4837, doi: 10.1007/s12665-01 Abstract Bacterial attenuation in porous media is often higher in columns than in the field. This study investigates whether this

In Hanemaayer, A. (editor) Artificial Intelligence and Its Discontents. Palgrave. Abstract AI has often reached individuals covertly, rather than by their own choosing. Standard automatic version update

I Hanemaayer, A. (editor), Artificial Intelligence and Its Discontents. Palgrave. Abstract (book) On what basis can we challenge Artificial Intelligence (AI) - its infusion, investment, and implementatio

Health Informatics Journal Abstract This study aimed to explore radiologists’ views on using an artificial intelligence (AI) tool named ScreenTrustCAD with Philips equipment) as a diagnostic decision su

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.

Ai & Society. Curmudgeon paper Abstract There is a disturbing discrepancy between the AI ethics frameworks that highlight the technology’s ability to promote the social good and the relationship bet