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Effect of AI on Sustainable Development Goals published in Nature will be discussed at workshop

Discussion at workshop on Digitalization for Urban Sustainability on 15 May 2020

At the top: logo of Sustainable Development Goals. Below: Graphics of a horizontal bar graph with two measured categories "Targets inhibited by AI" (in orange) and "Targets enabled by AI" (in green), where the latter (green) shows significantly higher bars. The bar sfor Environment shows 30% orange, and 93% green. The bars for Economy shows 33% orange, and 70% green, and finally the bars for Society shows 38% orange and 82% green.
A look at how many of the targets in each area would be inhibited or enabled by artificial intelligence. Graphics by: David Callahan
Published Feb 24, 2020

The first study analyzing the effect of AI on Sustainable Development Goals (SDG) was published in Nature in January 2020. In this study, KTH researchers cooperated with Max Tegmark and other researchers from New Zealand, Germany and Spain. The findings will be discussed in the workshop Digitalization for Urban Sustainability on 15 May 2020 arranged by IVL and KTH Digitalization Platform.


The emergence of artificial intelligence (AI) and its progressively-wider impact on many sectors requires an assessment of its effect on the achievement of the Sustainable Development Goals (SDGs). Using a consensus-based expert-elicitation process, we find that AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets. Two areas where we identify high potential of AI are health (SDG 3) and sustainable cities (SDG 11).

We found limited published evidence for the negative impact of AI regarding SDG 3, while significant number of studies show AI's potential in improving across its various indicators. Most notably, deep learning has been shown to help at different stages of cancer treatment, including the estimation of the risk of developing cancer, detection of cancer, and the pathology of tumor cells. Regarding SDG 11, currently-available methods to measure pollution levels in urban areas are not accurate enough, and this problem causes around 500,000 premature deaths only in the European Union. We have identified that AI, together with accurate computer simulations, can be used to develop more robust and reliable non-intrusive methods to measure pollution levels (as well as extreme temperatures) in urban areas.

The role of artificial intelligence in achieving the Sustainable Development Goals (Nature Communications)


Ricardo Vinuesa, Hossein Azizpour, Iolanda Leite, Madeline Balaam, Virginia Dignum, Sami Domisch, Anna Felländer, Simone Daniela Langhans, Max Tegmark & Francesco Fuso Nerini

Workshop: Digitalization for Urban Sustainability

We are currently working on this area, and we will discuss our initial results at the Workshop on Digitalization for Urban Sustainability on 15 May 2020 arranged by IVL and KTH Digitalization Platform. The event is mainly for KTH researchers, however, if non-KTH employees wish to participate, please contact Susanna Berglund at .

Updates about agenda and registration will be published in the calendar event link:

Workshop on Digitalization for Urban Sustainability

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How AI will affect UN goals for climate, development and global stability