dc.contributor.author | Gupta, S. | |
dc.contributor.author | Langhans, S. D. | |
dc.contributor.author | Domisch, S. | |
dc.contributor.author | Fuso-Nerini, F. | |
dc.contributor.author | Felländer, A. | |
dc.contributor.author | Battaglini, M. | |
dc.contributor.author | Tegmark, M. | |
dc.contributor.author | Vinuesa, R. | |
dc.date.accessioned | 2023-08-29T09:32:35Z | |
dc.date.available | 2023-08-29T09:32:35Z | |
dc.date.issued | 2021-06-01 | |
dc.identifier.citation | Transportation Engineering: 4: 100064 (2021) | es_ES |
dc.identifier.uri | http://hdl.handle.net/10810/62256 | |
dc.description.abstract | "Since the early phase of the artificial-intelligence (AI) era expectations towards AI are high, with experts believing that AI paves the way for managing and handling various global challenges. However, the significant enabling and inhibiting influence of AI for sustainable development needs to be assessed carefully, given that the technology diffuses rapidly and affects millions of people worldwide on a day-to-day basis. To address this challenge, a panel discussion was organized by the KTH Royal Institute of Technology, the AI Sustainability Center and MIT Massachusetts Institute of Technology, gathering a wide range of AI experts. This paper summarizes the insights from the panel discussion around the following themes: The role of AI in achieving the Sustainable Development Goals (SDGs) AI for a prosperous 21st century Transparency, automated decision-making processes, and personal profiling and Measuring the relevance of Digitalization and Artificial Intelligence (D&AI) at the indicator level of SDGs. The research-backed panel discussion was dedicated to recognize and prioritize the agenda for addressing the pressing research gaps for academic research, funding bodies, professionals, as well as industry with an emphasis on the transportation sector. A common conclusion across these themes was the need to go beyond the development of AI in sectorial silos, so as to understand the impacts AI might have across societal, environmental, and economic outcomes. The recordings of the panel discussion can be found at: https://www.kth.se/en/2.18487/evenemang/the-role-of-ai-in-achieving-the-sdgs-enabler-or-inhibitor-1.1001364?date=2020â 08â 20&length=1&orglength=185&orgdate=2020â 06â 30 Short link: https://bit.ly/2Kap1tE © 2021" | es_ES |
dc.description.sponsorship | The authors acknowledge the KTH Sustainability Office and the KTH Digitalization Platform for their provided funding, which enabled the organization of this panel discussion. SG acknowledges the funding provided by the German Federal Ministry for Education and Research (BMBF) for the project “digitainable”. SDL acknowledges support through the Spanish Government | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Transportation Engineering | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/es/ | * |
dc.subject | Climate change | es_ES |
dc.subject | AI | es_ES |
dc.subject | Machine learning | es_ES |
dc.subject | Sustainability | es_ES |
dc.subject | Transportation system | es_ES |
dc.title | Assessing whether artificial intelligence is an enabler or an inhibitor of sustainability at indicator level | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2021 The Author(s) | es_ES |
dc.rights.holder | Atribución-NoComercial-CompartirIgual 3.0 España | * |
dc.relation.publisherversion | https://dx.doi.org/10.1016/j.treng.2021.100064 | es_ES |
dc.identifier.doi | 10.1016/j.treng.2021.100064 | |
dc.contributor.funder | KTH Sustainability Office | |
dc.contributor.funder | Leibniz Competition | |
dc.contributor.funder | German Federal Ministry for Education and Research | |