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A definition, benchmark and database of AI for social good initiatives


Initiatives relying on artificial intelligence (AI) to deliver socially beneficial outcomes—AI for social good (AI4SG)—are on the rise. However, existing attempts to understand and foster AI4SG initiatives have so far been limited by the lack of normative analyses and a shortage of empirical evidence. In this Perspective, we address these limitations by providing a definition of AI4SG and by advocating the use of the United Nations’ Sustainable Development Goals (SDGs) as a benchmark for tracing the scope and spread of AI4SG. We introduce a database of AI4SG projects gathered using this benchmark, and discuss several key insights, including the extent to which different SDGs are being addressed. This analysis makes possible the identification of pressing problems that, if left unaddressed, risk hampering the effectiveness of AI4SG initiatives.

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Fig. 1: Projects addressing the SDGs.
Fig. 2: Projects addressing different aspects of climate action.

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  1. Hager, G. D. et al. Artificial intelligence for social good. Preprint at (2017).

  2. Wang, D., Khosla, A., Gargeya, R., Irshad, H. & Beck, A. H. Deep learning for identifying metastatic breast cancer. Preprint at (2016).

  3. Davenport, T. & Kalakota, R. The potential for artificial intelligence in healthcare. Future Healthc. J. 6, 94–98 (2019).

    Article  Google Scholar 

  4. Rolnick, D. et al. Tackling climate change with machine learning. Preprint at (2019).

  5. Zhou, Y., Wang, F., Tang, J., Nussinov, R. & Cheng, F. Artificial intelligence in COVID-19 drug repurposing. Lancet Digit. Health 2, e667–e676 (2020).

    Article  Google Scholar 

  6. Hilbert, M. Big data for development: a review of promises and challenges. Dev. Policy Rev. 34, 135–174 (2016).

    Article  Google Scholar 

  7. Taylor, L. & Schroeder, R. Is bigger better? The emergence of big data as a tool for international development policy. GeoJournal 80, 503–518 (2015).

    Article  Google Scholar 

  8. Floridi, L. & Cowls, J. A unified framework of five principles for AI in society. Harv. Data Sci. Rev. 1, (2019).

  9. Taddeo, M. & Floridi, L. How AI can be a force for good. Science 361, 751–752 (2018).

    Article  MathSciNet  Google Scholar 

  10. Vinuesa, R. et al. The role of artificial intelligence in achieving the Sustainable Development Goals. Nat. Commun. 11, 1–10 (2020).

    Article  Google Scholar 

  11. Chui, M. et al. Notes From The AI frontier: Insights From Hundreds Of Use Cases. (McKinsey Global Institute, 2018).

  12. International Telecommunication Union (ITU) AI Repository;

  13. AI for Good Global Summit (28−31 May 2019, Geneva, Switzerland) (AI for Good, 2019);

  14. Strickland, E. How IBM Watson overpromised and underdelivered on AI health care. In IEEE Spectrum: Technology, Engineering, and Science News (IEEE, 2019).

  15. Ross, C. & Swetlitz, I. IBM pitched its Watson supercomputer as a revolution in cancer care. It’s nowhere close. In STAT (5 September 2017).

  16. Goel, A. et al. Using Watson for enhancing human-computer co-creativity. In 2015 AAAI Fall Symp. Ser. (IEEE, 2015).

  17. Abebe, R. et al. Roles for computing in social change. In FAT* ’20: Proc. 2020 Conf. on Fairness, Accountability, and Transparency (ACM, 2019);

  18. Green, B. ‘Good’ isn’t good enough. In Proc. AI for Social Good Worksh. NeurIPS (2019).

  19. United Nations Development Program (UNDP) Sustainable Development Goals. (UNDP, 2015).

  20. Ram, A. Europe’s AI start-ups often do not use AI, study finds. Financial Times (5 March 2019).

  21. Strubell, E., Ganesh, A. & McCallum, A. Energy and policy considerations for deep learning in NLP. Proc. 57th Annual Meeting of the Association for Computational Linguistics 3645–3650 (ACL, 2019).

  22. Inter-American Development Bank fAIrLAC Observatory (IADB, 2020);

  23. Oxford Initiative on AI×SDGs. (2020).

  24. Floridi, L., Cowls, J., King, T. C. & Taddeo, M. How to design AI for social good: seven essential factors. Sci. Eng. Ethics 26, 1771–1796 (2020).

    Article  Google Scholar 

  25. Dandres, T. et al. Consequences of future data center deployment in Canada on electricity generation and environmental impacts: A 2015–2030 prospective study. J. Ind. Ecol. 21, 1312–1322 (2017).

    Article  Google Scholar 

  26. Strubell, E., Ganesh, A. & McCallum, A. Energy and policy considerations for deep learning in NLP. Preprint at (2019).

  27. Shrestha, P. Leading energy and tech groups call for International Centre for AI, Energy and Climate. Energy Live News (20 August 2019).

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J.C. acknowledges the receipt of a Doctoral Studentship from the Alan Turing Institute. M.T. and L.F. acknowledge the Oxford Initiative on AI for SDG, which is supported by grants from Facebook, Google and Microsoft.

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Correspondence to Luciano Floridi.

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Cowls, J., Tsamados, A., Taddeo, M. et al. A definition, benchmark and database of AI for social good initiatives. Nat Mach Intell 3, 111–115 (2021).

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