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Abstract

The concept of AI for Social Good(AI4SG) is gaining momentum in both information societies and the AI community. Through all the advancement of AI-based solutions, it can solve societal issues effectively. To date, however, there is only a rudimentary grasp of what constitutes AI socially beneficial in principle, what constitutes AI4SG in reality, and what are the policies and regulations needed to ensure it. This paper fills the vacuum by addressing the ethical aspects that are critical for future AI4SG efforts. Some of these characteristics are new to AI, while others have greater importance due to its usage.

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Notes

  1. 1.

    United Nations’ Sustainable Development Goals. https://aiforgood.itu.int/about/.

  2. 2.

    https://www.mckinsey.com/featured-insights/artificial-intelligence/applying-artificial-intelligence-for-social-good.

  3. 3.

    Child Advice Chatbots Fail Sex Abuse Test https://www.bbc.com/news/technology-46507900.

References

  1. Al-Abdulkarim, L., Atkinson, K., Bench-Capon, T.: Factors, issues and values: revisiting reasoning with cases. In: Proceedings of the 15th International Conference on Artificial Intelligence and Law, pp. 3–12 (2015)

    Google Scholar 

  2. Burns, A., Rabins, P.: Carer burden in dementia. Int. J. Geriatr. Psychiatry 15(S1), S9–S13 (2000)

    Article  Google Scholar 

  3. Butler, D.: Ai summit aims to help world’s poorest. Nat. News 546(7657), 196 (2017)

    Article  Google Scholar 

  4. Eicher, B., Polepeddi, L., Goel, A.: Jill Watson doesn’t care if you’re pregnant: grounding AI ethics in empirical studies. In: Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, pp. 88–94 (2018)

    Google Scholar 

  5. Fang, F., et al.: Deploying paws: field optimization of the protection assistant for wildlife security. In: Twenty-Eighth IAAI Conference (2016)

    Google Scholar 

  6. Lakkaraju, H., et al.: A machine learning framework to identify students at risk of adverse academic outcomes. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1909–1918 (2015)

    Google Scholar 

  7. Lu, H., et al.: A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic-and molecular-phenotypes of epithelial ovarian cancer. Nat. Commun. 10(1), 1–11 (2019)

    Article  Google Scholar 

  8. Mathur, V., Stavrakas, Y., Singh, S.: Intelligence analysis of Tay twitter bot. In: 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), pp. 231–236. IEEE (2016)

    Google Scholar 

  9. Oliver, N.: Big data for social good: opportunities and challenges. In: 12th World Telecommunication/ICT Indicators Symposium (WTIS 2014) [Date of reference 20 May 2015] (2014). http://www.itu.int/en/ITU-D/Statistics/Documents/events/wtis2014/003INF-E.pdf

  10. Petersen, E.E., et al.: Vital signs: pregnancy-related deaths, united states, 2011–2015, and strategies for prevention, 13 states, 2013–2017. Morb. Mortal. Wkly Rep. 68(18), 423 (2019)

    Google Scholar 

  11. Tabuchi, H., Gelles, D.: Doomed boeing jets lacked 2 safety features that company sold only as extras. The New York Times, 21 March 2019

    Google Scholar 

  12. Taddeo, M., Floridi, L.: How AI can be a force for good. Science 361(6404), 751–752 (2018)

    Article  MathSciNet  Google Scholar 

  13. Taddeo, M., Floridi, L.: Regulate artificial intelligence to avert cyber arms race (2018)

    Google Scholar 

  14. Yadav, A., et al.: POMDPs for assisting homeless shelters – computational and deployment challenges. In: Osman, N., Sierra, C. (eds.) AAMAS 2016. LNCS (LNAI), vol. 10003, pp. 67–87. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46840-2_5

    Chapter  Google Scholar 

  15. Zhou, W., Kapoor, G.: Detecting evolutionary financial statement fraud. Decis. Support Syst. 50(3), 570–575 (2011)

    Article  Google Scholar 

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Acknowledgments

This research is funded by University of Central Florida provost scholarship for joint research with National Academy members.

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Correspondence to Ramya Akula .

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Akula, R., Garibay, I. (2021). Ethical AI for Social Good. In: Stephanidis, C., et al. HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence. HCII 2021. Lecture Notes in Computer Science(), vol 13095. Springer, Cham. https://doi.org/10.1007/978-3-030-90963-5_28

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  • DOI: https://doi.org/10.1007/978-3-030-90963-5_28

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