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AI in Support of the SDGs: Six Recurring Challenges and Related Opportunities Identified Through Use Cases

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The Ethics of Artificial Intelligence for the Sustainable Development Goals

Part of the book series: Philosophical Studies Series ((PSSP,volume 152))

Abstract

This chapter provides an overview of six topics related to governance, ethical, legal, and social implications of artificial intelligence (AI) for sustainable development goals (SDGs) initiatives. We identified six common challenges and related opportunities to mitigate such challenges, as referred to by the authors analysing the chapters provided in the book The Ethics of Artificial Intelligence for the Sustainable Development Goals. They are (1) governance and collaboration, (2) private investments and the role of big tech companies, (3) AI and communities, (4) AI and individuals, (5) jobs and skills, and (6) impact assessment.

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Notes

  1. 1.

    Such superiority in terms of, for example, data processing shall be benchmarked against the environmental impact of using AI.

  2. 2.

    The “Brussels effect” refers to the impact of the European regulation on other jurisdictions and the likelihood that they adopt similar norms. Such effect relates to the chronological anteriority of the European legislator in filling one legislative vacuum related to the digital space, for example, concerning data protection law in 2016 with the General Data Protection Regulation.

  3. 3.

    For example, the prevalent European views on human-centricity and AI do not necessarily coincide with the Chinese ones. None of the three dominant schools of Chinese philosophical thinking place human beings in a supreme position within the universe. On the Chinese interpretation of human-centricity and anthropomorphism: “Applying Ancient Philosophy to Artificial Intelligence”, available at https://www.noemamag.com/applying-ancient-chinese-philosophy-to-artificial-intelligence/ accessed 4.6.2022.

  4. 4.

    Homomorphic encryption makes it possible to analyse encrypted data without revealing the data’s content (Stephenson et al. 2023).

  5. 5.

    A linear model of production and consumption has been dominating over the past one and a half century in the globe. “In the supply chain in this one-way model, the goods are manufactured from raw materials in production processes, sold, used, and subsequently at the end of its lifetime as the specific product is discarded as waste to landfill or incinerated. The raw materials are once extracted from the nature, usually discarded at the end of the use of a particular product. This model simply runs on a linear path and hence sometimes termed as linear model. Linear model does not support environmental sustainability and resource efficiency” (Ghosh 2020).

  6. 6.

    On the topic (‘Towards a Green Energy Economy? The EU Energy Union’s Transition to a Low-Carbon Zero Subsidy Electricity System – Lessons from the UK’s Electricity Market Reform’ 2016).

  7. 7.

    The concept of a social licence to operate relates to organisational studies and corporate social responsibility aiming to integrate legitimacy in corporate strategy (Morrison 2014).

  8. 8.

    Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation).

  9. 9.

    Article 22 refers to solely automated decision-making process, which renders the interpretation of “solely” crucial to the determination of the scope of a right of explanation (Bayamlıoğlu n.d.).

  10. 10.

    On the topic (‘Artificial Intelligence, Machine Learning, Automation, Robotics, Future of Work and Future of Humanity: A Review and Research Agenda: Computer Science & IT Journal Article | IGI Global’ n.d.)

  11. 11.

    “Using the discourse of human rights but without reflecting the full intent of human rights promotes a customary usage of the terms that undermines the meaning of ‘human rights.’ While this cannot effect actual State obligations, it can have serious implications for people’s and duty-bearers’ understanding of human rights entitlements, as well as for accountability and civil society monitoring of human rights situations” (Williams and Blaiklock 2016).

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Authors and Affiliations

  1. Saïd Business School, University of Oxford, Oxford, UK

    Francesca Mazzi

  2. Oxford Internet Institute, University of Oxford, Oxford, UK

    Mariarosaria Taddeo & Luciano Floridi

  3. Alan Turing Institute, British Library, London, UK

    Mariarosaria Taddeo

  4. Department of Legal Studies, University of Bologna, Bologna, Italy

    Luciano Floridi

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  1. Saïd Business School, University of Oxford, Oxford, UK

    Francesca Mazzi

  2. Oxford Internet Institute, University of Oxford, Oxford, UK

    Luciano Floridi

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Mazzi, F., Taddeo, M., Floridi, L. (2023). AI in Support of the SDGs: Six Recurring Challenges and Related Opportunities Identified Through Use Cases. In: Mazzi, F., Floridi, L. (eds) The Ethics of Artificial Intelligence for the Sustainable Development Goals . Philosophical Studies Series, vol 152. Springer, Cham. https://doi.org/10.1007/978-3-031-21147-8_2

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