As artificial intelligence (AI) continues to proliferate into every area of modern life, there is no doubt that society has to think deeply about the potential impact, whether negative or positive, that it will have. Whilst scholars recognise that AI can usher in a new era of personal, social and economic prosperity, they also warn of the potential for it to be misused towards the detriment of society. Deliberate strategies are therefore required to ensure that AI can be safely integrated (...) into society in a manner that would maximise the good for as many people as possible, whilst minimising the bad. One of the most urgent societal expectations of artificial agents is the need for them to behave in a manner that is morally relevant, i.e. to become artificial moral agents (AMAs). In this article, I will argue that exemplarism, an ethical theory based on virtue ethics, can be employed in the building of computationally rational AMAs with weak machine ethics. I further argue that three features of exemplarism, namely grounding in moral exemplars, meeting community expectations and practical simplicity, are crucial to its uniqueness and suitability for application in building AMAs that fit the ethos of AI4SG. (shrink)

Frente a una narrativa distópica presente en los medios de comunicación y cultura popular que caracteriza el avance y desarrollo de la inteligencia artificial como una amenaza o riesgo existencial quiero valorar de manera crítica y constructiva el rol de la inteligencia artificial para el bien común. La tecnología digital también se puede aplicar para la solución de grandes problemas de la humanidad, como los 17 Objetivos de Desarrollo Sostenible y sus 169 metas de la agenda 2030. En este artículo, (...) comentaré distintos casos de uso y aplicación de la inteligencia artificial y la robótica encaminados a conseguir los 17 Objetivos de Desarrollo Sostenible y qué principios éticos deben guiar su aplicación para que la inteligencia artificial consiga la ambiciosa agenda 2030. También comentaré el plan de acción de España y la estrategia nacional para cumplir la agenda 2030 y de qué manera incorpora las TIC. (shrink)

The idea of artificial intelligence for social good is gaining traction within information societies in general and the AI community in particular. It has the potential to tackle social problems through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies. This article addresses this gap by identifying seven ethical factors that (...) are essential for future AI4SG initiatives. The analysis is supported by 27 case examples of AI4SG projects. Some of these factors are almost entirely novel to AI, while the significance of other factors is heightened by the use of AI. From each of these factors, corresponding best practices are formulated which, subject to context and balance, may serve as preliminary guidelines to ensure that well-designed AI is more likely to serve the social good. (shrink)

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. (shrink)

Value Sensitive Design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, ML (...) may lead to AI systems adapting in ways that ‘disembody’ the values embedded in them. To address this, we propose a threefold modified VSD approach: 1) integrating a known set of VSD principles (AI4SG) as design norms from which more specific design requirements can be derived; 2) distinguishing between values that are promoted and respected by the design to ensure outcomes that not only do no harm but also contribute to good; and 3) extending the VSD process to encompass the whole life cycle of an AI technology in order to monitor unintended value consequences and redesign as needed. We illustrate our VSD for AI approach with an example use case of a SARS-CoV-2 contact tracing app. (shrink)

The pervasiveness of AI-empowered technologies across multiple sectors has led to drastic changes concerning traditional social practices and how we relate to one another. Moreover, market-driven Big Tech corporations are now entering public domains, and concerns have been raised that they may even influence public agenda and research. Therefore, this chapter focuses on assessing and evaluating what kind of business model is desirable to incentivise the AI for Social Good (AI4SG) factors. In particular, the chapter explores the implications of (...) this discourse for SDG #17 (global partnership) and how this goal may encourage Big Tech corporations to strengthen multi-stakeholder partnerships that promote effective public-private and civil society partnerships and the meaningful co-presence of non-market and market values. In doing so, the chapter proposes an analysis of the sociological notion of "social license to operate" (SLO) elaborated in the mining and extractive industry literature and introduces it into the discourse on sustainable digital business models and responsible management of risks in the digital age. This serves to explore how such a social license can be adopted as a practice by digital business models to foster trust, collaboration and coordination among different actors - AI researchers and initiatives, institutions and civil society at large - for the support of SDGs interrelated targets and goals. (shrink)

This paper offers three contributions to the burgeoning movements of AI for Social Good (AI4SG) and AI and the United Nations Sustainable Development Goals (SDGs). First, we introduce the SDG-Intense Evaluation framework (SDGIE) that aims to situate variegated automated/AI models in a larger ecosystem of computational approaches to advance the SDGs. To foster knowledge collaboration for solving complex social and environmental problems encompassed by the SDGs, the SDGIE framework details a benchmark structure of data-algorithm-output to effectively standardize AI approaches (...) to the SDGs. Second, as a specific instantiation of the SDGIE framework, the SDG Impact Intensity Model (SDGIIM) is theoretically and operationally established. SDGIIM embeds expert decision-making and SDG keyword banks in textual data processing to determine overall SDG “impact intensity.” Ideally, SDGIIM can be applied to textual data sets from any sector or discipline: academia, business, government, non-profit, civil society, etc. Third, the SDGIIM instantiation is applied to the specific domain of academic journal rating systems as a case study. Traditionally, academic journals have been evaluated on loosely conceived and empirically shaky notions of ‘quality.’ Aligned with the trend of AI4SG and broader calls to action, ‘impact’ is rapidly becoming the primary normative consideration for assessing academic journals. We hypothesize and demonstrate that SDGIIM is capable of producing evaluations aligned with experts’ expectations of SDG impact intensity; the consistent analysis and rating of textual data sets that embody the SDGs with varying degrees of meaning and, ultimately, promote positive impact on the actual material conditions of the world. (shrink)

The Chinese government and technology companies assume a proactive stance towards digital technologies and AI and their roles in users’—and more generally, people’s—lives. This vision of ‘Tech for Good’, i.e., the development of good digital technologies and AI or the application of them for good, is also shared by major technology companies in the globe, e.g., Google, Microsoft, and Facebook. Interestingly, these initiatives have invited a number of critiques for their feasibility and desirability, particularly in relation to the social and (...) political conditions of liberal democratic societies. In this article, I discuss whether these critiques also apply to the Chinese context and contend that Confucian philosophy provides the normative resources to answer these critiques. This cross-cultural analysis, therefore, allows us to formulate a different account of AI4SG, which I shall call ‘AI for Datong’, and helps us in our reimagining of the normative vision for AI. (shrink)

Autonomous weapons systems, often referred to as ‘killer robots’, have been a hallmark of popular imagination for decades. However, with the inexorable advance of artificial intelligence systems (AI) and robotics, killer robots are quickly becoming a reality. These lethal technologies can learn, adapt, and potentially make life and death decisions on the battlefield with little-to-no human involvement. This naturally leads to not only legal but ethical concerns as to whether we can meaningful control such machines, and if so, then how. (...) Such concerns are made even more poignant by the ever-present fear that something may go wrong, and the machine may carry out some action(s) violating the ethics or laws of war. -/- Researchers, policymakers, and designers are caught in the quagmire of how to approach these highly controversial systems and to figure out what exactly it means to have meaningful human control over them, if at all. -/- In Designed for Death, Dr Steven Umbrello aims to not only produce a realistic but also an optimistic guide for how, with human values in mind, we can begin to design killer robots. Drawing on the value sensitive design (VSD) approach to technology innovation, Umbrello argues that context is king and that a middle path for designing killer robots is possible if we consider both ethics and design as fundamentally linked. Umbrello moves beyond the binary debates of whether or not to prohibit killer robots and instead offers a more nuanced perspective of which types of killer robots may be both legally and ethically acceptable, when they would be acceptable, and how to design for them. (shrink)