When nudge comes to shove: Liberty and nudging in the era of big data

Sætra, Henrik Skaug

doi:10.1016/j.techsoc.2019.04.006

Cited by 49 publications

(30 citation statements)

References 16 publications

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“…AI ethics has emerged as a vibrant field of study, and this article proposes to use SDGs as a system for analyzing the effects of AI. Among the most researched areas related to AI ethics are issues of privacy and surveillance [23][24][25][26], how technology can aid efforts to manipulate and persuade [27,28], biased systems [29][30][31], issues of power and technology [32][33][34][35], how technology changes human relations [36], and the potentially polarizing effects of AI-based social media [37,38].…”

Section: What Is Ai?mentioning

confidence: 99%

“…Fake news is also connected to AI-based social media [66]. In addition, AI allows for more effective manipulation-or nudging-of individuals, and while Thaler and Sunstein [67] argue that nudging should be done for good, it is quite unlikely that actors with other intentions will abstain from using such techniques to promote their own self-interest over that of other citizens, consumers, and individuals in general [27,28].…”

Section: Sdg16: Promote Peaceful and Inclusive Societies For Sustainamentioning

confidence: 99%

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AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System

Sætra

2021

Sustainability

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Artificial intelligence (AI) is associated with both positive and negative impacts on both people and planet, and much attention is currently devoted to analyzing and evaluating these impacts. In 2015, the UN set 17 Sustainable Development Goals (SDGs), consisting of environmental, social, and economic goals. This article shows how the SDGs provide a novel and useful framework for analyzing and categorizing the benefits and harms of AI. AI is here considered in context as part of a sociotechnical system consisting of larger structures and economic and political systems, rather than as a simple tool that can be analyzed in isolation. This article distinguishes between direct and indirect effects of AI and divides the SDGs into five groups based on the kinds of impact AI has on them. While AI has great positive potential, it is also intimately linked to nonuniversal access to increasingly large data sets and the computing infrastructure required to make use of them. As a handful of nations and companies control the development and application of AI, this raises important questions regarding the potential negative implications of AI on the SDGs. The conceptual framework here presented helps structure the analysis of which of the SDGs AI might be useful in attaining and which goals are threatened by the increased use of AI.

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Section: What Is Ai?mentioning

confidence: 99%

Section: Sdg16: Promote Peaceful and Inclusive Societies For Sustainamentioning

confidence: 99%

AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System

Sætra

2021

Sustainability

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“…Some of the key issues that might give rise to the dilemma relate to platform and monopoly power [10][11][12], social media and its effects on human relations [13], and issues related to human cognition, polarization, filter bubbles, and pressure to conform [1,4,5,14]. Other issues of relevance include privacy and surveillance [15,16], the manipulative power of tech [17,18], algorithmic bias resulting in racist and discriminatory AI systems [6,8,19,20], and the carbon footprint of AI and Big Data [21][22][23].…”

Section: The Moral Problem-the Ethicist's Dilemmamentioning

confidence: 99%

The AI ethicist’s dilemma: fighting Big Tech by supporting Big Tech

2021

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Assume that a researcher uncovers a major problem with how social media are currently used. What sort of challenges arise when they must subsequently decide whether or not to use social media to create awareness about this problem? This situation routinely occurs as ethicists navigate choices regarding how to effect change and potentially remedy the problems they uncover. In this article, challenges related to new technologies and what is often referred to as ‘Big Tech’ are emphasized. We present what we refer to as the AI ethicist’s dilemma, which emerges when an AI ethicist has to consider how their own success in communicating an identified problem is associated with a high risk of decreasing the chances of successfully remedying the problem. We examine how the ethicist can resolve the dilemma and arrive at ethically sound paths of action through combining three ethical theories: virtue ethics, deontological ethics and consequentialist ethics. The article concludes that attempting to change the world of Big Tech only using the technologies and tools they provide will at times prove to be counter-productive, and that political and other more disruptive avenues of action should also be seriously considered by ethicists who want to effect long-term change. Both strategies have advantages and disadvantages, and a combination might be desirable to achieve these advantages and mitigate some of the disadvantages discussed.

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“…Nudging-digital and otherwise-has also raised autonomy concerns, though there is significant disagreement about how warranted they are [35,72,79,84,88]. Sunstein argues that nudges do not threaten autonomy, as long as (1) they do not foreclose options, (2) they do not impose significant costs on making any particular choice, and (3) they aim to further the target's interests [84].…”

Section: Autonomymentioning

confidence: 99%

Measuring Automated Influence: Between Empirical Evidence and Ethical Values

Susser

Grimaldi

2021

Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society

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Automated influence, delivered by digital targeting technologies such as targeted advertising, digital nudges, and recommender systems, has attracted significant interest from both empirical researchers, on one hand, and critical scholars and policymakers on the other. In this paper, we argue for closer integration of these efforts. Critical scholars and policymakers, who focus primarily on the social, ethical, and political effects of these technologies, need empirical evidence to substantiate and motivate their concerns. However, existing empirical research investigating the effectiveness of these technologies (or lack thereof), neglects other morally relevant effects-which can be felt regardless of whether or not the technologies "work" in the sense of fulfilling the promises of their designers. Drawing from the ethics and policy literature, we enumerate a range of questions begging for empirical analysis-the outline of a research agenda bridging these fields-and issue a call to action for more empirical research that takes these urgent ethics and policy questions as their starting point. CCS CONCEPTS• Security and privacy → Social aspects of security and privacy; • Human-centered computing → HCI design and evaluation methods.

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When nudge comes to shove: Liberty and nudging in the era of big data

Cited by 49 publications

References 16 publications

AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System

AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System

The AI ethicist’s dilemma: fighting Big Tech by supporting Big Tech

Measuring Automated Influence: Between Empirical Evidence and Ethical Values

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