Attention, moral skill, and algorithmic recommendation

Philosophical Studies https://doi.org/10.1007/s11098-023-02083-6 Attention, moral skill, and algorithmic recommendation Nick Schuster1 · Seth Lazar1 Accepted: 17 November 2023 © The Author(s) 2024 Abstract Recommender systems are artificial intelligence technologies, deployed by online platforms, that model our individual preferences and direct our attention to content we’re likely to engage with. As the digital world has become increasingly saturated with information, we’ve become ever more reliant on these tools to efficiently allocate our attention. And our reliance on algorithmic recommendation may, in turn, reshape us as moral agents. While recommender systems could in principle enhance our moral agency by enabling us to cut through the information saturation of the internet and focus on things that matter, as they’re currently designed and implemented they’re apt to interfere with our ability to attend appropriately to morally relevant factors. In order to analyze the distinctive moral problems algorithmic recommendation poses, we develop a framework for the ethics of attention and an account of judicious attention allocation as a moral skill. We then discuss empirical evidence suggesting that attentional moral skill can be thwarted and undermined in various ways by algorithmic recommendation and related affordances of online platforms, as well as economic and technical considerations that support this concern. Finally, we consider how emerging technologies might overcome the problems we identify. Keywords Artificial intelligence · Attention · Machine learning · Moral skill · Recommender systems 1 Introduction As Nobel laureate Herbert Simon first noted over 40 years ago, a wealth of information makes attention a scarce resource (Simon, 1971). Since then, the rise of the internet, big data, and artificial intelligence (AI) has not only drastically increased the amount of information available to us, it’s also fundamentally transformed how * Nick Schuster Seth Lazar 1 The Australian National University, Canberra, Australia 13 Vol.:(0123456789) N. Schuster, S. Lazar information is produced, distributed, and consumed. This technological revolution has therefore had a transformative effect on the attention economy.1 Among the most notable features of the digital attention economy is the way online platforms filter and rank information according to individual users’ preferences, among other factors. This process centrally involves algorithmic recommender systems. Built with advanced machine learning (ML) techniques, these tools now play a critical role in directing our attention in digital environments to the products we buy, the entertainment we consume, the news we read, and even the jobs we work, the homes where we live, and the people with whom we interact. Indeed, the information saturation of the digital world has made recommender systems not just useful but necessary for effective agency. These tools, and the sociotechnical systems in which they’re embedded, therefore raise pressing moral concerns about how we now allocate our attention. On the one hand, they enable us to access an unprecedented amount of information with ease, potentially augmenting our agency in morally significant ways. For instance, they can direct us to far more information of personal, social, and political importance than we would be exposed to without them. On the other hand, our reliance on algorithmic recommendation could reshape our agency in morally problematic ways. Online platforms can direct us toward things we should not attend to just as easily as toward things we should. And even when they direct our attention to the right things, they may not do so in the right ways, to the right degrees, or for the right reasons. In this essay, we argue that judicious attention allocation is a moral skill and that our growing reliance on algorithmic recommendation threatens our development and exercise of that skill. In Sect. 2, we situate our account of judicious attention allocation in a broader theory of the ethics of attention. In Sect. 3, we draw on empirical evidence and technical considerations to argue that recommender systems and the online platforms they serve can thwart and undermine attentional moral skill in various ways. Finally, in Sect. 4, we consider how generative AI systems could filter and rank content such that they scaffold and protect judicious attention allocation instead. A brief conclusion follows. 2 Judicious attention allocation as a moral skill 2.1 The ethics of attention In the broadest terms, attention is “the selective directedness of our mental lives” (Mole, 2021, p. 1). While we can be generally aware of multiple things at once, we can only focus our attention on a relatively small subset at any given time. Attention 1 Critics have raised a multitude of worries about AI technologies in the attention economy in recent years: AI might weaken market competition and democratic governance (Hindman, 2018), lead to social isolation (Turkle, 2011) and addiction (Bhargava & Velasquez, 2021), enable exploitation (Bueno, 2016), and erode individual liberties (Williams, 2018), to name a few. The concerns we’ll raise are compatible with these worries, but don’t depend on any of them. 13 Attention, moral skill, and algorithmic recommendation can be fleeting, or it can be more sustained. Momentarily noticing a headline as you scroll through your newsfeed and getting engrossed in a story are both ways of paying attention. Attention can also be exogenous (automatically responsive to stimuli) as well as endogenous (deliberately directed by the agent). An alarm can grab your attention without you having to think about it or make an effort to focus on it; but if you know it’s coming you can listen for it and once you hear it you can actively resist distractions. Insofar as effective action requires us to focus on certain features of our circumstances while being at most peripherally aware of others, allocating our attention well is necessary for good practical agency (Allport, 1987; Neumann, 1987; Watzl, 2017; Wu, 2011). If you don’t pay attention to the time, you’ll miss your three o’clock meeting. And regular deficient attention to such things could jeopardize your career. Indeed, attention plays a central role in explaining various aspects of practical agency, including perception (Carrasco, 2011), emotion (Brady, 2013; De Sousa, 1990), decision-making (Orquin & Loose, 2013), intentionality (Wu, 2011, 2016), and self-control (Berkman et al., 2017; Bermúdez, 2017). As such, attention allocation is subject not just to descriptive analysis but to normative assessment as well. There are, for instance, better and worse ways of allocating our attention in the service of both knowledge acquisition and practical ends. Thus, there are both epistemic and prudential norms of attention. Checking your calendar is a good way to verify the location of your meeting; a (...truncated)