In this article, we argue that rational persuasion can be a _pro tanto_ wrong and that online platforms possess features that are especially conducive to this wrong. We begin by setting out an account of rational persuasion. This consists of four jointly sufficient conditions for rational persuasion and is intended to capture the core, uncontroversial cases of such persuasion. We then discuss a series of wrong-making features which are present in methods of influence commonly thought of as _pro tanto_ wrong, (...) such as manipulation and paternalism. It is next shown that these wrong-making features are also present in a range of cases that are, by the jointly sufficient conditions already established, rational persuasion, and so some forms of rational persuasion are _pro tanto_ wrong, including in some ways that have not previously been remarked upon. Finally, we demonstrate that online settings possess a number of features that are especially conducive to wrongful rational persuasion. (shrink)

I aim to illustrate how the recommender systems of digital platforms create a particularly problematic kind of vulnerability in their users. Specifically, through theories of scaffolded cognition and scaffolded affectivity, I argue that a digital platform’s recommender system is a cognitive and affective artifact that fulfills different functions for the platform’s users and its designers. While it acts as a content provider and facilitator of cognitive, affective and decision-making processes for users, it also provides a continuous and detailed amount of (...) information to platform designers regarding users’ cognitive and affective processes. This dynamic, I argue, engenders a kind of vulnerability in platform users, structuring a power imbalance between designers and users. This occurs because the recommender system can not only gather data on users’ cognitive and affective processes, but also affects them in an unprecedentedly economic and capillary manner. By examining one instance of ethically problematic practice from Facebook, I specifically argue that rather than being a tool for manipulating or exploiting people, digital platforms, especially by their underlying recommender systems, can single out and tamper with specific cognitive and affective processes as a tool specifically designed for mind invasion. I conclude by reflecting how the understanding of such AI systems as tools for mind invasion highlights some merits and shortcomings of the AI Act with regards to the protection of vulnerable people. (shrink)

In recent years, with the advances in machine learning and neuroscience, the abundances of sensors and emotion data, computer engineers have started to endow machines with ability to detect, classify, and interact with human emotions. Emotional artificial intelligence (AI), also known as a more technical term in affective computing, is increasingly more prevalent in our daily life as it is embedded in many applications in our mobile devices as well as in physical spaces. Critically, emotional AI systems have not only (...) the ability to not passively read and classify emotions, but most also have an ability to predict and ‘nudge’ users to certain desired emotional states. Drawing from Piredda (2020)’s account on affective artifacts and other recent accounts, we've examined various emerging emotion-sensing technologies such as recommender algorithms, personal AI assistants, work-related emotion trackers, and emotional AI toys and robots through the lens of affective artifacts. We show how these technologies fulfill the criteria of being affective artifacts: they are artifactual, multifunctional, semi-agentive, and semi-interpesonal. Emotional AI systems as affective artifacts can influence the affective states of the users (e.g., help regulate emotions of ourselves and others), and importantly, our manipulation of these algorithms can intersect with the maintenance and construction of our sense of self and identity. (shrink)