Abstract Recent years have seen a surge in applications and technologies aimed at motivating users to achieve personal goals and improve their wellbeing. However, these often fail to promote long-term behaviour change, and sometimes even backfire. We consider how self-determination theory (SDT), a metatheory of human motivation and wellbeing, can help explain why such technologies fail, and how they may better help users internalize the motivation behind their goals and make enduring changes in their behaviour. In this work, we systematically reviewed 15 papers in the ACM Digital Library that apply SDT to the design of behaviour change technologies (BCTs). We identified 50 suggestions for design features in BCTs, grounded in SDT, that researchers have applied to enhance user motivation. However, we find that SDT is often leveraged to optimize engagement with the technology itself rather than with the targeted behaviour change per se. When interpreted through the lens of SDT, the implication is that BCTs may fail to cultivate sustained changes in behaviour, as users’ motivation depends on their enjoyment of the intervention, which may wane over time. An underexplored opportunity remains for designers to leverage SDT to support users to internalize the ultimate goals and value of certain behaviour changes, enhancing their motivation to sustain these changes in the long term.

The development of increasingly agentic and human-like AI assistants, capable of performing a wide range of tasks on user's behalf over time, has sparked heightened interest in the nature and bounds of human interactions with AI. Such systems may indeed ground a transition from task-oriented interactions with AI, at discrete time intervals, to ongoing relationships -- where users develop a deeper sense of connection with and attachment to the technology. This paper investigates what it means for relationships between users and advanced AI assistants to be appropriate and proposes a new framework to evaluate both users' relationships with AI and developers' design choices. We first provide an account of advanced AI assistants, motivating the question of appropriate relationships by exploring several distinctive features of this technology. These include anthropomorphic cues and the longevity of interactions with users, increased AI agency, generality and context ambiguity, and the forms and depth of dependence the relationship could engender. Drawing upon various ethical traditions, we then consider a series of values, including benefit, flourishing, autonomy and care, that characterise appropriate human interpersonal relationships. These values guide our analysis of how the distinctive features of AI assistants may give rise to inappropriate relationships with users. Specifically, we discuss a set of concrete risks arising from user--AI assistant relationships that: (1) cause direct emotional or physical harm to users, (2) limit opportunities for user personal development, (3) exploit user emotional dependence, and (4) generate material dependencies without adequate commitment to user needs. We conclude with a set of recommendations to address these risks.

Digital self-control tools (DSCTs) help people control their time and attention on digital devices, using interventions like distraction blocking or usage tracking. Most studies of DSCTs’ effectiveness have focused on whether a single intervention reduces time spent on a single device. In reality, people may require combinations of DSCTs to achieve more subjective goals across multiple devices. We studied how DSCTs can address individual needs of university students (n = 280), using a workshop where students reflect on their goals before exploring relevant tools. At 1-3 month follow-ups, 95% of respondents still used at least one type of DSCT, typically applied across multiple devices, and there was substantial variation in the tool combinations chosen. We observed a large increase in self-reported digital self-control, suggesting that providing a space to articulate goals and self-select appropriate DSCTs is a powerful way to support people who struggle to self-regulate digital device use.

Interfaces increasingly mimic human social behaviours. Beyond prototypical examples like chatbots, basic automated systems like app notifications or self-checkout machines likewise address or 'talk to' people in person-like ways. Whilst early evidence suggests social cues can enhance user experience, we lack a good understanding of when, and why, their use in interaction design may be inappropriate. We combined a qualitative survey (n=80) with experience sampling, interview, and workshop studies (n=11) to understand people's attitudes and preferences regarding how a range of automated systems talk to/at them. We thematically analysed examples of phrasings or conduct our participants disliked, their reasons, and how they would prefer to be treated instead. One category of inappropriate use we identified is when social design elements are used to manipulate user behaviour. We distinguish four such tactics: 'agents' playing on users' emotions (e.g., guilt-tripping, coaxing), being pushy, mothering users, or being passive-aggressive. Another category regards pragmatics: personal or situational factors that can make even a seemingly helpful or friendly message come across as rude, tactless, invasive, etc. These include contextual insensitivity (e.g., embarrassing users in public); expressing clearly false personalised care; or treating a user in ways they find misaligned with the system's role or the nature of their relationship. We discuss these inappropriate uses in terms of an emerging 'social' class of dark and anti-patterns. From participant suggestions, we offer recommendations for improving how interfaces treat people in interaction, including broader normative reflections on treating users respectfully.