Computers as Bad Social Actors: Dark Patterns and Anti-Patterns in Interfaces that Act Socially
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Abstract (arXiv)
Technologies increasingly mimic human-like social behaviours. Beyond prototypical conversational agents like chatbots, this also applies to basic automated systems like app notifications or self-checkout machines that address or 'talk to' users in everyday situations. Whilst early evidence suggests social cues may enhance user experience, we lack a good understanding of when, and why, their use may be inappropriate. Building on a survey of English-speaking smartphone users (n=80), we conducted experience sampling, interview, and workshop studies (n=11) to elicit people's attitudes and preferences regarding how automated systems talk to them. We thematically analysed examples of phrasings/conduct participants disliked, the reasons they gave, and what they would prefer instead. One category of inappropriate behaviour we identified regards the use of social cues as tools for manipulation. We describe four unwanted tactics interfaces use: agents playing on users' emotions (e.g., guilt-tripping or coaxing them), being pushy, `mothering' users, or being passive-aggressive. Another category regards pragmatics: personal or situational factors that can make a seemingly friendly or helpful utterance come across as rude, tactless, or invasive. These include failing to account for relevant contextual particulars (e.g., embarrassing users in public); expressing obviously false personalised care; or treating a user in ways that they find inappropriate for the system's role or the nature of their relationship. We discuss these behaviours in terms of an emerging 'social' class of dark and anti-patterns. Drawing from participant recommendations, we offer suggestions for improving how interfaces treat people in interactions, including broader normative reflections on treating users respectfully.
Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Feb 2023.
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Citing papers per year: 2024: 3; 2025: 8; 2026: 9.
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- 2025Why human-AI relationships need socioaffective alignmentcited by 47
- 2025DarkBench: Benchmarking Dark Patterns in Large Language Modelscited by 25
- 2025A Pragmatic View of AI Personhoodcited by 12
- 2024Characterizing and modeling harms from interactions with design patterns in AI interfacescited by 11
- 2025SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agentscited by 8
- 2025Characterizing Unintended Consequences in Human-GUI Agent Collaboration for Web Browsingcited by 7
- 2025When Should Users Check? Modeling Confirmation Frequency in Multi-Step Agentic AI Taskscited by 6
- 2024CURATe: Benchmarking Personalised Alignment of Conversational AI Assistantscited by 5
- 2025When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Beingcited by 3
- 2026Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interactioncited by 3
- 2026The Bots of Persuasion: Examining How Conversational Agents' Linguistic Expressions of Personality Affect User Perceptions and Decisionscited by 2
- 2024The Voice: Lessons on Trustworthy Conversational Agents from "Dune"cited by 1
8 more
- 2026The AI Genie Phenomenon and Three Types of AI Chatbot Addiction: Escapist Roleplays, Pseudosocial Companions, and Epistemic Rabbit Holescited by 1
- 2026Polite But Boring? Trade-offs Between Engagement and Psychological Reactance to Chatbot Feedback Stylescited by 1
- 2026Human-Centred LLM Privacy Audits: Findings and Frictionscited by 1
- 2025Theory of Mind and Self-Disclosure to CUIscited by 0
- 2026The Fake Friend Dilemma: Relational Trust and the Political Economy of Conversational AIcited by 0
- 2026Playing Games with My Heart: An Evaluation of AI Companion Appscited by 0
- 2026Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interactioncited by 0
- 2026AI Watchdog: Agent Interfaces for Detecting and Defending Against Manipulative Dark Patterns in AI Conversationscited by 0
- 2026AI Watchdog: Agent Interfaces for Detecting and Defending Against Manipulative Dark Patterns in AI Conversations22 Aug 2026
- 2026Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interaction7 Jul 2026
- 2026Playing Games with My Heart: An Evaluation of AI Companion Apps8 Apr 2026
- 2026Human-Centred LLM Privacy Audits: Findings and Frictions12 Mar 2026
- 2026The Bots of Persuasion: Examining How Conversational Agents' Linguistic Expressions of Personality Affect User Perceptions and Decisions19 Feb 2026
- 2026Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction30 Jan 2026
- 2026Polite But Boring? Trade-offs Between Engagement and Psychological Reactance to Chatbot Feedback Styles28 Jan 2026
- 2026The AI Genie Phenomenon and Three Types of AI Chatbot Addiction: Escapist Roleplays, Pseudosocial Companions, and Epistemic Rabbit Holes19 Jan 2026
- 2026The Fake Friend Dilemma: Relational Trust and the Political Economy of Conversational AI6 Jan 2026
- 2025A Pragmatic View of AI Personhood30 Oct 2025
- 2025When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Being24 Oct 2025
- 2025SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agents13 Oct 2025
8 more
- 2025When Should Users Check? Modeling Confirmation Frequency in Multi-Step Agentic AI Tasks6 Oct 2025
- 2025Theory of Mind and Self-Disclosure to CUIs14 Jul 2025
- 2025Characterizing Unintended Consequences in Human-GUI Agent Collaboration for Web Browsing15 May 2025
- 2025DarkBench: Benchmarking Dark Patterns in Large Language Models13 Mar 2025
- 2025Why human-AI relationships need socioaffective alignment4 Feb 2025
- 2024CURATe: Benchmarking Personalised Alignment of Conversational AI Assistants28 Oct 2024
- 2024The Voice: Lessons on Trustworthy Conversational Agents from "Dune"10 Jul 2024
- 2024Characterizing and modeling harms from interactions with design patterns in AI interfaces17 Apr 2024
- 2025A Pragmatic View of AI Personhoodcited by 12
- 2025SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agentscited by 8
- 2025Characterizing Unintended Consequences in Human-GUI Agent Collaboration for Web Browsingcited by 7
- 2025When Should Users Check? Modeling Confirmation Frequency in Multi-Step Agentic AI Taskscited by 6
- 2025A Pragmatic View of AI Personhood30 Oct 2025
- 2025SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agents13 Oct 2025
- 2025When Should Users Check? Modeling Confirmation Frequency in Multi-Step Agentic AI Tasks6 Oct 2025
- 2025Characterizing Unintended Consequences in Human-GUI Agent Collaboration for Web Browsing15 May 2025
- 2025Why human-AI relationships need socioaffective alignmentcited by 47
- 2025DarkBench: Benchmarking Dark Patterns in Large Language Modelscited by 25
- 2024Characterizing and modeling harms from interactions with design patterns in AI interfacescited by 11
- 2025When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Beingcited by 3
- 2026Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interactioncited by 3
- 2026The Bots of Persuasion: Examining How Conversational Agents' Linguistic Expressions of Personality Affect User Perceptions and Decisionscited by 2
- 2024The Voice: Lessons on Trustworthy Conversational Agents from "Dune"cited by 1
- 2026The AI Genie Phenomenon and Three Types of AI Chatbot Addiction: Escapist Roleplays, Pseudosocial Companions, and Epistemic Rabbit Holescited by 1
- 2026Polite But Boring? Trade-offs Between Engagement and Psychological Reactance to Chatbot Feedback Stylescited by 1
- 2026Human-Centred LLM Privacy Audits: Findings and Frictionscited by 1
- 2025Theory of Mind and Self-Disclosure to CUIscited by 0
- 2026The Fake Friend Dilemma: Relational Trust and the Political Economy of Conversational AIcited by 0
12 most cited of 15 All 15 (JSON)
- 2026AI Watchdog: Agent Interfaces for Detecting and Defending Against Manipulative Dark Patterns in AI Conversations22 Aug 2026
- 2026Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interaction7 Jul 2026
- 2026Playing Games with My Heart: An Evaluation of AI Companion Apps8 Apr 2026
- 2026Human-Centred LLM Privacy Audits: Findings and Frictions12 Mar 2026
- 2026The Bots of Persuasion: Examining How Conversational Agents' Linguistic Expressions of Personality Affect User Perceptions and Decisions19 Feb 2026
- 2026Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction30 Jan 2026
- 2026Polite But Boring? Trade-offs Between Engagement and Psychological Reactance to Chatbot Feedback Styles28 Jan 2026
- 2026The AI Genie Phenomenon and Three Types of AI Chatbot Addiction: Escapist Roleplays, Pseudosocial Companions, and Epistemic Rabbit Holes19 Jan 2026
- 2026The Fake Friend Dilemma: Relational Trust and the Political Economy of Conversational AI6 Jan 2026
- 2025When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Being24 Oct 2025
- 2025Theory of Mind and Self-Disclosure to CUIs14 Jul 2025
- 2025DarkBench: Benchmarking Dark Patterns in Large Language Models13 Mar 2025
12 newest of 15 All 15 (JSON)