Resisting Humanization: Ethical Front-End Design Choices in AI for Sensitive Contexts

• URL: http://arxiv.org/abs/2603.24853v1
• Date: Wed, 25 Mar 2026 22:39:16 GMT
• Title: Resisting Humanization: Ethical Front-End Design Choices in AI for Sensitive Contexts
• Abstract summary: We argue that humanization in AI front-end design is a value-driven choice that profoundly shapes users' mental models.<n>We discuss two AI systems developed by Chayn, a nonprofit organization supporting survivors of gender-based violence.
• Score: 1.1565654851982565
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Ethical debates in AI have primarily focused on back-end issues such as data governance, model training, and algorithmic decision-making. Less attention has been paid to the ethical significance of front-end design choices, such as the interaction and representation-based elements through which users interact with AI systems. This gap is particularly significant for Conversational User Interfaces (CUI) based on Natural Language Processing (NLP) systems, where humanizing design elements such as dialogue-based interaction, emotive language, personality modes, and anthropomorphic metaphors are increasingly prevalent. This work argues that humanization in AI front-end design is a value-driven choice that profoundly shapes users' mental models, trust calibration, and behavioral responses. Drawing on research in human-computer interaction (HCI), conversational AI, and value-sensitive design, we examine how interfaces can play a central role in misaligning user expectations, fostering misplaced trust, and subtly undermining user autonomy, especially in vulnerable contexts. To ground this analysis, we discuss two AI systems developed by Chayn, a nonprofit organization supporting survivors of gender-based violence. Chayn is extremely cautious when building AI that interacts with or impacts survivors by operationalizing their trauma-informed design principles. This Chayn case study illustrates how ethical considerations can motivate principled restraint in interface design, challenging engagement-based norms in contemporary AI products. We argue that ethical front-end AI design is a form of procedural ethics, enacted through interaction choices rather than embedded solely in system logic.

Related papers

• When Should an AI Act? A Human-Centered Model of Scene, Context, and Behavior for Agentic AI Design [0.44743648495907423]
  Agentic AI increasingly intervenes proactively by inferring users' situations from contextual data.<n>We propose a conceptual model that reframes behavior as an outcome integrating interpretive Scene, Context, and Human Behavior Factors.<n>We derive five agent design principles that guide intervention depth, timing, intensity, and restraint.
  arXiv  Detail & Related papers  (2026-02-26T09:56:37Z)
• AI Automatons: AI Systems Intended to Imitate Humans [54.19152688545896]
  There is a growing proliferation of AI systems designed to mimic people's behavior, work, abilities, likenesses, or humanness.<n>The research, design, deployment, and availability of such AI systems have prompted growing concerns about a wide range of possible legal, ethical, and other social impacts.
  arXiv  Detail & Related papers  (2025-03-04T03:55:38Z)
• The AI Interface: Designing for the Ideal Machine-Human Experience (Editorial) [1.8074330674710588]
  This editorial introduces a Special Issue that explores the psychology of AI experience design.<n>Papers in this collection highlight the complexities of trust, transparency, and emotional sensitivity in human-AI interaction.<n>By findings from eight diverse studies, this editorial underscores the need for AI interfaces to balance efficiency with empathy.
  arXiv  Detail & Related papers  (2024-11-29T15:17:32Z)
• Aligning Generalisation Between Humans and Machines [74.120848518198]
  AI technology can support humans in scientific discovery and forming decisions, but may also disrupt democracies and target individuals.<n>The responsible use of AI and its participation in human-AI teams increasingly shows the need for AI alignment.<n>A crucial yet often overlooked aspect of these interactions is the different ways in which humans and machines generalise.
  arXiv  Detail & Related papers  (2024-11-23T18:36:07Z)
• Survey of User Interface Design and Interaction Techniques in Generative AI Applications [79.55963742878684]
  We aim to create a compendium of different user-interaction patterns that can be used as a reference for designers and developers alike. We also strive to lower the entry barrier for those attempting to learn more about the design of generative AI applications.
  arXiv  Detail & Related papers  (2024-10-28T23:10:06Z)
• Position: Towards Bidirectional Human-AI Alignment [109.57781720848669]
  We argue that the research community should explicitly define and critically reflect on "alignment" to account for the bidirectional and dynamic relationship between humans and AI.<n>We introduce the Bidirectional Human-AI Alignment framework, which not only incorporates traditional efforts to align AI with human values but also introduces the critical, underexplored dimension of aligning humans with AI.
  arXiv  Detail & Related papers  (2024-06-13T16:03:25Z)
• Characterizing and modeling harms from interactions with design patterns in AI interfaces [0.19116784879310028]
  We argue that design features of interfaces with adaptive AI systems can have cascading impacts, driven by feedback loops. We propose Design-Enhanced Control of AI systems (DECAI) to structure and facilitate impact assessments of AI interface designs.
  arXiv  Detail & Related papers  (2024-04-17T13:30:45Z)
• Antagonistic AI [11.25562632407588]
  We explore the shadow of the sycophantic paradigm, a design space we term antagonistic AI. We consider whether antagonistic AI systems may sometimes have benefits to users, such as forcing users to confront their assumptions. We lay out a design space for antagonistic AI, articulating potential benefits, design techniques, and methods of embedding antagonistic elements into user experience.
  arXiv  Detail & Related papers  (2024-02-12T00:44:37Z)
• Enabling High-Level Machine Reasoning with Cognitive Neuro-Symbolic Systems [67.01132165581667]
  We propose to enable high-level reasoning in AI systems by integrating cognitive architectures with external neuro-symbolic components. We illustrate a hybrid framework centered on ACT-R and we discuss the role of generative models in recent and future applications.
  arXiv  Detail & Related papers  (2023-11-13T21:20:17Z)
• Seamful XAI: Operationalizing Seamful Design in Explainable AI [59.89011292395202]
  Mistakes in AI systems are inevitable, arising from both technical limitations and sociotechnical gaps. We propose that seamful design can foster AI explainability by revealing sociotechnical and infrastructural mismatches. We explore this process with 43 AI practitioners and real end-users.
  arXiv  Detail & Related papers  (2022-11-12T21:54:05Z)
• Relational Artificial Intelligence [5.5586788751870175]
  Even though AI is traditionally associated with rational decision making, understanding and shaping the societal impact of AI in all its facets requires a relational perspective. A rational approach to AI, where computational algorithms drive decision making independent of human intervention, has shown to result in bias and exclusion. A relational approach, that focus on the relational nature of things, is needed to deal with the ethical, legal, societal, cultural, and environmental implications of AI.
  arXiv  Detail & Related papers  (2022-02-04T15:29:57Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.