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ARXIV:2603.24853 · ETHICAL AI DESIGN · SUBMITTED 02 APR · 02:30 UTC · FRESHNESS STALE
ARXIV:2603.24853ETHICAL AI DESIGNSUBMITTED 02 APR · 02:30 UTCFRESHNESS STALESilvia Rossi · Diletta Huyskes · Mackenzie Jorgensen · arXiv
This research explores ethical front-end design choices in AI conversational interfaces to prevent user misalignments and foster autonomy, particularly in sensitive contexts.
Opportunity summary
Pain This research explores ethical front-end design choices in AI conversational interfaces to prevent user misalignments and foster autonomy, particularly in sensitive contexts.
Evidence 0 refs | 0 sources | 17% coverage
Blocker Evidence unverified
This research explores ethical front-end design choices in AI conversational interfaces to prevent user misalignments and foster autonomy, particularly in sensitive contexts. Less attention has been paid to the ethical significance of front-end design…
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…
ScienceToStartup currently rates this 3.0/10 on the public viability pass. 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.
Ethical AI Design moved forward this cycle; last verified April 2026. Public score 3.0/10.
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This research explores ethical front-end design choices in AI conversational interfaces to prevent user misalignments and foster autonomy, particularly in sensitive contexts.
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10.48550/arXiv.2603.24853This research explores ethical front-end design choices in AI conversational interfaces to prevent user misalignments and foster autonomy, particularly in sensitive contexts.
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.
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Proof status
unverified0 refs; 0 sources; 17% coverage.
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Dimensions overall score 3.0
PROBLEM
This research explores ethical front-end design choices in AI conversational interfaces to prevent user misalignments and foster autonomy, particularly in sensitive contexts. Less attention has been paid to the ethical significance of front-end design choices, such as the intera...
METHOD
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 elemen...
RESULT
ScienceToStartup currently rates this 3.0/10 on the public viability pass. 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.
WHY NOW
Ethical AI Design moved forward this cycle; last verified April 2026. Public score 3.0/10.
Abstract-backed public claims while anchored extraction refreshes.
This research explores ethical front-end design choices in AI conversational interfaces to prevent user misalignments and foster autonomy, particularly in sensitive contexts. 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.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 3.0/10 on the public viability pass. 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.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Ethical AI Design moved forward this cycle; last verified April 2026. Public score 3.0/10.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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This research explores ethical front-end design choices in AI conversational interfaces to prevent user misalignments and foster autonomy, particularly in sensitive contexts.
Segment
Ethical AI Design
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