From Rights to Rites: Expectations Management in Smart-Home AI

2026-04-26

AI Summary

This study addresses the growing prevalence of AI-powered smart home systems and the persistent gap in ethical risk mitigation and user expectation management. Drawing on semi-structured interviews with 33 practitioners from leading platforms, the research employs constructivist grounded theory to propose an Expectation Management (EM) model. Moving beyond traditional expectation confirmation theory and trust calibration frameworks, the model foregrounds moral judgment, situated action, and cross-cultural differences, elucidating how practitioners navigate user expectations amid organizational power dynamics and cultural rituals. The study identifies four key design tensions and articulates a five-stage EM design guideline, offering a practical, human-centered framework for developing responsible AI systems in smart home environments.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Intelligent User Interfaces
• Intelligent Robots: Embodied AI

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Domestic voice assistants and smart-home devices are increasingly embedded in everyday routines, yet their ethics are often treated as an afterthought or delegated to compliance teams. To explore how expectations about smart-home AI are constructed and managed, we conducted 33 semi-structured interviews with designers, developers, and researchers from major smart-home platforms (Amazon Alexa, Microsoft Azure IoT, and Google Nest). Using a constructivist grounded theory approach, we develop Expectations Management (EM): a culturally embedded model describing how practitioners shape, calibrate, and repair expectations by balancing organisational rights with culturally situated rites. We show that EM differs from expectation-confirmation theory and trust-calibration by foregrounding moral judgement, situated action, and cross-cultural variation. Our analysis reveals four recurring design tensions: automation vs. autonomy, helpfulness vs. intrusiveness, personalisation vs. predictability, and transparency vs. obscurity and distils them into a five-phase EM Design Playbook that supports moral prudence. We discuss implications for responsible smart-home design and offer guidance for human-centred AI.

Problem

• Expectations Management
• Smart-Home AI
• Ethics
• Design Tensions
• Human-Centred AI

Innovation

• Expectations Management
• Smart-Home AI
• Moral Prudence
• Design Tensions
• Culturally Situated Rites