Studying Human Attitudes Towards Robots Through Experience

2026-04-05 · Source: IEEE Spectrum · Field: Technology & Digital — Robotics & Autonomous Systems, Social Sciences & Behavioral Studies · Depth: Novice, medium

Summary

The RAI Institute conducted a free popup robot experience in summer 2025 at CambridgeSide mall to gauge public perception and comfort with advanced robotics. The initiative aimed to provide direct interaction with robots, countering sensationalized media portrayals. The experience featured a museum area with historical and modern robots, including the RAI Institute's UMV, and an interactive "Drive-a-Spot" arena where visitors could control a Boston Dynamics Spot quadruped robot using a custom, adaptive video game controller. The driving arena simulated various environments like factories, homes, hospitals, and outdoor/disaster scenarios. Participants, ranging from ages two to over 90, completed pre- and post-interaction surveys assessing comfort and suitability of robots in different contexts, alongside emotional reactions and open-ended feedback. The study found that hands-on interaction significantly increased public comfort and perceived suitability of robots across diverse settings.

Key takeaway

For AI scientists and robotics developers aiming for broader public acceptance of autonomous systems, prioritize designing and deploying hands-on interaction experiences. Your efforts should focus on creating accessible, direct encounters with robots, as this approach demonstrably increases comfort and perceived suitability, especially in social and domestic settings where ambivalence is highest. Consider integrating expert human interaction to further enhance the experience.

Key insights

Direct, hands-on robot interaction significantly boosts public comfort and perceived suitability across various environments.

Principles

• Active engagement surpasses passive exposure for attitude shifts.
• Initial discomfort in specific contexts can be mitigated by experience.

Method

A popup robot experience allowed public interaction with a Spot robot via an adaptive controller. Pre- and post-interaction surveys measured comfort and suitability across five scenarios, capturing demographic and emotional data.

In practice

• Design adaptive controllers for broad accessibility.
• Simulate diverse environments for contextual evaluation.
• Integrate expert interaction alongside robot experiences.

Topics

• Human-Robot Interaction
• Public Perception of Robots
• Spot Robot
• Experiential Learning
• Robot Acceptance

Best for: AI Scientist, General Interest, Research Scientist, Robotics Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by IEEE Spectrum.