View Proposal

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Proposer

Minja Axelsson

Title

User Perceptions of Deceptive Patterns in Social Robots

Goal

Empirically evaluate how users perceive deceptive patterns of a social robot, and the robot using those deceptive patterns.

Description

Recent research has explored how robots might use deceptive designs or “dark patterns” to manipulate or trick users into doing something they might not have intended to do. However, these explorations have mainly focused on theoretical and simulated interactions. This project aims to explore how users experience a real-life physical robot using deceptive patterns, and whether they are deceived by those patterns. The project involves implementing deceptive patterns on a social robot using ROS etc, from a pre-determined script taken from literature, also including adaptive dialogue using e.g., LLMs. It also involves a user study examining user perceptions of the deceptive patterns. The outcome of the project will be a robot implementation using deceptive patterns, and a cutting-edge user study on how users perceive those patterns.

Resources

Background

[1] Dula, E., Rosero, A., & Phillips, E. (2023, April). Identifying dark patterns in social robot behavior. In 2023 Systems and Information Engineering Design Symposium (SIEDS) (pp. 7-12). IEEE.

Url

Difficulty Level

Variable

Ethical Approval

None

Number Of Students

2

Supervisor

Minja Axelsson

Keywords

social robots, deceptive design, dark patterns, robotics, responsible ai, hri

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Science in Artificial Intelligence
Master of Science in Human Robot Interaction
Master of Science in Robotics