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The Deese-Roediger-McDermott DRM Task: A Simple Cognitive Paradigm to Investigate False Memories in the Laboratory
Published on: January 31, 2017
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Unavoidable social contagion of false memory from robots to humans
Tsung-Ren Huang1, Yu-Lan Cheng1, Suparna Rajaram2
1Department of Psychology, National Taiwan University.
The American Psychologist
|November 20, 2023
Summary
Conversational AI can implant false memories, with 77% of misinformation becoming false memory. Forewarnings did not prevent this social contagion of memory, highlighting risks of AI-generated content.
Area of Science:
- Cognitive Psychology
- Human-Computer Interaction
- Artificial Intelligence Ethics
Background:
- Conversational agents, like AI chatbots, are increasingly common.
- These agents may spread misinformation or disinformation, raising concerns about memory and decision-making.
- The potential for social contagion of false memories from AI interactions is not well understood.
Purpose of the Study:
- To investigate if conversational agents can cause social contagion of false memory.
- To determine the effectiveness of forewarnings in mitigating AI-induced false memories.
- To assess the influence of AI misinformation compared to human misinformation.
Main Methods:
- Two experiments (N=120) used a social robot to deliver misinformation to participants before a memory task.
- A social contagion of memory paradigm was employed to control information exposure.
- Forewarnings, both one-time and frequent, were tested as mitigation strategies.
Main Results:
- The social robot was as effective as humans in influencing participants' memory.
- 77% of neutral misinformation provided by the robot resulted in false memories.
- Forewarnings, even frequent ones, did not prevent false memory contagion but increased cautiousness.
Conclusions:
- Conversational agents pose a significant risk for social contagion of false memory.
- Current forewarning strategies are insufficient to prevent AI-driven memory contamination.
- Designing AI to avoid uncertain information or provide robust warnings is crucial.
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