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Human preferences toward algorithmic advice in a word association task
Eric Bogert1, Nina Lauharatanahirun2, Aaron Schecter3
1Department of Supply Chain and Information Management, Northeastern University, Boston, MA, 02115, USA.
Scientific Reports
|August 25, 2022
Summary
Algorithmic advice increased response changes and confidence in creative tasks, but decreased accuracy. Humans showed both appreciation and aversion to AI recommendations, impacting problem-solving outcomes.
Area of Science:
- Human-Computer Interaction
- Cognitive Psychology
- Artificial Intelligence
Background:
- Algorithms increasingly support creative tasks like text generation.
- Human responses to algorithmic advice vary, from complacency to mistrust.
- Understanding human-AI interaction in creative domains is crucial.
Purpose of the Study:
- To investigate human reactions to algorithmic advice in a creative task.
- To compare responses to algorithmic versus crowd-sourced advice.
- To assess the impact of advice quality and question difficulty on human decision-making.
Main Methods:
- A preregistered online experiment with 154 participants and 2772 observations.
- Participants completed the Remote Associates Test (RAT) twice, receiving advice in between.
- Advice varied in source (algorithmic vs. crowd) and quality, and questions varied in difficulty.
Main Results:
- Individuals receiving algorithmic advice changed responses 13% more frequently and reported higher confidence.
- However, algorithmic advice led to a 13% decrease in identifying the correct solution.
- Both algorithmic and crowd advice influenced human responses, with varying effects on accuracy.
Conclusions:
- Algorithmic advice can enhance confidence and engagement in creative tasks but may reduce accuracy.
- Human-AI collaboration in creative fields presents both opportunities and challenges.
- Further research is needed to optimize algorithmic support for creative problem-solving.
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