01
Foundational study
Disciplinary Differences in AI Verification
Do engineers and designers approach the verification of AI-generated outputs differently?
How Social Influence Shapes Decisions with AI
Subjective decision-making · Peer influence · Generative AI
When people make subjective decisions with AI in groups, they must evaluate both the AI’s recommendation and one another’s judgments. I study how they decide whether a teammate’s agreement or disagreement offers useful information, exerts social influence, or both.
Research Questions
The question this opened
When individual and group decisions produce different outcomes, how does peer pressure change whose judgment guides the group’s response to AI?
02
Main study · Current phase
Social Influence in AI-Assisted Decision-Making
How does a teammate’s agreement or disagreement change the subjective decisions people make with AI?
Method
01
Mixed-method survey
A survey of 117 engineering and design students compared AI use, trust, confidence, perceived value, and verification expectations.
02
Controlled within-subject experiment
Graduate students first make subjective business decisions with ChatGPT recommendations independently, then revisit them after discussing a standardized agreement or disagreement position with a teammate.
The discussion adds a social position but no new evidence, allowing changes to be examined as peer influence rather than informational gain.
Findings
01
Verification expectations differed by discipline
Engineers and designers used and valued AI similarly, but engineers expected stronger verification. This distinction showed that individual AI use could not explain what happens when people evaluate AI together.
02
Peer-pressure effects are being tested
The study measures changes in decisions, confidence, and intention to seek additional information after discussion. Data collection and analysis are ongoing; findings will be added when the evidence is ready.
Product and Design Impact
What changed: The foundational study redirected the research from individual AI verification toward peer pressure in group decisions and supports designing GenAI for specific, consequential work rather than treating individual and group use as the same context.
Protect independent input
Use private votes so no participant dominates or withdraws from the discussion.
Represent the group fairly
Capture everyone’s comments and show an aggregate of votes rather than privileging the loudest position.
Track what discussion changes
Show confidence changes and identify when the group needs more information before deciding.
This direction is intended for workplace collaboration and decision-support tools used by managers, research leads, and project leaders making subjective decisions. It remains a design hypothesis until the main study is complete.
Research Notes
Dated reflections on consequential changes in the research—not a forced weekly timeline
[A decision that changed how you study the problem]
[Explain the decision, what prompted it, the alternatives you considered, and how it changed the research. This can be several paragraphs when you are ready.]
[A pattern, tension, or unexpected observation]
[Describe what you observed, why it matters, and how cautiously it should be interpreted at this stage of the project.]
[Something that changed your thinking]
[Share what you previously assumed, what challenged that assumption, and what you are thinking about differently now.]
These are draft placeholders. Notes can be added, removed, or reordered whenever the research evolves.
