# CAREER: Calibrating User Trust in GenAI Chatbots: Investigating the Effects of Competing Cues and Interactivity Strategies to Mitigate Unfounded Cognitive Heuristics

> **NSF 01002829DB NSF RESEARCH & RELATED ACTIVIT** · Michigan State University (MI) · $582,392

## Abstract

Artificial intelligence (AI) that produces new content - text, images or videos - in response to the user input is known as generative AI. The output of these systems is designed to look and feel like human communication. However, generative AI systems can lead users to trust the system too much, leading them to share inappropriate information for the circumstances. For example, conversational AI systems, or chatbots, talk like humans and may encourage users to trust them without enough objective information to support that trust. This affects decision-making and can lead to unsafe disclosures of personal information. The goal of this research is to find ways to reduce quick user judgments from affecting decisions and help design AI systems that are safer and more responsible. The investigators will design, build, and test strategies that counter quick intuitive judgments using theories of communication and Human-AI interaction. The results of this study will be shared in a toolbox to help others design AI chatbots more ethically and responsibly. The toolbox will also help teach people about AI and chatbots, which will equip them for the workforce of the future.

This CAREER project investigates strategies to ensure that user trust of Generative AI (GenAI) chatbots is warranted. Warranted trust involves assessments based on the actual capacities of the AI chatbot, rather than  reliance on unfounded heuristics (or cognitive rules of thumb). This will be achieved in two phase

## Key facts

- **NSF award ID:** 2440090
- **Awardee organization:** Michigan State University (MI)
- **SAM.gov UEI:** R28EKN92ZTZ9
- **PI:** Maria D Molina
- **Primary program:** 01002829DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** CAREER-Faculty Erly Career Dev, Cyber-Human Systems
- **Estimated total:** $582,392
- **Funds obligated:** $334,794
- **Transaction type:** Continuing Grant
- **Period:** 06/15/2025 → 05/31/2030

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2440090

## Citation

> US National Science Foundation, Award 2440090, CAREER: Calibrating User Trust in GenAI Chatbots: Investigating the Effects of Competing Cues and Interactivity Strategies to Mitigate Unfounded Cognitive Heuristics. Retrieved via AI Analytics 2026-06-07 from https://api.ai-analytics.org/grant/nsf/2440090. Licensed CC0.

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