The Psychology of Gen AI Series

The Psychology of GenAI is a monthly research series created in collaboration between the ARF and MSI. Through rigorous, targeted experiments and occasional support from external collaborators, the series examines the cognitive and psychological dynamics that arise in interactions between humans and generative AI, from bias and framing effects to memory, persona and decision-making. In marketing and advertising research, where AI is increasingly used to support insight generation, strategy and recommendations, understanding how AI outputs are shaped by learned patterns, prompt structure and intrinsic bias is critical. Each study therefore goes beyond identifying what happens in human-AI interaction to also offer practical implications and guidance for marketers and advertisers to use these tools more critically, responsibly and effectively.
What AI Recommends—and Why: Inside the Logic of “Best” Product Choices

What AI Recommends—and Why: Inside the Logic of “Best” Product Choices

  • Psychology of Gen AI
  • ARF; MSI

As generative AI tools increasingly shape how consumers search, shop, compare and evaluate products, understanding how they make recommendations has become critical for marketers. This seventh experiment in our ongoing Psychology of Gen AI series, is the first phase in a study that examines how large language models (LLMs), like ChatGPT and Claude, determine what qualifies as the “best” product—and reveals that their recommendations are far from neutral. Instead, they tend to rely on narrow, repetitive sets of familiar brands and structured response patterns that may reinforce existing market leaders. The findings highlight important implications for brand visibility, competitive dynamics and how marketers should position their products in AI-driven environments.

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When Language Becomes Targeting: How Gender Cues Shape AI Recommendations

When Language Becomes Targeting: How Gender Cues Shape AI Recommendations

  • Psychology of Gen AI
  • ARF; MSI; Iris Flex

As generative AI tools increasingly influence product discovery and decision-making, subtle cues in user language can shape what consumers are shown—and how options are framed. This second phase of the sixth study in the Psychology of Gen AI series examines how implicit and explicit gender signals affect AI-generated product recommendations, revealing systematic differences in categories, brand repetition, descriptive language and price information. The findings raise important questions for advertisers and researchers about bias, brand visibility and the growing cultural role of AI in shaping consumer norms.

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When Style Becomes Signal: How Gendered Language Shapes Generative AI Output

When Style Becomes Signal: How Gendered Language Shapes Generative AI Output

  • Psychology of Gen AI
  • ARF; MSI; Iris Flex

As generative AI tools become embedded in advertising and marketing research workflows, questions about bias increasingly extend beyond outputs to the interaction itself. This experiment, the first phase of the sixth study in the Psychology of Gen AI series, examines whether gendered patterns can enter AI through subtle differences in how prompts are phrased. By systematically varying linguistic styles using psychologically grounded traits, the research shows that implicit, style-based, gender cues shape AI prompt construction more strongly than explicit, gender labels, with important implications for how bias may propagate upstream in AI-assisted marketing and research applications.    

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Why Synthetic Respondents Flatten Consumer Sentiment

Why Synthetic Respondents Flatten Consumer Sentiment

  • Psychology of Gen AI
  • ARF; MSI

This fifth experiment in the Psychology of Gen AI series reveals that large language models apply a rigid, rule-driven logic when evaluating privacy scenarios—even when humans typically shift their reasoning based on framing, emotion and social context. Unlike consumers, who blend intuition, feeling and social perspective into their judgments, GPT-4o relied on a single internal rule across all testing conditions: data use is acceptable only with explicit consent. This consistency offers value for certain analytic tasks but exposes limits for advertising research that depends on emotional nuance and context-sensitive consumer insight.    

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Steering AI Bias: How Persona Prompts Unlock Nuance in Gen AI Responses

Steering AI Bias: How Persona Prompts Unlock Nuance in Gen AI Responses

  • Psychology of Gen AI
  • ARF; MSI

Large language models mirror human cognitive biases—but can those biases be guided? This experiment, the second phase in the fourth study on loss aversion in the Psychology of Gen AI series, reveals that while loss aversion remains deeply ingrained in AI responses, introducing persona information, such as demographics or personality traits, can increase variability and make outputs more nuanced.  For advertisers and researchers, this opens the door to design strategic prompts that spark richer and more nuanced, human-like responses.  

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Testing AI’s Strategic IQ: Can Generative Models Think Like Top Executives?

Testing AI’s Strategic IQ: Can Generative Models Think Like Top Executives?

  • Psychology of Gen AI
  • ARF; MSI

The ARF and MSI tested whether generative AI can adopt executive personas and provide credible, role-specific strategies in this third study in the Psychology of Gen AI series. This experiment highlights how AI performs when “thinking like” organizational leaders, its limitations in institutional logic and feasibility,  and how human-in-the-loop feedback can refine outputs and create nuanced and worthwhile results.  

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PG VS R: The Psychology of Prompted Thought

PG VS R: The Psychology of Prompted Thought

  • Psychology of Gen AI
  • ARF; MSI

Can sanitized AI tools truly capture the nuance required for advertising and brand research? Is a less restrained one more likely to produce skewed results? This comparative deep dive, from ARF and MSI, is the second study in the Psychology of Gen AI series. It explores how two popular large language models—ChatGPT-4o and Grok 3—respond when prompted with complex topics. The findings highlight how content moderation affects not only tone and specificity, but the very boundaries of inquiry. For advertising researchers navigating sensitive brand perception topics, understanding these model tradeoffs is essential.

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Alternative Explanations: Can AI Rethink Its Own Reasoning?

Alternative Explanations: Can AI Rethink Its Own Reasoning?

  • Psychology of Gen AI
  • ARF; MSI

Can AI challenge its own conclusions rather than merely reinforcing them? In this first experiment in the Psychology of Gen AI series, researchers explored whether large language models (LLMs) like ChatGPT can go beyond efficiency and exhibit deeper critical thinking skills. By prompting AI to evaluate and compare hypotheses—including its own—this study reveals how LLMs can serve as interpretive collaborators in research and theoretical reasoning.

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