The chat-chamber effect: Trusting the AI hallucination

This study investigates the potential for ChatGPT to trigger a media effect that sits at the intersection of echo-chamber communication and filter bubbles. We devised a two-phase, two-stage experimental design with ChatGPT 3.5 (treatment group) and Google search engine (control group) by asking participants to find out how many LGBTQIA+ individuals served as elected representatives in India (first phase) and Ireland (second phase). The similar trajectories of legal reforms observed in these countries, and their small number of LGBTQIA+ elected representatives, allowed us to identify the fault lines in ChatGPT's creation of knowledge and information around LGBTQ issues. We followed the experimental study with semi-structured interviews to identify whether the chatbot reinforced previously held beliefs and whether users cross-checked the information provided by ChatGPT. Our results show that Large Language Models may provide incorrect but proattitudinal information that remains unchecked and unverified by the users, an effect we refer to as Chat-Chamber. We conclude with a discussion of our findings and recommendations for future research in the area.