糖心Vlog

Is generative artificial intelligence technology a helpful tool or a big problem? Nearly four years after ChatGPT became a household name, . But understanding how much they actually trust the work it produces, and the answers it provides, remains an important question. New research from 糖心Vlog, based on a longitudinal analysis of hundreds of thousands of Reddit posts since 2022, sheds light on the general perception of AI and suggests that the public remains largely divided on how much it can be trusted.

Recently published in the journal, the study examined how trust and distrust toward generative AI were expressed over time, the dimensions and reasons underlying these attitudes and how these patterns differed across groups represented in the posts.

Its primary finding is that trust, which was expressed in about 31% of posts, modestly outpaced distrust (26%) in the technology, while 41% of posts expressed neither and 1% expressed both.

鈥淭hese findings give us an important starting point and help to establish a baseline understanding which can help inform responsible AI design, governance and literacy efforts,鈥� said Shadi Rezapour, PhD, an assistant professor in the Nick Howley College of Engineering and Computing, who led the research. 鈥淚t will be important to see how these attitudes around trust and distrust evolve as the technology becomes more widely used.鈥�

In what is believed to be the first large-scale, longitudinal study of how attitudes of trust and distrust in AI have evolved over the last four years, Rezapour鈥檚 in the School of Computer and Information Sciences, joined by researchers from Drexel鈥檚 College of Arts and Sciences and , gathered and analyzed more than 230,000 posts from 39 AI-related subreddits between November 2022 and June 2025. They looked at posts expressing views on systems such as ChatGPT, LLaMA, Claude and other widely discussed GenAI tools.

What does it mean to 鈥榯rust鈥� AI?

鈥淲e defined trust as a belief that Generative AI is reliable, competent or acts with integrity, leading people to have positive expectations about its performance or behavior,鈥� said Aria Pessianzadeh, a doctoral candidate in the School of Computer and Information Sciences, and lead author of the study. 鈥淒istrust is more than simply the absence of trust. It reflects active skepticism or concern about the technology鈥檚 reliability, competence or ethical implications, which can lead to negative expectations or more cautious behavior.鈥�

In addition to trust and distrust, and their dimensions, to better understand how these attitudes vary between different groups of people, the team broke down the type of commenter, or 鈥渢rustor,鈥� represented in each post into 10 categories using self-identifying information from their posts: generative AI users, software developers, researchers or academics, tech industry professionals, general public, media and journalists, business leaders or executives, AI ethicists or advocacy groups, artists or creatives and educators or knowledge workers.

Using computational models, the researchers analyzed the large volume of Reddit posts and categorized them based on the trust or distrust expressed and the reasons behind those views.

Views of trust tended to outweigh distrust among business leaders, academics, software developers and tech professionals. Distrust was more frequently expressed among posts categorized as representing the general public, AI ethicists and media and journalists. Generative AI users, which were the largest group, along with educators and knowledge workers, showed a relatively balanced level of trust and distrust, the study reported.

How do people form opinions about AI?

One theme that persisted across user groups was that personal experience with AI was the most frequently expressed reason underlying both trust and distrust. People also tended to express their views in terms of technological efficacy and reliability of the output, rather than ethical or normative aspects of the technology, such as judgments associated with a program鈥檚 relative transparency or integrity.

鈥淲hat stood out was how practical people鈥檚 judgments of AI tended to be,鈥� Pessianzadeh said. 鈥淭hey were primarily asking: 鈥楧oes it work? Is it accurate? Can I rely on it?鈥� Competence, reliability and familiarity were central to expressions of trust, while unreliability and incompetence were major sources of distrust. Ethical and value-oriented concerns were certainly present, but they were much less prominent in everyday discussions. For many users, trust in AI is expressed primarily in relation to their direct experience with what these systems can actually do, suggesting that people are more focused on whether AI programs 鈥榳ork鈥� than whether the technology is 鈥榞ood.鈥欌��

Some of the clearest fluctuations in trust and distrust occurred around periods when the researchers observed the public release of new AI products, such as GPT-4 and LLaMA 2, as well as major announcements, such as OpenAI鈥檚 Dev Day. Around several major releases in 2023, the monthly share of posts expressing trust increased modestly. By contrast, distrust increased around OpenAI鈥檚 Dev Day in late 2023.

鈥淒espite these fluctuations, trust maintained its modest lead over distrust. However, neither category dominated the discourse, underscoring a persistent tension in attitudes expressed in GenAI discourse,鈥� the researchers reported in the study.

How to Move Forward

Acknowledging this co-existence of trust and distrust will be important, the researchers suggest, as regulators set up governance and design standards to ensure safe use of the technology.

鈥淎 persistent duality like this means that responsible governance of the technology should consider that users will include both those who are confident in AI as well as those who are skeptical,鈥� said Rezapour. 鈥淥ur findings also suggest that governance cannot focus only on whether people find AI useful. It should address questions of reliability, transparency, bias and accountability in ways that connect these concerns to people's everyday experiences with the technology.鈥�

The researchers note that although this is a large-scale study, the fact that all of its data was drawn from Reddit posts could be a limiting factor. The relatively low prominence of ethical dimensions simply may be a reflection of how people communicate on social media 鈥� emphasizing immediate experiences of usefulness and performance, while broader ethical or normative concerns may be expressed less explicitly or require more contextual interpretation, according to the researchers.

They recommend that future research broaden the dataset to include languages other than English, additional social media platforms and populations beyond the online communities represented in the current study.

鈥淭hese findings are a useful starting point, but trust in AI is not static and people鈥檚 attitudes change based on their experiences with these systems, new capabilities and major developments in the technology,鈥� Rezapour said. 鈥淭herefore, researchers should continue to examine how attitudes about AI technology evolve in the coming years. With the rapidity of its adoption, it鈥檚 understandable that perceptions will be divided for some time. As these systems become increasingly embedded in everyday life, it will be important to understand whether trust and distrust continue to fluctuate, and what experiences, capabilities and broader developments drive those changes.鈥�

In addition to Rezapour and Pessianzadeh, Naima Sultana, Hilde Van den Bulck, PhD; David Gefen, PhD, and Shahin Jabbari, PhD, participated in this research.

Read the full paper here: