“We have entered a period in which the relationship between information and truth has become fundamentally contested,” says Jemielniak, a professor at Kozminski University. Digital technologies have made reliable information easier to access, but they have also made false claims easier to produce, distribute and amplify. The result is an environment in which accurate scientific findings compete for attention with conspiracy theories, manipulated data and emotionally powerful misinformation, often on platforms that reward engagement rather than accuracy.

During the mid-twentieth century, public confidence in scientists was closely linked to perceptions of progress and prosperity. Scientific institutions were associated with public health, technological innovation and solutions to social problems. That confidence has weakened as people have encountered corporate influence scandals, research fraud, high-profile retractions and an overwhelming volume of scientific information. These factors alone do not explain the collapse of trust, Jemielniak says, but they become more damaging when combined with a digital infrastructure designed to spread provocative content at high speed.

Social media recommendation systems typically measure success through clicks, comments, shares and viewing time. They do not necessarily distinguish between a carefully conducted study and a sensational claim. Content that generates anger, fear or surprise can therefore travel farther than cautious explanations of uncertainty. Online communities can also form around almost any belief, creating echo chambers in which users repeatedly encounter claims that confirm their existing views. “What is historically distinctive is the contemporary infrastructure that accelerates these cycles by rewarding outrage, simplifying complex disputes into identity signals, and turning epistemic conflict into content,” Jemielniak explains.

The problem is intensified by the specialisation of modern science. Research fields have become so technically complex that even trained scientists often depend on specialists outside their own disciplines. For the public, evaluating a claim may require knowledge of experimental design, statistical inference, measurement error, causal reasoning and the limits of available evidence. Most people cannot independently verify such claims, so they must rely on institutions and experts. This condition, known as epistemic dependence, is not irrational; it is an unavoidable feature of a society built on advanced knowledge. But it becomes fragile when institutions appear secretive, conflicted or inconsistent.

“When people cannot evaluate scientific claims for themselves, they must rely on trust,” Jemielniak says. If that trust is weakened by misconduct, contradictory expert statements or alienating technical language, alternative explanations can become more attractive. Such explanations often appear simpler and more personal, even when they lack empirical support. The appeal comes not necessarily from superior evidence, but from the sense that the explanation is understandable, emotionally satisfying and connected to everyday experience.

Human cognition also gives personal stories an advantage over statistical evidence. For most of human history, people exchanged knowledge through narratives shared within families and communities. A personal account of an illness improving after a treatment, or a child developing symptoms after vaccination, is concrete and emotionally vivid. By contrast, a peer-reviewed analysis may summarise thousands of cases using probability estimates, confidence intervals and discussions of methodological limitations. Statistics can provide stronger evidence, but stories are often easier to remember and more compelling to share. This cognitive preference can cause isolated experiences to outweigh large bodies of carefully collected data.

Scientific disputes become even more difficult to resolve when they are tied to political identity. Climate change, vaccine safety and evolution are no longer treated solely as empirical questions in many communities; they have become signals of group membership. Research discussed in Jemielniak’s book suggests that greater scientific literacy can sometimes intensify partisan divisions over climate change. When people use their knowledge to defend an existing political identity, additional information may strengthen motivated reasoning rather than encourage impartial evaluation. Changing one’s position can also carry social costs, including criticism, exclusion or estrangement from friends and relatives.

The consequences extend beyond individual beliefs. Research covering 158 countries between 2000 and 2019 found that social media can support democracy by enabling broader participation and exposure to diverse viewpoints, while disinformation is associated with democratic decline. In democratic systems, high levels of disinformation are linked to a greater likelihood of autocratisation. In authoritarian systems, misinformation can help rulers preserve the status quo. When citizens cannot agree on basic facts, expertise is dismissed as inherently biased and truth is reduced to personal opinion, democratic institutions lose the shared factual foundation required for collective decision-making.

Jemielniak rejects the idea that the answer is simply to provide more scientific information. Decades of research suggest that additional facts do not automatically change attitudes or behaviour, particularly when distrust is rooted in social experience, political identity or perceived institutional betrayal. Rebuilding confidence requires understanding where different groups draw the boundaries of trust, including legitimate concerns about pharmaceutical companies, government decisions and past failures within science. The response must also involve structural reforms: greater transparency, clearer communication of uncertainty, accountability for digital platforms, transparent political advertising and sustained support for high-quality journalism. Trust, Jemielniak argues, cannot be demanded as a consequence of expertise. It must be earned through openness, accountability and a visible commitment to the public interest.

Subject of Research: Public trust in science, anti-science sentiment, misinformation and the relationship between scientific expertise and democracy.

Article Title: Why Public Trust in Science Is Falling in the Age of Information

Web References: https://www.routledge.com/Anti-Science-Shortcuts-to-a-Big-Idea/Jemielniak/p/book/9781041212980; http://dx.doi.org/10.4324/9781003726517

References: Jemielniak, Dariusz. Anti-Science: Shortcuts to a Big Idea. DOI: 10.4324/9781003726517

Keywords: Science communication, science journalism, science advocacy, scientific literacy, scientific community, education, society, sociology, communications, mass media, propaganda, public relations, social media, misinformation, human thought, scientific method, philosophy of science, sociolinguistics, democracy, public trust in science

In response to these concerns, regulatory bodies and digital platforms are taking steps to enforce transparency by mandating the clear disclosure of AI-generated or AI-synthesized content. These disclosure labels aim to inform the public when content originates from AI systems, thereby ostensibly empowering users to better judge the authenticity and reliability of the information they encounter. However, provocative new research published in the Journal of Science Communication reveals that such transparency measures may inadvertently undermine their intended purpose, potentially diminishing trust in accurate scientific information while simultaneously enhancing the perceived credibility of false claims.

This unexpected effect, coined the “truth–falsity crossover effect,” emerged from a rigorous experimental study conducted by Teng Lin, a doctoral candidate, and Yiqing Zhang, a master’s student, both from the School of Journalism and Communication at the University of Chinese Academy of Social Sciences in Beijing. Their investigation focused precisely on social media posts relaying science-related information, making their findings highly relevant to the platforms where much science communication now occurs.

The research design involved recruiting 433 participants via the Credamo platform during early 2024. Participants were exposed to four distinct categories of social media-style posts: accurate information with and without an AI generation disclosure label, and false information with and without the same label. The texts were meticulously crafted through the advanced GPT-4 language model, reworking items originally published by China’s Science Rumour Debunking Platform. Each post was verified for factual correctness by the researchers before participant evaluation. The subjects then rated the perceived credibility of each post on a five-point scale, with additional assessments of their attitudes toward AI and their engagement with the topic in question.

The study’s revelations defy conventional expectations about transparency and trust. Rather than uniformly reducing misinformation acceptance, the AI disclosure labels distorted credibility perceptions in a paradoxical manner. When AI labels accompanied truthful scientific posts, participants rated these messages as less credible, signaling a penalty against AI-generated veracity. Contrastingly, false posts bearing the AI disclosure were judged more credible than those without it. This asymmetry in perception highlights an alarming vulnerability in the current approach to AI content disclosure.

This “truth–falsity crossover effect” indicates that labeling content as AI-generated does not straightforwardly help users differentiate fact from fiction. Instead, it seems to redistribute trust inversely, devaluing true statements and lending undue legitimacy to falsehoods. The complex psychological processes underlying this effect may be influenced by the public’s mixed feelings about AI technology, expectations of AI capabilities, and skepticism about the veracity of machine-produced material.

Further exploration within the study reveals that individual predispositions toward AI critically shape these credibility judgments. Participants harboring more negative attitudes toward AI demonstrated an intensified distrust of true information flagged as AI-generated. However, intriguingly, this skepticism did not entirely eliminate the enhanced credibility granted to false information with AI disclosures. The attenuation of this credibility boost varied across specific scientific topics, implying an intricate interplay between content type, personal biases, and disclosure signals.

These findings underscore that “algorithm aversion,” or the tendency to distrust automated systems, does not result in a simple wholesale rejection of AI-created content. Instead, it triggers a nuanced and asymmetric cognitive reaction that can paradoxically empower misinformation. This revelation calls into question the efficacy of blanket labeling policies and challenges policymakers to reconsider their assumptions about public responses to AI disclosures.

The implications of this research are profound for regulators and digital platform developers who aim to safeguard the public from the deleterious effects of misinformation. The study’s authors advocate for a more sophisticated and layered approach to disclosure strategies rather than simplistic labels that merely notify audiences of AI authorship. One promising direction is the implementation of a dual-label system that not only acknowledges the AI origin of content but also communicates whether the information has undergone independent verification or includes clear risk warnings. This nuanced labeling could provide users with richer contextual cues about the reliability and potential hazards associated with the content.

Moreover, Lin and Zhang suggest adopting a graded or categorical labeling framework tailored to the inherent risk profile of the scientific information presented. For instance, AI-generated content related to critical sectors such as medicine and health could carry stringent warnings, reflecting their potential to impact public health outcomes adversely if incorrect. In contrast, topics such as emerging technologies or general scientific advancements might warrant lighter disclosure requirements due to a lower associated risk. This tiered approach recognizes the heterogeneous nature of scientific communication and better aligns transparency efforts with real-world consequences.

These recommendations highlight the necessity for rigorous empirical evaluation of any proposed disclosure policies before widespread deployment. The researchers emphasize that transparency interventions designed without careful testing may unintentionally erode trust in valid scientific facts while amplifying misinformation, thereby compromising the very objectives they seek to achieve. This work serves as a clarion call for multidisciplinary collaborations among social scientists, communication experts, and technologists to refine disclosure methodologies that effectively promote informed public engagement.

In sum, as AI increasingly permeates the science communication ecosystem, understanding how disclosure practices influence public credibility assessments is crucial. This study’s unexpected findings disrupt the assumption that labeling AI-generated content unequivocally enhances user discernment. Instead, it reveals a more intricate landscape where transparency alone may be insufficient or even counterproductive. Consequently, this pioneering research compels a reevaluation of current regulatory paradigms and encourages the development of more sophisticated, context-aware solutions that mitigate misinformation while bolstering public trust in genuine scientific knowledge.

Subject of Research: People
Article Title: Visible Sources and Invisible Risks: Exploring the Impact of AI Disclosure on Perceived Credibility of AI-Generated Content
News Publication Date: 9-Mar-2026
Web References: https://doi.org/10.22323/358020260107085703
Image Credits: Federica Sgorbissa – SISSA Medialab
Keywords: AI, Science Communication, Credibility, Misinformation, Disclosure, Social Media, Algorithm Aversion, Cognitive Psychology

A.J. Jacobs is a figure well-known for his multifaceted approach to storytelling, weaving humor, scientific inquiry, memoir, and practical self-help into narratives that engage a broad spectrum of audiences. His background includes contributions to highly respected publications such as The New York Times, New York magazine, and Entertainment Weekly, as well as serving as editor-at-large for Esquire magazine. His media presence spans popular platforms like The Today Show, Oprah, The Colbert Report, Good Morning America, and multiple TED Talks, establishing him as a significant voice in the discourse on science and society.

The central theme of Jacobs’ upcoming presentation targets the phenomenon of “Truth Decay,” a term used to describe the diminishing role of facts and analysis in public life. This degradation challenges not only scientists and researchers but also the institutions responsible for safeguarding scientific integrity. Truth Decay exacerbates skepticism and mistrust, undermining societal progress and public health initiatives. Jacobs’ insights will explore strategies aimed at restoring faith in science through transparent, engaging, and nuanced communication.

Nash Rochman, assistant professor at CUNY SPH and investigator at CUNY ISPH, emphasizes the timeliness of Jacobs’ work. He notes that scientific communication today must overcome not only the public’s presumed boredom but also pervasive doubts regarding the credibility of research entities. Rochman anticipates a rich, interactive dialogue that will include audience participation, reflecting a dynamic approach to addressing these persistent challenges. The goal is to cultivate a space where complexity is respected rather than oversimplified for mass consumption.

The event is scheduled to take place on the CUNY SPH campus, located at 55 West 125th Street, in the 7th-floor auditorium of the building. This setting is symbolic: a hub of public health scholarship convening to dissect the intersecting issues of science dissemination, public trust, and evidence utilization. Hosting such a talk within an academic institution engaged in population health and implementation science underscores the vital link between research and practice.

Jacobs’ approach to storytelling is of particular relevance in an age where social media platforms often prioritize immediacy over depth. His ability to use humor as a vehicle to translate dense scientific concepts into accessible narratives encourages a reconceptualization of how evidence is framed and discussed in public forums. This is especially critical given the volume of misinformation and the speed at which it can propagate in digital ecosystems.

The partnership between CUNY SPH and CUNY ISPH for this event highlights the interconnectedness of academic disciplines working to enhance community health outcomes. While CUNY SPH focuses on training future public health leaders and advancing health policy, CUNY ISPH dedicates itself to implementation science—the study of effective methods to adopt and embed evidence-based interventions within real-world settings. Together, their collaboration signals a collective commitment to addressing not only the scientific content but also the transmission mechanisms vital to public comprehension and trust.

An understanding of psychological and sociological dimensions is fundamental when tackling the erosion of scientific trust. Jacobs’ talk will likely explore cognitive biases, the psychological appeal of simplicity, and the pitfalls of rapid information consumption, all of which contribute to the “truth decay” dilemma. Addressing these elements requires a balance between maintaining scientific rigor and fostering relatability, a nuanced artistry Jacobs has mastered.

The event, though free, requires registration—a detail reflecting the anticipated interest and the organizers’ intent to curate an engaged audience. This educational opportunity offers attendees a chance to participate in an evolving conversation about the future of science communication, particularly as it relates to public health challenges in a world saturated by information but often starved for understanding.

As misinformation increasingly jeopardizes public health interventions, especially during crises such as pandemics, the discourse facilitated by this event could not be more critical. Engaging with experts who navigate the delicate interplay between fact and narrative equips public health professionals, communicators, and the general public with tools to counteract falsehoods and reinforce evidence-based decisions.

Ultimately, Jacobs’ presentation is poised to ignite a renewed commitment to fostering scientific literacy through storytelling that respects complexity. This event exemplifies the proactive efforts of academic institutions to dismantle barriers between knowledge producers and the public, promoting a more informed, participatory, and resilient society.

Subject of Research: Science communication and public trust in scientific research
Article Title: Battling Truth Decay: Communicating Nuance in a World Hooked on Fast Factoids
News Publication Date: October 9, 2025
Web References:
– https://sph.cuny.edu/
– https://cunyisph.org/
References: None provided
Image Credits: CUNY SPH
Keywords: Public health, Science communication