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<td><span style="font-family:Helvetica, sans-serif; font-size:20px;font-weight:bold;">PsyPost – Psychology News</span></td>
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<td><a href="https://www.psypost.org/people-who-are-more-likely-to-die-seem-to-care-less-about-the-future/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">People who are more likely to die seem to care less about the future</a>
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<p><p>Two studies of individuals who had purchased life insurance found that those assigned higher mortality risk ratings by insurers tended to be more focused on the present and less concerned about the future. These individuals were less likely to follow what researchers call a “slow life strategy,” were more inclined toward short-term mating, and tended to be more impulsive, less conscientious, and less likely to consider future consequences. The findings were published in <a href="https://doi.org/10.1016/j.evolhumbehav.2025.106683"><em>Evolution and Human Behavior</em></a>.</p>
<p>Mortality risk refers to the likelihood that a person will die within a given time frame due to factors such as age, medical conditions, lifestyle behaviors, and environmental exposures. Public health researchers use such data to track population trends and guide interventions. In the context of life insurance, mortality risk is a core factor used to set premiums and coverage levels. Insurance companies use medical exams, family history, and other personal data to estimate this risk and assign applicants to actuarial categories that reflect their relative likelihood of dying.</p>
<p>In this new research, psychologists Aaron W. Lukaszewski and Joseph H. Manson proposed that insurance-based mortality risk ratings could serve as a scientifically valid measure of an individual’s objective risk of death. Drawing on evolutionary psychology, they predicted that people with higher mortality risk would show behavioral traits reflecting a shorter time horizon. From an evolutionary perspective, investing in long-term goals may only be adaptive when individuals can reasonably expect to survive to enjoy the benefits. When the future is uncertain or potentially short, prioritizing immediate rewards may be more advantageous.</p>
<p>The first study involved 273 U.S. residents recruited via Amazon’s Mechanical Turk. All participants had purchased an individual life insurance policy within the previous five years and reported the underwriting risk rating assigned to them. They completed questionnaires assessing impulsivity, prosociality, and industriousness using the Life History Rating Form, as well as items from the Sociosexual Orientation Inventory that assessed preferences for long- versus short-term mating.</p>
<p>In this framework, low impulsivity, high prosociality, and high industriousness are considered indicators of a “slow life strategy,” which reflects a long-term, future-oriented pattern of development. This contrasts with a “fast life strategy,” characterized by impulsivity, short-term focus, and higher mating effort, particularly in unpredictable or harsh environments.</p>
<p>The second study included 402 U.S. residents recruited mainly through the platform Prolific. All participants had purchased an individual life insurance policy in the previous 10 years and had undergone a paramedical exam as part of the underwriting process. Participants completed a broader set of questionnaires that measured mating and parenting effort, short-term mating orientation, consideration of future consequences, risk propensity, impulsiveness, aggression, conscientiousness, and childhood environmental conditions.</p>
<p>Participants’ mortality risk was categorized based on their life insurance underwriting classifications. These classifications, which were consistent across insurance companies, were grouped into low, medium, or high risk categories for analysis. Researchers controlled for factors such as age, sex, and tobacco use.</p>
<p>The results from both studies supported the central hypothesis. Individuals with higher insurance-based mortality risk were more likely to exhibit traits linked to a fast life strategy. These traits included higher impulsiveness, lower conscientiousness, and less concern for future consequences. In the first study, higher mortality risk was also associated with a stronger orientation toward short-term mating, although this effect was not consistently observed in the second study.</p>
<p>The researchers also measured participants’ self-estimated mortality risk—how soon they thought they would die compared to others, and at what age they expected to die. These subjective estimates did not correlate with the actuarial risk ratings. However, they were independently associated with similar behavioral traits, as well as with indicators of harsh or chaotic childhood environments. This suggests that people’s perceptions of their own life expectancy may be shaped more by past experiences and subjective beliefs than by the medical and biometric data used by insurers.</p>
<p>“The most consistent finding across two studies was that measures of mortality risk associated with personality traits related to present-future tradeoffs, most credibly impulsivity, concern for future consequences, and conscientiousness,” the authors wrote. “As such, our findings provide the most actuarially sound evidence to date in support of the adaptationist prediction that personality traits related to time horizon are calibrated during ontogeny in response to an individual’s risk of death.”</p>
<p>The findings suggest that people with higher mortality risk may adopt a psychological orientation that prioritizes immediate rewards and de-emphasizes future planning. This has implications for understanding decision-making, goal-setting, and health-related behaviors, particularly in individuals facing greater health or environmental risks.</p>
<p>However, it is important to note that the research is correlational. The design does not allow for conclusions about causality—whether higher mortality risk causes present-focused thinking, or whether certain personality traits influence behaviors that raise mortality risk. Additionally, while insurance-based mortality ratings are actuarially grounded, the proprietary nature of underwriting algorithms means that researchers cannot be entirely certain which variables contribute most to a person’s rating.</p>
<p>The paper, “<a href="https://doi.org/10.1016/j.evolhumbehav.2025.106683">People who are more likely to die care less about the future: Life insurance risk ratings predict personality</a>,” was authored by Aaron W. Lukaszewski and Joseph H. Manson.</p></p>
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<td><a href="https://www.psypost.org/researchers-identify-neural-mechanism-behind-memory-prioritization/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Researchers identify neural mechanism behind memory prioritization</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Jun 30th 2025, 08:00</div>
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<p><p>New research has uncovered how the brain dynamically adjusts its neural activity to prioritize more important information in working memory. The study, published in <em><a href="https://doi.org/10.1126/sciadv.adr8015" target="_blank">Science Advances</a></em>, found that when people are asked to remember multiple items, their brains amplify the neural signals for the more relevant ones, allowing for more accurate and confident recall.</p>
<p>Working memory is a short-term system the brain uses to store information temporarily, helping people make decisions, plan, and learn. But working memory is limited: trying to hold on to too many things at once reduces the quality of each memory. Past studies have shown that people can overcome some of these limits by allocating more mental resources to items they consider more important. The new study aimed to explain how this prioritization happens at the level of brain activity.</p>
<p>The researchers used a combination of brain imaging and computational modeling to examine how neural activity changes when people hold multiple items in memory, each with a different level of importance. They found that signals in visual areas of the brain were stronger and more precise for high-priority items. These differences in brain activity predicted how well each item was remembered. Activity in frontal brain regions also appeared to help direct attention toward more important information, shaping the quality of the memories stored elsewhere in the brain.</p>
<p>The study focused on a specific type of memory called visual working memory, which involves holding visual information in mind for a short period. For example, remembering where you parked your car or keeping track of a moving object both rely on this type of memory. The researchers designed an experiment that required participants to remember the locations of two items shown briefly on a screen. One of the items was more likely to be tested later, making it more important to remember. Participants had to hold both items in memory for 12 seconds before using an eye movement to indicate the remembered location of one of them.</p>
<p>To study what happened in the brain during this task, the researchers used functional magnetic resonance imaging, which measures blood flow as a proxy for neural activity. They scanned the brains of 11 participants while they performed the memory task over multiple sessions. By applying a complex decoding model to the imaging data, the researchers were able to estimate not only what participants were remembering but also how uncertain they were about each memory. The model treated neural activity as a probabilistic code, where stronger or more focused patterns of activity reflected more confident memory representations.</p>
<p>The results showed that neural signals in the visual cortex—the area of the brain involved in processing visual information—were more intense for the high-priority memory items. These stronger signals translated to smaller memory errors and greater confidence. On average, participants remembered the high-priority items more accurately and responded more quickly when asked to recall them. Their eye movements were closer to the correct location, and they took less time to respond. These behavioral improvements matched the patterns observed in the brain data.</p>
<p>The study also found that the magnitude of neural activity in the frontal cortex predicted how well participants could distinguish between high- and low-priority memories. This suggests that the frontal cortex plays a regulatory role, sending signals that adjust the strength of memory representations in visual areas depending on how important each item is. In other words, the frontal brain regions help direct the mental spotlight, increasing the “volume” of the memories that matter most.</p>
<p>The researchers measured this prioritization using a variety of statistical techniques. They showed that across trials, participants’ brain activity reflected differences in uncertainty between high- and low-priority items. These differences predicted not only how accurately participants remembered the items but also how much they prioritized one over the other. On trials where the gap in neural precision was larger, the behavioral performance difference was also larger.</p>
<p>The team also examined how different brain areas contributed to this process. They identified several regions—including the intraparietal sulcus and the prefrontal cortex—that showed brain activity that scaled with either the total amount of memory resource being used or with how it was distributed between the two items. One area in particular, the superior precentral sulcus, appeared to play a key role in adjusting this balance, possibly by sending feedback signals to visual areas. This finding supports the idea that working memory is not just a passive storage system but an active process that involves coordination across multiple brain areas.</p>
<p>By combining high-resolution brain imaging with a computational model, the researchers were able to isolate the contribution of neural “gain”—a measure of signal strength—in shaping the quality of working memory. They found that assigning higher gain to a memory item made its representation more precise and reduced uncertainty. This relationship is consistent with theoretical frameworks that treat memory and attention as probabilistic systems, where the brain maintains not just information but also a sense of how reliable that information is.</p>
<p>The study does have some limitations. The sample size was small, with only 11 participants, and all data came from a controlled lab setting. Real-world memory tasks are more complex and influenced by additional factors like emotion, motivation, and distractions. The researchers also noted that their model focused primarily on visual areas of the brain, leaving open questions about how other regions contribute to memory prioritization under different circumstances.</p>
<p>In future research, the authors suggest extending the approach to situations involving more than two memory items or different types of information. They also note that the ability to decode multiple memory representations from brain activity could have applications in brain-computer interfaces or in understanding disorders that affect attention and memory.</p>
<p>The study, “<a href="https://doi.org/10.1126/sciadv.adr8015" target="_blank">Neural mechanisms of resource allocation in working memory</a>,” was authored by Hsin-Hung Li, Thomas C. Sprague, Aspen H. Yoo, Wei Ji Ma, and Clayton E. Curtis.</p></p>
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<td><a href="https://www.psypost.org/love-addiction-linked-to-memory-and-attention-problems/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Love addiction linked to memory and attention problems</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Jun 30th 2025, 06:00</div>
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<p><p>A new study has found that people experiencing symptoms of love addiction are more likely to report problems with memory, attention, and cognitive functioning in daily life and at work. These effects appear to be closely linked to anxiety and depression, which themselves are associated with higher levels of love addiction. The study also found that frequent social media use is a strong predictor of love addiction symptoms. The findings, published in <em><a href="https://psycnet.apa.org/record/2026-22394-001" target="_blank">Behavioural Brain Research</a></em>, provide new insight into how emotional dependence on romantic partners can impact mental performance and well-being.</p>
<p>Love is often viewed as a powerful and positive force, but in some cases, it can become overwhelming and compulsive. Love addiction is a term used to describe a pattern of obsessive thoughts and behaviors directed toward a romantic partner, often accompanied by emotional instability, anxiety when apart, and an excessive focus on maintaining the relationship. Individuals with this pattern may experience symptoms similar to those seen in drug addiction, such as mood swings, loss of control, and intense craving. Despite the emotional suffering that often accompanies these symptoms, love addiction has received relatively little attention in clinical settings.</p>
<p>The researchers behind the current study aimed to better understand how love addiction affects people’s perception of their own cognitive functioning. They were particularly interested in exploring whether symptoms of love addiction are directly related to cognitive problems, or whether these problems are better explained by associated psychological symptoms like anxiety and depression. They also examined whether social media use plays a role in the development of love addiction, given the ways in which digital platforms can amplify romantic surveillance, jealousy, and emotional dependence.</p>
<p>To investigate these questions, the researchers analyzed data from 600 Italian adults who completed an online questionnaire between July 2022 and May 2023. The participants ranged in age from 18 to over 50, with most falling between 26 and 35 years old. About three-quarters were women, and over two-thirds had a university degree. The survey included a variety of standardized psychological and cognitive measures, including assessments of anxiety, depression, resilience, memory ability, attention, and social media use.</p>
<p>Participants were divided into three groups based on their level of love addiction symptoms: those with no symptoms, those with mild to moderate symptoms, and those with severe symptoms. Compared to those with no love addiction symptoms, individuals in the mild and severe groups reported more frequent cognitive failures, including problems remembering things, concentrating, and completing tasks at work or home. These subjective difficulties were especially prominent in the group with severe symptoms.</p>
<p>Interestingly, even those with only mild love addiction symptoms reported noticeable declines in perceived cognitive functioning. They also reported higher levels of anxiety and depression. Statistical analyses revealed that these psychological symptoms mediated the link between love addiction and cognitive complaints. In other words, love addiction appears to contribute to emotional distress, which in turn makes people feel less cognitively capable.</p>
<p>The study also found that people who used social media more frequently were more likely to exhibit symptoms of love addiction. This was true even after accounting for other factors such as age, gender, and education. Mediation models showed that social media use was indirectly linked to perceived cognitive problems through its effects on love addiction, anxiety, and depression. The more someone used social media, the more likely they were to report love addiction symptoms, which increased the likelihood of experiencing emotional symptoms that contributed to cognitive difficulties.</p>
<p>To test the robustness of these findings, the researchers performed additional analyses excluding participants with diagnosed psychiatric conditions. The results remained largely the same, suggesting that the effects of love addiction on perceived cognitive decline are not merely a reflection of underlying clinical disorders. The researchers also reversed the direction of their mediation models to test whether anxiety and depression might cause love addiction, but this alternative explanation was not supported by the data.</p>
<p>Beyond the cognitive effects, the study identified other important differences between groups. People with more severe love addiction symptoms tended to have lower levels of education, lower resilience, and less effective coping strategies. These individuals were also more likely to be currently using psychotropic medications and to report a history of psychological conditions.</p>
<p>Although the study was based on self-reported data and cannot confirm cause-and-effect relationships, it raises important concerns about how emotional attachment, social media habits, and mental health can interact to shape cognitive self-perception. The authors note that people experiencing love addiction often describe intense emotional suffering, especially when relationships are marked by rejection or instability. This emotional turmoil may not only impair their sense of well-being but also interfere with their ability to function in daily life.</p>
<p>From a clinical perspective, the findings suggest that targeting anxiety and depression in people with love addiction may help alleviate the cognitive complaints they experience. This approach could involve therapy, medication, or other mental health interventions aimed at improving emotional regulation. The study also highlights the potential role of education and resilience in protecting against love addiction, and suggests that digital literacy and awareness campaigns could be useful in mitigating its development, especially among young adults.</p>
<p>One implication of the study is that subjective cognitive difficulties in people with love addiction may serve as early warning signs. While subjective complaints don’t always correspond directly to objective cognitive impairments, they are often associated with future risk. This makes them an important target for early screening and intervention.</p>
<p>The authors acknowledge limitations in their work. The sample was not balanced in terms of gender, as most respondents were women. The recruitment method—snowball sampling through online platforms—may also have introduced bias. In addition, the study relied entirely on self-report questionnaires, which do not capture objective cognitive performance and are subject to personal interpretation. Future research could benefit from longitudinal designs that track individuals over time and include objective neuropsychological testing.</p>
<p>The study, “<a href="https://psycnet.apa.org/doi/10.1016/j.bbr.2025.115621" target="_blank">Love addiction symptoms and subjective cognitive complaints: The mediator role of depression and anxiety and the impact of social media use</a>,” was authored by Gianpaolo Maggi, Chiara Giacobbe, Lorenzo Borrello, Angelo Barone, Clara Mastromarino, Paolo Antonelli, and Gabriella Santangelo.</p></p>
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<td><a href="https://www.psypost.org/positive-early-experiences-may-buffer-suicidal-thoughts-in-those-with-trauma-symptoms-new-study-finds/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Positive early experiences may buffer suicidal thoughts in those with trauma symptoms, new study finds</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Jun 29th 2025, 14:00</div>
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<p><p>A new study published in the journal <em><a href="https://doi.org/10.1080/07481187.2025.2476985" target="_blank">Death Studies</a></em> suggests that positive childhood experiences can reduce the impact of trauma-related stress on suicidal thoughts in young adults. Researchers found that even among college students who reported symptoms of posttraumatic stress disorder and a history of adverse childhood experiences, those who recalled more supportive, affirming experiences from childhood were less likely to report suicidal ideation.</p>
<p>The findings offer evidence that early-life support may serve as a protective factor for suicide risk later in life—even in the presence of trauma. The study underscores the importance of both preventing early adversity and fostering positive relational experiences during childhood, especially in light of growing mental health concerns among college-aged populations.</p>
<p>Posttraumatic stress disorder, or PTSD, is a mental health condition that can develop in response to traumatic events. Symptoms include distressing memories, avoidance of reminders, emotional numbness, negative changes in beliefs and mood, and feelings of disconnection from others. These symptoms can cause psychological pain and lead to a sense of hopelessness, both of which are known contributors to suicidal ideation.</p>
<p>Suicidal ideation refers to thoughts about ending one’s life. These can range from vague feelings of despair to detailed plans. In the United States, suicide is the second leading cause of death among people aged 15 to 24. According to national data, nearly one in four college students has had suicidal thoughts in the past year.</p>
<p>Previous studies have shown that both PTSD and childhood trauma—often measured by a history of adverse childhood experiences, such as abuse or neglect—are associated with higher rates of suicidal thoughts. On the other hand, positive experiences during childhood, such as having a caring adult or feeling safe at home, may help buffer the negative impact of early adversity.</p>
<p>The new study was designed to explore how these factors interact. Specifically, the researchers wanted to find out whether benevolent childhood experiences could lessen the relationship between PTSD symptoms and suicidal ideation—even in those who had experienced high levels of adversity.</p>
<p>The study involved 837 undergraduate students at a university in the Southeastern United States. The average age of participants was 19, and most identified as White (88%) and female (76%). Participants completed a series of online questionnaires that measured posttraumatic stress symptoms, suicidal ideation, adverse childhood experiences, and benevolent childhood experiences.</p>
<p>To measure PTSD symptoms, the researchers used a widely accepted checklist that asks about the severity of different trauma-related symptoms over the past month. Suicidal ideation was assessed using a scale that includes both passive and active thoughts about death, such as wishing one were dead or making a plan to end one’s life.</p>
<p>Adverse childhood experiences were measured using a 10-item questionnaire that included questions about abuse, neglect, and household dysfunction before age 18. Participants answered “yes” or “no” to each item. The more “yes” answers, the higher their score.</p>
<p>Benevolent childhood experiences were measured with a similar 10-item scale that asked about positive early life experiences, such as having a good friend or feeling that their parents believed they were important.</p>
<p>The researchers then analyzed how all three factors—PTSD symptoms, adverse childhood experiences, and benevolent childhood experiences—interacted to predict suicidal ideation. They used a statistical method that allowed them to examine the combined effects of these variables across different levels.</p>
<p>About 27% of participants reported some degree of suicidal ideation in the past year. Around 17% had experienced four or more adverse childhood experiences, a threshold often associated with higher risk for mental health problems. At the same time, the vast majority—nearly 80%—reported high levels of benevolent childhood experiences.</p>
<p>As expected, participants with more severe PTSD symptoms were more likely to report suicidal ideation. Higher levels of adverse childhood experiences also increased suicide risk. But the presence of positive early experiences consistently reduced this risk.</p>
<p>The most important finding came from the three-way interaction analysis. The researchers discovered that benevolent childhood experiences reduced the strength of the relationship between PTSD symptoms and suicidal ideation—regardless of how many adverse experiences a participant had faced.</p>
<p>In other words, students with PTSD symptoms were less likely to think about suicide if they had also experienced supportive and affirming interactions in childhood. This buffering effect held true across all levels of adversity. Even those with high trauma exposure appeared to benefit from positive early relationships.</p>
<p>These results align with a well-supported psychological theory known as the Three-Step Theory of Suicide. This theory proposes that suicidal ideation emerges from the combination of psychological pain and hopelessness and intensifies when a person lacks a sense of connectedness to others or to meaningful aspects of life. Benevolent childhood experiences may provide a foundation for that sense of connectedness, even in the face of later trauma.</p>
<p>There are limitations to consider. The research was cross-sectional, meaning it captured a snapshot in time. Because of this, it cannot determine whether PTSD symptoms cause suicidal thoughts or whether benevolent experiences directly prevent them. Longitudinal studies following individuals over time would help clarify the direction of these relationships.</p>
<p>Another limitation is the study’s reliance on retrospective self-reporting. Participants were asked to recall childhood experiences, which could be subject to memory biases. People may remember or interpret past events differently depending on their current mental state.</p>
<p>The sample was also limited in diversity. Most participants were White, heterosexual, and cisgender women enrolled in college. These findings may not generalize to more diverse populations, including people with different racial, cultural, educational, or socioeconomic backgrounds.</p>
<p>Finally, while the study is consistent with the Three-Step Theory of Suicide, it did not directly measure the theory’s core components—such as hopelessness, psychological pain, or connectedness. Future research could incorporate more direct assessments of these concepts to better test the theory.</p>
<p>The study, “<a href="https://doi.org/10.1080/07481187.2025.2476985" target="_blank">Adverse and benevolent childhood experiences moderate the association between PTSD symptoms and suicidal ideation</a>,” was authored by Mary C. Jensen, Stella W. J. Son, Evan J. Basting, Alyssa M. Medenblik, Jacqueline A. Sullivan, Tara Cornelius, and Gregory L. Stuart.</p></p>
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<td><a href="https://www.psypost.org/readers-struggle-to-understand-ais-role-in-news-writing-study-suggests/" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Readers struggle to understand AI’s role in news writing, study suggests</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Jun 29th 2025, 12:00</div>
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<p><p>A new study published in <em><a href="https://doi.org/10.1080/08934215.2024.2424553" target="_blank">Communication Reports</a></em> has found that readers interpret the involvement of artificial intelligence in news writing in varied and often inaccurate ways. When shown news articles with different byline descriptions—some noting that the article was written with or by AI—participants offered a wide range of explanations about what that meant. Most did not see AI as acting independently. Instead, they constructed stories in their minds to explain how AI and human writers might have worked together.</p>
<p>As AI technologies become more integrated into journalism, understanding how people interpret AI’s role becomes increasingly important. Generative artificial intelligence refers to tools that can produce human-like text, images, or audio based on prompts or data. In journalism, this often means AI is used to summarize information, generate headlines, or even write full articles based on structured data. </p>
<p>Since 2014, some newsrooms have used AI to automate financial and sports stories. But the release of more advanced tools, such as ChatGPT in late 2022, has expanded the possibilities and made AI much more visible in everyday news production. For example, in 2023, a large media company in the United Kingdom hired reporters whose work includes AI assistance and noted this in their bylines. However, readers are not always told exactly how AI contributed, which can create confusion or suspicion.</p>
<p>The researchers behind the new study wanted to know how people understand bylines that mention AI and whether their interpretations are influenced by their familiarity with media and attitudes toward artificial intelligence. They were especially interested in whether people could accurately infer what AI did during the creation of a news article just based on the wording in the byline. This is important because trust in journalism depends on transparency, and previous controversies—<a href="https://futurism.com/sports-illustrated-ai-generated-writers" target="_blank">such as Sports Illustrated being accused</a> of using AI-generated content without disclosure—have shown that unclear authorship can damage credibility.</p>
<p>To explore these questions, the research team designed an online study involving 269 adult participants. The sample closely reflected the U.S. population in terms of age, gender, and ethnicity. Participants were recruited through Prolific, an online platform often used for social science research, and were paid for their time. After giving consent, participants completed a short questionnaire measuring their media literacy and general attitudes toward artificial intelligence. Then, each person was randomly assigned to read a slightly edited Associated Press article about a health story. The article was the same for everyone, except for one line at the top—the byline.</p>
<p>This byline varied in five different ways: some said the story was written by a “staff writer,” while others said it was written “by staff writer with AI tool,” “with AI assistance,” “with AI collaboration,” or simply “by AI.” After reading the article, participants were asked to explain what they thought the byline meant and how they interpreted the role of AI in writing the article.</p>
<p>The responses showed that readers tried to make sense of the byline even when it wasn’t entirely clear. This act of constructing meaning from limited information is known as “sensemaking”—a process where people use what they already know or believe to understand something new or ambiguous. In this case, people relied on their personal experiences, assumptions about journalism, and existing knowledge of AI.</p>
<p>Many participants assumed that AI helped in some way, even if they couldn’t say exactly how. Some thought the AI wrote most of the article, with a human editor stepping in to clean things up. Others believed that a human wrote the bulk of the article, but used AI for smaller tasks, such as checking facts or suggesting better wording. </p>
<p>One person imagined the journalist typed in a few keywords, and AI pulled together text from the internet to generate the article. Another described a collaborative effort where AI gathered background information, and the human writer then evaluated its accuracy. These mental models—often called “folk theories”—illustrate how readers try to fill in the gaps when information is missing or vague.</p>
<p>Interestingly, even when the byline said the article was written “by AI,” many participants still assumed a human had been involved in some way. This suggests that most people do not see AI as a fully independent writer. Instead, they believe human oversight is necessary, whether for guidance, supervision, or final editing.</p>
<p>Some participants expressed skepticism or even frustration with the byline. When the article said it was written by a “staff writer,” but didn’t include a name, some assumed that this was an attempt to hide the fact that AI had actually written it. Others said the writing quality was poor, and attributed that to AI involvement—even when the article had been described as written by a human. In both cases, the absence of a named author led to negative judgments. This finding supports earlier research showing that readers expect transparency in authorship, and when those expectations are not met, they may distrust the content.</p>
<p>To further understand what influenced these interpretations, the researchers grouped participants based on their media literacy and their general attitudes toward AI. Media literacy refers to how well people understand the media they consume, including how news is produced. </p>
<p>The researchers found that participants with higher media literacy were more likely to believe that AI had done most of the writing. Those with lower media literacy were more likely to assume that a human wrote the article, or that the work was a human-AI collaboration. Surprisingly, prior attitudes toward AI did not significantly affect how participants interpreted the byline.</p>
<p>This suggests that how much people know about the media may matter more than how they feel about artificial intelligence when trying to figure out who wrote a story. It also shows that simply including a phrase like “with AI assistance” is not enough to give readers a clear understanding of AI’s role. The study found that people often misinterpret or overthink these statements, and the lack of standard language around AI involvement only adds to the confusion.</p>
<p>The study has some limitations. Because the researchers did not include a named author in any of the byline conditions, it’s possible that participants reacted negatively because they missed seeing a real person’s name—something they expect from journalism. It’s also worth noting that the article used in the study was based on science reporting, which tends to be more objective and less interpretive. Reactions to AI involvement might be stronger for topics like politics or opinion writing. Future studies could explore how these findings apply to other types of journalism and examine how people respond when articles include a full disclosure or transparency statement about AI use.</p>
<p>Despite these limitations, the study raises important questions for news organizations. As AI becomes more common in the newsroom, it is not enough to say that a story was produced “with AI.” Readers want to know what exactly the AI did—did it write the first draft, summarize data, suggest edits, or merely spellcheck the final copy? Without this clarity, readers are left to guess, and those guesses often lean toward suspicion or confusion.</p>
<p>The researchers argue that greater transparency is needed, not only as a matter of ethics but as a way to maintain trust in journalism. According to <a href="https://www.spj.org/spj-code-of-ethics/" target="_blank">guidelines from the Society of Professional Journalists</a>, journalists are expected to explain their processes and decisions to the public. This expectation should extend to AI use. As with human sources, AI contributions need to be clearly cited and described.</p>
<p>The study, “<a href="https://doi.org/10.1080/08934215.2024.2424553" target="_blank">Who Wrote It? News Readers’ Sensemaking of AI/Human Bylines</a>,” was authored by Steve Bien-Aimé, Mu Wu, Alyssa Appelman, and Haiyan Jia.</p></p>
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<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
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