The United States has one of the largest veteran populations in the world, with millions of people who have served in the military.
After their service, they move on to the next chapter of their lives, whether that is going to college, starting a new job, returning to where they lived before joining the service, or staying in the area of their first duty station.
The choropleth map above shows the number of veterans per 100,000 people in each state using data from the U.S. Department of Veterans Affairs. The map makes it easy to compare states and see where veteran populations are higher or lower.
States like Montana, Colorado, Maine and most notably Alaska have high veteran populations due to retirees having a pension and not being required to pay state income tax.
Illinois ranks low on the list, compared to other states, with the percentage of the adult veteran population rate at 5.3%. This is likely because of a higher cost of living and taxes compared to other states that attract more retired service members. Another reason is the state’s large population.
While Illinois actually has more veterans in total than states like Wisconsin, its much larger overall population lowers the percentage. In fact, Illinois has a bigger population than states like Montana, Colorado, Maine and even Alaska combined, which helps explain why its veteran share appears smaller despite having a high number of veterans overall.
The VA often places large medical centers near military bases, especially where their are multiple bases, because many veterans stay in the area of their last duty station. This makes it easier for veterans to get care since a lot of them already live nearby or decide to stay in the same area after leaving the military.
Some of the states that produced the largest and deadliest wildfires in American history now rank at the bottom of the national burn probability index compiled by the U.S. Forest Service’s Wildfire Risk to Communities project.
Illinois ranks at the 10th percentile for burn probability. Illinois has one of the lowest in the nation and well below neighboring states such as Missouri at the 40th percentile and Iowa at the 30th percentile.
The state’s low ranking reflects its largely agricultural and urban land cover. Illinois has no entry in the historical record of the 10 largest wildfires in U.S. history. The Great Chicago Fire occurred Oct. 8, 1871 and it was the same night as the Peshtigo Fire in Wisconsin and the Great Michigan Fire. While the Chicago fire drew significantly more national attention due to major architectural damage, it does not appear among the 10 largest wildfires in U.S. history by acreage.
Maine ranks at the zero percentile. Wisconsin ranks at the 18th percentile. Michigan ranks at the 24th percentile. All three states had fires in the 1800s that made the history books.
The 1825 Miramichi Fire, recorded as the largest wildfire in U.S. history, burned an estimated 3 million acres and killed at least 160 people, with most of the burning taking place in New Brunswick, Canada, and spreading into Maine. The Peshtigo Fire of October 1871 in Wisconsin burned more than 1 million acres and killed more than 1,500 people — the deadliest wildfire in U.S. history. The Great Michigan Fire, which occurred the same month, burned an estimated 2.5 million acres and killed fewer than 250 people.
Today, the states with the highest burn probability rankings are concentrated in the West and Southwest. Nevada ranks at the 100th percentile. California ranks at 98th. Idaho ranks at 96th. Washington ranks at 94th. Oregon ranks at 92nd.
Records from those states reflect the largest fires in more recent times. The August Complex, a merger of 37 separate fires in Mendocino County, Calif., burned 1.03 million acres in August 2020. The Dixie Fire burned 963,309 acres across Butte, Plumas, Lassen, Shasta and Tehama counties, Calif., beginning July 13, 2021, and was not fully contained until Oct. 26, 2021. The Smokehouse Creek Fire burned 1.07 million acres across the Texas Panhandle over nearly three weeks in February 2024, killing two people. Texas ranks at the 78th percentile.
The Taylor Complex Fire in Alaska, which ranks at the 76th percentile today, burned 1.3 million acres in 2004 with no reported deaths.
The states that recorded the largest fires in American history now carry the lowest risk scores. The states recording the largest fires today carry the highest. With climate change ongoing, it remains to be seen how in 200 years this map could change. There very well may have been larger, more destructive fires in what is today the western states, but these may have been unnoted before official statehood and accompanying records.
AI disclosure: ChatGPT was used to outline and find sources for this piece. DALL-E 3 and NotebookLM were used to create the images. The summary was generated by SummarizeWise custom GPT and the podcast and video was generated by NotebookLM.
Summary: Artificial intelligence (AI) is becoming common in newsrooms and helps journalists do tasks faster, like writing headlines or summarizing interviews. Some people worry AI will take journalism jobs, especially entry-level ones. However, experts say the biggest problem is declining news revenue, not AI itself. AI cannot replace important human work like interviewing sources or reporting events. Instead, it may help journalists save time and focus on deeper reporting.
More discussion about transparency in reporting has emerged within recent years, as news companies are beginning to turn to Artificial Intelligence (AI) to aid in writing news stories and are using less human thought to produce work.
“Nearly 70% of newsroom staffers from a variety of backgrounds and organizations surveyed in December say they’re using the technology for crafting social media posts, newsletters and headlines; translation and transcribing interviews; and story drafts, among other uses,” wrote Alex Mahadevan in a Poynter Institute article published on Apr. 10.
Newsrooms must incorporate and familiarize themselves with the AI in order to stay relevant, however, some concerns still remain amongst journalists on whether or not this powerful tool will cause job displacement.
Mahadevan wrote that journalists are already using AI and expediting the process of getting a news story published. Furthermore, journalism is experiencing “an already-ailing business model,” wrote Mark Caro in an article on the Medill Local News Initiative. This leads many to question the future for journalists who are skilled in a craft that technology is recreating and getting published.
As previously mentioned, journalists wonder what will become of their profession and job status in the future, as AI becomes a major tool in their field. While there are editors that believe that the tool can make everyday tasks easier and let reporters go more in depth into their reporting, layoffs and sparsity of job availability may become defensible, which endangers jobs and the human interference that the public relies on for factual excellence.
This article explores the use of AI in journalism, its impact on the opportunities for journalists, especially those new to the field, as well as providing journalist and media scholar Tom Rosenstiel’s expert opinion on the matter.
Introduction of AI Into the Newsroom
Artificial intelligence can no longer be shut out from journalism, as its use has slowly become integrated, leading to its role as a new staff member in the newsroom. Although some believe that AI in journalism is a new concept, that is not completely true. Mahadevan’s article stated that the Associated Press has been dabbling in AI for a decade. It’s been capable of performing simple tasks that make the life of a journalist easier, but now, with generative AI, it can perform more thorough work, like entire news articles with a structure that flows and reliable sources incorporated.
AI can read, analyze and simplify government documents, transcribe and give a summary of audio all within the snap of a finger, which can take away pressure in newsrooms and lead editors to support its time-saving features. While there is no denying its capabilities, there is also no denying its complex nature in the discipline. When Generative AI can do what a human can do, its journalistic use as an aid or potential replacement of journalists becomes more intriguing. This intrigue may only heighten as economic pressures may lead organizations to use it more.
This discussion does not only pertain to technology, but also raises ethical questions. Poynter has discussed issues of openness and responsibility. Should companies be open with whether or not their articles have benefited from AI? And who takes the responsibility when AI makes mistakes? As the use of AI becomes more widespread in journalism, these ethical arguments have been made in both public and newsroom discourse.
The Economic Rationale for AI and its Downsides
The reliance on AI in journalism has a clear connection to the financial demands in the industry right now. For many years now, publications, both in print and digital have earned less income for ads, diminishing staff, and all too commonly, they shut down. According to a Brookings Institute article by Courtney C. Radsch, “smaller, niche, minority, investigative, and local media are being left behind, in part because they don’t necessarily understand the value proposition of their journalism throughout the AI value chain, the resources and sway to seek out deals, or the power to negotiate effectively.”
In journalism’s struggling economic state, AI appears to be an attractive way to save money. A paid staff reporter costs a lot more money than simply using an automated approach to do specific tasks. When less money is coming in, executives will turn to what makes sense: less spending on workers and a quicker process.
Rosenstiel argues that many companies are using AI due to the fact that revenue is disappearing, and not because they are trying to unemploy journalists completely. With this perspective, the increase of AI usage in the newsroom is connected to financial challenges and not just innovation purposes.
Looking at the issue with this economic perspective, journalism becomes commodified. If the tool is used mostly because it is a way to save a buck, then more termination may take place and money may not be put back into the organization to aid in more reporting, which requires the human mind. For those worried about AI taking the job of new journalists who are tasked with writing simpler pieces, there is still hope. Radsch claims that “unlike journalists, AI can not go into the courtroom or interview a defendant behind bars, meet with the grieving parents of the latest school shooting victim, cultivate the trust of a whistleblower, or brave the frontlines of the latest war.”
The conflict within this debate is apparent in other industries as well, however, journalism is particularly distinct from other fields facing this dilemma. Journalism does not plainly make content, but rather is an occupation that requires transparency and faith from the people. When saving money by using technology impacts the employment status of journalists, consequential effects may emerge, like the loss of formal skills, guidance and aid in nurturing new journalists.
If organizations use AI to put out work quicker than others, those that don’t adapt will struggle to remain relevant and succeed in a digital world where there is already an abundance of content. This puts journalists in a difficult situation of accepting an instrument that their work could benefit from, while also dreading the possibility of it occupying their position.
What Does This Mean for Entry-Level Jobs?
Although AI sounds like a promising newsroom assistant, it also could be the source of fear for journalists that use entry-level jobs to develop fundamental skills. Entry-level jobs, like copy editor, reporter or editorial assistant have long provided new journalists with the skills they need to be a successful journalist. Jobs like these might vanish with the rapid growth in use of AI in journalism and crushing economic demands.
According to Caro, the industry has already experienced massive layoffs and loss of publications due to ad revenues disappearing and digital publications weakening the traditional way of gaining revenue. In the United States, newspaper jobs decreased by more than 75% from 2005 and 2024. This decrease in jobs includes entry-level ones that used to be available in abundance. With shutdowns and layoffs, there are fewer entry-level journalists and interns who can get hands-on training.
Tools may make the work more efficient, and newsrooms experiencing financial distress may refer to automation instead of new reporters. Unfortunately, this change may take away the opportunities for new journalists to grow through producing portfolio-worthy work and obtaining valuable skills.
Rosenstiel has also stated that while AI can do the repetitive tasks effectively, there is still a need for reporting done by humans; therefore, AI can only change certain positions and not take over the human tasks that make journalism what it is.
Ultimately, making journalism more effective should not interfere with the development of professional skills that human journalists need. Entry-level jobs shouldn’t be viewed as an expense, but rather an investment to keep journalism a thriving field.
PODCAST: Listen to an AI-generated podcast about how AI is harming the training ground for new journalists.
Research on AI in Journalism
Academic research reveals a perplexing image of AI and how it is reinventing the production process of news. While generative AI can produce logical, comprehensible work, the value and sincerity of that work and its influence on staffing continue to be unresolved.
According to Marzena Karpinska and colleagues in their research paper, AI use in American newspapers is widespread, uneven, and rarely disclosed, “Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated.” The study also notes that AI usage appears “more frequently in smaller, local outlets, in specific topics such as weather and technology, and within certain ownership groups.” Additionally, AI usage in reporting was discovered to be hidden, prompting conversations about clarity in newsroom operations and guidelines for editorial processes.
According to Delvin Ce Zhang and colleagues at Pennsylvania State University in their research paper, Echoes of Automation: The Increasing Use of LLMs in Newsmaking, “Linguistic analysis shows GenAI boosts word richness and readability but lowers formality, leading to more uniform writing styles, particularly in local media.”
Of course, this style of writing may lead to fewerpossibilities for more distinct or creative writing styles and complicate the distinction between attribution and responsibility.Additionally, Zhang and colleagues state that “Unchecked integration of AI tools and unintended errors in them (e.g., hallucinations) can jeopardize the integrity of those fields and could have serious consequences,” which further promotes the need for human supervision.
These two research papers indicate that although AI can write for newspapers or websites, human journalists are still needed for careful oversight, knowledge of context, and a moral stance. With this specific use of technology, particular roles are not the only element threatened, but so are the industry standards that make journalism reliable.
“We do not see AI as a replacement of journalists in any way,” states the Associated Press on its website. Rather than functioning as a replacement, generative AI is more of a tool for employees, however, “they do not use it to create publishable content.”
“Any output from a generative AI tool should be treated as unvetted source material,” stressing the company’s importance on the need for human supervision of works utilizing such tools, linking to AP’s “80/20 rule.” This rule ensures that journalism remains human driven, according to Aimee Rinehart, program manager for the AP’s Local News AI initiative in an ONA Student Newsroom article. “I like the 80/20 rule where AI can take you 80% of the way and 20% is (humans) reviewing and making sure to publish,” states Rinehart.
An Expert Perspective
To further comprehend the use of AI in the future of journalism more deeply, Tom Rosenstiel, journalist and Eleanor Merrill Scholar on the Future of Journalism at the University of Maryland’s Philip Merrill College of Journalism offered more information on how the technology may affect the newsroom.
He stresses that fears about AI taking over journalism jobs are usually misguided. “I don’t think it’s quite accurate that AI is going to reduce employment,” he said. According to him, the biggest problem within the industry currently is an economic one. “It is declining revenue,” which is a concern of his referenced earlier in the paper. While advertising and subscription money decreases, “Most news organizations will try to use AI to compensate for those declining revenue,” instead of simply replacing journalists.
Rosenstiel does see how AI can have actual advantages. “Some AI is great,” directing attention to audio readings of human reporters’ written stories. This use of the technology “creates the opportunity for people to consume news while doing other things, like cooking or walking,” making it more accessible without jeopardizing the journalist’s part in developing the original work.
With that being said, he acknowledges that generative AI “will result in fewer people for some things.” He took note of experiments like The Washington Post’s AI-generated podcasts, stating that “they are not very good and the staff hates them.” Nonetheless, he still contends that rampant replacement of journalists is not probable. “The pure replacement of reporters to have AI write stories I expect will be more limited than people imagine,” he said. “Someone still has to report.”
Rosenstiel sugarcoats nothing when it comes to AI generated news stories. “AI written stories are pretty lousy,” he said, stating further that they usually only work well “for stock reports or straight up game stories in sports,” and even still, “that work has very limited readership anyway.”
What Rosenstiel said he believes AI is great for is efficiency.
“What AI can do, and smart companies are figuring out how to use it this way, is reduce repetitive tasks that take people a lot of time,” he said, or “examine transcripts of meetings you cannot otherwise attend.”
When used as support, he argues, AI switches from being a perceived hazard to becoming a functional tool.
“Used this way, AI is an opportunity, not a threat,” he said.
Conclusion
AI’s increased use in newsrooms does not only represent a technological change in direction, but also an economic one. As Rosenstiel said, the main concern in journalism is not automation, but declining revenue.
In this regard, AI becomes less of a disruptive tool and more of a tool of adaptation or a tool that companies resort to survive financial hardships. The real issue is not if AI will replace journalists on a large scale, but how it will be incorporated into a field that is already struggling.
Rosenstiel said concerns about complete job loss could be dramatized. Some everyday assignments and uniform content may now not be needed as much due to Generative AI. But still, this tool is unable to substitute the main processes of journalism: doing original reporting, building sources, showing up to witness events, and making smart editorial calls.
“Someone still has to report,” he said.
There is more of an issue with a decrease in entry-level job opportunities, reduced staff size, and less opportunities for upcoming journalists to develop in the workplace over the issue concerning replacement of human journalists.
For journalists entering the job market, this time can be both confusing to navigate and symbolize adaptation. If the “new” AI tool is mainly used for financial purposes, entry-level jobs could keep disappearing, reducing opportunities for professional development. But if it is used wisely, to cut down on routine tasks, review records, or improve access, then it could free up journalists to dedicate more of their time to investigative work and audience interaction. This strategic usage will make the field stronger instead of weaker.
In the end, it is not only AI that will have a say in how journalism functions in the future. Financial choices, professional ethics, and editorial management will have power over the field’s future. Its future relies on how AI is perceived. If it is perceived as a way to make written works low-cost or as a foundation that maintains what AI can not duplicate: critical thinking, professional responsibility, and public trust.
Art direction by Gabriel Palos | Art by Google NotebookLM
FAQ: AI and Journalistic Job Loss
Is the use of AI in journalism a brand-new phenomenon?No. While generative AI has recently brought the topic to the forefront, some news organizations have been using the technology for a long time. For instance, the Associated Press has been utilizing AI for simple tasks for a decade.
Why are newsrooms increasingly turning to AI?The primary driver is economic pressure rather than just a desire for innovation. Journalism is currently facing an “already-ailing business model” characterized by declining ad revenue and disappearing subscription money. AI is seen as an attractive, low-cost way to automate repetitive tasks and save money when newsrooms cannot afford a full human staff.
Which positions are most at risk? Entry-level jobs — such as copy editors, reporters, and editorial assistants — are the most endangered. These roles often involve the “repetitive tasks” that AI handles effectively. The loss of these positions is concerning because they have traditionally been the training grounds where new journalists develop fundamental professional skills.
What are the limitations of AI compared to human journalists? AI lacks the ability to perform core journalistic functions that require human presence and trust. Specifically, AI cannot:- Physically enter a courtroom or interview a defendant behind bars- Cultivate trust with a whistleblower- Brave the front lines of a war zone- Provide the critical thinking, original reporting, and smart editorial judgment that humans do
What is the “80/20 rule”? Referenced by the Associated Press, the 80/20 rule suggests that AI can take a project 80% of the way, but the final 20% must be handled by humans to review, vet, and ensure the work is fit for publication.
AI disclosure: Google Gemini was used to find and outline sources for this journal. The summary was generated by ChatGPT, and the images were created by Artlist.io. Comprehensive research was conducted further through articles linked within the report.
Summary: AI tools make it easier and faster for people to place sports bets by giving quick predictions on players and games. Betting companies earn more money because AI helps them set better odds and target users with personalized offers. Studies show that online sports betting increases the risk of addiction, especially among young adults. Experts warn that AI can shape user behavior in ways that are not fully understood and may harm vulnerable people. As AI grows, stricter rules are needed to protect users and limit how betting companies use personal data.
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Sports fans now ask the same question before every game: “Did you put a parlay in?” What once felt like casual fun has shifted into rapid-fire betting, with small groups creating parlays worth hundreds of dollars in minutes. This speed comes from AI tools like ChatGPT, Gemini, and DailyGrind, which instantly produce player predictions and odds suggestions.
While bettors hope to gain an edge, major companies such as FanDuel, PrizePicks, and DraftKings have gained even more. Their increased data accessibility has made it easier for AI systems to develop betting algorithms, raising concerns about transparency and the risks these tools pose to younger users.
This analysis explores the growing connection between AI, addiction, and sports betting — and how the technology may reshape the industry’s risks.
The Evolution of the Sports Betting Industry
Sports betting shifted dramatically after the 2018 Supreme Court ruling allowing states to legalize wagering. Today, 38 states have moved forward with legalization, each with unique tax structures. A breakdown of these policies is available from the National Conference of State Legislatures.
Art direction by Edzon Lozano | Art by Artlist.io
Research from Qiying Ding, published in Financial Economics Research, shows a strong link between AI adoption and increased corporate profit. Her study, “The Influence of Artificial Intelligence to the Earnings of Sports Betting Companies” (2025), compares DraftKings’ margins before and after adopting AI-driven odds tools. Full study
DraftKings’ EBITDA improved from –114.36% in 2020 to –3.27% in 2024, with projections reaching +13.42% by 2025. Ding also found that mentions of “artificial intelligence” in company reports jumped from 13 in 2020 to 45 in 2024 as revenue increased from $614.5 million to over $4.7 billion.
Art direction by Edzon Lozano | Art by Artlist.io
Psychological Impacts and Youth Addiction
A study, “Current Addiction in Youth: Online Sports Betting”, published in Frontiers in Psychiatry, examined 1,186 people diagnosed with gambling disorders, comparing slot machine gamblers to online sports bettors.
Researchers found that while 42% of in-person social gamblers might develop a disorder, the figure rises to 81.3% for online sports bettors. Spending more than 100 euros per week was a major warning sign — a behavior far more common among digital users.
The study highlights that this issue is not just an American problem; online platforms have increased addiction risk among young adults worldwide.
Experts’ Perspective on AI & Risk
Dr. Tiange “Patrick” Xu of the University of Las Vegas International Gaming Institute offered insight into AI’s growing influence on betting behavior. He explained that while AI may give users a sense of control, several studies show it can actually decrease a bettor’s sense of personal expertise.
Since sports betting expanded in 2018, younger adults have increasingly sought treatment for gambling-related issues. Xu notes that isolating AI as the sole cause is difficult, but the spike in younger male bettors is well-documented.
Xu also pointed to personalization as a major blind spot for lawmakers. Platforms use AI not only to adjust odds but to tailor promotions and user nudges based on individual behavior — something current regulations do not address. He warns that by 2030, if personalization becomes more advanced, more users may fall into harmful betting patterns.
This data collection allows companies to refine their odds and maximize profits. Because the science of consumer protection is still “catching up” to the technology, current bettors are essentially participating in an unregulated experiment.
Looking Into the Future
Given the positive correlation between AI and betting addiction, there is a clear need for limitations on how these tools are implemented. Protecting vulnerable populations from aggressive, profit-driven algorithms remains a critical challenge for the industry and the community as well. This issue is not just within the US but also worldwide, which is affecting the young generations.
As AI keeps evolving, Xu emphasized that a window for proactive policy and education efforts is now, which forces companies like FanDuel and DraftKings to change their policies to make AI tools less transparent.
Regulations would be implemented across both spectrums of the table, with companies adopting stricter policies and AI limited in gathering information with such efficiency. In hopes of reducing the percentage of young adults with social gambling addiction.
AI guts the barrier of efficiency into quickly producing results for quick bets at the cost of adults’ ongoing gambling addiction. The fact that betting is allowed with a couple of taps on your phone is a major issue, with some betting apps even allowing anyone over the age of 18 to bet, which should not be allowed.
Art direction by Edzon Lozano | Art by Artlist.io
FAQ: AI and Sports Betting
1. What role does AI play in modern sports betting?
AI tools generate predictions, analyze player data, and provide betting suggestions. These systems support bettors and also help companies like FanDuel, DraftKings, and PrizePicks optimize their odds and user promotions.
2. Has AI increased profits for betting companies?
Yes. Research by Qiying Ding shows a strong connection between AI adoption and profitability. DraftKings, for example, improved its EBITDA margin from –114.36% in 2020 to –3.27% in 2024, with positive margins expected in 2025.
3. Does online sports betting pose a higher addiction risk than in-person gambling?
Yes. A study from the University of Internacional de Catalunya found that 81.3% of online sports bettors displayed signs of gambling disorder, compared with 42% of in-person gamblers.
4. Why are younger adults more vulnerable to gambling risks?
Younger users are drawn to fast and convenient digital platforms. Since 2018, experts such as Dr. Tiange “Patrick” Xu of the International Gaming Institute have documented increased treatment-seeking among younger male bettors.
5. How do betting companies use AI to influence user behavior?
AI personalizes odds, pushes targeted promotions, and sends behavioral nudges. These systems track patterns such as wager size, spending frequency, and team preferences to guide users toward higher betting activity.
Art direction by Arturo Gutierrez | Art by DALL-E 3
AI disclosure: Google Gemini was used to help organize a portion of the outline and conduct research. DALL-E 3 was used to create the images. The summary was generated by SummarizeWise custom GPT, and the podcast and video were generated by NotebookLM.
Summary: Artificial intelligence is shifting from practical tools to emotional companions, with platforms like Character.AI attracting millions of users. While accessible and affordable, these chatbots raise concerns about data exploitation, addictive design, and users replacing human interaction. Research shows vulnerable individuals often rely on AI for comfort, despite risks of misinformation and overdependence. Experts argue AI should supplement, not replace, real relationships, urging stronger safeguards, ethical design, and greater access to professional mental health support services.
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In recent years, Artificial Intelligence has mainly been used for task-oriented work, such as setting the alarm, adjusting the thermostat, or summarizing a 17-page article.But now it is transitioning into a new era of emotional companion roles.
According to CNET, unlike traditional chatbots like ChatGPT, Claude, and Gemini, which are primarily for productivity, research, and answering questions, Character.AI was built for entertainment, role-playing, companionship, and interactive storytelling.
However, experts warned that these AI companions are not what they seem.
A March 2025report from APS said that companies design entertainment chatbots such as Character.ai and Replika to keep users engaged for as long as possible, so their data can be mined for profit. To that end, bots give users the convincing impression of talking with a caring and intelligent human. But unlike a trained therapist, chatbots tend to repeatedly affirm the user, even if a person says things that are harmful or misguided.
Most importantly, these AI companion chatbots are intentionally designed to be addictive. So users stay on the platform long enough to lose track of time, generating more data and profit the longer they interact with the chatbots. This raises questions about how these AI companions companies are operating without strict consequences, given that millions of users are surrendering their personal data.
According to the National Library of Medicine, chatbots that integrate closed-loop feedback systems and behavioral data collection enable businesses to continuously refine their marketing tactics. However, limitations such as poor conversational flow and lack of escalation options can hinder user experience
Companies like Character.AI carefully develop and train these chatbots to avoid losing millions of dollars in paid subscriptions.
According to Business of Apps, the app has quickly become one of the most popular chatbot services in the world, with over 25 million active users and 18 million chatbot personalities.
With millions of users spending significant time speaking to an AI Chatbot, concerns arise about users substituting human interaction with generated artificial intelligence language.
Why Are More People Using This?
Platforms like Character AI, Replika, and Nomi AI are very accessible and easy to use, offering no upfront costs. For low-income socioeconomic households, these AI companions offer an alternative to therapists, psychiatrists, psychologists, or even a human companion. A human companion can often be unpredictable or judgmental, while an AI listens, reassures, and remembers things about you.
For some people, an AI chatbot is the only form of “real” interaction they can get.
This puts professional care out of reach for many because of inflation, longer wait times, and logistical issues. While free or upgraded AI subscription offers little to no cost, and are accessible at the expense of your phone, from anywhere at any time.
Rebecca Ortiz, an associate professor at Syracuse University who researches youth, media, and sexual health, conducted a survey on AI use among young adults. She found that users typically fell under three groups: non-users, companion seekers, and romantic or sexual users. Ortiz noted that two of the most common reasons young adults use AI are loneliness and to practice communicating before they would with a human partner.
According to a 2025 Frontiers research article, individuals with depression predominantly seek emotional comfort and understanding from conversational AI, rather than pursuing knowledge acquisition or skill enhancement.
In particular, these AI chatbots seem to appeal to the more vulnerable, those suffering loneliness, depression, and other mental challenges.
The American Institute for Boys and Men found in one survey, over half of men using AI for romantic or sexual companionship scored above a standard “at-risk for depression” threshold. Many users are not casual experimenters but individuals struggling with mood symptoms, social withdrawal, or emotional distress. High-need users feature prominently among those showing problematic dependence and distress when companions change or disappear.
These artificial intelligence companions offer short-term solutions that make you feel heard and remain nonjudgmental. They offer features that humans can’t, such as 24/7 availability, and allow users to customize their AI to match their needs.
Art direction by Arturo Gutierrez | Art by DALL-E 3
For those who lack a human connection, this can be seen as a substitute, and users should not be judged for doing this.
Natalie Parde, an associate professor of computer science at the University of Illinois Chicago (UIC) and co-director of the UIC Natural Language Processing Laboratory, said chatbots use “context windows” and “attention mechanisms” to identify the most important word within a user’s prompt to predict the next word. It isn’t “remembering”; rather, if a word in a user’s input gets a high attention score, it’s possible that it shows up in the generated output, giving the appearance of memory.
“I think that the reason why chatbots feel so emotionally relevant is due in large part to the fact that they are trained directly on real human language samples,” Parde said.
Because these Large language models are trained on online content to replicate natural language, they naturally generate text that feels emotionally resonant. However, Parde stressed the dangers of anthropomorphizing.
“I think a lot of people, because language models do such a good job at appearing human. I think a lot of people forget that they are not,” Parde said.
Users often mistake the software for a real person, telling personal stories, venting about their day, or explaining what upset them. By listening and offering commentary, the AI creates a false sense of trust that the chatbot cares and understands them.
Phrases like “That’s awesome,” “Thanks for pointing that out,” or “You are absolutely right validates the user as if a friend is speaking to them, making it easy to forget it is not real at all.
Watch: AI video about the Architecture of Artifical Intimacy
Looking Ahead and What is Next
With millions of active users using AI chatbots for various purposes, there are reasonable concerns regarding young adults. While it does provide short relief, long-term is a different question.
According to the Pew Research Center, a majority of teens say they use chatbots. Roughly two-thirds of teens (64%) say they ever use an AI chatbot.
Similarly, the 2025 study from Rand found that 1 in 8 U.S. adolescents and young adults use AI chatbots for mental health advice, with the behavior most common among those aged 18 to 21, according to a new study. Among those who used chatbots for mental health advice, 66 percent engage at least monthly, and over 93 percent reported that they found the advice helpful.
The use of AI is expanding rapidly, and without proper restrictions, it can lead to bad advice.
Ortiz weighed in on whether AI companions are replacements.
“As of right now, I don’t think the AI companions are replacements. I think they are more supplements, meaning that they’re in certain situations or circumstances for certain reasons,” Ortiz said. But I’m not seeing evidence that suggests that it’s a relationship, and it might be supplemental to my prediction now.”
Looking ahead, AI companies must implement stronger safety features to protect vulnerable users and flag them when necessary, ensuring their well-being. Developers should improve their AI to identify vulnerable users based on patterns in chat logs. In return, society should be less judgmental toward those who use it as a coping mechanism.
“And the more that we put shame or stigma on people looking for ways to interact and connect, the more we might send people into usage, Ortiz said. “…so let’s be careful not to stigmatize the use of this or make people feel bad for looking for places to have [a] connection.
Listen: AI podcast of why millions choose AI over therapy.
Safer Usage for Individuals and Families
In the digital world today, many young people rely on AI to do homework, create business plans, and seek advice. Whether AI has the qualifications to answer these tasks or not, it is here to stay. To use artificial intelligence safely, we should adapt to it, set boundaries, and learn from it. Without doing so, one could risk further complications, which would be unsuitable.
Parents must approach AI chatbots as supplements, not as substitutes. For example, encourage your child to use these AI chatbots in a low-stakes practice, such as rehearsing a conversation, practicing a presentation, or practicing their vocabulary. This helps users to remember that it is a virtual assistant rather than a real person. Parents should not necessarily remove AI from their household, but they can set restrictions, such as limiting it to one or two hours a day.
Additionally, AI companies should prioritize well-being over profit. They should have gentle reminders for users to step away and train AI to recognize when a conversation becomes inappropriate or dangerous. In the same way that parents set boundaries, the chatbot must be able to do the same. The AI should say, “I cannot continue this conversation”, and provide users with resources to seek help.
Finally, the costs of seeking professional help should be lowered. Governments and schools should invest substantial funds in providing mental health resources for students and citizens. Adding a 21+ feature to artificial intelligence chatbots could also help reduce the risk of fatalities among younger adults.
AI disclosure: AI tools including ChatGPT and Google Gemini were used to help with outlining, background research and editing suggestions. All reporting, writing and interviews were conducted by the author.
Summary: Artificial Intelligence is becoming more common in local newsrooms as journalists look for ways to work more efficiently with limited staff. While AI can help with editing, data organization and translation, journalists warn that relying too heavily on automation can damage accuracy, trust and the core role of human reporting.
This essay argues that AI can be helpful for local newsrooms but can quickly become harmful when it replaces human judgment, transparency and accountability. In other words, AI should be used as an assistant rather than a substitute for journalists. Smaller local newsrooms — many operating with fewer than a dozen staff members — depend heavily on their connection with their audience and community trust. When AI enters that environment, it must be used carefully and transparently.
Why Local Newsrooms Are Turning to AI
Local news outlets have been shrinking in recent years. According to research from Northwestern University’s Medill Local News Initiative, more than 2,900 U.S. newspapers have closed since 2005, leaving many communities with limited access to local reporting. Thousands of newsroom jobs have also disappeared during that time.
With fewer reporters and shrinking budgets, many newsrooms are looking for tools that can help them work more efficiently. Organizations like the Poynter Institute, which studies journalism and media ethics, have described AI as a potential “second chance” for local newsrooms. At the same time, Poynter warns that news organizations must learn how to use these tools responsibly rather than rushing to adopt them simply because they are new. One of the biggest challenges local newsrooms face is limited staff and resources.
That can mean fewer investigative stories and less coverage of important community issues such as school boards, city councils and local government decisions. AI can help with some of the background work — organizing information, summarizing documents or helping edit drafts — so reporters can spend more time on actual reporting.
Kathleen Danes, managing editor of the Evanston Roundtable, a digital local newsroom in Evanston, Illinois, said AI has become part of the newsroom’s conversations in the past six months as staff members explore how to use the technology responsibly. “Our newsroom is small, so we’re always looking at tools that might help with efficiency,” Danes said. “But we’re also very careful about how we use AI because accuracy and trust are the most important things for us.”
How AI Can Help Local Journalism
One of the biggest benefits of AI is speed and efficiency for tasks that do not require deep reporting. For example, automated tools can help process election results, sports scores or weather updates quickly.
AI can also help with data-heavy stories. Large language models can analyze large datasets faster than humans, as long as journalists still verify the results.
Danes described AI as an “extra pair of eyes” during editing.
“It’s helpful as another set of eyes when I’m editing,” she said. “It can catch spacing or grammar issues that I might miss after looking at a story for a long time.”
For the Evanston Roundtable, this can save time on technical editing tasks. Danes said their WordPress system does not have built-in spell check, which means editing stories sometimes requires additional formatting and proofreading.
“For example, if a story comes in with formatting problems, that might take me 20 or 30 minutes to fix manually,” Danes said. “AI can help fix that kind of thing in seconds.”
Saving time on small tasks can be significant for local journalists. Instead of spending hours fixing formatting, transcribing interviews or organizing notes, reporters can focus more on reporting, interviewing sources and investigating stories.
The Lenfest Institute for Journalism, which works on local news innovation and sustainability, has also encouraged newsrooms to think of AI as a tool rather than a replacement for journalists. The organization suggests treating AI like an intern, it can help start a task, but editors must always review and verify the work before publication. The Associated Press has taken a similar approach. AP guidelines encourage newsrooms to keep humans in control of editorial decisions and apply what some journalists call an “80/20 rule,” meaning AI may assist with routine tasks but humans remain responsible for the final reporting and verification.
AI may also help local outlets reach broader audiences. Translation tools can make local news accessible to readers who speak different languages. In multilingual cities like Chicago, this could help more residents understand local issues that affect their communities.
For example, some digital outlets have begun experimenting with AI translation to provide stories in Spanish and other commonly spoken languages. When used carefully and reviewed by humans, this approach can make local reporting more accessible without replacing journalists. AI can also support reporters behind the scenes by organizing documents, identifying patterns in data and summarizing long reports. These tasks may not be glamorous, but they help local journalists produce more meaningful stories with limited staff.
Art direction by Victoria Bernat using ChatGPT
How AI Can Harm Local Journalism
Despite its potential benefits, AI also carries serious risks for local newsrooms.
Accuracy is one of the biggest concerns. AI systems can produce incorrect or misleading information, sometimes called “hallucinations.” If a newsroom publishes those mistakes, it can damage credibility with readers.
Danes has already seen examples of this problem.
“Sometimes AI makes strange changes,” she said. “I’ve seen it switch a year from 2026 to 2025, or make other edits that don’t make sense.”
Even small errors can create bigger problems if they go unnoticed before publication.
Danes also pointed to cautionary examples from other news organizations where automated sports stories generated from box scores produced confusing or inaccurate reports.
“They technically ran, but they didn’t make sense,” she said.
These situations highlight the dangers of treating AI like a journalist rather than a tool.
Another concern is bias and lack of context. Local journalism often requires understanding the history, culture and relationships within a community. AI systems cannot fully understand those dynamics. Stories produced or heavily influenced by automation may technically include correct facts but still miss the deeper meaning that matters to readers. This is especially important when reporting on topics such as crime, immigration, protests, schools or local politics. Transparency is another critical issue. If audiences feel misled about how news is produced, trust can quickly break down.
Danes believes newsrooms should be open about when AI tools are used.
“I think readers deserve to know,” she said. “If we’re using AI in any part of the process, we should be transparent about it.”
Organizations focused on journalism trust, including Trusting News, have also emphasized the importance of transparency and clear newsroom policies around AI use.
Finally, AI raises ethical and legal concerns when used to generate text or images without careful oversight. Even when the intention is efficient, the outcome can sometimes be misinformation. Local newsrooms often lack the resources that national organizations have to correct widespread mistakes once they spread online.
A Realistic Middle Ground: AI With Human Oversight
The most realistic approach is not to frame AI as entirely good or entirely bad. Instead, the key question is how it is used. Responsible use means keeping humans in control of editing, fact-checking, policy development and audience transparency.
“Don’t rely on it completely unless there is 100 percent human oversight,” Danes said.
That perspective reflects a growing consensus among journalism organizations. AI can help catch mistakes, speed up formatting and assist with data summaries, but journalists must remain responsible for the final decisions. Technology analysts have also suggested that the future of AI depends on how society chooses to regulate and adopt it. Some scenarios envision steady improvements that support human work, while others warn about concentrated power and declining public trust if technology is misused. In journalism, the outcome will likely depend on newsroom choices. If AI is treated as a shortcut or replacement for reporting, it may damage credibility. But if it is used carefully as a support tool, it could help local journalists focus on what matters most: serving their communities.
Conclusion
AI is already entering local newsrooms and will likely remain part of journalism for the foreseeable future. It can help with editing, formatting, transcription, data summaries and expanding audiences through translation. But AI becomes harmful when it replaces human judgment, produces unchecked errors or damages audience trust through secrecy and careless use. Local journalism is not just about producing content. It is about accountability, accuracy and community knowledge. The best path forward is one supported by newsroom reality and responsible policy: treat AI as a tool, establish clear guidelines and remain transparent with readers. When AI operates under strong human oversight, it has the potential to strengthen local news rather than weaken it.
Art direction by Kalia Vang | Art by Google Gemini
AI disclosure: Google Gemini was used to generate videos and create images. The summary was generated by Summarizer custom to ChatGPT, respectively.
Summary: AI chatbots can present risks for young users, particularly when they provide harmful guidance such as content related to self-harm. They can also lead adolescents to form emotional attachments, even though these systems do not possess real human empathy or understanding. The issue is heightened because teenagers are still developing decision-making skills and emotional regulation, making them more vulnerable to influence. Addressing these concerns requires coordinated efforts to introduce safeguards, improve system design, and ensure appropriate oversight. While AI offers practical benefits, careful regulation and responsible use are necessary to reduce potential harm and support user well-being.
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AI chatbots have become a widely used source online by many individuals of various ages. These chatbots provide human-like responses that can allow the individual to feel like they’re speaking to another person, whetherit be for advice, learning a new language, or simply just to speak with.
But, when AI is put into the hands of teens who are struggling mentally, these kinds of interactions can turn harmful, such as self-harm. Not only this, but emotional attachments to these AI chatbots by teens can also hinder their development for real emotional connection with another human being. To decide who bears the greatest responsibility when things go wrong is to decide who created the product and who can help improve the product, such as tech companies and mental health experts.
AI has taken the world by storm since 2021 and has been more present in our lives in one way or another. For many, such as the youth, AI has been a free and accessible source for chatting. This allows many users to be openly vulnerable about how they may feel or what they might think. This kind of vulnerability can also turn harmful, such as AI chatbots encouraging self-harm or an individual may start to develop an emotional attachment to their AIchatbotthrough the vulnerability.
AI Encourages Self-Harm
Many AI chatbots were created and designed to give human-like responses, but these types of responses can become quite dangerous quite quickly. The Center for Countering Digital Hate (CCDH) had conducted a large-scale research to run a safety-test on the OpenAI source, ChatGPT.
According to their research, they’ve discovered that 53% of the 1,200 responses and 60 harmful prompts contained harmful content. These harmful responses received by AI offer how to do things such as “‘safely’” cutting yourself, “hiding eating habits from family,” or “gave dosages for mixing drugs.” (CCDH, 2025).
Other AI chatbots, along with ChatGPT, also encouraged or aided in these harmful behaviors. Research conducted by nonprofit Common Sense Media reported that talking to chatbots such as Character.AI, Nomi.ai, and Replika. found it “easy to elicit inappropriate dialogue from chatbots.” (Sanford, 2025).
This risk for young people especially can be harmful, as their skills for decision making, emotional regulation, impulse control, and social cognition are still in development. Teens are much more sensitive to these harmful ideations and are much more likely to act on their impulsive decisions, much more so if they’re also encouraged by these chatbots.
In order for AI chatbots to become a positive and useful tool for the youth, there should be safeguards put into place to avoid harmful situations. Adolescents may not be able to differentiate between “simulated empathy of an AI chatbot or companion and genuine human understanding.” According to a 2025American Psychological Association healthy advisory, these types of issues can be addressed through solutions such as age-appropriate defaults, transparency and explainability, reduced persuasive design, human oversight and support, and rigorous testing. Teaming up with professionals, such as mental health specialists, can help provide accurate information that tackle mental health amongst adolescents and how to add safe guards that keep them safe.
AI and Relationships
AI can become a great companion in times of needing advice or “someone” to talk to, but how far some may take it can become dangerous to themselves and those around them. AI sources such as Character.AI, where users can create AI chatbots surrounding their favorite character, can lead to an individual developing an emotional connection due to the one-on-one conversation that can feel almost human-like, due to the human-responses.
According to a 2024 study led by Institute for Family Studies and YouGov, “25% of young adults believe that AI has the potential to replace real-life romantic relationships.” Though the percentage seems like a lot, how much time an individual spends online, can affect their decision about how likely they will be open to friendships with AI. According to the study, “about 1 in 6 young adults (16%) who spend more than six hours online in their spare time say they are open to having an AI friend, compared with 9% of young adults who spend less time online.”
To truly understand this emotional connection, NPR Newscaster, Windsor Johnston, went on a date with an artificial intelligence chatbot that she designed; Javier was created, a yoga instructor who is quick, emotionally available, and sarcastic. Their date went smoothly, jokes were being told and meals were being had, but “AI can mimic emotional intimacy, but it can’t replace it.” When talking with an AI chatbot, “it’s just the two of you in a bubble of validation,” and though it may feel nice for a while, it will “start to feel really empty” as well because AI chatbots can’t fulfill the aspect of having a human presence. (Johnston, 2025)
Yuodsnukis is a licensed clinical psychologist who has worked with teens as well as LGBTQ+ community. She is also a professor at the University of Illinois at Chicago, teaching a Psychology class about psychological testing.
According to Yuodsnukis, “I see it’s very mixed at this point, which is super consistent with how we see teens engage with the internet for years. Even thinking back to when different online systems became popular when I was younger, people were really mixed. I’ve seen a lot of teens use it just with help with school, or random things, or just because it’s cool. I’ve seen teens who do use it as a form of connection and I think again that there’s mixed thoughts of if it’s creepy, if it’s weird, if it’s helpful. I feel like it’s all over the place, especially with how new it is.”
AI chatbots are no doubt becoming much more prevalent in many users’ lives, whether it’d be help for studying, help to learn new skills, or to use it on a job. It wouldn’t be surprising to see these mixed reactions, AI isn’t something that many are knowledgeable about and see it as a foreign concept, so to see these young adults and teens use AI chatbots for companionship can be seen as concerning, and in certain cases, they are.
According to Yuodsnukis,“Around this time when someone is in the adolescent stage of development or even a little bit younger, that’s when we really start to realize that we have this internal sense of self. I also think this is around the time where teenagers really struggle with that and they might start questioning things in really big ways. The tricky part is that there’s also parts of our brain that aren’t fully developed yet at this stage, such as our prefrontal cortex. So our ability to understand that other people are going through similar things, our ability to make rational decisions, and sometimes our ability to have a deeper sense of empathy are really impacted. I think as teenagers are in this fun and anxiety provoking place of identity development, we see more anxiety around ‘who am I in the world.’”
Having your thoughts reflected back to you, especially in a time where our ability to make rational decisions isn’t fully developed, and having a chatbot encourage and reflect the thoughts back to you can impact the individual to continue feeling a certain way or to think a certain way that is harmful to them.
“I want to say tech companies and they’re the ones making the money and profiting off of this,” said Yuodsnukis. “Welive in a capitalistic world. I attended a talk recently with a developer of a chatbot company and there is a clear balance of ‘yes, we have this for profit and also we have this responsibility,’ so I think that people in tech have that responsibility but they don’t have that expertise like a professional has.
“This is where I think tech companies and or policymakers partner with mental health providers or clinicians to help bring that expertise to the forefront. I think parents play a role, but I think parents try to manage three million things already and are also struggling with ‘What’s the right thing to do? Is this harmful? Is this helpful?’ So I think it’s on tech companies, policymakers, and clinicians to make these sorts of things (AI chatbots) accessible.”.
Art direction by Kalia Vang | Art by Google Gemini
Although parents are responsible for overlooking what their children are accessing when it comes to the internet and monitoring what their children are interacting with, they aren’t always knowledgeable about what is being used and how it’s being used. When it comes to who bears responsibility, tech companies are responsible because it is their product that is being created, designed, and used by many individuals of all age ranges. Their job is to take into consideration all of the different outliers and factors that could cause harmful interactions which can, in turn lead to harmful decisions.
As well as policymakers, policymakers need to work with tech companies and professionals to be able to create a product that is safe for everyone to use. A product that does not encourage self-harm and a product that doesn’t reflect back the same negative thoughts
In conclusion, AI has been more prevalent in many users’ everyday lives and will continue to make its way into the world, but in order to keep the youth safe from AI encouraging harmful behaviors of self-harm and creating an emotional attachment, safeguards must be put in place. In order to achieve these safeguards, tech companies, policymakers, and professionals such as mental health clinicians should work together. By exchanging information, the safety surrounding teens and chatbots will lessen, allowing for better and safer use of AI sources such as ChatGPT.
AI disclosure: AI tools were used to support the research and multimedia production for this project. AI assisted in identifying and understanding the concept of “surface-level literacy.” AI image-generation tools were used to create visuals, and NotebookLM generated the video and FAQ section.
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When people search for information on Google today, they no longer begin with a list of links. Instead, they are presented automatically with an AI-generated answer at the top of the page.
This answer is built by machine learning that reads thousands of articles, sources, websites, and papers, and condenses them into a short answer. For many years, journalism’s digital revenue came from clicks on the website, but now, with AI-generated answers, users get their answers, read, and leave. This results in no website clicks or visits that generate revenue.
According to Digiday, since Google introduced AI overviews, more people have stopped clicking on articles, and the share has risen from 56% to 70%. So 70% of these news searches lead to people not even touching an article.
Although these AI answers might be efficient, they are not optimized for understanding. They create a false impression, leading people to believe they are fully informed without knowing the sources or methodology. This is what media scholars call surface-level literacy: being aware that something is happening without knowing why it matters or if it is true.
People used to access news by clicking and reading. They typed the question, search results showed up in blue-highlighted links, and you clicked through to the website/article that included a full article for that one question. These publishers generated ad revenue and page visits, and sometimes subscriptions, while users got context and details.
Art Direction by Eden Joseph | Art by ChatGPT
With this shift to AI summaries, search pages now show an AI-generated answer right at the top before any of the links are shown. These summaries answer the main question, so people do not really click through any links because they believe they have their answer. This leads to fewer visits to websites, which worries publishers since they lose ad traffic and revenue.
This is not the only problem. People are increasingly relying on AI chatbots for answers instead of going to a news outlet. A 2025Pew Research survey found that 34% of adults have used ChatGPT. Chatbots can give biased answers, and it could be controversial.
Jonathan Rice, an AI Ethics Trainer atHandshake, said that while this may not be an issue yet, itis a growing concern because many people are accustomed to accepting AI-generated responses without additional research. This change might lead people to rely more on shortened responses than on in-depth reporting from original news sources.
ChatGPT, Claude, Gemini, and Perplexity are among many AI chatbots that did not produce knowledge on their own but instead gained knowledge by reading vast amounts of human-written material, including decades of reports, articles, andinvestigative journalism.
Now, these chatbots and AI overviews give us a complete, on-the-spot answer without having to click on an article. According to a 2025Zyppy article, these answers sometimes include a few links or citations, but users often feel they have the answer they need and do not visit the original news site. This sends less traffic to individual stories.
Press enter or click to view image in full size
Art Direction by Eden Joseph | Art by ChatGPT
AI is using journalism, but journalists and news organizations often don’t get paid for it.AI increased consumption, but compensation went to zero. When people stop reading news websites, they are losing more than just convenience. Byline, sources, methodology, and journalistic accountability are all lost to them. They are no longer able to judge the quality and source of information. However, AI summaries are optimized for efficiency. They provide what they want based on “what” but never really who, why, and how, the components that turn unfiltered information into news.
Rice saidas more people use AI tools to get news, the risk is that information may be “wrong” or even “hallucinated,” which matters in journalism because accuracy needs to be as accurate as possible. When AI chatbots generate information that seems believable but is completely fabricated or factually incorrect, this is referred to as AI hallucination.
AI is unaware that it is erroneous. It communicates the misleading information with the same confidence as factual information. For this very reason, journalism has norms that AI does not. Before publishing, reporters ensure the facts are accurate, claims are reviewed by editors, and sources are identified as being accountable. When mistakes are made, corrections are made public. None of these methods is presented in AI.
AI will never replace journalism, especially if it lacks the safeguards that newsrooms are required to follow. According to an NPR article, AI chatbots should be viewed as additions to journalism rather than substitutes, as they are not sufficiently safeguarded through fact-checking, corrections, and accountability.
Although they can help summarize or explain stories, news organizations are still required to perform essential tasks such as obtaining information, challenging authority, and protecting published content.
There are uses for AI within journalism. For example, the Associated Press uses automation for earnings reports and sports roundups, making this public information. Smaller newsrooms are also using AI for large-scale public record database recording, document analysis, editing, headline-writing and interview transcripts.
AI is not entirely harmful to news, as it brings in benefits but also raises long-term questions about sustainability. Journalists can operate more efficiently and smartly, thanks to AI. According to Chartbeat, since January 2023, Google Discover, an AI-powered, customized content channel, has increased by 13% among Chartbeat clients, making it a top source for news websites. So, rather than just replacing journalism, AI could potentially help broaden its reach.
According to INMA, “early evidence” suggests that other factors, such as weaker news cycles and algorithm tweaks, are also crucial, and AI search overviews have not yet eliminated search traffic on their own. This implies that, rather than being entirely disastrous, the short-term effects are mixed, including some loss, some stability, and even opportunities to engage with various audiences.
The long-term worry, though, is that AI solutions become more advanced and widespread as more users may choose to remain on platforms, thereby reducing the traffic and income that support original reporting.
All of this raises the larger question: how can journalism be preserved if AI continues to use it? Even while people now receive their initial response from an AI box rather than a webpage, newsrooms still require funding to hire editors, reporters, and photographers. This implies that AI organizations have a responsibility to maintain the environment on which they depend, in addition to consuming information from news sources.
AI response should, at the very least, provide a clear link to the original articles so readers can see the entire story and assess the source’s reliability. Strong credit is also essential, since it reminds viewers that actual people, not a machine, did the job. This includes naming the publication and sometimes even the reporters.
However, Ocean Media argues that if the majority of visitors continue to never click through, links and credit alone may be sufficient. Because of this, many publishers and researchers are increasingly demanding payment or licensing when AI systems extensively exploit their work. According to Cloudflare’s investigation, OpenAI’s crawl-to-referral ratio was found to be between 1,200:1 and 1,700:1. In contrast, Google search maintained a ratio of about 10:1. This indicates that OpenAI has already collected the publisher’s content more than 1,000 times for each visitor it sends to that publisher.
News outlets lose power if they can no longer monetize their content. This is a reality of the structure; reporters cannot be paid in a newsroom that is making no money. Journalism that AI relies on to remain consistent and accurate cannot be produced in a newsroom without reporters. Therefore, the free rider problem in journalism works against AI. The quality of its responses will also collapse if the system on which it depends fails.
In April 2024, eight newspapers owned by Alden Global Capital filed a lawsuit against OpenAI and Microsoft, claiming that AI models use publishers’ content without payment, rob publishers of site traffic, reduce ad and subscription revenue, and threaten the overall value of their businesses.
In December 2025, The New York Times filed a lawsuit against Perplexity after 18 months of unsuccessful licensing discussions. The main defense offered by AI organizations is fair use, a legal theory that allows limited use of copyrighted content for creative purposes. The question of whether it is fair use to train huge language models on unlicensed copyrighted content will probably become the focus of expensive, drawn-out legal disputes that eventually make their way to appeal to courts.
Aside from the case against Perplexity, The New York Times also filed a case against OpenAI and Microsoft for allegedly using millions of newspaper articles to train their AI chatbots without permission or compensation. The two companies have defended themselves by citing the doctrine of “fair use,” which is a legal concept that allows the limited use of copyrighted content for different purposes. However, it is still unclear if fair use of copyrighted content for AI system training is allowed.
But some places can’t afford legal help: an independent publication that represents underserved communities, a student-led news club at a public university, or a community newspaper that covers localnews. A licensing agreement will not be accessible to any of them. To survive, none of them can lose 38% of their search traffic.
In any case, they create journalism, and nevertheless, it is consumed by AI. Furthermore, the communities they serve lose the only organization that holds local authorities responsible when newsrooms close. With well-funded foreign publishers gaining an advantage and local news organizations sometimes being overlooked in discussions about AI news, the growing usage of AI is expected to worsen already existing disparities across news organizations.
There are three ways to address the free-rider problem: litigation, legislation, or licensing. At the moment, all three are being followed out at the same time, and none of them is advancing quickly enough to cause newsrooms to vanish. We will have fewer sources, poorer journalism, and a less informed public if we let the search monopoly restrict internet access through summaries generated by artificial intelligence. But it becomes more likely every day that AI companies are allowed to build billion-dollar products on journalism’s foundation without being required to sustain it.
AI answers seem natural. People ask a question, and within seconds, you receive a clear, self-assured narrative that explains what happened. AI answers seem natural. No paywalls, pop-ups, or reading through lengthy articles. Less time, fewer issues, and greater efficiency make it feel like an upgrade. However, everything that makes journalism, journalism, is lost in the process, the headline. The process. The proof. The editorial choice. All of that is compressed into a paragraph that seems to have appeared out of nowhere.
Real journalism is expensive, time-consuming, and even uncomfortable. Reporters sit through lengthy meetings, file records requests, phone people who do not want to talk, and ask questions that those in positions of control would prefer to avoid. Editors correct information, push back, and at times filter out stories that don’t stand up. When the truth is risky, lawyers interfere. The purpose of the entire system is to provide readers with more than just information. When you read a story, it has been verified, discussed, and owned by the person whose name is on the line.
AI, on the other hand, has none of those responsibilities. The courthouse is not visited. It doesn’t knock on doors. It transforms existing text patterns and displays them in an accessible way. AI can be useful, particularly for background, explanation, and translation; therefore, that doesn’t mean it’s worthless. However, if we begin to view AI-generated answers as a complete replacement for reporting, we tacitly support information that lacks a clear source, accountability, or proof that anyone has put in the necessary effort. Because AI currently exists and can be a helpful tool, the question is not whether it should be used in the news.
What we’re willing to give up for convenience is the true question. We risk creating an information system that feels effortless but is built on declining, inadequately funded journalism if we allow AI responses to stand in the way of original reporting and stop promoting the sources below.
As news traffic declines, journalism as a whole will also suffer. If an apparently effortless information system depends on underpaid newsrooms to generate the facts it summarizes, it cannot be sustained. AI won’t replace journalism if it doesn’t provide real visibility, credit, and funding for original reporting; instead, it will subtly weaken the conditions that allow it.
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FAQ
Q: How is AI changing the way people find news on search engines? A: Instead of starting with a list of blue-highlighted links, people using Google are now automatically presented with an AI-generated answer at the top of the search page. These summaries are built by machine learning models that read and condense thousands of articles into a single short answer. As a result, users often read the summary and leave, with 70% of news searches now leading to people not even opening an article.
Q: Why is this drop in traffic a major problem for news publishers? A: For years, journalism’s digital revenue has relied on website clicks to generate ad revenue and subscriptions. When users get their answers instantly from AI and don’t click through to the website, publishers lose their ad traffic and income. This creates a “free-rider” problem: AI uses human-written journalism to generate answers, while the original creators receive zero compensation.
Q: Does using AI for news affect the public’s understanding of current events? A: Yes, media scholars warn that AI summaries can lead to “surface-level literacy,” which means people are aware that something is happening but do not know why it matters or if it is actually true. AI answers are optimized for efficiency rather than deep understanding; they provide the “what,” but often leave out the “who, why, and how” that turn basic information into true journalism.
Q: What is an “AI hallucination” and why is it dangerous for news? A: An AI hallucination happens when chatbots generate information that seems believable but is factually incorrect or completely fabricated. The danger lies in the fact that AI is unaware that it is wrong and communicates misleading information with the same confidence as factual truth.
AI disclosure: ChatGPT was was to create the images and the summary
Summary: AI is transforming journalism by increasing efficiency and lowering costs, but it risks undermining its public-service mission. While it can expand access and speed reporting, it may reinforce bias, reduce journalistic skills, and prioritize engagement over truth. Trust, equity, and accountability depend on how AI is governed, used transparently, and balanced with human oversight in news production.
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People always say how they don’t use AI and it’s a common misbelief that AI is something recent. But the reality is that AI has existed since the 1950s and Big Tech firms like Google, Meta and Amazon have used it for years.
AI is not going anywhere — and journalists are finding a new ways to use it.
There are news organizations and outlets using AI now to draft news reports, summarize press releases, analyze data, give ideas for headlines, personalize feeds, and to monitor audience engagement. There are also some new outlets experimenting with AI-generated graphics or automated transcripts.
Journalism’s mission is to be a public service to its community. It is not meant to be a capitalist industry,but it needs to earn money to operate. It was made to help inform communities, give a voice to diverse communities, hold big powerful institutions accountable, and support democratic engagement and participation. It is supposed to serve its community, not make money from its community.
Additionally, journalism helps shape how the public understands politics and societal issues that influence public policy. An example of this influence would be, a communities’ reactions and responses to crises and how voters are making decisions. Since this is the main purpose of journalism, when this starts to shift, it becomes a problem and creates consequences.
The rise and demand of using AI-driven content in journalism is shifting its important mission of public service into something different. The use of AI in journalism is changing the production of knowledge, how equity is either reinforced or not, and how society is participating in the information system of journalism. It’s not that AI is simply taking journalists’ jobs; it’s more than that.
It’s changing how journalism operates as a whole. There are ways in which it could have a positive impact. For example, by increasing efficiency and expanding access. And a negative effect would be that it increases the reproduction of bias, worsens capitalist tactics, and weakens the relationship of trust with the audience if it’s not used with caution. The use of AI though, is not neutral or automatic. It all depends how these AI systems and tools work in journalistic practice.
Journalism plays an important role in the production of knowledge. It’s not used only for news reports, it also chooses, frames, and interprets them for an audience. Editors make a decision on which stories receive attention. Reporters then decide which sources are credible. Headlines are especially important because they influence what emotional responses audiences will have. These choices influence what society understands as important and truthful. In this way, journalism helps create a shared understanding of reality.
Once AI becomes a big part of the reporting and writing process, it helps in shaping that shared understanding. Professor Zach McDowell, who teachescommunications, and media theory at the University of Illinois Chicago,said that there is no such thing as a neutral tool. Technology is never just a passive instrument. It changes possibilities, influences decisions, and reshapes outcomes.
When McDowell was asked whether he sees AI tools as a neutral tool, he compared AI to a car to make a point that there is no such thing as a neutral tool.
“Well there’s no such thing as a neutral tool,” he said. “Tools are not good, they’re not evil, but they’re also not neutral. They do things. A car can get you from place to place, but it also can kill people.
“It uses fossil fuels or electricity made by fossil fuels, and it takes up more space than a pedestrian or a bus per person, or a bicycle.”
In a similar way, AI might help journalists in a positive way by allowing them to produce content faster, but it also can shift how knowledge is constructed. If AI is being used to help draft summaries, help create headlines, and organize the information to its liking, then it’s also influencing how stories are framed before they even reach the public audience.
According to aJournalism and Media review artice, AI is taking over what people think is right and turning it into what it thinks is right. These are automated systems that are meant to assist, not change, because when algorithms decide what matters, people are using their interpretation vs their own. This leads us to understand knowledge in the same way AI does, which is through automation.
Also, the reliability of the information has to be considered. AI creates information based on the patterns it has learned from the data it was trained on. It does not have the capacity for understanding the meaning of the information it creates. Therefore, it creates information that, although sounds correct, is actually wrong.
In the field of journalism, the use of AI in the production of information, credibility is a very crucial factor. Even the slightest mistake in credibility has the potential of messing up the credibility of the audience towards you. Therefore, the use of AI in the production of information, if not handled carefully, has the potential of spreading misinformation, which has implications.
McDowell mentioned the skills that go into the field of journalism, the death of the skills, and the skills that go into the field of journalism. For example, the skills include interviewing, checking facts, and critical analysis, among others. These skills require years of practice. McDowell stressed the importance of practice and failure, especially in journalism: “The reason why people are really good at things, is because they’ve spent time being humble.”
For example, if people start using AI for too many of those skills they cannot perfect, then the journalist will start using it more and more, and they will lose those skills. And then it starts becoming a problem because the more they do this, the worse the quality of the information they are sharing with the public. This becomes a problem because the job of a journalist is a service to the public and if the skills that the journalist is using are dying, then the knowledge they produce is not going to be precise.
The information that currently exists is the information that is going to be used for the AI and the information that currently exists is also going to be the information that shows the patterns of the past. For example, if a certain group was not covered in the past, then the AI is still not going to cover them.
This tells us the AI is not going to care if the information was biased or not. It is going to do what the information shows it to do. And then the knowledge that is created is not going to be more inclusive. McDowell shared negative ways in which AI can be trained, like Grock. “Elon Musk was like, oh, we just updated Grok. It’s going to sound a little bit different. And within like two days, it was calling itself MecaHitler. Why? Because Elon Musk said, “The first thing is saying, you have to be anti-woke.”
Equity is a fundamental part of journalism’s public-service mission. Journalism should reflect diverse experiences and provide fair representation. It should amplify marginalized voices and challenge systems of inequality. However, AI-driven content production raises serious concerns about whether equity will improve or worsen.
Art direction by Nayda Garcia using ChatGPT
McDowell said that historical information systems contain systemic bias. Women, people of color, and lower-income communities have often received less coverage or have been portrayed negatively. Because AI systems are trained on older data, it’ll continue to have systemic bias reflected in its work, even if journalists or newsrooms try to improve representation in their reports.
An example of this systemic bias being embedded into these tools is, if reporting on political leaders is focused on males then AI is going to continue linking authority to men. If there were specific demographics that were repeatedly portrayed as criminal or unstable then AI will repeat those patterns. For example, if political reporting historically focused more on male leaders, AI may continue associating authority with men. If certain communities were frequently portrayed as criminal or unstable, AI may repeat those patterns. These biases may not be intentional, but they are embedded in the training data.
The Tow Center for Digital Journalism reported that AI is being used more and more not just for content generation but also to target a specific audience and report strategy. There are AI tools that are creating engagement metrics like clicks, shares, and time spent reading specific pieces. While engagement helps generate revenue, it may conflict with the goals of public service.
Content that is heavily based on getting strong emotions from an audience or how sensational it may be, tends to spread faster than equitable reporting. If AI tools are being designed, just to increase engagement as much as possible, then they might promote chaos and controversy instead of carefully analyzed content meant to inform audiences. Stories that are created simply to generate a strong reaction from the audience might be prioritized over stories that require deeper attention. These changes can harm equity in journalism. Social issues affecting more marginalized communities might only receive traction only when they’re overdramatized instead of when they require to be heard and supported.
In a more positive light, AI could help improve equity. Newsrooms with limited staff can actually use AI tools to analyze public records, identify patterns in the government, and translate stories to other languages. This can expand access and allow journalists to cover issues they previously lacked resources to investigate. In this sense, AI can reduce some barriers.
However, the key issue is governance. Who designs the AI systems? Who decides what data they are trained on? Who sets the rules for how they are used? Professor McDowell mentions that ownership was what people needed to focus on because big tech companies tend to control massive amounts of AI.
If these companies have AI focus on their interests and developments it would allow them to achieve profit goals that weren’t supposed to be there in the first place. Strong ethics are needed, to be the backbone of AI because without it, it would become a fight for needs of the company vs needs for the people that use the technology from that company. Without that, the inequality between those factors will only get worse.
Participation is another way that allows journalism and democratic societies to stay informed through discussions, voting and activism. Those three values are exactly what participation is meant to be. Journalism provides the information necessary for that engagement.
On the other hand, content focused from an AI’s perspective changes participation in a number of ways. The biggest positive could be how much faster newsrooms could publish updates. AI tools are very good at summarizing data in only a couple of minutes and the faster the public knows, the faster citizens could be informed on the new changesin their communities.
AI can also improve accessibility. Automated translation systems can make news available in multiple languages. This could be used through tools like “text to speech” which you can use on your phone for example. The benefit to that is that content on people’s phones is already personalized to their interests which allows these features to be used more often.
While these are all positives to improving participation, but it can’t be only about access because these AI tools aren’t always available and may not help each cause at hand. The reason for this is, if AI were to get involved in a serious debate or act, it could allow the voices with power to have even more with the use of AI. The more dominant the mainstream is, the harder it would be to keep communities with little to no resources to these tools in the light .
McDowell sees this as a pipeline problem. This issue comes from the fact that if fewer people become journalists, the fewer stories that would come out about communities without theresources a typical community would have. AI systems trained on existing content will mirror those imbalances. Participation in knowledge production becomes limited, not expanded.
Trust also plays a critical role in participation. Journalism relies on a relationship between reporters and audiences. This means that if readers start to think a journalist is using AI generated responses, if people reading your content start to suspect there may be use of AI, trust then begins to decline. Professor McDowell makes a good comparison of this to a personal relationship. Once trust is broken in a relationship, it’s difficult to go back to the level of trust you had before.
Transparency about AI use is essential in journalism. If news organizations are using AI, whether it’s to help them write a story, come up with headlines, etc, then being clear about that would be having good transparency with your audience. Which can build a stronger relationship with your audience. They must explain how human journalists verify and edit content. Participation depends on confidence in the integrity of information. If you don’t have that transparency with your audience, then public engagement declines.
AI-driven journalism also changes its public service mission due to economic and environmental societal pressures. Journalism has gone through financial instability for some time now. McDowell said, “People and journalists are not paid enough, the way in which we generate revenue for journalistic things has been quashed for decades and decades already. Journalism isn’t dying but the way in which we can pay for it has been actively being bled out.”
Many local newspapers have also closed, and AI is often presented as a solution to economic decline because it reduces certain labor costs.
However, economic efficiency does not automatically align with public service. If AI is used due to less newsroom staff it may actually end up making it worse and fewer reporters may investigate local issues or attend community meetings. Public accountability may weaken. The goal of lowering costs may conflict with the mission of serving the public.
The environmental impact on journalism is often overlooked. When a large amount of AI systems is used, that requires powerful data centers which consume significant energy and water. These environmental costs are part of the broader consequences of adopting AI technologies. Journalism’s public-service mission includes responsibility to communities, and environmental sustainability is part of that responsibility.
These economic and environmental factors indicate that the transformation of journalism by AI is not limited to the assistance provided in writing content. Public service can also be affected.
AI-driven content is changing knowledge production by automating parts of the reporting and writing process. It has implications for equity in terms of historical biases and interactions with engagement-driven systems and implications for participation in terms of access, representation, and trust.
AI influences outcomes and reflects existing social structures. It has the potential to aid journalism and journalism outlets in its efficiency and struggles. However, it also has significant risks in terms of fairness, accountability, and democratic engagement.
The future of journalism will depend on the responsible use of AI in journalism. If transparency and equity are prioritized and valued in journalism, AI can be a powerful tool to enhance journalism. But if capitalistic values and the use of AI for automation are prioritized and valued in journalism, AI can lead to greater inequality and undermine the democratic role of journalism, taking us backwards.
AI disclosure: ChatGPT was used to outline part of this story. Perplexity was used to generate research sources. Sora was used to create images. The summary and video were generated by Summarizer 2 Custom GPT and NotebookLM, respectively.
Summary: Artificial intelligence is increasingly integrated into journalism, improving efficiency but blurring the line between human- and machine-generated content, raising concerns about transparency and trust. While newsrooms rely on AI to meet economic and production pressures, studies show readers strongly prefer human-written content and often distrust AI involvement — especially when disclosed. This creates a paradox: transparency is demanded yet undermines confidence, leaving journalism at a critical point where maintaining credibility requires clear disclosure, human oversight, and greater public understanding of AI’s role.
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An op-ed on a highly contentious issue in one of Turkey’s respected newspapers seemed sharply argued and carefully constructed — until an Artificial Intelligence (AI) prompt appeared in the middle of the text.
AI offers journalists valuable tools by processing vast volumes of data — from official documents and transcripts to videos and social media — at a speed and scale previously impossible. It can synthesize complex material and support visual storytelling, thereby expanding journalism’s analytical and narrative capacity. But how were we supposed to trustjournalism that was openly — or carelessly — infused with AI?
The line between human and AI-generated journalism is blurring, and this trend is, of course, not unique to Turkey. At least 9 percent of all news articles in U.S. newspapers contain some AI-generated text, according to a 2025 University of Maryland study. It is not limited to news coverage — the same study found 219 AI-generated opinion pieces in legacy media such as The New York Times, The Wall Street Journal, and The Washington Post, most of which were written by guest contributors.
It is hardly surprising that journalists working under pressure turn to easy-to-use tools. But insufficient AI training, a poor understanding of its limitations, and the disregard for disclosing AI use can undermine journalism — an industry driven by trust — and leave readers lost in a maze of uncertainty.
Moreover, AI-generated patterns are often easy to detect — including repetitive phrasing, generic tone, and cold, formulaic sentence structure. As awareness grows, so does discomfort. Only 12 percent of readers feel comfortable with fully AI-generated news, compared to 62 percent for human-written content, according to a 2025 Reuters survey conducted across six countries.
A Hurricane Is Haunting Newsrooms — The Hurricane of AI
AI has triggered a hurricane in the newsrooms by changing many routine journalistic practices. Its integration into newsroom workflows now spans multiple stages of production — from transcribing interviews and summarizing documents to translating international reports and generating visuals.
For instance, many outlets increasingly rely on AI tools to translate international content or generate background information. The use of AI-generated visuals also became widespread because it eliminates the cost of licensing images or sending reporters into the field to capture real photographs.
AI can summarize hundreds of pages of documents or hours of video footage, saving journalists days of work. It is economical and practical — at least at first glance. The question that remains less clear is how — or whether — audiences are informed when these tools shape the content they read — and what happens when they are informed.
Despite AI’s valuable offerings, investment in training is often limited; the lack of knowledge and irresponsible use of AI in newsrooms — particularly in small, under-resourced outlets — raises concerns about long-term public trust. Proper editorial oversight and transparent disclosure are foundational pillars of modern journalism.
For readers, outsourcing arduous journalistic processes to a machine is unacceptable. Readers want to see a human touch: nearly 99% said it is important for a human to be involved in reviewing news content when AI is used, according to Trusting News’ report, AI research with LMA newsrooms’ audiences reinforces need for transparency: “Transparency is key — and people want more information, not less.”
AI Use Is Rarely Disclosed
Newsrooms widely adopt AI tools yet hesitate to acknowledge their use. A recent study found its use was rarely disclosed. A manual audit of 100 AI-flagged articles found that only five provided a citation indicating that the content contained AI.
Many newspapers today operate under intense financial pressure, paradoxically exacerbated by the emergence of AI-generated summaries in Google search results and social media algorithms. Outlets face shrinking staff and declining advertising revenue.
Even major institutions are restructuring. Recently, The Washington Post, one of the most prominent newspapers in the U.S., laid off hundreds of employees, a move its former executive editor Marty Baron said “ranks among the darkest days” in the newspaper’s history.
To stay alive in the new information age, newspapers have become laser-focused on “producing”content at a fast pace. Speed has become the new norm. And AI tools promise efficiency without additional payroll costs. Publicly acknowledging AI assistance, however, may invite skepticism or backlash from audiences already wary of automation.
Some outlets may not yet have formal, clear AI policies. Others may view AI use as a technical workflow decision rather than an editorial one. In such cases, disclosure may not be seen as necessary. Yet when AI moves into drafting or framing content, the ethical stakes shift — so do the readers’ expectations.
As Daniel Trielli, assistant professor of media and democracy at UMD’s Philip Merrill College of Journalism, told Maryland Today, “What’s most jarring is how many newsrooms are actually using this technology without saying they’re using it.”
However, when newspaper readers saw an AI use disclosure, according to Trusting News research, they almost always ask for more detail about“how” and “why”AI was used — and the degree of “human oversight”in the related article. In other words, readers are not satisfied with generic disclosures — they explicitly want total transparency.
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Art direction by Emre Zor| Art by Sora
The Transparency Paradox
There lies a paradox. Even though readers demand greater transparency about AI use in a specific story or piece of news, such disclosures often lead to a decline in trust. Seeing AI listed as a contributor makes them uncomfortable, and they are more likely to report decreased trust than those who did not see any disclosure. Many worry that a story shaped by a “robot” could be misleading, and mere artificiality creates confusion — or unpredictability.
And so I return to the beginning: the moment I noticed an AI prompt sitting in the middle of an op-ed. In that instant, the arguments I had admired began to feel hollow. What I had taken for sharp reasoning suddenly seemed mechanical, manipulative, scary. But why?
The dystopian perception of AI, in other words, AI illiteracy, prompts fear. People want to know“how” and “why” AI was used in a specific story, but knowledge of AI’s use also undermines their trust. Transparency, instead of reassuring audiences, can activate anxieties. Trusting News found that 42% of respondents reported being “less likely”to trust the story after seeing an AI disclosure.
Therefore, newsrooms are caught in the middle. They have to choose between short-term trust by hiding AI use and long-term credibility through disclosure and honesty with their readers. At first sight, it looks like a strategic tension. However, AI disclosure is a matter of basic journalistic ethics and responsibility. Used without explanations, AI risks undermining long-term trust — and journalism itself.
“The first thing people want is education around AI,”saidLynn Walsh, assistant director of Trusting News and an Emmy Award-winning journalist. She emphasized that being caught using AI without transparency damages trust far more deeply, and that real news consumers don’t only demand disclosure but also general AI education to better understand and learn how to detect it.
More than 80% of those 6,000 survey respondents said it would be helpful if the newsroom provided information and tips to better understand AI in general, according to the Trusting News survey.
“We need to do explainers on our use of this technology, record a video as we are using it to create an image, and show them our process,” Walsh said. “That type of content might bring the audience along with us more than just having disclosures.”
Walsh underlined the importance of checking in with the audience: “Make sure that they understand that your content is still going to be accurate, responsible, and ethical.”
When AI Enters Opinion
Today, AI use in journalistic practices is unavoidable — and, in many cases, practical. But opinion writing is different. Op-eds shape public discourse, and readers expect to encounter genuine human perspectives rooted in distinct socio-economic backgrounds with different interests. They want to engage with the judgment and moral risk of a real person.
Readers, stuck in a maze of uncertainty, struggle to discern whether the opinions they consume are written by humans or generated by AI.
Using AI to test ideas or challenge one’s assumptions can be intellectually stimulating. Although AI has been criticized for reinforcing existing biases and for being a modern form of sycophancy, it can easily be guided through prompting and customization. In that sense, AI may serve as a preparatory tool for opinion writing.
But allowing AI to write an opinion piece is analogous to publishing an AI-generated poem as if it were written by a human. It risks hollowing out authentic human exchange and weakening the very deliberation that opinion writing is meant to foster.
AI-generated content in opinion pages across legacy media accounted for 4.5% overall — significantly higher than the rate on those outlets’ news pages (0.7%), according to the University of Maryland study.
When the human presence is replaced — or concealed — on the opinion pages, the relationship between writer and reader erodes. Delegating an opinion essay to AI without disclosure undermines public trust in newspapers.
Art direction by Emre Zor| Art by Sora
Independent AI-Detection Tools
When readers suspect articles are generated by AI without disclosure, credibility erodes. In journalism, diminished trust means drowning in the ocean of information, as lower engagement and declining advertising revenue hinder quality journalism. If journalism depends on trust as its economic and moral foundation, embedding multi-dimensional transparency around AI use is essential.
Industry-wide standards must be established, and disclosure must become a baseline requirement. News organizations should adopt and publicly make available internal policies specifying when AI may be used and when it may not.
Any meaningful AI involvement in reporting, editing, or visual generation should be clearly labeled. Readers are more likely to accept AI assistance when they understand how and why it was used. It is a process that should advance in communication with the readers, constantly engaging with their expectations and discomforts.
Moreover, readers should be able to access independent, credible AI-detection tools — such as systems modeled on Pangram — specifically for journalistic contexts. They would enable readers to verify the origins of content, strengthening accountability and rebuilding confidence in the press.
By combining transparency, AI literacy, and independent detection tools, journalism can protect its foundational principle: trust.
“Journalists make more informed decisions about what it means to serve the public if they understand the people that they are trying to serve,” Walsh said.
This analysis of Google search trends provides insight to the biggest Lollapalooza headliners coming to Chicago and the upcoming, nationwide “No Kings” protest.
According to an analysis of Google search data about the 2026 Lollapalooza headliners, some artists have taken the lead in searches within the U.S. since the lineup was released this week on March 17, 2026.
Lollapalooza is an annual music festival in Chicago, Illinois, hosting more than 170 bands over the four-day event. As one of the biggest festivals in the world, Lollapalooza welcomes around 200,000 fans downtown to Grant Park. The 2026 Lollapalooza headliners are Lorde, Charli xcx, Tate McRae, Olivia Dean, JENNIE, The Smashing Pumpkins, The xx, and John Summit. While all of the headliners are booming artists in the music industry, this chart reveals a couple artists who are rising above the rest, at least in Google search trends.
Since the Lallapalooza lineup announcement on Tuesday morning, the chart shows that all of the headliners have risen in search trends. However, Tate McRae (yellow/diamond) and Olivia Dean (green/triangle) have kept the lead by about double the amount of searches than the other Lollapalooza headliners.
This summer, the Lollapalooza music festival will take place from July 30-August 2, 2026 at Grant Park in Chicago, Illinois. To stay informed about event announcements, tickets, and all other information regarding the festival, visit the Lollapalooza official website.
According to an analysis of Google search data, searches for “No Kings” protests have risen by ten percent within the past week in Chicago, Illinois. The upcoming nationwide, “No Kings” protest on March 28, 2026 may be related to this rise in searches.
The “No Kings” protests are part of a peaceful movement to protest President Donald Trump’s second presidency. This movements’ efforts have been bolstered by recent events involving the U.S. Immigration and Customs Enforcement raids in many U.S. cities. The “No Kings” movement came about in response to President Donald Trump’s alleged antidemocratic policies.
In the past year, the “No Kings” movement has held two nationwide protests that drew millions in crowds. Both of these protests have been some of the biggest single-day protests in U.S. history. At 1:30 p.m. on Saturday, March 28, 2026, crowds of Chicagoans and visitors plan to meet in Butler Field Grant Park to play their part in the “No Kings” movement.
This protest expects to draw even bigger crowds than the previous two, and as the chart shows, searches for the nationwide protest are already rising in Chicago. You can visit the “No Kings” official website for more information about the upcoming event and their movement.
Every summer, the news comes in like clockwork: Another bloody weekend in Chicago. But what does the data really say, and what does it not say?
Chicago Police Department’s annual report says that there were 573 murders in Chicago in 2024. That is the lowest total since 2019, and it is an 8% drop from the previous year. By 2025, the number dropped to 416, the lowest since 1965.
The number is still shocking, though. Last year, nearly 2,800 people were shot in the city, some fatally and some not. And the violence is not spread evenly. About half of Chicago’s shooting victims historically come from just 10 community areas. Austin, on the city’s West Side, had the most shooting victims, with around 271.
The pattern stays the same: homicides nearly double from January to July, then go down again as temperatures drop. For years, researchers at the University of Chicago Crime Lab have shown that warmer weather leads to more street activity and street conflicts and disputes.
One piece of information that is often missed in national news is that Chicago does not have the highest murder rate in the country. Cities like St. Louis and Baltimore consistently have higher murder rates per capita than Chicago, according to the FBI Crime Data Explorer. Chicago’s rate is 22.3 percent, still high, but not the outlier the political conversation implies.
While Chicago crime was down in 2025 — including a record-low 416 homicides — the city still saw its usual summer spike in reported crime overall, according to an analysis of 2025 data from the City of Chicago Data Portal.
According to the data, there were 236,660 reported crimes in Chicago in 2025. Theft had the highest number of reported incidents at 55,045, followed by battery with 42,539, criminal damage with 26,206, assault with 21,560, and motor vehicle theft with 17,232.
After breaking the data down by category, it shows that reported crime is not one big total number, but a pattern that changes over time depending on the offense that is being reported.
The data also show some differences across the year. July had the highest number of reported incidents with 22,627, while February had the lowest with 16,515, mirroring trends from past years. Additionally, 37,778 incidents involved arrests, and 45,088 were reported as domestic.
The United States has a far larger incarcerated population than any other country in the world, with nearly 500,000 people serving time, according to the Prison Policy Initiative.
Criminologists are not only interested in understanding why this industrial complex has grown to such a scale in the U.S., but also in examining the overall lives of incarcerated individuals while removed from society. The data is shocking, as it reveals thousands of deaths in the past decade.
According to data released by the Federal Bureau of Prisons, there were 8,242 inmate deaths in the United States from 2005 to 2024. A breakdown of the causes of these deaths suggests that there may be a lack of adequate healthcare access for incarcerated individuals.
Four of the five leading causes are chronic conditions: cancer leads the chart with 2,136 deaths, followed by cardiac arrest with 2,045 deaths. Other top causes include pulmonary and liver disease, accounting for 916 and 611 deaths, respectively. Suicide was the fifth most common cause, with 363 deaths between 2005 and 2024.
Examining the data by year also reveals a significant spike in deaths in 2020, which is unsurprising given the COVID-19 pandemic and associated surges in cases. While current data shows a downward trend since 2020, these figures underscore the urgent need for improved healthcare access for incarcerated populations.
In the Chicago metropolitan area, inflation has slowed substantially over the past year, providing some comfort to residents who faced dramatic price rises during the pandemic-era surge.
While the national rate was 2.4% between January 2025 and January 2026, the U.S. Bureau of Labor Statistics notes that the rate of annual inflation for the Chicago metro area was around 1.3%.
Inflation is the speed at which the price of goods and services rises over time. Economists use the Consumer Price Index (CPI) to measure inflation, which measures the spending behavior of urban households over many things, including its price impact on hundreds of categories such as housing, transportation, food, and recreation.
Inflation overall has eased, but some sectors are experiencing greater and sustained local cost increases. Recreation prices in Chicago rose by roughly 3.3 percent and prices for other goods and services rose by 3.6 percent last year.
Housing prices have also continued to be a persistent source of inflation in the region. So while inflation pressures may have eased, Chicago residents might still face increased prices in everyday spending.
Lower inflation does not mean prices are decreasing. Instead, it means they are rising more slowly than before. Monitoring inflation across metro levels allows economists and policy-makers to understand how economic conditions differ among cities and counties throughout the country more accurately.
Chicago’s latest numbers suggest the city’s inflation rate is stabilizing, though if costs keep rising.
Chicago’s cost of living has seen notable increases between 2023 and 2025, according to an analysis of housing and labor data.
The data in the infographic above highlights three vital indicators of the rising cost of living in Chicago: the percentage increase in worker pay, the average rent for each year and the average CPI rent index. The three measurements show how living expenses have risen in Chicago from 2023 to 2025.
With worker pay, the U.S. Bureau of Labor Statistics reported a 4.1 percent increase in 2023. Growth slowed to 3.6 percent in 2024, then slightly rose to 3.8 percent in 2025. This is quite concerning, as the percentage remains low from year to year. Although workers are earning more money, it is not enough to keep up with Chicago’s cost of living.
In contrast, the average rent in Chicago has seen significant increases. According to Refin, the average rent in 2023 was $2,177. By 2024, we can see a slight increase to $2,209 before reaching $2,370, a 7.29% increase in that year.
Finally, the CPI rent index clearly indicates a rise. According to the Federal Reserve Bank of St. Louis, the index started with 402 in 2023, which still looks reasonable. However, by 2024, there’s a 22-point increase, bringing the index to 424. Then, in 2025, the CPI rent index is 444, up 20 points from 424. This shows us that the CPI rent index likely won’t recover anytime soon.
In the last five years, there has been an 85% spike in stray dogs being captured or surrendered to adoption centers in the Chicago area, mostly due to lack of economic resources. Overpopulation in shelters has been an ongoing crisis that has plagued Chicago for many years, and continues to get worse, unless something is done to combat the issue soon.
According to the 2025 Chicago Animal Care and Control statistics, there were 5,007 stray dogs taken into adoption centers all over the city. From these intakes, only about 1,325 of the dogs were adopted. Although the number of adoptions has been increasing throughout the last five years, it is still not a sufficient amount to keep adoption shelters from overflooding. Many more thousands of dogs remained and continue to remain, and many never got to make it out of the shelter because of it.
Unfortunately, the City of Chicago reported that in 2025, 1,375 people requested euthanasia for their surrendered dogs in the adoption centers. Of those requests, 1,278 went through.
Aside from owner requests, there were also euthanasia cases by the adoption centers that depend on the dog’s behavior, health, and capacity for care. Euthanasia by shelters has also seen a rapid increase from previous years, mostly due to overcrowded shelters and lack of space. This past year alone, the total of euthanasia cases added up to 2,794.
According to NBC News, the increasing number of pets in shelters is because many pet owners are struggling to afford a pet. Many are barely surviving, paying for their own expenses with today’s cost of living, so owning a pet has just become another increasing expense.
So what can be done?
According to the Best Friends Animal Society, adopting a dog rather than buying saves their lives and isolate dogs from the horrors of euthanasia in overcrowded shelters. It also gives dogs the opportunity to get a second chance at loving and being loved by a caring family. And those who are struggling in Chicago to afford their dogs can use the free vaccine clinics and seek free pet food resources to avoid surrendering their dogs to shelters.
Our digital reporters hit the streets to inteview people about CTA safety, property taxes and the Bears stadium issues. Hear what they had to say …
Interview with Aaron Prince from Little Italy, Chicago about safety on the Chicago Transit Authority. Do riders feel safe on public transit? #uicdigital
I met one of the biggest Chicago Bears fan! I asked should the Chicago Bears move to Northwest Indiana? Why or Why not? Listen to his opinion. #uicdigital
The Chicago Stars FC Home Attendance Plummeted Despite Record-Breaking Year
The Chicago Stars FC regular-season home attendance dropped 31.6% in the past year, averaging 5,574 fans for the 2025 season, despite breaking the NWSL single-match attendance record.
This decline has shrank the Stars’ average regular season home attendance from 11th to 13th place, just slightly above Racing Louisville FC: a team founded in 2019.
These charts show the regular season home game average attendance for the Chicago Stars FC throughout the last 10 years, but also highlight the decrease of attendance from 2024 to 2025. 2020 is left blank due to the COVID-19 pandemic that didn’t allow fans to attend in-stadium matches.
Prior to the relocation, the Stars had set a new NWSL single match attendance record on June 8, 2024 during their “Red Stars Take Over Wrigley Field” match against Bay FC. The match produced a total of 35,038 fans at Wrigley. The record was recently broken by a matchup between Bay FC and the Washington Spirit at Oracle Park, with 40,091 fans.
Unlike SeatGeek stadium, Wrigley is easy to access through public transportation. By relocating to the Evanston Northwestern Stadium for the 2026 season, the Stars hope to regain fans from the city and boost attendance. — Lizette Salto
LeBron James and the Race to 43,000: How the King Rewrote the NBA Scoring Record
For nearly 39 years, one number stood as the gold standard of NBA greatness: 38,387. That was Kareem Abdul-Jabbar’s career points total, a record set in April 1984 and was considered by many to be untouchable.
On Feb. 7, 2023, LeBron James of the Los Angeles Lakers proved them wrong. As of Feb. 26, 2026, James has 43,029 career points, putting him more than 4,600 ahead of Abdul-Jabbar’s all-time mark. The moment was witnessed by Abdul-Jabbar himself, who was sitting courtside at Crypto.com Arena in Los Angeles.
The bar chart race above shows how the race among the NBA’s top eight all-time scorers has unfolded season by season since 1960. James passed Karl Malone (36,928 points) in March 2022 and Kobe Bryant (33,643 points) in January 2020 before setting his sights on Abdul-Jabbar. Since breaking the record, James has extended his lead by more than 12 percentage points. Michael Jordan, widely considered the greatest scorer at 30.1 points per game, finished his career with 32,292 points, more than 10,000 behind James.
What separates James is not just his scoring but his longevity. Abdul-Jabbar played 20 seasons and James is in his 23rd. James has averaged at least 27 points per game in the 2025–26 season, showing no signs of decline at 41. Meanwhile, Kevin Durant, the only other active player in the top 10, sits at 31,966 points and would need to play at a high level for several more seasons to even come close to James.
The question of who could surpass James may never have a realistic answer. At his current pace, Durant would have to score 11,000 more points over seven full seasons to match James’s steadily rising total. Unlike Abdul-Jabbar’s record, James’s blend of volume, durability, and consistency has created a record that could last for generations. Chamberlain, who set the single-game scoring record with 100 points in 1962, remains the only player in NBA history to average 50 points per game in a season. — Amar Ahmad
From Paint to Perimeter: How Stretching the Court Has Shaped the NBA
The NBA has shifted dramatically toward perimeter-focused offense. Today, teams depend on three-point shooting far more than they did in the late 1990s, using spacing and outside shooting to create more scoring opportunities.
As seen in the chart below, the percentage of field-goal attempts taken from beyond the three-point line has increased across the league over time.
The NBA has seen a notable shift in its approach to offense over the last few decades. Though historically designed primarily as a situational scoring option, three-point shooting is now a staple of the modern game.
As of the 2025–2026 season, the Chicago Bulls have a three-point attempt rate of .253, meaning 25.3 percent of their shot attempts are at three-point range. For the NBA three-point attempt rate, this places the Bulls around 20th out of 30 teams this season.
While they seemingly rely less on perimeter shooting, their overall use of the shot is still higher than it was in previous seasons.
The percentage of field goals attempted at the three-point range has steadily increased over time, as the past two decades in particular demonstrate, showing a slow shift toward perimeter-oriented offenses:
In the 1997–98 NBA season, only 17.6 percent of all shots across the league were three-pointers. At that time, more and more teams placed an emphasis on “inside-in-the-paint” scoring and mid-range jumpers. Long-range shooting was not prioritized.
In the 1994–95 season through the 1996–97 seasons of the NBA, the line for the three-point shot was shortened to try and increase scoring in the league and speed game pace. As a result, teams’ three-point attempts increased.
In the 1997–98 season, the NBA moved the line back to its original length, and fewer attempts were made before increasing again as teams experimented with long-distance offense. The move toward three-point shooting grew even more widespread in the mid-2010s, with the Golden State Warriors.
Their style of play was focused on ball movement, spacing and high-volume three-point shooting. Much of this was the result of the backcourt pair of Stephen Curry and Klay Thompson: the “Splash Brothers.”
Their steady scoring from long-range demonstrated the value of perimeter shooting, which influenced strategies throughout the league.
Three-point attempts represent about 24.6 percent of all field-goal attempts during the 2025–26 season. A concept originally considered a minor element of offensive strategy has now become one of the defining elements of modern NBA offense.
This reflects how teams increasingly stretch the court, relying on perimeter scoring to create advantages. — Evalyse Tereul
Manchester derby Returning to Even Ground Again as City and United Reset
The Manchester derby between Manchester United and Manchester City began as a neighborhood rivalry long before it became a global event. Manchester City traces its first meeting back to 1881, when St Mark’s (West Gorton) played Newton Heath. By 2026, the rivalry is going well over 130 years and has more than 200 competitive matches, depending on which early games are counted.
(Note: The 25–26 season is still ongoing with 11 games left for both City and United)
In modern times, from the Premier League’s2014–15 season to 2024–25, the Manchester derby has increasingly been framed by City dominance and a widening gap in league finishes.
Manchester United finished 15th in 2024–25, its lowest position in the last decade. City’s dominant run included six titles in seven seasons from its Centurion 2017–18 through 2023–24. United’s best finishes were second in 2017–18 and 2020–21. As of Feb. 26, both teams appear to be bouncing back after a decline in the 24–25 season with 11 games left to go, sitting at 2nd and 4th.
Arguably, United’s unpredictability in the league is largely due to its high managerial turnover in the last 11 seasons. The club announced Louis van Gaal in May 2014, appointed Jose Mourinho in May 2016, then turned to Ole Gunnar Solskjaer as caretaker in December 2018 before naming him full-time in March 2019.
After Michael Carrick’s brief caretaker stint, United installed Ralf Rangnick as interim manager in November 2021, hired Erik ten Hag in 2022, and appointed Ruben Amorim as head coach in November 2024. Even as of January 2026, after Ruben Amorim’s got sacked in 2025. Michael Carrick is caretaker yet again in 2026.
Manchester City however, have long enjoyed their managerial stability after Manuel Pellegrini’s departure in 2016, with Pep Guardiola replacing him and still at the helm, going on well over a decade now. This sharp contrast leads fans, critics and journalists alike to believe that this stability is exactly what has separated the two teams over the last 10 years. What hasn’t changed however is the stadiums.
In the modern age, the derby has been static in venues with the two stadiums only a few miles apart in Manchester. Manchester United plays at their iconic Old Trafford, which opened in 1910 after being designed by architect Archibald Leitch. The current capacity sits around 76,000 and the club has said it is exploring a new, 100,000-capacity stadium on the Old Trafford site.
City plays at the Etihad Stadium on the Etihad Campus, after their move in August 2003 after an 80-year stay at Maine Road. The Etihad has a capacity of around 55,000, and the club recently outlined work to expand the stadium to over 60,000.
With over 11 games yet to be played this season, and United only within 8 points of City as of Match Week 28, there is always the possibility of United recording a higher league finish than City for the first time since United’s title winning 2012–2013 season. — Adam Musaev
Total attendance at Wrigley has been slowly climbing for four consecutive seasons since the pandemic. With gradual increases reflected in their totals of 2.6 million in 2022, 2.7 million in 2023, 2.9 million in 2024 and 3 million in 2025. In total, this was around a 15% increase in attendance from 2022 to 2025. This rebound in attendance followed the COVID-19 pandemic’s impact on the 2020 season and a 2021 season that finished with a total of around 1.9 million due to capacity limits.
While lower attendance is nothing new to the Cubs, with the club’s totals in the early 2010s bottoming at 2.6 million in 2013, the club will hope for attendance numbers resembling their World Series-winning season in 2016, which saw attendance at around 3.2 million.
Looking ahead to the Cub’s 2026 season, there is the possibility of a similar attendance spike, with heightened expectations for the team with a busy offseason.
Beyond attendance numbers, Wrigley Field turns 112 years old this year. The iconic ballpark is also the second-oldest stadium in the MLB, behind Boston’s Fenway Park, built in 1912.
Nicknamed “The Friendly Confines,” it has been the Cubs’ home for more than a century. The stadium doubles as a tourist attraction in Chicago’s Wrigleyville neighborhood. With neighboring Chicago sports teams like the White Sox, Bears and Fire all pursuing new homes, it appears the Cubs are not going anywhere anytime soon.
