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Can chatbots really improve mental health?

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Recently, I found myself pouring my heart out, not to a human, but to a chatbot named Wysa on my phone. It nodded – virtually – asked me how I was feeling and gently suggested trying breathing exercises.

As a neuroscientist, I couldn’t help but wonder: Was I actually feeling better, or was I just being expertly redirected by a well-trained algorithm? Could a string of code really help calm a storm of emotions?

Artificial intelligence-powered mental health tools are becoming increasingly popular – and increasingly persuasive. But beneath their soothing prompts lie important questions: How effective are these tools? What do we really know about how they work? And what are we giving up in exchange for convenience?

Of course it’s an exciting moment for digital mental health. But understanding the trade-offs and limitations of AI-based care is crucial.

Stand-in meditation and therapy apps and bots

AI-based therapy is a relatively new player in the digital therapy field. But the U.S. mental health app market has been booming for the past few years, from apps with free tools that text you back to premium versions with an added feature that gives prompts for breathing exercises.

Headspace and Calm are two of the most well-known meditation and mindfulness apps, offering guided meditations, bedtime stories and calming soundscapes to help users relax and sleep better. Talkspace and BetterHelp go a step further, offering actual licensed therapists via chat, video or voice. The apps Happify and Moodfit aim to boost mood and challenge negative thinking with game-based exercises.

Somewhere in the middle are chatbot therapists like Wysa and Woebot, using AI to mimic real therapeutic conversations, often rooted in cognitive behavioral therapy. These apps typically offer free basic versions, with paid plans ranging from US$10 to $100 per month for more comprehensive features or access to licensed professionals.

While not designed specifically for therapy, conversational tools like ChatGPT have sparked curiosity about AI’s emotional intelligence.

Some users have turned to ChatGPT for mental health advice, with mixed outcomes, including a widely reported case in Belgium where a man died by suicide after months of conversations with a chatbot. Elsewhere, a father is seeking answers after his son was fatally shot by police, alleging that distressing conversations with an AI chatbot may have influenced his son’s mental state. These cases raise ethical questions about the role of AI in sensitive situations.

Guided meditation apps were one of the first forms of digital therapy.
IsiMS/E+ via Getty Images

Where AI comes in

Whether your brain is spiraling, sulking or just needs a nap, there’s a chatbot for that. But can AI really help your brain process complex emotions? Or are people just outsourcing stress to silicon-based support systems that sound empathetic?

And how exactly does AI therapy work inside our brains?

Most AI mental health apps promise some flavor of cognitive behavioral therapy, which is basically structured self-talk for your inner chaos. Think of it as Marie Kondo-ing, the Japanese tidying expert known for helping people keep only what “sparks joy.” You identify unhelpful thought patterns like “I’m a failure,” examine them, and decide whether they serve you or just create anxiety.

But can a chatbot help you rewire your thoughts? Surprisingly, there’s science suggesting it’s possible. Studies have shown that digital forms of talk therapy can reduce symptoms of anxiety and depression, especially for mild to moderate cases. In fact, Woebot has published peer-reviewed research showing reduced depressive symptoms in young adults after just two weeks of chatting.

These apps are designed to simulate therapeutic interaction, offering empathy, asking guided questions and walking you through evidence-based tools. The goal is to help with decision-making and self-control, and to help calm the nervous system.

The neuroscience behind cognitive behavioral therapy is solid: It’s about activating the brain’s executive control centers, helping us shift our attention, challenge automatic thoughts and regulate our emotions.

The question is whether a chatbot can reliably replicate that, and whether our brains actually believe it.

A user’s experience, and what it might mean for the brain

“I had a rough week,” a friend told me recently. I asked her to try out a mental health chatbot for a few days. She told me the bot replied with an encouraging emoji and a prompt generated by its algorithm to try a calming strategy tailored to her mood. Then, to her surprise, it helped her sleep better by week’s end.

As a neuroscientist, I couldn’t help but ask: Which neurons in her brain were kicking in to help her feel calm?

This isn’t a one-off story. A growing number of user surveys and clinical trials suggest that cognitive behavioral therapy-based chatbot interactions can lead to short-term improvements in mood, focus and even sleep. In randomized studies, users of mental health apps have reported reduced symptoms of depression and anxiety – outcomes that closely align with how in-person cognitive behavioral therapy influences the brain.

Several studies show that therapy chatbots can actually help people feel better. In one clinical trial, a chatbot called “Therabot” helped reduce depression and anxiety symptoms by nearly half – similar to what people experience with human therapists. Other research, including a review of over 80 studies, found that AI chatbots are especially helpful for improving mood, reducing stress and even helping people sleep better. In one study, a chatbot outperformed a self-help book in boosting mental health after just two weeks.

While people often report feeling better after using these chatbots, scientists haven’t yet confirmed exactly what’s happening in the brain during those interactions. In other words, we know they work for many people, but we’re still learning how and why.

AI chatbots don’t cost what a human therapist costs – and they’re available 24/7.

Red flags and risks

Apps like Wysa have earned FDA Breakthrough Device designation, a status that fast-tracks promising technologies for serious conditions, suggesting they may offer real clinical benefit. Woebot, similarly, runs randomized clinical trials showing improved depression and anxiety symptoms in new moms and college students.

While many mental health apps boast labels like “clinically validated” or “FDA approved,” those claims are often unverified. A review of top apps found that most made bold claims, but fewer than 22% cited actual scientific studies to back them up.

In addition, chatbots collect sensitive information about your mood metrics, triggers and personal stories. What if that data winds up in third-party hands such as advertisers, employers or hackers, a scenario that has occurred with genetic data? In a 2023 breach, nearly 7 million users of the DNA testing company 23andMe had their DNA and personal details exposed after hackers used previously leaked passwords to break into their accounts. Regulators later fined the company more than $2 million for failing to protect user data.

Unlike clinicians, bots aren’t bound by counseling ethics or privacy laws regarding medical information. You might be getting a form of cognitive behavioral therapy, but you’re also feeding a database.

And sure, bots can guide you through breathing exercises or prompt cognitive reappraisal, but when faced with emotional complexity or crisis, they’re often out of their depth. Human therapists tap into nuance, past trauma, empathy and live feedback loops. Can an algorithm say “I hear you” with genuine understanding? Neuroscience suggests that supportive human connection activates social brain networks that AI can’t reach.

So while in mild to moderate cases bot-delivered cognitive behavioral therapy may offer short-term symptom relief, it’s important to be aware of their limitations. For the time being, pairing bots with human care – rather than replacing it – is the safest move.



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Ramp Debuts AI Agents Designed for Company Controllers

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Financial operations platform Ramp has debuted its first artificial intelligence (AI) agents.

The new offering is designed for controllers, helping them to automatically enforce company expense policies, block unauthorized spending, and stop fraud, and is the first in a series of agents slated for release this year, the company said in a Thursday (July 10) news release.

“Finance teams are being asked to do more with less, yet the function remains largely manual,” Ramp said in the release. “Teams using legacy platforms today spend up to 70% of their time on tasks like expense review, policy enforcement, and compliance audits. As a result, 59% of professionals in controllership roles report making several errors each month.”

Ramp says its controller-centric agents solve these issues by doing away with redundant tasks, and working autonomously to go over expenses and enforce policy, applying “context-aware, human-like” reasoning to manage entire workflows on their own.

“Unlike traditional automation that relies on basic rules and conditional logic, these agents reason and act on behalf of the finance team, working independently to enforce spend policies at scale, immediately prevent violations, and continuously improve company spending guidelines,” the release added.

PYMNTS wrote earlier this week about the “promise of agentic AI,” systems that not only generate content or parse data, but move beyond passive tasks to make decisions, initiate workflows and even interact with other software to complete projects.

“It’s AI not just with brains, but with agency,” that report said.

Industries including finance, logistics and healthcare are using these tools for things like booking meetings, processing invoices or managing entire workflows autonomously.

But although some corporate leaders might hold lofty views for autonomous AI, the latest PYMNTS Intelligence in the June 2025 CAIO Report, “AI at the Crossroads: Agentic Ambitions Meet Operational Realities,” shows a trust gap among executives when it comes to agentic AI that highlights serious concerns about accountability and compliance.

“However, full-scale enterprise adoption remains limited,” PYMNTS wrote. “Despite growing capabilities, agentic AI is being deployed in experimental or limited pilot settings, with the majority of systems operating under human supervision.”

But what makes mid-market companies uneasy about tapping into the power of autonomous AI? The answer is strategic and psychological, PYMNTS added, noting that while the technological potential is enormous, the readiness of systems (and humans) is much murkier.

“For AI to take action autonomously, executives must trust not just the output, but the entire decision-making process behind it. That trust is hard to earn — and easy to lose,” PYMNTS wrote, noting that the research “found that 80% of high-automation enterprises cite data security and privacy as their top concern with agentic AI.”



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How automation is using the latest technology across various sectors

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Artificial Intelligence and automation are often used interchangeably. While the technologies are similar, the concepts are different. Automation is often used to reduce human labor for routine or predictable tasks, while A.I. simulates human intelligence that can eventually act independently.

“Artificial intelligence is a way of making workers more productive, and whether or not that enhanced productivity leads to more jobs or less jobs really depends on a field-by-field basis,” said senior advisor Gregory Allen with the Wadhwani A.I. center at the Center for Strategic and International Studies. “Past examples of automation, such as agriculture, in the 1920s, roughly one out of every three workers in America worked on a farm. And there was about 100 million Americans then. Fast forward to today, and we have a country of more than 300 million people, but less than 1% of Americans do their work on a farm.”

A similar trend happened throughout the manufacturing sector. At the end of the year 2000, there were more than 17 million manufacturing workers according to the U.S. Bureau of Labor statistics and the Federal Reserve Bank of St. Louis. As of June, there are 12.7 million workers. Research from the University of Chicago found, while automation had little effect on overall employment, robots did impact the manufacturing sector. 

“Tractors made farmers vastly more productive, but that didn’t result in more farming jobs. It just resulted in much more productivity in agriculture,” Allen said.

ARTIFICIAL INTELLIGENCE DRIVES DEMAND FOR ELECTRIC GRID UPDATE

Researchers are able to analyze the performance of Major League Baseball pitchers by using A.I. algorithms and stadium camera systems. (University of Waterloo / Fox News)

According to our Fox News Polling, just 3% of voters expressed fear over A.I.’s threat to jobs when asked about their first reaction to the technology without a listed set of responses. Overall, 43% gave negative reviews while 26% reacted positively.

Robots now are being trained to work alongside humans. Some have been built to help with household chores, address worker shortages in certain sectors and even participate in robotic sporting events.

The most recent data from the International Federation of Robotics found more than 4 million robots working in factories around the world in 2023. 70% of new robots deployed that year, began work alongside humans in Asia. Many of those now incorporate artificial intelligence to enhance productivity.

“We’re seeing a labor shortage actually in many industries, automotive, transportation and so on, where the older generation is going into retirement. The middle generation is not interested in those tasks anymore and the younger generation for sure wants to do other things,” Arnaud Robert with Hexagon Robotics Division told Reuters.

Hexagon is developing a robot called AEON. The humanoid is built to work in live industrial settings and has an A.I. driven system with special intelligence. Its wheels help it move four times faster than humans typically walk. The bot can also go up steps while mapping its surroundings with 22 sensors.

ARTIFICIAL INTELLIGENCE FUELS BIG TECH PARTNERSHIPS WITH NUCLEAR ENERGY PRODUCERS

gif of AI rendering of pitching throwing a ball

Researchers are able to create 3D models of pitchers, which athletes and trainers could study from multiple angles. (University of Waterloo)

“What you see with technology waves is that there is an adjustment that the economy has to make, but ultimately, it makes our economy more dynamic,” White House A.I. and Crypto Czar David Sacks said. “It increases the wealth of our economy and the size of our economy, and it ultimately improves productivity and wages.”

Driverless cars are also using A.I. to safely hit the road. Waymo uses detailed maps and real-time sensor data to determine its location at all times.

“The more they send these vehicles out with a bunch of sensors that are gathering data as they drive every additional mile, they’re creating more data for that training data set,” Allen said.

Even major league sports are using automation, and in some cases artificial intelligence. Researchers at the University of Waterloo in Canada are using A.I. algorithms and stadium camera systems to analyze Major League Baseball pitcher performance. The Baltimore Orioles joint-funded the project called Pitchernet, which could help improve form and prevent injuries. Using Hawk-Eye Innovations camera systems and smartphone video, researchers created 3D models of pitchers that athletes and trainers could study from multiple angles. Unlike most video, the models remove blurriness, giving a clearer view of the pitcher’s movements. Researchers are also exploring using the Pitchernet technology in batting and other sports like hockey and basketball.

ELON MUSK PREDICTS ROBOTS WILL OUTSHINE EVEN THE BEST SURGEONS WITHIN 5 YEARS

graphic overview of ptichernet system of baseball player's pitching skills

Overview of a PitcherNet System graphics analyzing a pitcher’s baseball throw. (University of Waterloo)

The same technology is also being used as part of testing for an Automated Ball-Strike System, or ABS. Triple-A minor league teams have been using the so-called robot umpires for the past few seasons. Teams tested both situations in which the technology called every pitch and when it was used as challenge system. Major League Baseball also began testing the challenge system in 13 of its spring training parks across Florida and Arizona this February and March.

Each team started a game with two challenges. The batter, pitcher and catcher were the only players who could contest a ball-strike call. Teams lost a challenge if the umpire’s original call was confirmed. The system allowed umpires to keep their jobs, while strike zone calls were slightly more accurate. According to MLB, just 2.6% of calls were challenged throughout spring training games that incorporated ABS. 52.2% of those challenges were overturned. Catchers had the highest success rate at 56%, followed by batters at 50% and pitchers at 41%.

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Triple-A announced last summer it would shift to a full challenge system. MLB commissioner Rob Manfred said in June, MLB could incorporate the automated system into its regular season as soon as 2026. The Athletic reports, major league teams would use the same challenge system from spring training, with human umpires still making the majority of the calls.

Many companies across other sectors agree that machines should not go unsupervised.

“I think that we should always ensure that AI remains under human control,” Microsoft Vice Chair and President Brad Smith said.  “One of first proposals we made early in 2023 was to insure that A.I., always has an off switch, that it has an emergency brake. Now that’s the way high-speed trains work. That’s the way the school buses, we put our children on, work. Let’s ensure that AI works this way as well.”



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Artificial intelligence predicts which South American cities will disappear by 2100

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The effects of global warming and climate change are being felt around the world. Extreme weather events are expected to become more frequent from droughts to floods wreaking havoc on communities as well as blistering heatwaves and bone-chilling cold snaps.

While these will affect localized areas temporarily, one inescapable consequence of the increasing temperatures for costal communities around the globe is rising sea levels. This phenomenon will have even more far-reaching effects, displacing hundreds of millions of people as coastal communities are inundated by water, some permanently.

These South American cities will disappear

While there is no doubt that sea levels will rise, predicting exactly how much they will in any given location is a tricky business. This is because oceans don’t rise uniformly as more water is added to the total volume.

However, according to models from the Intergovernmental Panel on Climate Change (IPCC) the most optimistic scenario is between 11 inches and almost 22 inches, if we can curb carbon emissions and keep the temperature rise to 1.5C by 2050. The worst case scenario would be 6 and a half feet by the end of the century.

Caracol Radio in Colombia asked various artificial intelligence systems which cities in South America would disappear due to rising sea levels within the next 200 years. These are the ones most at risk according to their findings:

  • Santos, Brazil
  • Macaió, Brazil
  • Floreanópolis, Brazil
  • Mar de Plata, Argentina
  • Barranquilla, Colombia
  • Lima, Peru
  • Cartagena, Colombia
  • Paramaribo, Surinam
  • Georgetown, Guayana

The last two will be underwater by the end of the century according to modeling done by the non-profit Climate Central along with numerous other communities in low-lying coastal areas.

Their simulator only makes forecasts until the year 2100 as the above image shows for the areas along the northeastern coast of South America including Paramaribo and Georgetown.

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