Online Businesses and Franchises Being Scammed By Generative AI

Sometime last year, Ian Lamont's inbox began piling up with inquiries about a job listing. The Boston-based owner of a how-to guide company hadn't opened any new positions, but when he logged onto LinkedIn, he found one for a "Data Entry Clerk" linked to his business's name and logo.

As reported by Business Insider, Lamont soon realized his brand was being scammed, which he confirmed when he came across the profile of someone purporting to be his company's "manager." The account had fewer than a dozen connections and an AI-generated face.

He spent the next few days warning visitors to his company's site about the scam and convincing LinkedIn to take down the fake profile and listing. By then, more than twenty people reached out to him directly about the job, and he suspects many more had applied.

Generative AI's potential to bolster business is staggering. According to one 2023 estimate from McKinsey, in the coming years it's expected to add more value to the global economy annually than the entire GDP of the United Kingdom. At the same time, GenAI's ability to almost instantaneously produce authentic-seeming content at mass scale has created the equally staggering potential to harm businesses.

Since ChatGPT's debut in 2022, online businesses have had to navigate a rapidly expanding deepfake economy, where it's increasingly difficult to discern whether any text, call, or email is real or a scam. In the past year alone, GenAI-enabled scams have quadrupled, according to the scam reporting platform Chainabuse.

In a Nationwide insurance survey of small business owners last fall, a quarter reported having faced at least one AI scam in the past year. Microsoft says it now shuts down nearly 1.6 million bot-based signup attempts every hour. Renée DiResta, who researches online adversarial abuse at Georgetown University, tells me she calls the GenAI boom the "industrial revolution for scams" — as it automates frauds, lowers barriers to entry, reduces costs, and increases access to targets.

The consequences of falling for an AI-manipulated scam can be devastating. Last year, a finance clerk at the engineering firm Arup joined a video call with whom he believed were his colleagues. It turned out that each of the attendees was a deepfake recreation of a real coworker, including the organization's chief financial officer. The fraudsters asked the clerk to approve overseas transfers amounting to more than US$ 25 million, and assuming the request came through the CFO, he green-lit the transaction.

Business Insider spoke with professionals in several industries — including recruitment, graphic design, publishing, and healthcare — who are scrambling to keep themselves and their customers safe against AI's ever-evolving threats. Many feel like they're playing an endless game of whack-a-mole, and the moles are only multiplying and getting more cunning.

Last year, fraudsters used AI to build a French-language replica of the online Japanese knives store Oishya, and sent automated scam offers to the company's 10,000-plus followers on Instagram. The fake company told customers of the real company they had won a free knife and that all they had to do was pay a small shipping fee to claim it — and nearly 100 people fell for it. Kamila Hankiewicz, who has run Oishya for nine years, learned about the scam only after several victims contacted her asking how long they needed to wait for the parcel to arrive.

It was a rude awakening for Hankiewicz. She's since ramped up the company's cybersecurity and now runs campaigns to teach customers how to spot fake communications. Though many of her customers were upset about getting defrauded, Hankiewicz helped them file reports with their financial institutions for refunds. Rattling as the experience was, "the incident actually strengthened our relationship with many customers who appreciated our proactive approach," she says.

For now, small business owners should stay vigilant, says Robin Pugh, the executive director of Intelligence for Good, a non-profit that helps victims of internet-enabled crimes. They should always validate they're dealing with an actual human and that the money they're sending is actually going where they intend it to go.

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Google Hurricane Model Tries Forecasting Events

A few weeks ago, Google DeepMind and Google Labs released the latest AI hurricane model to the public. The Google team claims its AI model performs better than traditional hurricane models on both track and intensity forecasts.

This AI model is not a traditional physics-based model like the ECMWF (European) or the GFS (American) model.

Models like the ECMWF (European) use numerical weather prediction, solving fluid dynamics, thermodynamics, and radiation equations on a high-resolution global grid. This requires immense computational resources and supercomputer infrastructure. Just one run can take several hours for the supercomputers to finish. (It is worth mentioning that ECMWF also has an AI model)

The Google AI Model is built on a trained neural network, which mimics the human brain, that can make inferences almost instantly after training. It learns from decades of vast historical weather data – essentially doing very advanced pattern recognition, thus it outputs forecasts without solving the complex differential equations of physics. So the process takes just a minute to complete a 15-day forecast.

Just like the ECMWF (European) model, Google’s AI model produces 50 ensemble members. The ensemble members are solutions that are each slightly perturbed. Think of it as a family of solutions rather than just one track and intensity.

Google claims that in tests for 2023–24 storms in the North Atlantic and East Pacific, its 5-day track forecasts were ~85 miles closer to actual tracks than ECMWF’s ENS ensemble and their AI model outperformed NOAA’s best intensity model – the HAFS model – on intensity forecasts, matching or exceeding high-resolution physics-based accuracy.

To truly be able to judge the accuracy of the Google AI model – or any model – researchers need lots more data. So, this 2025 hurricane season, expect many scientists to monitor the model to see how it performs.

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About 16 B Passwords Were Compromised

There were about 16 billion passwords to Apple, Facebook, Google, and other social media accounts, as well as government services, that were leaked in what researchers are calling the largest data breach ever, according to reports.

The leak exposed 16 billion login credentials and passwords, prompting both Google to tell billions of users to change their passwords and the FBI to warn Americans against opening suspicious links in SMS messages, according to a report published a few days ago in Forbes.

Researchers at Cybernews, who have been investigating the leak, found "30 exposed datasets containing from tens of millions to over 3.5 billion records each."

All but one of these datasets have not been previously reported as being exposed, so the data impacted is all considered new.

"This is not just a leak – it’s a blueprint for mass exploitation," the researchers said. And they are right. These credentials are ground zero for phishing attacks and account takeover. "These aren’t just old breaches being recycled," they warned, "this is fresh, weaponizable intelligence at scale."

Most of that intelligence was in the format of a URL, followed by logins and passwords. That information then allowed access to "pretty much any online service imaginable, from Apple, Facebook, and Google, to GitHub, Telegram, and various government services."

While worrisome, the researchers found that the datasets were exposed very briefly – with enough time for them to be discovered, but not long enough for researchers to figure out who was controlling the data.

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Sabrina Carpenter's Funny Response To Critics

Pop singer Sabrina Carpenter is barking back at the backlash surrounding her suggestive album cover.

The outspoken star is set to release her new album "Man's Best Friend" on 29 August, but the 26-year-old "Espresso" hitmaker took to social media last 25 June, to sarcastically slam critics of her provocative album cover.

In her caption, Carpenter wrote that she "signed some copies of Man's Best Friend for you guys & here is a new alternate cover approved by God available now on my website" alongside a white heart emoji.

The breakout singer's 11 June album announcement garnered criticism with its imagery showing Carpenter, dressed in a black dress and high heels, kneeling on the ground in a dog-like pose while an unidentified man stands off to the side and pulls her by the hair.

In the new photos, Carpenter faces the camera and looks away in two separate shots – one close-up and another full-body photograph – as she stands and holds onto a man, with her hands on his arm and back.

"Man's Best Friend," Carpenter's seventh studio effort, follows the release of her breakthrough 2024 album "Short n' Sweet," which catapulted her to superstardom after the former Disney star worked for years in the music industry.

The album, which peaked at No. 1 on the Billboard 200 chart, spawned the hit singles "Espresso," "Please Please Please," "Taste" and "Bed Chem," as well as solidified the singer's playful pin-up girl image.

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Breathalyzer Will Someday Detect Diseases

There is a new breathalyzer-like system that could one day detect illnesses by spotting biological markers in the air we exhale, researchers report.

The hope is that this could simplify medical diagnoses by making health monitoring as simple as breathing into a device, the scientists say. Their prototype device, called the airborne biomarker localization engine (ABLE), condensates airborne molecules into concentrated liquid droplets.

The droplets ABLE generates are compatible with existing tech, including simple test strips, making the "platform both highly accessible and very low-cost," study co-author Bozhi Tian, a professor at the University of Chicago, told Live Science in an email. The scientists described ABLE in a report published 21 May in the journal Nature Chemical Engineering.

"As a researcher working on biosensing and bioelectronics, I am very excited to see this work," said Jinghua Li, an associate professor in the Department of Materials Science and Engineering at The Ohio State University, who was not involved in the study.

"Airborne biomarker detection has long attracted significant interest, though achieving the required sensitivity has remained a challenge," Li told Live Science in an email. Once the technology is validated, "users could simply exhale onto a test strip and receive a health assessment within minutes in the future," she said.

Many diagnostic tests require blood draws, saliva swabs or urine samples — but collecting such samples can introduce risk, inconvenience, or both to patients. Sampling breath could help sidestep these problems.

The body emits volatile organic compounds (VOCs) — small organic molecules that are typically gaseous at room temperature — and these can be found in human breath. Studies suggest that specific chemicals can be tied to medical conditions, making them a potential tool for diagnosis. Several scientists recently compiled a database of 327 different breathborne VOCs that have also been tentatively linked to diseases, including asthma, diabetes and lung cancer.

However, there's a difficulty in using VOCs for diagnostics: they are present at incredibly low concentrations, sometimes numbering as few as 1 in a trillion particles of exhaled air. This makes monitoring these compounds challenging.

Now, ABLE can suck in exhaled air through a pump, add water vapor via a humidifier, and cool the mixture to cause condensation. This changes the airborne compounds into concentrated droplets that slide into a collection reservoir, ready for testing.

The prototype device measures 4 by 8 inches (10 by 20 centimeters) and costs less than US$ 200 to build, according to Tian. It can collect about 1 milliliter of condensate in 10 minutes, providing enough sample for existing liquid-detection methods to analyze.

As proof of concept, the researchers tested ABLE's ability to collect several airborne chemicals. One experiment looked for glucose in exhaled human breath, confirming that the samples were not too dilute and could be accurately tied to blood-sugar concentrations in the blood. "The high sensitivity of ABLE allows the usage of glucose test strips as the downstream sensors," the researchers reported.

The team also ran experiments with "humanized" lab mice imbued with microbes from human infants, who were born either preterm or full-term. They compared the concentrations of glycosphingolipids — known regulators of inflammation — in the breath of the two sets of mice, finding higher levels in the "preterm" group.

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