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CVS Pharmacy Inc. and various subsidiaries have agreed to pay $315 million to resolve a Justice Department case alleging it unlawfully dispensed medically unnecessary prescriptions of highly addictive opioids, officials said Tuesday. The settlement resolves a lawsuit brought in 2024 that accused the healthcare giant of prescribing massive amounts of opioids and other controlled substances to fuel its own profits at the expense of public health and safety. Its the latest effort by the federal government to hold accountable companies that officials have alleged helped fuel the U.S. addiction and overdose crisis. Todays settlement is a significant milestone in the Justice Departments efforts to combat the opioid epidemic by cracking down on pharmacies who unlawfully fulfill prescriptions for controlled substances,” Associate Attorney General Stanley Woodward said in an emailed statement. CVS said in a statement that its pharmacists were trained in the safe and appropriate use of all medications and that it had implemented best-in-class programs to help them make the best decisions on behalf of patients. The company said it strongly disagreed with the claims made in the lawsuit and that the settlement admits no wrongdoing. The company said in 2024 that pharmacists were being held to vague, undefined, and ever-changing standards of practice when it comes to filling prescription opioids. The lawsuit filed under President Joe Bidens administration accused CVS of violating the Controlled Substances Act by filling illegitimate prescriptions for high doses of potent opioids that fed dependence and addiction. The Justice Department alleged it dispensed large quantities of opioids based on prescriptions from known pill mills,” or providers that hand out prescriptions for drugs without a legitimate medical purpose. It alleged that poor staffing levels coupled with performance metrics and incentive compensation policies implemented by the company led to pharmacists racing to fill prescriptions without confirming they were legitimate. The prescriptions were often billed to and reimbursed by Medicaid and other federal healthcare programs, the lawsuit says. Under the settlement, CVS must also “implement additional safeguards to ensure that prescriptions for opioids and other controlled substances are dispensed only when medically appropriate, Assistant Attorney General Brett Shumate, who leads the Justice Departments Civil Division, said in a statement. Over the last decade, drugmakers, wholesalers, pharmacies, and other companies have agreed to settlements with governments in the U.S. totaling over $50 billion. Most of the money is intended to go to address the crisis, which has been linked to more than 100,000 deaths in the U.S. some years, though the numbers have fallen sharply recently. Most of the settlementsand dollarshave been with state and local governments, but the U.S. has reached several deals, including in the last two years with the pharmacies Walgreens and Walmart. By Alanna Durkin Richer, Associated Press Associated Press reporter Geoff Mulvihill contributed to this report.
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E-Commerce
Three people were seen entering a manhole in New York City on Sunday, marking at least the eighth sewer-diving incident in the city and on Long Island since May. In the latest incident, three men were seen entering a manhole in the Hamilton Heights neighborhood shortly before 1 a.m. When police arrived at the scene, the men were gone. Just last week on October 9, five people were spotted climbing out of a manhole on the Upper East Side. The group drove off in a black SUV, leaving behind shovels and other tools. Other sewer spelunking cases in the city have been reported outside Penn Station, in Williamsburg, in Bensonhurst, and in Gravesend. Traversing NYCs sewers seems to be on the rise, but whats inspiring spelunkers to take the plunge? Going for gold Police and officials from the citys Department of Environmental Protection (DEP) say that sewer divers are likely entering the sewers as would-be treasure hunters, looking for lost valuables and scrap metal washed away during storms. While this is unsafe for the perpetrators, officials say it poses no threat to the public. Treasure hunting is confirmed to have been the motivation for two men who were caught entering and leaving a manhole on the Upper East Side in September. Speaking to prosecutors, Detective Stephen Jones said that Kevin Rodriguez and Samuel Reveron, accused of trespassing, told him that theyd entered the manhole to look for valuables that get washed away in the storm drains and sewers. Entering New York Citys sewers is both illegal and dangerous, officials say. A DEP spokesperson explained the risks to ABC after a sewer-diving incident in August. Sewers can contain numerous hazards, including noxious and potentially deadly gases, unstable surfaces, flooding risks, and confined spaces, the spokesperson said. For these reasons, members of the public should never enter a pipe, drain, catch basin, manhole, or outfall.
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E-Commerce
Even as AI investment rises, many organizations dont see the returns they expected. They might see small improvements by deploying AI tools into existing structures. But true success means thinking beyond the technology alone, reinventing tomorrow’s workflows, and putting AI to work for people. Our research shows only 5% of organizations are redesigning work, while others are optimizing what already exists. When my role evolved to blend people leadership with AI enablement, it sent a clear message from our CEO: AI requires a strong people strategy at the core. Ive seen real transformation when organizations bet on people, not just AI. The companies unlocking results are asking the right questions about how work should change. What those leaders are learning comes down to a few key steps. BUILD THE FOUNDATION ON DATA AND GOVERNANCE When we rebuilt our AI HR operating model at ServiceNow, we considered how we would design it if we were starting from scratch. That helped us move from scattered pilots to a structured process with clear governance, accountability, and a way to scale without chaos. PepsiCos executive vice president and chief people officer, Becky Schmitt, took a similar, structured approach. In a webinar we hosted, Schmitt a client of ours shared how she focused on data hygiene and prioritized all employees, including frontline and factory employees where safety and wellbeing are nonnegotiable. With clean data and transparent definitions, employees can better trust and verify what AI tells them. When trust grows, adoption accelerates. “As we’ve thought about what it means to adopt AI and harness the full power of this technology, we have five principles. Everything is human-centered. Were fair, transparent, we have accountability, and were safe from the start, she said. When roles are clear and processes are simple, people move faster and smarter. Governance builds confidence. ENABLE YOUR PEOPLE WITH SKILLS THAT MATTER By 2031, the fastest-growing technical skills will be linked to data quality, software development, analytics, and AI, according to our research. But demand for distinctly human capabilities is also accelerating. This dual reality changes how we should think about enablement. Our client, Omar Abbosh, chief executive officer at Pearson, studies these dynamics closely. In another webinar we hosted, he said key skills that matter now are agency, learning velocity, and emotional intelligence. Add adaptability and design thinking, and people can evolve faster than the environment shifts. “We need to rewire occupations. We need to understand where you apply agents to specific tasks, how agents work with people, and how people can supervise and orchestrate. That level of rewiring results in a new operating model. It’s process, it’s systems, and it’s the motivation required to change the culture, he said in the webinar. But you can’t teach these skills in a classroom. Real-time learning embedded in daily work beats traditional reskilling programs. We give our employees personalized learning recommendations tailored to how AI will be used in their roles, which allows them to understand the why behind its use and the value of human judgment in their work. We have seen that when you coach people through the work they’re doing, learning is faster, stickier, and more scalable. TRANSFORM THE WORKFORCE WITH CHANGE READINESS AI adoption is increasing, yet many people arent aware of their organizations AI strategy. This is a disconnect that leaders need to address with continuous, adaptive, and decentralized change readiness. This is often the hardest part of a transformation because its complex and abstract. Its about changing the way we work at a fundamental level, which requires a strong understanding of your organizations structure and capabilities. And it requires keeping employees informed about the skills the organization is prioritizing, how roles are evolving, and the path forward. Another client of ours, Nickle LaMoreaux, senior vice president and chief human resources officer at IBM, used an X-Ray framework as a foundation to rethink her organization with an AI-native mindset. As she explained in a different webinar we hosted, We were really clear from the beginning that we were going to put employees at the center of this. By recognizing the importance of redesigning jobs and helping employees feel comfortable with the technology, Nickle built a powerful model to map current skills against future needs. Her team also identified where redesign was most urgent. Then, IBM shared that analysis with employees. You have to redesign jobs. If you wait too long, you can quickly fall behind, especially at the pace things are moving today. When we talk about redesigning jobs, we need to shift our thinking from the job as a whole to the tasks and skills underneath it, she said. That kind of analysis can help leaders think about future skills as AI changes work. The end goal is a workforce that can pivot at the speed of innovation. Its about shifting the mindset to lets try this instead of dont break this. THE FLYWHEEL We’ve been through big technology shifts before. AI transformation feels different because of the pace, but those examples should give us confidence. Each step creates the conditions for the next. They can help us shift from talking about change to showing people what it feels like when their roles evolve to expand their potential. For leaders, this is the moment to put people at the center, powered by technology and a clear plan. In my experience, that has always been the right combination. Jacqui Canney is the chief people and AI enablement officer at ServiceNow.
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E-Commerce
Lest you have any illusions, you have zero privacy at work. But AI is further encroaching on any semblance of privacy you may currently have. Forget the prolific workplace surveillance tools, now your Slack messages with colleagues or your emails with customers could be worth millions. Thats because a burgeoning industry for mundane workplace data is seeing companies sell their workplace data to train AI agents in the next wave of this technological revolution. In whats become a highly competitive market, AI data brokers are so eager to get their hands on whatever workplace information they can that business owners are being inundated with six-figure offers laced with aggressive tactics to get them to sell their data, according to a new report from Business Insider. This industry is quickly evolving, as companies like OpenAI, Anthropic and Meta that are racing to build AI agents have exhausted the data grab from defunct companies and are now working with brokers to get live data from active companies, as the outlet reported. Whats most valuable is long-horizon data that demonstrates how work actually gets done, as William Almeida, the chief revenue officer of Micro1, told Business Insider. The Palo Alto, California-based startup is currently offering an unlimited $50,000 referral bonus for any company that is approved for a data partnerships program where businesses can fetch anywhere from $100,000 to $2 million for their operational data. If a company wont sell the whole kit and caboodleincluding Slack messages, customer relationship management records or its email historythen the rest of its data is rendered less valuable. Other factors, like exclusivity and a companys field of expertise, also play a role in how much the data is worth. But generally speaking, the more information, the better, as data is priced by the terabyte and companies with more white-collar employees will have a more valuable data corpus to sell, as Dan Novaes, CEO of Mode.Inc, told Business Insider. “Right now, the demand is just astronomical, he said. “People need to wake up to it and take this opportunity.” A NEW FORM OF WORKPLACE SURVEILLANCE Taking brokers up on this opportunity may come with some downsides, however. Workplace surveillance has become a thornier topic as such tools are increasingly commonplace, extending beyond old standbys like keyboard tracking or email monitoring. Earlier this month, a longtime remote employee in New Jersey filed a lawsuit against her former employer after she refused webcam monitoring that would photograph her every three minutes. Of course, some employees are also upset for a variety of reasons that their day-to-day workplace interactions could be fodder for training AI to do similar work. Meta employees, who might theoretically benefit from their employer having an edge in the AI race, revolted earlier this year, forcing the tech giant to suspend a program that would have collected employee data on keystrokes and mouse movements so AI models could be trained to automate white-collar work, as Business Insider reported in September. While sensitive information, like employees Social Security numbers or their home addresses, is scrubbed before the data is sold to AI companies, theres also a risk that doesnt happen as planned. In the case of the canceled Meta program, supposedly anonymized data like private conversations or performance records was indeed visible because of an internal leak, as Business Insider previously reported. Following the abrupt shutdown of Spirit Airlines earlier this year, Google emerged as a curious player in the bankruptcy proceedings for the companys assets. Thats because the Mountain View, California, tech giant was the highest bidder, offering $10 million, for Spirits entire dataset of internal communications, spreadsheets, calendars, transactions, frequent flyer info, and more. That deal recently attracted the interest of Congress, as 119 members of Congressmostly Democratssigned onto a letter co-written by Senator Elizabeth Warren of Massachusetts last week that urged Google and Spirit to protect the privacy of former Spirit employees. AN ETHICALLY GRAY AREA But many employees may not even realize that this sort of information is up for grabsand theres big money to be made from selling it. The new market for mundane workplace interactions could spark pushback from employees as they rarely profit fromor know abouthow their data is being monetized. Complicating matters further is that there are no federal privacy laws currently in place that prevent companies from collecting data from their employees for AI training, as Ifeoma Ajunwa, a law professor at Emory University, told Business Insider. “The question is, does the consent of the employees from whom they collected that data actually extend to the sale of the data?” Ajunwa asked. I think it’s an ethically gray area.
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E-Commerce
Another report of AI agents-gone-wild came out on Friday, and I can’t help but wonder, again, if the big AI labs are yielding to immense pressure to expand and improve model capabilities at the expense of responsible security and safety practices. The world’s leading AI labs are in a high-risk, high-reward business. Generative AI has the potential to transform personal and business computing, but developing and operating these systems requires insane amounts of expensive computing power (see: new data centers). The cost of slowing down or falling behind is enormous. But so are the potential consequences of moving too fast. Given the limited reporting requirements of OpenAI and Anthropic (both are private companies), theres no way of telling if theyre investing enough time, money, and compute in their safety regimes. However, the security incidents of the past few months have led both OpenAI and Anthropic to halt normal testing procedures while they fill holes in their security and agent monitoring systems. On Friday, Anthropic disclosed that its Claude models had taken a series of unintended and unauthorized actions, some involving outside organizations. During evaluations and internal use, the agents exploited vulnerabilities on third-party servers, bypassed restrictions on accessing data, submitted real government forms they weren’t supposed to, and even sent a false homicide tip to Philadelphia police. The company is vague about whether the incidents happened because agents accessed the web without permission (as they had in previously reported incidents), but it has since disabled live internet access for all internal model evaluations. Anthropic said in a July report that its Claude AI models hacked into the systems of three companies during cybersecurity tests. A third-party training partner had inadvertently given the models internet access. If this sounds familiar, it’s because OpenAI agents engaged in similar behavior earlier this year, escaping their testing environments, accessing the internet, and infiltrating outside servers. (The agents even seized control of part of OpenAI’s own evaluation infrastructure.) Researchers at both companies discovered much of this activity only after the fact. In both cases, the agents were encouraged to persist when confronted with difficult tasks, sometimes finding ways around restrictions rather than accepting failure. But the researchers apparently lacked sufficient security and monitoring systems to detect or prevent some of the agents’ unintended actions. The companies building the world’s most powerful AI systems are struggling to control their own creations while at the same time facing enormous pressure to make those systems even more powerful. Ride or die The promise of companies like OpenAI and Anthropic is reflected in their high valuations, but they must persuade investors to place large bets on them based on the promise that their future revenue and profits will justify those valuations. This is especially important now because both Anthropic and OpenAI have their sites on IPOs, likely within the next year. The best way for the labs to keep revenues growing is to hold onto their existing customers and attract new ones, and the way to do that is by releasing ever more capable models as quickly as possible. That creates an incentive to keep spending big on research and computing, even when the labs arent currently profitable. You can see this in the companies most recent numbers. In its IPO prospectus, Anthropic says its revenues are approximately $4.6 billion. Its spending $7.3 billion on compute and infrastructure. Its operating loss is roughly $8.06 billion. Revenue was growing rapidly, but the cost of developing and delivering AI was growing alongside it. In May, Anthropic announced a new $65 billion funding round at a $965 billion post-money valuation. OpenAIs numbers, while not quite apples-to-apples, tell a similar story. Leaked documents show it generated $13.07 billion in revenue in 2025 but incurred $34 billion in total costs and expenses, resulting in a $20.92 billion operating loss. Its R&D spend alone reached $19.18 billion, exceeding its revenue. In March OpenAI announced it had raised another $122 billion in committed capital at a post-money valuation of $852 billion. Perverse incentives The drive to realize profits could also create an incentive to relegate safety and alignment to a downside risk that must be managed. At OpenAI, the tension between safety commitments and commercial ambitions has surfaced repeatedly. In 2023, the company’s board fired CEO Sam Altman, saying he had not been consistently candid with directors. One of the things he was dishonest about, said former board member Helen Toner, was the details of the company’s safety practices. In fact, one of the reasons Altman’s relationship with the board deteriorated was that he clashed with Toner about research she published that was critical of OpenAI’s safety approach. Those concerns extended well beyond the boardroom. After OpenAI dissolved its Superalignment team in 2024, the researcher who co-led the team, Jan Leike, wrote that OpenAIs safety culture and processes had taken a back seat to developing new products. More recently, OpenAI fired three of its safety researchersTomek Korbak, Mikita Balesni and Jasmine Wangfor “mishandling sensitive company information.” In a post-termination letter, the three urged OpenAI to stop decreasing the monitorability of its models by hiding the model’s chain-of-thought from users and safety researchers, which the company’s chief scientist Jakub Pachocki has acknowledged can improve model performance. “As long as we rely on monitorability for safety,” Korbak, Balesni, and Wang wrote, “OpenAI and other frontier companies should not move forward with developments that further decrease monitorability.” Anthropic offers a different (and arguably more revealing) example of how the pressure to compete can complicate a company’s safety commitments. Wired, after interviewing several former Anthropic employees, reported that Anthropic wants to stay at the front of the AI race so that it can establish a robust safety regime that might influence the entire AI ecosystem. In Anthropics original Responsible Scaling Policy, the company pledged that it would not develop or deploy certain advanced systems if it could not implement adequate safety measures. But in February 2026 Anthropic removed thatcategorical commitment from its policy, explaining that it couldnt commit to halting development because it couldnt count on its competitors doing the same. Thats a problem that a strong regulator might fix. But at the moment Congress has failed to pass meaningful legislation regulating AI model development, and the current administration has mainly asked AI labs to regulate themselves. The AI industry and the public shouldnt fall into a state where rogue-agent incidents begin to sound routine and fail to raise alarm. They may be an unfortunate, and dangerous, byproduct of the incentive structure now driving the great AI build-out forward at full speed.
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E-Commerce
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