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https://www.bleepingcomputer.com/new...blic-roll-out/Leak confirms OpenAI is preparing ads on ChatGPT for public roll out
OpenAI is now internally testing 'ads' inside ChatGPT that could redefine the web economy.
Up until now, the ChatGPT experience has been completely free.
While there are premium plans and models, you don't see GPT sell you products or show ads. On the other hand, Google Search has ads that influence your buying behaviour.
OpenAI is planning to replicate a similar experience.
...
Greed fuels all!
new ways to over customers and employees
https://prospect.org/2025/12/02/pric...he-machine-ai/
A YEAR AGO, I WROTE ABOUT WHAT I TERMED surveillance pricing: companies offering individualized prices based on personal data. The idea was that a business equipped with granular information about demographics, purchase history, social and financial interactions, or even medical status could exploit a customer’s willingness to pay. Uber could charge more when a rider booked on a company credit card; people aren’t as price-sensitive when someone else is paying. Delta could jack up fares after learning that a traveler needs to attend a funeral; desperation could translate into opportunity.
I couldn’t be certain how many businesses used surveillance pricing. The proliferation of third-party pricing consultants touting “digital pricing transformations” seemed like a strong indicator. But concealment was key to the strategy, to minimize the anger generated by charging different prices to different people. For instance, when a reporter at SFGate logged in to hotel booking platforms using his regular IP address in high-wage San Francisco, he received a quote of $829 a night. But when he used a virtual private network set up to originate from Phoenix or Kansas City, prices were more than $500 less. Without a public price, it takes research to understand if someone is being ripped off.
A month after my report, Lina Khan’s Federal Trade Commission announced an investigation into surveillance pricing, seeking information from eight third-party consultants. The agency only had a short time to conduct the study before the changeover of power in Washington. But days before Donald Trump’s inauguration, it issued “research summaries” of the work done thus far. (Trump’s FTC has yet to finish the study.)
Stephanie Nguyen, the FTC’s chief technologist under Khan, told me those eight pricing consultants were working with over 250 clients, suggesting broad reach across the economy. Services included individually targeted pricing, segmentation of customers based on their profiles, and ranking tools that alter what products people see atop a web page or search. A customer clicking on fast shipping, for example, suggests an urgency that would lead them to tolerate higher prices.
The key to surveillance pricing is data. Nguyen and Sam Levine, the FTC’s former head of the Bureau of Consumer Protection, recently wrote a paper about how customers deliver that data when they sign up for loyalty programs. Enticed by promised discounts and concierge treatment, customers consent to data collection that allows companies to build intricate social graphs; one customer profile created by the grocery chain Kroger stretched to 62 pages. The discounts often aren’t maintained or are curtailed, loyalty card fees expand over time, and the more loyal a customer, the more data is collected and the more they pay over time, according to the report.
One case study is the McDonald’s app, which has 185 million users and provides seamless access on smartphones, our personal data-spewing machines. According to a recent earnings call, after downloading the app, a customer goes from 10.5 annual McDonald’s visits on average to 26. McDonald’s clearly wants its customers on the app. Its popular Monopoly game gives out stickers on the packaging of items like Big Macs and fries; you collect the right ones to win big prizes. But this year, instead of filling out a physical game board, Monopoly pieces now must be scanned into the app.
“This is about taxing people who don’t turn over their data, and manipulating people who do,” Levine said. “Do we really want a world in which you will have to pay a premium if you want to shop anonymously?”
The result of these strategies is that supply and demand no longer solely determines price, as in textbook economics. AI-based pricing has become more critical than sale volume or product quality. Customers seeking a fair deal are simply outworked, unable to avoid being targeted. “There used to be moments where you really blew it, you had to buy a last-minute airline ticket and they’ve got you,” said Tim Wu, former compe ion policy chief in the Biden White House. “That’s really daily life now.”
Consumers used to benefit from what economists would call imperfect information. The uncertainty of defining the optimal price, and the ability in open markets for new businesses to undercut compe ors, gave consumers a fighting chance to get a deal, or just to manage their life without being tracked and prodded. Technology eliminates that information inefficiency. “What these technologies are about is eliminating all risk for the shareholder,” Hepner said. “There’s no more error. It is a well-oiled extraction machine.”
Surveillance pricing bills have not seen the same success, though their failure revealed critical information. In California, AB 446, which would have banned pricing based on personal data, was held back, giving sponsors time to build support next year. That’s because businesses across the economy, even ones not suspected of surveillance pricing, swarmed Sacramento to defend their practices. “It was fascinating over the course of that legislative process to see the opposition come out and openly say, ‘Hey, we’re actually doing this, you mean we can’t do this anymore?’” Hepner told me.
Some economists allege that tech pricing crackdowns threaten discounts and other potential benefits for consumers. But it’s hard to believe that companies would hire the most sophisticated engineers to figure out how to reduce their revenues. As Nguyen told me, the argument to preserve discounts boils down to this: “You can have privacy or low prices, but you can’t have both.”
"tech pricing crackdowns"
https://arstechnica.com/ai/2025/12/m...proven-agents/Microsoft drops AI sales targets in half after salespeople miss their quotas
Microsoft has lowered sales growth targets for its AI agent products after many salespeople missed their quotas in the fiscal year ending in June, according to a report Wednesday from The Information. The adjustment is reportedly unusual for Microsoft, and it comes after the company missed a number of ambitious sales goals for its AI offerings.
AI agents are specialized implementations of AI language models designed to perform multistep tasks autonomously rather than simply responding to single prompts. So-called “agentic” features have been central to Microsoft’s 2025 sales pitch: At its Build conference in May, the company declared that it has entered “the era of AI agents.”
The company has promised customers that agents could automate complex tasks, such as generating dashboards from sales data or writing customer reports. At its Ignite conference in November, Microsoft announced new features like Word, Excel, and PowerPoint agents in Microsoft 365 Copilot, along with tools for building and deploying agents through Azure AI Foundry and Copilot Studio. But as the year draws to a close, that promise has proven harder to deliver than the company expected.
According to The Information, one US Azure sales unit set quotas for salespeople to increase customer spending on a product called Foundry, which helps customers develop AI applications, by 50 percent. Less than a fifth of salespeople in that unit met their Foundry sales growth targets. In July, Microsoft lowered those targets to roughly 25 percent growth for the current fiscal year. In another US Azure unit, most salespeople failed to meet an earlier quota to double Foundry sales, and Microsoft cut their quotas to 50 percent for the current fiscal year.
...
Having the best year of his life under Trump and then Elon saves his life...lucky man
cool anecdote
snacks doesn't us AI.
WASHINGTON, Dec 8 (Reuters) - The U.S. Commerce Department is prepared to allow Nvidia's H200 chip to be exported to China, a person familiar with the matter told Reuters.
China good now.
You fell in line.
You always do.
is this a death panel?
In January, the federal Centers for Medicare & Medicaid Services will launch the Wasteful and Inappropriate Services Reduction (WISeR) Model to test AI-powered prior authorizations on certain health services for Medicare patients in six states: Arizona, New Jersey, Ohio, Oklahoma, Texas and Washington. The program is scheduled to last through 2031.
The program effectively inserts one of private insurance’s most unpopular features — prior authorization — into traditional Medicare, the federal health insurance program for people 65 and older and those with certain disabilities. Prior authorization is the process by which patients and doctors must ask health insurers to approve medical procedures or drugs before proceeding.https://stateline.org/2025/12/04/med...ors-lawmakers/The companies get paid based on how much money they save Medicare by denying approvals for “unnecessary or non-covered services,” CMS said in a statement unveiling the program.
one wonders how much of AI is just human drudges impersonating AI or at least, cleaning up and fine-tuning it
This technology will destroy all your jobs and render you useless to society. You should adopt it today, and subscribe to our product so we can make more money!
So scared
you're a terrible reader, period
^doesn't use AI
Trump's EO purporting to limit the ability of US states to regulate AI puts South African billionaire crony David Sacks in charge of determining who's in compliance or not
https://www.whitehouse.gov/president...igence-policy/
having lived through the Tipper Gore PRMC furore, it's striking that AI suicide machines -- er, companion chatbots -- are being treated as an inevitability
https://futurism.com/artificial-inte...chatbots-kenyaDuring a period of desperation in which he struggled to find a job in his trained field of global aviation, a Kenyan man named Michael Geoffrey Asia writes for the initiative that he was introduced to the world of data labeling and chat moderation. In Asia’s case, the “chats” turned out to be “romantic and intimate conversations on platforms I’d never heard of.”
Though it was far from what he had planned to do after graduating from aviation school, he took on a job as a “text chat operator” with the Australian firm New Media Servicesin order to feed his family. He made his home, he writes, in the Mathare slums of Nairobi, and it was all he could do to keep a roof over their heads.
“What I didn’t know was that the role would require me to assume multiple fabricated iden ies, and use pseudo profiles created by the company to engage in intimate and explicit conversations with lonely men and women,” Asia writes.
To do the job, Asia had to assume various iden ies, taking on lengthy backstories in order to play the role of “chatbot” for someone on the other side of the world. “Sometimes I would be assigned a conversation that had been ongoing for several days and had to continue it smoothly so the user wouldn’t realize the person responding had changed,” he wrote.
In any given work day, Asia would assume “three to five different personas” simultaneously, all of varying genders. He was paid per message, a flat rate of $0.05 per, which had to meet a required character count. He also had to type at least 40 words a minute, and keep up with a dashboard displaying the total number of messages sent.
“Falling behind on metrics could lead to warnings, reduced assignments, or termination,” Asia explained.
The work was emotionally exhausting, with chat users confiding intimate details about their real-life relationships, as well as their own emotional trauma, falsely believing they were talking to an unfeeling AI chatbot.
“My faith taught me that love should be real, intimacy sacred, and that deception was destructive to both the liar and the deceived,” Asia wrote. “Yet here I was, professionally deceiving vulnerable people who were genuinely looking for connection — taking their money, their trust, their hope, and giving them nothing real in return.”
In order to hide his demeaning job, Asia used a cover story with his family: that he was a remote IT worker, taking tickets to fix broken servers. “Little did they know that I had just told another man, ‘I love you,'” Asia wrote.
There was also a non-disclosure agreement, a mandatory contract that meant Asia couldn’t tell his loved ones even if he wanted to. “How do you explain that you get paid to tell strangers you love them while your real family sleeps three meters away?” he writes.
Asia’s story of work-life struggle is heartbreaking, and he’s far from alone. Though exact numbers are hard to find thanks to the secretive nature of tech subcontracting, estimates suggest there are between 154 and 435 million gig workers engaged in online work. Not all of them are doing Asia’s job, though high-stress, low-pay jobs like AI data labeling, content moderation, and text chat operation tend to be staffed by workers from underdeveloped African, South American, and Southeastern Asian nations.
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