Meta has hit pause on new terms of service for its business customers that would have granted it the right to grab any content from their websites. Not only that, but it would also have shifted the blame for every error produced through faulty AI to its customers.

The new terms of service were revealed on October 19 and initially due to take effect on October 30, though Meta later pushed the start date back to November 20.

But that small delay wasn’t enough to calm customer pushback, and now Meta has posted a note on Facebook’s business help center saying that the update had now been paused indefinitely.

Given the strength of feeling, Meta’s U-turn will not have come as a surprise. The terms would have been seen as far too onerous for customers, as well as exposing them to a legal minefield of the sort that UK regulators recently warned about.

In a statement to Harvard’s Nieman Lab, the company said that “We’re pausing the changes as we continue to engage with stakeholders and take our time to get this right.”

Meta has had a troubled time recently. Two weeks ago, it was fined for illegal use of customers’ data and in May, the company laid off 8,000 employees.

In Meta commercial terms changes slated to kick in on October 30, the company will shift the liability for any mistakes made by its AI models to its enterprise customers. The new language also makes those IT executives responsible for anything done by a partner or contractor.

The changes also finally put a stake into the heart of robots.txt, with Meta granting itself the right to grab, and use for its own purposes, any content associated with a Meta account.

The language allows Meta to “use automated software such as web scrapers, bots, robots, spiders, crawlers, and user agents and create test credentials to access, index, cache, analyze, collect, retrieve, or crawl the domains, web pages, or URLs, and any content available through them, that are associated with your products or services,” according to the new language on its website on Monday. Meta also wants to be able to “periodically pull updates from such domains, web pages, or URLs in order to provide, develop, improve, research, and maintain advertising and business products including business, commercial and related products to help you create and deliver ads and other commercial content.”

Consultants said the three biggest concerns they had about the changes were the web scraping, data ownership, and AI liability transfer.

Web scraping and data ownership

However, Meta emailed a statement to CIO.com late Monday suggesting that it was rethinking its position on web scraping. Saying that Meta wanted “to clarify” the web scraping changes, Emil Vazques, a Meta public affairs manager, said, “the crawling terms we consolidated only applied to our ads and business products and we’ve clarified that in the terms themselves. It does not change how Meta uses web crawlers. As always, content owners can use robots.txt to signal their preferences. This is not about scraping news sites, and these updates don’t give us new rights that supersede those preferences.”

As of Monday evening, New York time, the proposed document’s wording had yet to be altered to reflect this, but Vazques said that a change was coming soon.

The data ownership issue sets Meta apart from other AI vendors in that it wants to train its models on anything it encounters. Then again, the nature of Meta businesses focuses on advertising and would therefore be expected to seek more data control.

The new proposed phrasing, which Meta could alter before it takes effect later this month, said that using any Meta product grants Meta “a license to content that is covered by intellectual property rights like photos or videos you share, post, or upload on or in connection with our Meta Company Products. That license applies to content you or someone on your behalf, such as your agency that places an ad for you or your service provider that manages your Page content for you, makes available on or in connection with any Meta Company Products. Without limiting anything in our terms and for clarity, Meta may use such content … to provide, develop, improve, research, and maintain Meta Company Products.”

AI liability

But the change that prompted the most raised eyebrows involved AI liabilities. 

The proposed language said, “AI features may make mistakes and may not always produce accurate, complete, or suitable results,” and customers “are solely responsible for and assume any and all risks associated with such AI features and any resulting content.”

That AI clause, said Frank Dickson, principal analyst at Dickson Research, “turns accountability upside down. Meta builds the AI features, admits they ‘may make mistakes’ and then assigns ‘any and all risks’ to the business.”

Mike Wilkes, enterprise CISO at Aikido Security, agreed that the move is perplexing.

“The new AI provisions shift substantial responsibility for inaccurate or unsuitable outputs onto customers. That makes no sense,” he said. “As an example, the ASPCA is going to be liable for Meta creating unsuitable results when they ask Meta to create an image of a dog. Only Meta has control of the model being used to create that image. I see a very high flight risk among enterprise customers when platforms impose such onerous terms and conditions around content usage.”

The October 30 date that the US-based Meta chose is ironic. That is the day before Halloween, which is known as mischief night in the US, when children play pranks on their neighbors. Given that, Dickson said, the date for these changes is appropriate: “Meta is handing out the tricks and keeping the treats.” 

He added that the data grab is frightening. “What Meta wants is content: what a business posts, uploads, or shares on or in connection with Meta’s products,” he noted. “The trouble is the phrase ‘in connection with,’ which can stretch as far as Meta needs it to. The list of ‘Meta Company Products’ lives on a separate page that Meta can revise at will. The license grows every time that list does.”

And, Dickson noted: “Meta may use the content to ‘provide, develop, improve, research, and maintain’ its products. Those five verbs cover nearly everything a technology company does.”

‘Legal sophistry’

One of the obvious defensive measures for an enterprise is to sever all relations with Meta. But beyond the pragmatic difficulties of doing that, given the powerful market share enjoyed by Facebook, WhatsApp, Instagram and Threads, such a move may not even solve the problem. That is because Meta made other contract changes in July that make Meta licenses “perpetual” and that said, “this license survives termination of these terms by any party for any reason.”

That, said Noah Kenney, principal consultant at Digital 520, means that the “the general content license ends when content is deleted from Meta’s systems,” not when the enterprise ends a contract.

One additional twist to the new language is that Meta had recently tweaked it to no longer explicitly say that it would train it models on enterprise data. But Thomas Randall, a research director at Infotech, said that the wording change made by Meta amounted to legal sophistry. “The revised version drops the word ‘train’ and states that collection is just for developing and maintaining advertising and business products, alongside protecting Meta products’ integrity and security.”

But dropping the word “train” is “not a substantive fix,” he pointed out. “The revised terms are still flexible enough to cover most AI work. When combined with other aspects of the revised terms — continued use equals consent, broad indemnity, AS-IS disclaimer, and Meta’s freedom to discontinue products without notice or liability — this is a one-way street. The difference between ‘train Meta products’ and ‘developing and maintaining Meta products’ is a matter of how you pronounce tomato.”

Could force IT strategy changes

In addition, Aman Mahapatra, chief strategy officer for technology consulting firm Tribeca Softech, stressed that this contract could be an industry admission that robots.txt no longer delivers any meaningful protections. Agentic systems had already made robots.txt close to irrelevant. 

“October 30 ends a thirty-year assumption that robots.txt protects what you publish. It never did,” Mahapatra said. “It was a courtesy convention the web agreed to honor, and Meta’s own framing of robots.txt as a place for site owners to register preferences tells you exactly how it will be weighed against a signed contract.”

Mahapatra said the language in the new Meta commercial terms could force a significant change in IT strategy.

“‘On your behalf’ extends the license to whatever your agencies and vendors upload. ‘Associated’ extends the crawl to domains nobody has defined, including the ones where marketing pages sit beside product documentation, research, and investor materials,” Mahapatra said. “Most CIOs cannot tell me how many Meta pages, ad accounts, and WhatsApp numbers carry their brand, because marketing and agencies own them and IT never inventoried them.”

California is setting a precedent for AI use in scenarios where workers’ jobs are at stake.

Governor Gavin Newsom this week signed the No Robo Bosses Act (SB 947), which bans employers from relying solely on AI-powered automated decision-making systems (ADS), also known as “bossware,” to discipline or terminate workers.

Introduced by Senator Jerry McNerney, the act is the first of its kind in the US. It is set to take effect on July 1, 2027.

While applauded by many, on a wider scale, No Robo Bosses raises questions about what adequate human oversight looks like in this age of AI.

“A machine can recommend, but a human must decide,” noted Frank Dickson of Dickson Research. “The hard part is defining what ‘decide’ means.”

Combating AI bias and ‘troubling’ errors

ADS platforms are becoming ever more prevalent in hiring, as they promise to speed up and streamline HR processes, maximize productivity, and reduce costs. According to reports, more than half of employers use ADS to help make decisions around restructuring and role planning.

But, McNerney and others contended, AI is prone to bias and misjudgment, and there are examples of ADS making “troubling” errors, including mistaken firings. Meanwhile, on-device “bossware” or “tattleware” employee monitoring and productivity tracking software could potentially be used in reprimanding or firing decisions.

AI recruitment tools have similarly come under scrutiny of late, with job seekers alleging that platforms like Workday discriminate based on age, race, and disability.

To combat these issues, the bill, SB 947, seeks to set guardrails around AI use in the workplace. The legislation mandates human oversight and verification when enterprises apply ADS tools, and employers must inform workers if they have used them when making decisions about their jobs.

Further, SB 947 prohibits the use of ADS and bossware systems that analyze personal information and behaviors to essentially predict how employees will perform or act in the future. And at a worker’s request, employers must provide at least one year of the data used by an ADS system to make a disciplinary, termination, or deactivation decision.

Enterprises found violating any of these provisions are subject to a $500 civil penalty per violation.

“Employers are devastating workers’ livelihoods and taking no responsibility for the callous decisions of this unchecked technology,” said Lorena Gonzalez, president of the California Federation of Labor Unions, AFL-CIO. “This is unacceptable. We need stronger guardrails to make sure there is human review and oversight of any decision made by a machine that impacts a worker’s job and paycheck.”

Promoting decisions based on context, evidence

Dickson pointed out that the law is narrower than its name implies: ‘No Robo Bosses’ sounds like a ban, but it is not. “The law does not keep AI out of the decision. It keeps a human in it,” he said.

According to the legislation, a human must corroborate the system’s output using the data behind it and other supporting information like performance evaluations, personnel files, work product, peer reviews, or witness interviews. If the reviewer finds the output inaccurate, incomplete, or misleading, the employer cannot use it, Dickson said.

“The test is whether the human checked the evidence and had the power to say no [to the AI’s decision],” he said, observing that a manager simply forwarding the bot’s verdict is a mail carrier, not a decision maker. In a sense, it’s like an instant replay in sporting events: The umpire watches the video and makes a judgment call, rather than just rereading the call from the field.

“What matters is that they examined the evidence, not just the conclusion,” Dickson said. An employee’s disciplinary or termination notice must disclose whether an AI system was used, and confirm that a human reviewed and corroborated the decision. Human accountability is the point here; an employer owns the final decision.

“Accountability can’t be shifted to the AI,” said Valence Howden, advisory fellow at Info-Tech Research Group. How it comes to its conclusions must be continuously assessed for bias, error, and drift. 

“The bot has no human compass for rationale, and context is defined by who controls its model,” Howden said. “Without context, the human has no impact on the end result, and, given the rate of failure here, there are many (legal and other) implications.”

What enterprises can take away from California’s example

The grey area in the bill is the phrase “primarily relies,” Dickson pointed out; it does not specifically define what that means. “A prudent employer may assume that if the system’s output started the conversation, the decision is in scope, and document accordingly,” he said.

Enterprises should consider five factors when developing a plan around discipline and termination, he said:

1. Inventory: Know which tools score, rank, or flag employees. McNerney’s office cites hundreds of “bossware” products on the market, and many enterprises may not know which ones their managers use.
2. Reviewers: Name who corroborates decisions, train them, and give them real authority to overrule the system.
3. Data access: A reviewer cannot corroborate what they cannot see. If a vendor cannot show the inputs behind an output, the tool may be unusable for these decisions. That condition belongs in the contract.
4. Records: Keep the evidence that the reviewer examined, as employees have the right to request the personal data used.
5. Notice: Build a plain-language, standalone notice template now.

Dickson said that this is an IT problem as much as an HR one.

“Corroboration requires that the inputs to every automated decision are logged, retained, and retrievable by someone outside IT,” he said. “That is an architecture decision, and the CIO makes it.” And, while the $500 penalty might sound small, larger exposure may come later during wrongful termination disputes in which “the algorithm said so” proves a weak defense.

Info-Tech’s Howden advised enterprises to identify their high-risk, high-human-impact scenarios and cases, clarify which decisions, activities, and actions AI can take, and tag those that require human validation and involvement. They should also look at the volume and scale of these types of action so that volume alone doesn’t become a challenge to human involvement.

This is AI governance at a foundational level, Howden noted. “AI shouldn’t be allowed to make irreversible or material decisions and changes without oversight,” he said.

Ultimately, this move may drive enterprises to actually understand the criteria for hiring and firing, and look for issues and biases in the way decisions are made before an AI exposes poor decision logic and removes critical people. “Legal implications are more likely to shape the direction,” Howden said, “especially with the disclosure requirement.”