Photoshop

adobe-to-update-vague-ai-terms-after-users-threaten-to-cancel-subscriptions

Adobe to update vague AI terms after users threaten to cancel subscriptions

Adobe to update vague AI terms after users threaten to cancel subscriptions

Adobe has promised to update its terms of service to make it “abundantly clear” that the company will “never” train generative AI on creators’ content after days of customer backlash, with some saying they would cancel Adobe subscriptions over its vague terms.

Users got upset last week when an Adobe pop-up informed them of updates to terms of use that seemed to give Adobe broad permissions to access user content, take ownership of that content, or train AI on that content. The pop-up forced users to agree to these terms to access Adobe apps, disrupting access to creatives’ projects unless they immediately accepted them.

For any users unwilling to accept, canceling annual plans could trigger fees amounting to 50 percent of their remaining subscription cost. Adobe justifies collecting these fees because a “yearly subscription comes with a significant discount.”

On X (formerly Twitter), YouTuber Sasha Yanshin wrote that he canceled his Adobe license “after many years as a customer,” arguing that “no creator in their right mind can accept” Adobe’s terms that seemed to seize a “worldwide royalty-free license to reproduce, display, distribute” or “do whatever they want with any content” produced using their software.

“This is beyond insane,” Yanshin wrote on X. “You pay a huge monthly subscription, and they want to own your content and your entire business as well. Going to have to learn some new tools.”

Adobe’s design leader Scott Belsky replied, telling Yanshin that Adobe had clarified the update in a blog post and noting that Adobe’s terms for licensing content are typical for every cloud content company. But he acknowledged that those terms were written about 11 years ago and that the language could be plainer, writing that “modern terms of service in the current climate of customer concerns should evolve to address modern day concerns directly.”

Yanshin has so far not been encouraged by any of Adobe’s attempts to clarify its terms, writing that he gives “precisely zero f*cks about Adobe’s clarifications or blog posts.”

“You forced people to sign new Terms,” Yanshin told Belsky on X. “Legally, they are the only thing that matters.”

Another user in the thread using an anonymous X account also pushed back, writing, “Point to where it says in the terms that you won’t use our content for LLM or AI training? And state unequivocally that you do not have the right to use our work beyond storing it. That would go a long way.”

“Stay tuned,” Belsky wrote on X. “Unfortunately, it takes a process to update a TOS,” but “we are working on incorporating these clarifications.”

Belsky co-authored the blog this week announcing that Adobe’s terms would be updated by June 18 after a week of fielding feedback from users.

“We’ve never trained generative AI on customer content, taken ownership of a customer’s work, or allowed access to customer content beyond legal requirements,” Adobe’s blog said. “Nor were we considering any of those practices as part of the recent Terms of Use update. That said, we agree that evolving our Terms of Use to reflect our commitments to our community is the right thing to do.”

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Top Harvard Cancer researchers accused of scientific fraud; 37 studies affected

Lazy —

Researchers accused of manipulating data images with copy-and-paste.

The Dana-Farber Cancer Institute in Boston.

Enlarge / The Dana-Farber Cancer Institute in Boston.

The Dana-Farber Cancer Institute, an affiliate of Harvard Medical School, is seeking to retract six scientific studies and correct 31 others that were published by the institute’s top researchers, including its CEO. The researchers are accused of manipulating data images with simple methods, primarily with copy-and-paste in image editing software, such as Adobe Photoshop.

The accusations come from data sleuth Sholto David and colleagues on PubPeer, an online forum for researchers to discuss publications that has frequently served to spot dubious research and potential fraud. On January 2, David posted on his research integrity blog, For Better Science, a long list of potential data manipulation from DFCI researchers. The post highlighted many data figures that appear to contain pixel-for-pixel duplications. The allegedly manipulated images are of data such as Western blots, which are used to detect and visualize the presence of proteins in a complex mixture.

DFCI Research Integrity Officer Barrett Rollins told The Harvard Crimson that David had contacted DFCI with allegations of data manipulation in 57 DFCI-led studies. Rollins said that the institute is “committed to a culture of accountability and integrity,” and that “Every inquiry about research integrity is examined fully.”

The allegations are against: DFCI President and CEO Laurie Glimcher, Executive Vice President and COO William Hahn, Senior Vice President for Experimental Medicine Irene Ghobrial, and Harvard Medical School professor Kenneth Anderson.

The Wall Street Journal noted that Rollins, the integrity officer, is also a co-author on two of the studies. He told the outlet he is recused from decisions involving those studies.

Amid the institute’s internal review, Rollins said the institute identified 38 studies in which DFCI researchers are primarily responsible for potential manipulation. The institute is seeking retraction of six studies and is contacting scientific publishers to correct 31 others, totaling 37 studies. The one remaining study of the 38 is still being reviewed.

Of the remaining 19 studies identified by David, three were cleared of manipulation allegations, and 16 were determined to have had the data in question collected at labs outside of DFCI. Those studies are still under investigation, Rollins told The Harvard Crimson. “Where possible, the heads of all of the other laboratories have been contacted and we will work with them to see that they correct the literature as warranted,” Rollins wrote in a statement.

Despite finding false data and manipulated images, Rollins pressed that it doesn’t necessarily mean that scientific misconduct occurred and the institute has not yet made such a determination. The “presence of image discrepancies in a paper is not evidence of an author’s intent to deceive,” Rollins wrote. “That conclusion can only be drawn after a careful, fact-based examination which is an integral part of our response. Our experience is that errors are often unintentional and do not rise to the level of misconduct.”

The very simple methods used to manipulate the DFCI data are remarkably common among falsified scientific studies, however. Data sleuths have gotten better and better at spotting such lazy manipulations, including copied-and-pasted duplicates that are sometimes rotated and adjusted for size, brightness, and contrast. As Ars recently reported, all journals from the publisher Science now use an AI-powered tool to spot just this kind of image recycling because it is so common.

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