#ai-training-data

#ai-training-data

According to Uber, beginning later this year, drivers and couriers who opt into the program can complete "digital tasks" within Uber's Driver app. These tasks can include submitting a video of themselves speaking in their native language, uploading pictures of specific everyday items, or presenting documents written in a different language. After tasks are completed, the earnings will be in the users' balance within 24 hours. Compensation depends on the time commitment to complete tasks and their complexity.

The new change, which Cloudflare calls its Content Signals Policy, happened after publishers and other companies that depend on web traffic have cried foul over Google's AI Overviews and similar AI answer engines, saying they are sharply cutting those companies' path to revenue because they don't send traffic back to the source of the information. There have been lawsuits, efforts to kick-start new marketplaces to ensure compensation, and more-

"We've already run out of data," Neema Raphael, Goldman Sachs' chief data officer and head of data engineering, said on the bank's "Exchanges" podcast published on Tuesday.

For decades, publishers large and small have created the news, culture, entertainment, and educational resources that shape how society consumes information. Yet in recent years, the rise of artificial intelligence has added a new twist to the ongoing struggle for sustainable publishing. AI companies are building tools capable of generating responses, summaries, and insights trained on vast amounts of web content. The problem? Many publishers see little to no compensation for their role in shaping the data that fuels these systems.

When Is LinkedIn Going to Start Using My Data to Train Its AI Models? LinkedIn has announced that it will start using some of its users' data to train its AI models starting on November 3rd, 2025. Users from the EU, EEA, Switzerland, Canada, and Hong Kong will all be affected. At this stage, US users will not be affected, but this could soon change.

Media companies have filed so many lawsuits against AI companies over the past two years that the act has become routine. When I report on these in The Media Copilot newsletter, they're often digest items, adding to the pile of publishers who want fair compensation for the content AI labs have ingested to create large language models (LLMs). There are so many that elaborate infographics are required to keep track of them all.

When Google became the dominant search engine around 2004, not everyone was happy. Everyone from book publishers to music studios blasted the company for helping itself to copyrighted content without paying. The search giant eventually smoothed things over but now, twenty years later, Google has become the media industry's villain all over again-this time for gobbling that same content to train its AI tools.

The idea behind RSL is brutally simple. Instead of the old file -- which only said, "yes, you can crawl me," or "no, you can't," and which AI companies often ignore -- publishers can now add something new: machine-readable licensing terms. Want an attribution? You can demand it. Want payment every time an AI crawler ingests your work, or even every time it spits out an answer powered by your article?

believed to be the largest publicly reported recovery in the history of US copyright litigation.

Digital publishers are in a losing battle against Big Tech and AI for traffic and ad revenue. But the IAB Tech Lab has a plan to swing the momentum back in pubs' favor. On Tuesday, the Tech Lab announced a new publisher-focused working group that aims to ensure pubs are fairly compensated when AI scrapes their content for training. IAB Tech Lab CEO Anthony Katsur previewed the new initiative at AdMonsters' Sell Side Summit in Nashville, Tenn., on Monday.

The AI industry's quest for high-quality training data has led companies like Anthropic to explore controversial practices in acquiring books for their models.