HomeTop StoriesMeta delays controversial commercial terms update to November amid publisher backlash

Meta delays controversial commercial terms update to November amid publisher backlash

Meta delays controversial commercial terms update to November amid publisher backlash

Meta Platforms has extended the implementation date of its updated Commercial Terms and Self-Serve Ad Terms to November, pushing back the previous October 30 deadline following coordinated pushback from publishers, digital advertisers, and trade groups.

“We are extending the effective date of our updated Commercial Terms and Self-Serve Ad Terms to 20 November to allow more time for us to explain to our partners and stakeholders what’s changing and what’s not,” said Meta’s spokesperson.

Controversy and regulator’s pressure:

Major publishing coalitions, including the News/Media Alliance and the European Publishers Council, demanded the immediate withdrawal or suspension of the updated terms.

They argued that the new language granted Meta broad authorization to use automated software and web crawlers to index external business websites and utilize that content for artificial intelligence training and product development without explicit compensation.

The backlash prompted industry bodies to file formal complaints with antitrust and competition watchdogs in the European Union and the United Kingdom, requesting regulatory investigations into whether the terms violate fair competition rules.

Meta’s Response:

Meta defended the adjustments as necessary to streamline agreements and reduce overlap across its business tools, maintaining that the updates do not grant unlimited content rights.

However, the company delayed the rollout to provide stakeholders additional time for clarification, noting that businesses retain standard methods like robots.txt files to manage web crawler access.

The European Commission, which serves as the EU’s antitrust watchdog, said it welcomed the delay, adding that it had sent requests for information to companies that have not yet published summaries about the data used to train their AI models. 

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