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MeitY Asks Meta To Review Content Recommendation Algorithms

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MeitY Asks Meta To Review Content Recommendation Algorithms

The Centre has asked Meta, which operates Instagram and Facebook, to review its recommendation algorithms to prevent disproportionate exposure to a limited set of narratives and strengthen checks on content that could cause public disorder or incite violence. 

In an advisory dated October 10, the Ministry of Electronics and Information Technology (MeitY) directed Meta to provide adequate context for photographs, videos, graphics and other content depicting ongoing public events, particularly when their authenticity, date, location or circumstances may not be readily apparent to users, according to PTI.

The advisory also called for a review of Meta’s recommendation and content-ranking mechanisms to prevent potentially misleading, manipulated or out-of-context material from being disproportionately amplified or repeatedly recommended to users.

“Ensure that recommendation systems do not result in disproportionate exposure of users to a single or limited set of narratives, and endeavour to provide appropriate diversity of relevant and credible information,” the advisory said.

It also called for stronger mechanisms to rapidly identify, review and escalate content that gains significant reach through recommendation systems and could potentially cause widespread public confusion, apprehension, violence, or disturbances to public order.

The advisory came amid protests in Delhi by the Cockroach Janta Party (CJP) and opposition parties demanding the resignation of chief election commissioner Gyanesh Kumar over the Special Intensive Revision (SIR) of electoral rolls.

Similar concerns over content moderation were raised by the government earlier, following a CJP protest at Jantar Mantar in June.

While the advisory does not specify what prompted the government’s move, IT Ministry sources told PTI that agencies had flagged concerns over Meta’s recommendation algorithms, which allegedly appeared to favour certain types of content over others.


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