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Intermediaries Have Varying Functions, ‘One-Size-Fits-All’ Approach Not Suitable For Deepfake Regulation: The Software Alliance to MeitY

The organisation’s inputs come in response to the government’s plans to introduce amendments to India’s platform governance law, the IT Rules, 2021, to regulate generative AI, including deep fakes and synthetic content.

This image was created by using DALL-E.

The Ministry of Electronics & Information Technology (MeitY) must consider differences in the role and functions of different types of intermediaries and avoid a one-size-fits-all approach to regulation of deepfakes, BSA, The Software Alliance suggested in its letter to MeitY on February 2, 2024.

The letter explained:

“This is crucial due to key service-level, technical, functional, and user-based distinctions that ensure that all intermediaries do not have the same ability to address this issue. Further, the services provided by intermediaries may not pose the same kind of risk. For example, business-to-business and enterprise software services pose limited risk to user safety and public order, given the size of their user base and the fact that they do not provide services directly to consumers.”

The organisation’s inputs come in response to the government’s plans to introduce amendments to India’s platform governance law, the IT Rules, 2021, to regulate generative AI, including deep fakes and synthetic content. In December 2023, the IT Ministry had also issued an advisory seeking stricter monitoring of social media content by platforms, as outlined in Rule 3(1)b of the IT Rules, 2021. Read more about the advisory here.

The BSA, which provides software solutions to businesses globally, has also recommended that the government rely on alternative solutions like watermarking AI-generated content or other “disclosure methods” that can help users distinguish between real and AI-generated content.

Why does it matter?

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According to the IT Ministry’s advisory, platforms are required to proactively monitor, and scan social media content to detect deepfakes and take swift action against them. Currently, the government’s approach indicates that largely platforms would be held accountable for deepfake-related misinformation than the perpetrators. The Internet Freedom Foundation (IFF), in its letter to the IT Ministry, had also pointed out that such measures can lead to private entities becoming “arbiters of permissible speech” resulting in arbitrary censorship of online content in order to avoid any liabilities.

Are there any fool-proof methods to detect deepfakes?

The BSA, in its letter, emphasised on watermarking and the role of content provenance in detecting deepfakes. Provenance includes information such as when the media was created, when it was edited, what software was used, etc. All this is embedded as metadata or imperceptible watermarks by the software used to make them.

However, experts at MediaNama’s discussion on ‘Deepfakes and Democracy’ explained that at present, researchers have examined all watermarking techniques and have found that all such methods can possibly be broken or bypassed. Gautham Koorma, machine learning engineer and researcher from UC Berkeley, questioned, “I think we should be using watermarking, but keeping in mind its downside, that it can be easily broken by a sophisticated adversary. […] For a non-sophisticated actor, it might be a little bit more difficult, but this is why the push for detection, because once you have removed that watermark, then what do you do?”

Similarly, panelist Tarunima Prabhakar, co-founder of Tattle Civic Technologies, suggested that fingerprinting (adding provenance info to) a deepfake at the source is going to be necessary and to prevent users from removing the fingerprint, platforms should penalise content that doesn’t have a fingerprint. She warned that detecting deepfakes using algorithms isn’t going to work in the future when AI gets to a sophistication where it completely bypasses technical detection. But, Medianama Editor Nikhil Pahwa pointed out that even if the image was to carry a fingerprint, these could be faked. Read more about the report on deepfake generation and detection here.

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Written By

Curious about the intersection of technology with education, caste and welfare rights. For story tips, please feel free to reach out at sarasvati@medianama.com

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