#FactCheck-Viral Video Falsely Claims ‘Civil War-Like Situation’ in Lucknow; Actually Shows Slum Fire

What are Deepfakes? 

A deepfake is essentially a video of a person in which their face or body has been digitally altered so that they appear to be someone else, typically used maliciously or to spread false information. Deepfake technology is a method for manipulating videos, images, and audio utilising powerful computers and deep learning. It is used to generate fake news and commit financial fraud, among other wrongdoings. It overlays a digital composite over an already-existing video, picture, or audio; cybercriminals use Artificial Intelligence technology. The term deepfake was coined first time in 2017 by an anonymous Reddit user, who called himself deepfake. 

Deepfakes works on a combination of AI and ML, which makes the technology hard to detect by Web 2.0 applications, and it is almost impossible for a layman to see if an image or video is fake or has been created using deepfakes. In recent times, we have seen a wave of AI-driven tools which have impacted all industries and professions across the globe. Deepfakes are often created to spread misinformation. There lies a key difference between image morphing and deepfakes. Image morphing is primarily used for evading facial recognition, but deepfakes are created to spread misinformation and propaganda. 

Issues Pertaining to Deepfakes in India 

Deepfakes are a threat to any nation as the impact can be divesting in terms of monetary losses, social and cultural unrest, and actions against the sovereignty of India by anti-national elements. Deepfake detection is difficult but not impossible. The following threats/issues are seen to be originating out of deep fakes: 

• Misinformation: One of the biggest issues of Deepfake is misinformation, the same was seen during the Russia-Ukraine conflict, where in a deepfake of Ukraine’s president, Mr Zelensky, surfaced on the internet and caused mass confusion and propaganda-based misappropriation among the Ukrainians. 
• Instigation against the Union of India: Deepfake poses a massive threat to the integrity of the Union of India, as this is one of the easiest ways for anti-national elements to propagate violence or instigate people against the nation and its interests. As India grows, so do the possibilities of anti-national attacks against the nation. 
• Cyberbullying/ Harassment: Deepfakes can be used by bad actors to harass and bully people online in order to extort money from them. 
• Exposure to Illicit Content: Deepfakes can be easily used to create illicit content, and oftentimes, it is seen that it is being circulated on online gaming platforms where children engage the most. 
• Threat to Digital Privacy: Deepfakes are created by using existing videos. Hence, bad actors often use photos and videos from Social media accounts to create deepfakes, this directly poses a threat to the digital privacy of a netizen.  
• Lack of Grievance Redressal Mechanism: In the contemporary world, the majority of nations lack a concrete policy to address the aspects of deepfake. Hence, it is of paramount importance to establish legal and industry-based grievance redressal mechanisms for the victims. 
• Lack of Digital Literacy: Despite of high internet and technology penetration rates in India, digital literacy lags behind, this is a massive concern for the Indian netizens as it takes them far from understanding the tech, which results in the under-reporting of crimes. Large-scale awareness and sensitisation campaigns need to be undertaken in India to address misinformation and the influence of deepfakes. 

How to spot deepfakes? 

Deepfakes look like the original video at first look, but as we progress into the digital world, it is pertinent to establish identifying deepfakes in our digital routine and netiquettes in order to stay protected in the future and to address this issue before it is too late. The following aspects can be kept in mind while differentiating between a real video and a deepfake

• Look for facial expressions and irregularities: Whenever differentiating between an original video and deepfake, always look for changes in facial expressions and irregularities, it can be seen that the facial expressions, such as eye movement and a temporary twitch on the face, are all signs of a video being a deepfake. 
• Listen to the audio: The audio in deepfake also has variations as it is imposed on an existing video, so keep a check on the sound effects coming from a video in congruence with the actions or gestures in the video. 
• Pay attention to the background: The most easiest way to spot a deepfake is to pay attention to the background, in all deepfakes, you can spot irregularities in the background as, in most cases, its created using virtual effects so that all deepfakes will have an element of artificialness in the background. 
• Context and Content: Most of the instances of deepfake have been focused towards creating or spreading misinformation hence, the context and content of any video is an integral part of differentiating between an original video and deepfake. 
• Fact-Checking: As a basic cyber safety and digital hygiene protocol, one should always make sure to fact-check each and every piece of information they come across on social media. As a preventive measure, always make sure to fact-check any information or post sharing it with your known ones.  
• AI Tools: When in doubt, check it out, and never refrain from using Deepfake detection tools like- Sentinel, Intel’s real-time deepfake detector - Fake catcher, We Verify, and Microsoft’s Video Authenticator tool to analyze the videos and combating technology with technology. 

Recent Instance 

A deepfake video of actress Rashmika Mandanna recently went viral on social media, creating quite a stir. The video showed a woman entering an elevator who looked remarkably like Mandanna. However, it was later revealed that the woman in the video was not Mandanna, but rather, her face was superimposed using AI tools. Some social media users were deceived into believing that the woman was indeed Mandanna, while others identified it as an AI-generated deepfake. The original video was actually of a British-Indian girl named Zara Patel, who has a substantial following on Instagram. This incident sparked criticism from social media users towards those who created and shared the video merely for views, and there were calls for strict action against the uploaders. The rapid changes in the digital world pose a threat to personal privacy; hence, caution is advised when sharing personal items on social media​​.

Legal Remedies

Although Deepfake is not recognised by law in India, it is indirectly addressed by Sec. 66 E of the IT Act, which makes it illegal to capture, publish, or transmit someone's image in the media without that person's consent, thus violating their privacy. The maximum penalty for this violation is ₹2 lakh in fines or three years in prison. The DPDP Act's applicability in 2023 means that the creation of deepfakes will directly affect an individual's right to digital privacy and will also violate the IT guidelines under the Intermediary Guidelines, as platforms will be required to exercise caution while disseminating and publishing misinformation through deepfakes. The indirect provisions of the Indian Penal Code, which cover the sale and dissemination of derogatory publications, songs and actions, deception in the delivery of property, cheating and dishonestly influencing the delivery of property, and forgery with the intent to defame, are the only legal remedies available for deepfakes. Deep fakes must be recognized legally due to the growing power of misinformation. The Data Protection Board and the soon-to-be-established fact-checking body must recognize crimes related to deepfakes and provide an efficient system for filing complaints.

Conclusion 

Deepfake is an aftermath of the advancements of Web 3.0 and, hence is just the tip of the iceberg in terms of the issues/threats from emerging technologies. It is pertinent to upskill and educate the netizens about the keen aspects of deepfakes to stay safe in the future. At the same time, developing and developed nations need to create policies and laws to efficiently regulate deepfake and to set up redressal mechanisms for victims and industry. As we move ahead, it is pertinent to address the threats originating out of the emerging techs and, at the same time, create a robust resilience for the same. 

References 

• https://www.drishtiias.com/daily-updates/daily-news-analysis/deepfake-technology
• https://timesofindia.indiatimes.com/gadgets-news/explained-what-are-deepfakes-and-how-to-spot-one/articleshow/90916962.cms
• https://www.unite.ai/best-deepfake-detector-tools-and-techniques/

Introduction

YouTube is testing a new feature called ‘Notes,’ which allows users to add community-sourced context to videos. The feature allows users to clarify if a video is a parody or if it is misrepresenting information. The feature builds on existing features to provide helpful content alongside videos. Currently under testing, the feature will be available to a limited number of eligible contributors who will be invited to write notes on videos. These notes will appear publicly under a video if they are found to be broadly helpful. Viewers will be able to rate notes into three categories: ‘Helpful,’ ‘Somewhat helpful,’ or ‘Unhelpful’. Based on the ratings, YouTube will determine which notes are published. The feature will first be rolled out on mobile devices in the U.S. in English. The Google-owned platform will look at ways to improve the feature over time, including whether it makes sense to expand it to other markets. 

YouTube To Roll Out The New ‘Notes’ Feature

YouTube is testing an experimental feature that allows users to add notes to provide relevant, timely, and easy-to-understand context for videos. This initiative builds on previous products that display helpful information alongside videos, such as information panels and disclosure requirements when content is altered or synthetic. YouTube in its blog clarified that the pilot will be available on mobiles in the U.S. and in the English language, to start with. During this test phase, viewers, participants, and creators are invited to give feedback on the quality of the notes.

YouTube further stated in its blog that a limited number of eligible contributors will be invited via email or Creator Studio notifications to write notes so that they can test the feature and add value to the system before the organisation decides on next steps and whether or not to expand the feature. Eligibility criteria include having an active YouTube channel in good standing with Yotube’s Community Guidelines.

Viewers in the U.S. will start seeing notes on videos in the coming weeks and months. In this initial pilot, third-party evaluators will rate the helpfulness of notes, which will help train the platform’s systems. As the pilot moves forward, contributors themselves will rate notes as well.

Notes will appear publicly under a video if they are found to be broadly helpful. People will be asked whether they think a note is helpful, somewhat helpful, or unhelpful and the reasons for the same. For example, if a note is marked as ‘Helpful,’ the evaluator will have the opportunity to specify  if it is so because it cites high-quality sources or is written clearly and neutrally. A bridging-based algorithm will be used to consider these ratings and determine what notes are published. YouTube is excited to explore new ways to make context-setting even more relevant, dynamic, and unique to the videos we are watching, at scale, across the huge variety of content on YouTube.

CyberPeace Analysis: How Can Notes Help Counter Misinformation

The potential effectiveness of countering misinformation on YouTube using the proposed ‘Notes’ feature is significant. Enabling contributors to include notes on videos can offer relevant and accurate context to clarify any misleading or false information in the video. These notes can aid in enhancing viewers' comprehension of the content and detecting misinformation. The participation from users to rate the added notes as helpful, somewhat helpful, and unhelpful adds a heightened layer of transparency and public participation in identifying the accuracy of the content. 

As YouTube intends to gather feedback from its various stakeholders to improve the feature over time, one can look forward to improved policy and practical over time: the feedback mechanism will allow for continuous refinement of the feature, ensuring it effectively addresses misinformation. The platform employs algorithms to identify helpful notes that cater to a broad audience across different perspectives. This helps showcase accurate information and combat misinformation.

Furthermore, along with the Notes feature, YouTube should explore and implement prebunking and debunking strategies on the platform by promoting educational content and empowering users to discern between fact and any misleading information. 

Conclusion

The new feature, currently in the testing phase, aims to counter misinformation by providing context, enabling user feedback, leveraging algorithms, promoting transparency, and continuously improving information quality. Considering the diverse audience on the platform and high volumes of daily content consumption, it is important for both the platform operators and users to engage with factual, verifiable information. The fallout of misinformation on such a popular platform can be immense, and so, any mechanism or feature that can help counter the same must be developed to its full potential. Apart from this new Notes feature, YouTube has also implemented certain measures in the past to counter misinformation, such as providing authenticated sources to counter any election misinformation during the recent 2024 elections in India. These efforts are a welcome contribution to our shared responsibility as netizens to create a trustworthy, factual and truly-informational digital ecosystem.

References:

• https://blog.youtube/news-and-events/new-ways-to-offer-viewers-more-context/
• https://www.thehindu.com/sci-tech/technology/internet/youtube-tests-feature-that-will-let-users-add-context-to-videos/article68302933.ece

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Introduction

According to Statista, the global artificial intelligence software market is forecast to grow by around 126 billion US dollars by 2025. This will include a 270% increase in enterprise adoption over the past four years. The top three verticals in the Al market are BFSI (Banking, Financial Services, and Insurance), Healthcare & Life Sciences, and Retail & e-commerce. These sectors benefit from vast data generation and the critical need for advanced analytics. Al is used for fraud detection, customer service, and risk management in BFSI; diagnostics and personalised treatment plans in healthcare; and retail marketing and inventory management.

The Chairperson of the Competition Commission of India’s Chief, Smt. Ravneet Kaur raised a concern that Artificial Intelligence has the potential to aid cartelisation by automating collusive behaviour through predictive algorithms. She explained that the mere use of algorithms cannot be anti-competitive but in case the algorithms are manipulated, then that is a valid concern about competition in markets.

This blog focuses on how policymakers can balance fostering innovation and ensuring fair competition in an AI-driven economy. 

What is the Risk Created by AI-driven Collusion?

AI uses predictive algorithms, and therefore, they could lead to aiding cartelisation by automating collusive behaviour. AI-driven collusion could be through:

• The use of predictive analytics to coordinate pricing strategies among competitors.
• The lack of human oversight in algorithm-induced decision-making leads to tacit collusion (competitors coordinate their actions without explicitly communicating or agreeing to do so).

AI has been raising antitrust concerns and the most recent example is the partnership between Microsoft and OpenAI, which has raised concerns among other national competition authorities regarding potential competition law issues. While it is expected that the partnership will potentially accelerate innovation, it also raises concerns about potential anticompetitive effects such as market foreclosure or the creation of barriers to entry for competitors and, therefore, has been under consideration in the German and UK courts. The problem here is in detecting and proving whether collusion is taking place. 

The Role of Policy and Regulation

The uncertainties induced by AI regarding its effects on competition create the need for algorithmic transparency and accountability in mitigating the risks of AI-driven collusion. It leads to the need to build and create regulatory frameworks that mandate the disclosure of algorithmic methodologies and establish a set of clear guidelines for the development of AI and its deployment. These frameworks or guidelines should encourage an environment of collaboration between competition watchdogs and AI experts. 

The global best practices and emerging trends in AI regulation already include respect for human rights, sustainability, transparency and strong risk management. The EU AI Act could serve as a model for other jurisdictions, as it outlines measures to ensure accountability and mitigate risks. The key goal is to tailor AI regulations to address perceived risks while incorporating core values such as privacy, non-discrimination, transparency, and security.

Promoting Innovation Without Stifling Competition

Policymakers need to ensure that they balance regulatory measures with innovation scope and that the two priorities do not hinder each other. 

1. Create adaptive and forward-thinking regulatory approaches to keep pace with technological advancements that take place at the pace of development and allow for quick adjustments in response to new AI capabilities and market behaviours.n
2. Competition watchdogs need to recruit domain experts to assess competition amid rapid changes in the technology landscape. Create a multi-stakeholder approach that involves regulators, industry leaders, technologists and academia who can create inclusive and ethical AI policies. 
3. Businesses can be provided incentives such as recognition through certifications, grants or benefits in acknowledgement of adopting ethical AI practices. 
4. Launch studies such as the CCI’s market study to study the impact of AI on competition. This can lead to the creation of a driving force for sustainable growth with technological advancements. 

Conclusion: AI and the Future of Competition

We must promote a multi-stakeholder approach that enhances regulatory oversight, and incentivising ethical AI practices. This is needed to strike a delicate balance that safeguards competition and drives sustainable growth. As AI continues to redefine industries, embracing collaborative, inclusive, and forward-thinking policies will be critical to building an equitable and innovative digital future. 

The lawmakers and policymakers engaged in the drafting of the frameworks need to ensure that they are adaptive to change and foster innovation. It is necessary to note that fair competition and innovation are not mutually exclusive goals, they are complementary to each other. Therefore, a regulatory framework that promotes transparency, accountability, and fairness in AI deployment must be established.

References

• https://www.thehindu.com/sci-tech/technology/ai-has-potential-to-aid-cartelisation-fair-competition-integral-for-sustainable-growth-cci-chief/article69041922.ece 
• https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html 
• https://www.ey.com/en_in/insights/ai/how-to-navigate-global-trends-in-artificial-intelligence-regulation#:~:text=Six%20regulatory%20trends%20in%20Artificial%20Intelligence&text=These%20include%20respect%20for%20human,based%20approach%20to%20AI%20regulation. ‍
• https://www.business-standard.com/industry/news/ai-has-potential-to-aid-fair-competition-for-sustainable-growth-cci-chief-124122900221_1.html