#FactCheck - Viral Image of Broken Mahatma Gandhi Statue Is Not from Bangladesh

AI-generated content has been taking up space in the ever-changing dynamics of today's tech landscape. Generative AI has emerged as a powerful tool that has enabled the creation of hyper-realistic audio, video, and images. While advantageous, this ability has some downsides, too, particularly in content authenticity and manipulation. 

The impact of this content is varied in the areas of ethical, psychological and social harms seen in the past couple of years. A major concern is the creation of non-consensual explicit content, including nudes. This content includes content where an individual’s face gets superimposed onto explicit images or videos without their consent. This is not just a violation of privacy for individuals, and can have humongous consequences for their professional and personal lives. This blog examines the existing laws and whether they are equipped to deal with the challenges that this content poses. 

Understanding the Deepfake Technology

Deepfake technology is a media file (image, video, or speech) that typically represents a human subject that is altered deceptively using deep neural networks (DNNs). It is used to alter a person’s identity, and it usually takes the form of a “face swap” where the identity of a source subject is transferred onto a destination subject. The destination’s facial expressions and head movements remain the same, but the appearance in the video is that of the source. In the case of videos, the identities can be substituted by way of replacement or reenactment.

This superimposed content creates realistic content, such as fake nudes. Presently, creating a deepfake is not a costly endeavour. It requires a Graphics Processing Unit (GPU), software that is free, open-source, and easy to download, and graphics editing and audio-dubbing skills.  Some of the common apps to create deepfakes are DeepFaceLab and FaceSwap, which are both public and open source and are supported by thousands of users who actively participate in the evolution and development of these software and models. 

Legal Gaps and Challenges

Multiple gaps and challenges exist in the legal space for deepfakes and their regulation. They are:

1. The inadequate definitions governing AI-generated explicit content often lead to enforcement challenges.
2. Jurisdictional challenges due to the cross-border nature of crimes and the difficulties caused by international cooperation measures are in the early stages for AI content. 
3. There is a gap between the current consent-based and harassment laws for AI-generated nudes. 
4. Providing evidence or providing proof for the intent and identification of perpetrators in digital crimes is a challenge that is yet to be overcome. 

Policy Responses and Global Trends 

Presently, the global response to deepfakes is developing. The UK has developed the Online Safety Bill, the EU has the AI Act, the US has some federal laws such as the National AI Initiative Act of 2020 and India is currently developing the India AI Act as the specific legislation dealing with AI and its correlating issues. 

The IT Rules, 2021, and the DPDP Act, 2023, regulate digital platforms by mandating content governance, privacy policies, grievance redressal, and compliance with removal orders. Emphasising intermediary liability and safe harbour protections, these laws play a crucial role in tackling harmful content like AI-generated nudes, while the DPDP Act focuses on safeguarding privacy and personal data rights.

Bridging the Gap: CyberPeace Recommendations 

1. Initiate legislative reforms by advocating for clear and precise definitions for the consent frameworks and instituting high penalties for AI-based offences, particularly those which are aimed at sexually explicit material.
2. Advocate for global cooperation and collaborations by setting up international standards and bilateral and multilateral treaties that address the cross-border nature of these offences.
3. Platforms should push for accountability by pushing for stricter platform responsibility for the detection and removal of harmful AI-generated content. Platforms should introduce strong screening mechanisms to counter the huge influx of harmful content.  
4. Public campaigns which spread awareness and educate users about their rights and the resources available to them in case such an act takes place with them. 

Conclusion 

The rapid advancement of AI-generated explicit content demands immediate and decisive action. As this technology evolves, the gaps in existing legal frameworks become increasingly apparent, leaving individuals vulnerable to profound privacy violations and societal harm. Addressing this challenge requires adaptive, forward-thinking legislation that prioritises individual safety while fostering technological progress. Collaborative policymaking is essential and requires uniting governments, tech platforms, and civil society to develop globally harmonised standards. By striking a balance between innovation and societal well-being, we can ensure that the digital age is not only transformative but also secure and respectful of human dignity. Let’s act now to create a safer future!

References

• https://etedge-insights.com/technology/artificial-intelligence/deepfakes-and-the-future-of-digital-security-are-we-ready/
• https://odsc.medium.com/the-rise-of-deepfakes-understanding-the-challenges-and-opportunities-7724efb0d981 ‍
• https://insights.sei.cmu.edu/blog/how-easy-is-it-to-make-and-detect-a-deepfake/

Modern international trade heavily relies on data transfers for the exchange of digital goods and services. User data travels across multiple jurisdictions and legal regimes, each with different rules for processing it. Since international treaties and standards for data protection are inadequate, states, in an effort to protect their citizens' data, have begun extending their domestic privacy laws beyond their borders. However, this opens a Pandora's box of legal and administrative complexities for both, the data protection authorities and data processors. The former must balance the harmonization of domestic data protection laws with their extraterritorial enforcement, without overreaching into the sovereignty of other states. The latter must comply with the data privacy laws in all states where it collects, stores, and processes data. While the international legal community continues to grapple with these challenges, India can draw valuable lessons to refine the Digital Personal Data Protection Act, 2023 (DPDP) in a way that effectively addresses these complexities.

Why Extraterritorial Application? 

Since data moves freely across borders and entities collecting such data from users in multiple states can misuse it or use it to gain an unfair competitive advantage in local markets, data privacy laws carry a clause on their extraterritorial application. Thus, this principle is utilized by states to frame laws that can ensure comprehensive data protection for their citizens, irrespective of the data’s location.  The foremost example of this is the European Union’s (EU) General Data Protection Regulation (GDPR), 2016,  which applies to any entity that processes the personal data of its citizens, regardless of its location. Recently, India has enacted the DPDP Act of 2023, which includes a clause on extraterritorial application.

The Extraterritorial Approach: GDPR and DPDP Act

The GDPR is considered the toughest data privacy law in the world and sets a global standard in data protection. According to Article 3, its provisions apply not only to data processors within the EU but also to those established outside its territory, if they offer goods and services to and conduct behavioural monitoring of data subjects within the EU. The enforcement of this regulation relies on heavy penalties for non-compliance in the form of fines up to €20 million or 4% of the company’s global turnover, whichever is higher, in case of severe violations. As a result, corporations based in the USA, like Meta and Clearview AI, have been fined over  €1.5 billion and €5.5 million respectively, under the GDPR. 

Like the GDPR, the DPDP Act extends its jurisdiction to foreign companies dealing with personal data of data principles within Indian territory under section 3(b). It has a similar extraterritorial reach and prescribes a penalty of up to Rs 250 crores in case of breaches. However, the Act or DPDP Rules, 2025, which are currently under deliberation, do not elaborate on an enforcement mechanism through which foreign companies can be held accountable. 

Lessons for India’s DPDP on Managing Extraterritorial Application 

1. Clarity in Definitions: GDPR clearly defines ‘personal data’, covering direct information such as name and identification number,  indirect identifiers like location data, and, online identifiers that can be used to identify the physical, physiological, genetic, mental, economic, cultural, or social identity of a natural person. It also prohibits revealing special categories of personal data like religious beliefs and biometric data to protect the fundamental rights and freedoms of the subjects. On the other hand, the DPDP Act/ Rules define ‘personal data’ vaguely, leaving a broad scope for Big Tech and ad-tech firms to bypass obligations. 
2. International Cooperation: Compliance is complex for companies due to varying data protection laws in different countries. The success of regulatory measures in such a scenario depends on international cooperation for governing cross-border data flows and enforcement. For DPDP to be effective, India will have to foster cooperation frameworks with other nations. 
3. Adequate Safeguards for Data Transfers: The GDPR regulates data transfers outside the EU via pre-approved legal mechanisms such as standard contractual clauses or binding corporate rules to ensure that the same level of protection applies to EU citizens’ data even when it is processed outside the EU. The DPDP should adopt similar safeguards to ensure that Indian citizens’ data is protected when processed abroad.
4. Revised Penalty Structure: The GDPR mandates a penalty structure that must be effective, proportionate, and dissuasive. The supervisory authority in each member state has the power to impose administrative fines as per these principles, up to an upper limit set by the GDPR. On the other hand, the DPDP’s penalty structure is simplistic and will disproportionately impact smaller businesses. It must take into regard factors such as nature, gravity, and duration of the infringement, its consequences, compliance measures taken, etc.
5. Governance Structure: The GDPR envisages a multi-tiered governance structure comprising of   

• National-level Data Protection Authorities (DPAs) for enforcing national data protection laws and the GDPR, 
• European Data Protection Supervisor (EDPS) for monitoring the processing of personal data by EU institutions and bodies,  
• European Commission (EC) for developing GDPR legislation
• European Data Protection Board (EDPB) for enabling coordination between the EC, EDPS, and DPAs

In contrast, the Data Protection Board (DPB) under DPDP will be a single, centralized body overseeing compliance and enforcement. Since its members are to be appointed by the Central Government, it raises questions about the Board’s autonomy and ability to apply regulations consistently. Further, its investigative and enforcement capabilities are not well defined.

Conclusion 

The protection of the human right to privacy ( under the International Covenant on Civil and Political Rights and the Universal Declaration of Human Rights) in today’s increasingly interconnected digital economy warrants international standard-setting on cross-border data protection. In the meantime, States relying on the extraterritorial application of domestic laws is unavoidable. While India’s DPDP takes measures towards this, they must be refined to ensure clarity regarding implementation mechanisms. They should push for alignment with data protection laws of other States, and account for the complexity of enforcement in cases involving extraterritorial jurisdiction. As India sets out to position itself as a global digital leader, a well-crafted extraterritorial framework under the DPDP Act will be essential to promote international trust in India’s data governance regime.

Sources

• https://gdpr-info.eu/art-83-gdpr/ 
• https://gdpr-info.eu/recitals/no-150/ 
• https://gdpr-info.eu/recitals/no-51/ 
• https://www.meity.gov.in/static/uploads/2024/06/2bf1f0e9f04e6fb4f8fef35e82c42aa5.pdf 
• https://www.eqs.com/compliance-blog/biggest-gdpr-fines/#:~:text=ease%20the%20burden.-,At%20a%20glance,In%20summary 
• https://gdpr-info.eu/art-3-gdpr/ 
• https://www.legal500.com/developments/thought-leadership/gdpr-v-indias-dpdpa-key-differences-and-compliance-implications/#:~:text=Both%20laws%20cover%20'personal%20data,of%20personal%20data%20as%20sensitive. 

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Digitisation in Agriculture

The traditional way of doing agriculture has undergone massive digitization in recent years, whereby several agricultural processes have been linked to the Internet. This globally prevalent transformation, driven by smart technology, encompasses the use of sensors, IoT devices, and data analytics to optimize and automate labour-intensive farming practices. Smart farmers in the country and abroad now leverage real-time data to monitor soil conditions, weather patterns, and crop health, enabling precise resource management and improved yields. The integration of smart technology in agriculture not only enhances productivity but also promotes sustainable practices by reducing waste and conserving resources. As a result, the agricultural sector is becoming more efficient, resilient, and capable of meeting the growing global demand for food.

Digitisation of Food Supply Chains

There has also been an increase in the digitisation of food supply chains across the globe since it enables both suppliers and consumers to keep track of the stage of food processing from farm to table and ensures the authenticity of the food product. The latest generation of agricultural robots is being tested to minimise human intervention. It is thought that AI-run processes can mitigate labour shortage, improve warehousing and storage and make transportation more efficient by running continuous evaluations and adjusting the conditions real-time while increasing yield. The company Muddy Machines is currently trialling an autonomous asparagus-harvesting robot called Sprout that not only addresses labour shortages but also selectively harvests green asparagus, which traditionally requires careful picking. However, Chris Chavasse, co-founder of Muddy Machines, highlights that hackers and malicious actors could potentially hack into the robot's servers and prevent it from operating by driving it into a ditch or a hedge, thereby impending core crop activities like seeding and harvesting. Hacking agricultural pieces of machinery also implies damaging a farmer’s produce and in turn profitability for the season.

Case Study: Muddy Machines and Cybersecurity Risks

A cyber attack on digitised agricultural processes has a cascading impact on online food supply chains. Risks are non-exhaustive and spill over to poor protection of cargo in transit, increased manufacturing of counterfeit products, manipulation of data, poor warehousing facilities and product-specific fraud, amongst others. Additional impacts on suppliers are also seen, whereby suppliers have supplied the food products but fail to receive their payments. These cyber-threats may include malware(primarily ransomware) that accounts for 38% of attacks, Internet of Things (IoT) attacks that comprise 29%, Distributed Denial of Service (DDoS) attacks, SQL Injections, phishing attacks etc. 

Prominent Cyber Attacks and Their Impacts

Ransomware attacks are the most popular form of cyber threats to food supply chains and may include malicious contaminations, deliberate damage and destruction of tangible assets (like infrastructure) or intangible assets (like reputation and brand). In 2017, NotPetya malware disrupted the world’s largest logistics giant Maersk and destroyed all end-user devices in more than 60 countries. Interestingly, NotPetya was also linked to the malfunction of freezers connected to control systems. The attack led to these control systems being compromised, resulting in freezer failures and potential spoilage of food, highlighting the vulnerability of industrial control systems to cyber threats.

Further Case Studies

NotPetya also impacted Mondelez, the maker of Oreos but disrupting its email systems, file access and logistics for weeks. Mondelez’s insurance claim was also denied since NotPetya malware was described as a “war-like” action, falling outside the purview of the insurance coverage. In April 2021, over the Easter weekend, Bakker Logistiek, a logistics company based in the Netherlands that offers air-conditioned warehousing and food transportation for Dutch supermarkets, experienced a ransomware attack. This incident disrupted their supply chain for several days, resulting in empty shelves at Albert Heijn supermarkets, particularly for products such as packed and grated cheese. Despite the severity of the attack, the company successfully restored their operations within a week by utilizing backups. JBS, one of the world’s biggest meat processing companies, also had to pay $11 million in ransom via Bitcoin to resolve a cyber attack in the same year, whereby computer networks at JBS were hacked, temporarily shutting down their operations and endangering consumer data. The disruption threatened food supplies and risked higher food prices for consumers. Additional cascading impacts also include low food security and hindrances in processing payments at retail stores. 

Credible Threat Agents and Their Targets

Any cyber-attack is usually carried out by credible threat agents that can be classified as either internal or external threat agents. Internal threat agents may include contractors, visitors to business sites, former/current employees, and individuals who work for suppliers. External threat agents may include activists, cyber-criminals, terror cells etc. These threat agents target large organisations owing to their larger ransom-paying capacity, but may also target small companies due to their vulnerability and low experience, especially when such companies are migrating from analogous methods to digitised processes.

The Federal Bureau of Investigation warns that the food and agricultural systems are most vulnerable to cyber-security threats during critical planting and harvesting seasons. It noted an increase in cyber-attacks against six agricultural co-operatives in 2021, with ancillary core functions such as food supply and distribution being impacted. Resultantly, cyber-attacks may lead to a mass shortage of food not only meant for human consumption but also for animals.

Policy Recommendations

To safeguard against digital food supply chains, Food defence emerges as one of the top countermeasures to prevent and mitigate the effects of intentional incidents and threats to the food chain. While earlier, food defence vulnerability assessments focused on product adulteration and food fraud, including vulnerability assessments of agriculture technology now be more relevant.  

Food supply organisations must prioritise regular backups of data using air-gapped and password-protected offline copies, and ensure critical data copies are not modifiable or deletable from the main system.  For this, blockchain-based food supply chain solutions may be deployed, which are not only resilient to hacking, but also allow suppliers and even consumers to track produce. Companies like Ripe.io, Walmart Global Tech, Nestle and Wholechain deploy blockchain for food supply management since it provides overall process transparency, improves trust issues in the transactions, enables traceable and tamper-resistant records and allows accessibility and visibility of data provenance. Extensive recovery plans with multiple copies of essential data and servers in secure, physically separated locations, such as hard drives, storage devices, cloud or distributed ledgers should be adopted in addition to deploying operations plans for critical functions in case of system outages. For core processes which are not labour-intensive,  including manual operation methods may be used to reduce digital dependence. Network segmentation, updates or patches for operating systems, software, and firmware are additional steps which can be taken to secure smart agricultural technologies. 

References

1. Muddy Machines website, Accessed 26 July 2024.  https://www.muddymachines.com/ 
2. “Meat giant JBS pays $11m in ransom to resolve cyber-attack”, BBC, 10 June 2021. https://www.bbc.com/news/business-57423008 
3. Marshall, Claire & Prior, Malcolm, “Cyber security: Global food supply chain at risk from malicious hackers.”, BBC, 20 May 2022. https://www.bbc.com/news/science-environment-61336659 
4. “Ransomware Attacks on Agricultural Cooperatives Potentially Timed to Critical Seasons.”, Private Industry Notification, Federal Bureau of Investigation, 20 April  https://www.ic3.gov/Media/News/2022/220420-2.pdf. 
5. Manning, Louise & Kowalska, Aleksandra. (2023). “The threat of ransomware in the food supply chain: a challenge for food defence”, Trends in Organized Crime. https://doi.org/10.1007/s12117-023-09516-y 
6. “NotPetya: the cyberattack that shook the world”, Economic Times, 5 March 2022. https://economictimes.indiatimes.com/tech/newsletters/ettech-unwrapped/notpetya-the-cyberattack-that-shook-the-world/articleshow/89997076.cms?from=mdr 
7. Abrams, Lawrence, “Dutch supermarkets run out of cheese after ransomware attack.”, Bleeping Computer, 12 April 2021. https://www.bleepingcomputer.com/news/security/dutch-supermarkets-run-out-of-cheese-after-ransomware-attack/ 
8. Pandey, Shipra; Gunasekaran, Angappa; Kumar Singh, Rajesh & Kaushik, Anjali, “Cyber security risks in globalised supply chains: conceptual framework”, Journal of Global Operations and Strategic Sourcing, January 2020. https://www.researchgate.net/profile/Shipra-Pandey/publication/338668641_Cyber_security_risks_in_globalized_supply_chains_conceptual_framework/links/5e2678ae92851c89c9b5ac66/Cyber-security-risks-in-globalized-supply-chains-conceptual-framework.pdf 
9. Daley, Sam, “Blockchain for Food: 10 examples to know”, Builin, 22 March 2023 https://builtin.com/blockchain/food-safety-supply-chain 

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