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Introduction

Recently, the Delhi Police arrested a licensed telecom PoS agent, who identified himself as “Shivam Telecom," from a roadside kiosk adjacent to Hindu Rao Hospital. On the face of it, the headline may have simply read, “One man, one arrest." However, beneath that arrest is the unsettling story of a fully legitimate retail shop actively forging other people’s identification documents into weapons, one SIM card at a time, for as little as ₹500-600 each. This is not an account of an isolated offender; it is a peek into the vulnerability of SIM card security for typical end-users and the reasons why every mobile phone subscriber must pay attention to the unseen journey of his number.

 Why SIM Security Matters Now

Erstwhile, a SIM card was only a simple device for sending text messages and making calls. Today, however, it’s also a direct link to most of our lives online, be it online banking to verify it through one-time passwords (OTP) or Unified Payments Interface (UPI); social media platforms; or email accounts to reset a forgotten password, two-factor authentications (2FA), or even numerous other online services. Therefore, losing a SIM card and getting it fraudulently issued under your name, or criminals accessing your identity to buy a SIM, can be a serious cause of concern, as they can then impersonate you, conduct various frauds, bypass checks, or commit acts that can lead to you being wrongly implicated.

According to the investigation, criminals were procuring SIM cards through the authorized outlets of telecom companies, not unlicensed dealers. This clearly proves a deficiency in the Know Your Customer (KYC) process for the SIM card activation. The situation, however, is worse and is also highlighted by the fact that more than 21 lakh mobile numbers from the more than 114 crore mobile numbers reviewed under the Sanchar Saathi initiative launched by the department of telecommunications (DoT) were associated with fake or invalid identity documents. A state police chief of Tamil Nadu claims that 90% of the cyber fraud cases involved SIM cards obtained through misused identity documents.

How Illegally Activated SIMs Fuel Everyday Scams?

Once a SIM is activated using someone else's identity documents or biometric data, without their knowledge, it becomes a disposable, hard-to-trace tool for criminals. Here's how that plays out in practice:

1. Phishing and impersonation calls: Using an honest person’s details for a SIM registration allows the scammer to have a “clean” number that won’t tip off victims about a potential scam immediately when carrying out a fake bank call, fake delivery scam, or fake impersonation of an officer.
2. OTP and account-takeover fraud:  Since the SIM card is used as the anchor to OTP verification, an unauthorized SIM can be used to capture one-time passwords to activate new digital payments, create a new digital payments account, or use other personal information linked to your phone number to reset your service passwords.
3. Financial fraud and money mule networks: According to the investigators, such SIMs were extensively being used to open digital payment accounts as well as to flow money across a number of fraud chains, thus enabling the fraudsters to build a layer of financial infrastructure that is not linked with their actual identities.
4. Identity theft with real-world consequences: The identity of the Aadhaar holder (whose document was used to activate the SIM card) might be unaware that a SIM exists under his name until the fraud is uncovered during a loan default or a criminal investigation where he is forced to justify a crime committed using “his” number that he is oblivious to. 

That is the anonymity that SIM-card fraud has: the fact that the SIM on the face of it seems genuine, but the one operating it and the registered owner have absolutely no relationship whatsoever.

Red Flags Every Mobile User Should Watch For

Most people won't know their identity has been misused until something goes visibly wrong. A few warning signs are worth taking seriously:

1. Your SIM suddenly loses network connectivity or displays "No Service" for an extended period without any known outage, SIM replacement request, or billing issue.
2. You stop receiving OTPs or verification messages for banking, UPI, or other online services, particularly if login attempts continue to occur on your accounts.
3. You receive unexpected OTPs, verification codes, or account alerts for services you never signed up for, indicating that someone may be attempting to use your mobile number.
4. You receive calls or messages intended for someone else or asking you to confirm activities you never performed, which may suggest your number has been misused or duplicated.
5. Your bank or telecom provider notifies you of unusual account activity, failed identity verification, or changes that you did not authorize.
6. You discover multiple mobile connections registered in your name that you never requested, a risk that often remains unnoticed unless you proactively check through the Department of Telecommunications' Sanchar Saathi portal.

None of these guarantee fraud, but any of them is a reason to check further rather than assume it's a glitch.

Practical Steps to Protect Yourself

The good news is that Indian users now have direct tools to check and control this exposure:

1. Identify your SIMs: Via the Department of Telecom’s Sanchar Saathi website, you can access a list of all mobile numbers registered in your name. Report and get any SIMs you do not recognize deactivated promptly.
2. Safeguard your identity documents and biometrics: Do not disclose your Aadhaar information, OTPs, or biometrics to unofficial persons or retail agents. Ensure your SIM is activated in your presence by an official dealer of the telecom company.
3. Tighten the security of your accounts: Wherever possible, use the most secure multi-factor authentication methods; an authenticator app, rather than just SMS, would be ideal. Consider enabling account change or SIM swap notifications from your telecom provider.
4. Stay vigilant about your bank accounts and financial activities. Watch for unusual OTP requests, password change requests, login notifications, and unrecognized devices being logged into your online accounts. Being observant early on helps minimize losses.
5. Take swift action if a SIM stops working: Contact your telecom provider and report the misuse to the Sanchar Saathi website as well as your nearest cyber station, or file a complaint through the cybercrime helpline number.

A Shared Responsibility

Consumer vigilance is not enough to save the system. Telecom providers must verify customer authenticity and check their retail points sufficiently so that a roadside vendor of the likes of “Shivam Telecom” cannot have their retail outlet anywhere the retail outlets may not need to be established and can be run even from an abandoned car body on the street for weeks. Authorities are ensuring this by making all franchisees and PoS agents and distributors register, such that the individual activating each SIM is perfectly identifiable. Consumers should take precautions and report suspicious patterns and be vigilant for fraud detection and protect themselves by knowing the system, like the use of the Sanchar Saathi platform.

Conclusion

The Delhi fake SIM case proves that even sophisticated technologies are not enough to protect India’s telecom ecosystem. No amount of biometric validation, AI fraud prevention tools, or rigid KYC compliance can offset a single corrupt agent selling SIM cards over the counter. While law enforcement works to clamp down, the responsibility also falls upon consumers, who need to regularly monitor their SIM registrations, safeguard their identity, and report any suspicious transactions in time to minimize the threat of identity theft and SIM-based cybercrime.

Sources

• https://www.prokerala.com/news/articles/a1784141.html 
• https://the420.in/dots-sanchar-saathi-initiative-exposes-21-lakh-sim-cards-activated-illegally 
•  https://www.sancharsaathi.gov.in/ 
•  https://www.pib.gov.in/PressReleasePage.aspx?PRID=2113857 
• https://www.business-standard.com/amp/industry/news/nearly-4-million-sims-deactivated-as-govt-cracks-down-on-digital-fraud-125080500300_1.html 
• https://www.digit.in/news/telecom/here-are-5-new-sim-card-rules-implemented-by-dot-amid-rising-scams-and-frauds.html 

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Introduction
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When Tamil Nadu Police arrested a man from Vellore in May 2026 on suspicion of being the point person helping Indian youth to be smuggled into cyber scam compounds in Cambodia, the papers led with the accused. They shouldn't have led with the accused but with the system. The arrest, one in a long string of them in Tamil Nadu, Madurai, and other states, is not simply another one-off policing victory. Rather, the arrest gives us an insight into a larger, darker world: an international criminal organisation that has successfully combined human trafficking and cybercrime, a new trend in criminality that specialists are calling 'cyber slavery.'
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What Is Cyber Slavery?

“Cyber slavery” involves trafficking persons under the pretence of employment, forcing them into committing online fraud to serve criminal enterprises. Victims are not merely victims of the work they are forced to do; they are often turned into culprits as they become complicit in victimising others. Trafficked victims are compelled to participate in frauds targeted at unsuspecting victims all around the globe. These activities, organised into robust criminal schemes, involve victims of sex or labour trafficking who are forced into operating romance scams or the so-called "pig butchering" scams that defraud people of their investment in cryptocurrency, all in heavily secured complexes guarded with threats of violence and torture. The extent of the problem is enormous, with the UN Office of the High Commissioner for Human Rights estimating in a 2023 report that there are over 100,000 victims of cyber scam compounds in Cambodia and another 120,000 in Myanmar. Schemes throughout Southeast Asia were projected to commit as much as $39.9 billion in fraudulent schemes a year.
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Why Southeast Asia? The Geography of Organised Crime
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In order to answer why Cambodia, Myanmar, Laos, and the surrounding regions have developed into the cyber slavery hub of the world, we can draw together an array of structural reasons:

• Casino clampdown and crime diversification: Cambodia's ban on online gambling in 2019 broke down established casino-related criminal networks. This saw old casinos and Special Economic Zones turn into cyber scam compound operations.
• Corruption and state complicity: A pre-existing environment of corruption and involvement of politically linked figures permitted scamming networks to flourish, and the armed groups in the border areas of Myanmar are reportedly complicit in these operations through supplying land and protection for the networks to operate in.
• Poor governance in the border areas: The lack of state control in the frontier areas of Myanmar provided the criminal networks with a secure sanctuary in which they could operate with impunity and cross borders to escape crackdowns and move their operations.
• Post-pandemic growth: The economic stress associated with the COVID-19 pandemic led to an increase in the supply of vulnerable individuals available to fill the scam networks, as well as unprecedented profit margins on scams.

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The Recruitment Pipeline: How Are Indian Youth Trapped?
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The typical journey from an Indian town or village to a locked compound in Southeast Asia follows the same narrative:

• The bait: On platforms like Facebook, WhatsApp, and Telegram, gangs lure with posts of lucrative overseas employment for IT work, customer service, data entry, and digital marketing with attractive, albeit feasible, pay packages (Rs. 80,000 to Rs. 1.5 lakh per month) and destinations such as Thailand and Singapore added for a veneer of genuineness.
• The recruiters: Local agents who gain trust, arrange visas and flight tickets, and collect the application fees are key intermediaries. Cases registered in Vellore and Madurai hint at recruitment agents receiving a commission for each person successfully smuggled into a trap, linked to larger travel and immigration networks.
• The lie: Victims are assured that they will be working legitimately in Thailand, but on reaching the border and crossing over, they find themselves pushed into scam compounds in neighbouring countries and have their passports, mobile phones and devices confiscated, thus rendering any escape attempt futile.
• The trap: In the interim, fake interviews, false job promises and convincing flight tickets serve to maintain the facade until the victims are forced to participate in cyber-fraud schemes.

The Architecture of Coercion: Life Inside the Scam Compounds
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It is in these compounds that the fates of the victims become known. Survivor accounts, investigations and UN human rights reports provide evidence of these circumstances. These compounds are often surrounded by barbed wire fences, monitored with cameras and heavily guarded. Once a potential victim is captured, they are stripped of their passports and any other electronic devices, preventing them from being able to contact the outside world or to escape. Workers are allocated stringent targets, ranging from the number of potential victims they must solicit for scams and the amount of money they must acquire through such scams. Failure to do so, or perceived disobedience, may lead to beatings, electroshock treatment, starvation and long periods in confinement. These beatings are supplemented with psychological torture, with scammers assuring their victims that they owe money for their journey, stay and training. This method of debt bondage keeps people at the compound even when the opportunity for escape is presented to them. The victims are then forced to take part in more complex online scams, which involve romance scams, fake investment scams, and impersonation scams using scripts and with supervision. In some cases, families will be encouraged to pay for their captive relatives' release by ransom, whereas those who refuse to comply or meet performance requirements may be sold and transferred to another compound as a piece of property within a transnational criminal network.
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Cybercrime Is No Longer Just About Hacking
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This emergency challenges the existing notion of cybercrime. The scam compound of Southeast Asia is not about a lonely hacker or a standalone breach; it is a form of organised cyber slavery in which trafficked individuals are made to commit financial fraud on an industrial level.

The probe of India's NIA found that recruitment is done in the Indian states of Bihar and Uttar Pradesh. Transport agents in Chennai and Madurai provide logistics, and Dubai and Bangkok act as transit points on the way to Cambodia, Laos, and Vietnam. It makes use of cryptocurrency wallets, shadow banking, and shell companies for the movement of funds across international borders. Companies such as the Huione Group has been accused of facilitating billions of dollars in financial transactions for scam infrastructure before receiving sanctions from the U.S.

To illustrate the threat landscape, the U.S. Treasury imposed sanctions on 19 entities spread across Myanmar and Cambodia and said that cyber scam operations looted $10 billion worth last year. Also, cryptocurrency transactions related to trafficking crimes jumped by 85% last year, which speaks to the expanding nature of the global criminal infrastructure.
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India's Exposure: A National Vulnerability
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The scale of exposure for India is large and expanding. The most likely victims are educated, and aspirational young men and women from Tier 2 and Tier 3 cities, seeking work abroad, which perfectly aligns with the primary target of such human trafficking networks.

Repeated incidents of people from Tamil Nadu falling victim to these networks have come to light. As far back as 2022, the chief minister wrote to the prime minister that close to 300 Indians, roughly 50 Tamils included, were being held in Myanmar. The Madurai-Cambodia case that came to light in 2026 revealed an entire network spanning Cambodia, Laos, and Vietnam, with authorities believing that thousands of Indians might have been trafficked there over the past three years. Such cases from Kerala, Karnataka, Andhra Pradesh, and some northern Indian states have been reported. Last year, India had to charter Air Force flights to rescue over 549 Indians from cyber scam centres along the Myanmar-Thailand border.

The Indian embassy in Phnom Penh assisted the Indian nationals along with the CBI, MEA, and NIA in the rescue of 67 Indians in September 2024; however, these operations are largely reactive in the face of the vast and evolving transboundary crisis.
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Prevention
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The best solution is awareness. The following are tangible signs that a job offer might be a lead to trafficking:

Red Flags within the job offer:

• Receiving unsolicited recruitment messages on WhatsApp, Telegram or Instagram from unknown numbers/contacts.
• Offer of unbelievably high salaries in undefined roles like ‘data entry,’ ‘online marketing’ or ‘customer service’ outside India.
• Request for upfront money to cover costs of visas, travel, accommodation, and training.
• Job offers to places in Thailand or Singapore involving complex transit routes through other countries.
• An interview process entirely through messaging apps, where the company has no real office address or registration number.
• Urgency and/or confidentiality required.

Verification:

• Check if the recruiter is registered on MEA's e-Migrate portal-this is a portal where MEA lists authorised overseas recruiters.
• Verify the authenticity of the company through its business registration with official registries in the foreign country.
• Contact the Indian Embassy/Consulate in that foreign country if something doesn't add up about the offer.
• Do not hand over your passport to your employer on arrival; it is standard practice for recruiters working as traffickers to confiscate it.

What to do if trapped:

• Contact the closest Indian embassy or consulate immediately.
• Call the MEA overseas helpline: 1800-11-3090.
• Lodge a report on the National Cybercrime Reporting Portal (cybercrime.gov.in).

Policy Imperatives
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On their own, individual consciousness cannot undo such a massive criminal infrastructure. India has to enforce the Emigration Act rigorously, implement mandatory licensing of recruitment agents and create a specialised task force consisting of NIA, CBI, MEA and the states’ cybercrime units. Pre-departure orientations should also become mandatory for migrant workers who go to Southeast Asia. Globally, India needs to work more closely with Cambodia, Myanmar, Thailand and Laos via intel sharing protocols, victim repatriations and action against scam compounds. Financial probes must be on par with enforcement investigations to catch up with the perpetrators’ network, the cryptocurrency and hawala channels that facilitate money laundering and finance trafficking operations, as that would severely hit these networks.
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Conclusion
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This arrest of the recruiter in Vellore is just a small piece of a larger network. What we see in these instances is the marriage of cybercrime, trafficking, and financial fraud into a larger transnational ecosystem that systematically preys on the economic vulnerability of individuals. These young Indians are not simply falling for scams; they are being systematically targeted, recruited, trafficked, and forced into these criminal operations by a networked structure. The scam compounds in Cambodia and along the border of Myanmar and Thailand are only the end of a process that very likely starts with a convincing job offer on social media. Fighting cyber slavery will not be as simple as more arrests; we need education and international efforts, as well as policy responses that match the scope and scale of the problem.
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References
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1. https://the420.in/78415-2vellore-man-cambodia-cyber-slavery-trafficking-case/
2. https://the420.in/madhan-vadivel-cambodia-cyber-slavery-trafficking-racket-investigation/
3. https://www.newsonair.gov.in/tamil-nadu-police-arrest-key-recruiter-in-cambodia-cyber-slavery-racket/
4. https://kashmirdotcom.in/2026/05/16/cambodia-linked-human-trafficking-cyber-slavery-racket-nia-chargesheets-five-including-absconding-kingpin/
5. https://www.aljazeera.com/news/2025/7/16/more-than-1000-arrested-in-cambodian-cyber-scam-raids
6. https://www.pbs.org/newshour/world/why-southeast-asias-online-scam-industry-is-so-hard-to-shut-down
7. https://www.cfr.org/articles/how-myanmar-became-global-center-cyber-scams
8. https://www.amlrightsource.com/resources/scam-states-the-cybercrime-corruption-complex-in-southeast-asia-and-the-collapse-of-anti-money-laundering-enforcement
9. https://newlinesinstitute.org/global-security-mil-priorities/cybercrimes-human-trafficking-and-cryptocurrency-in-southeast-asias-special-economic-zones/
10. https://www.theweek.in/news/india/2026/03/21/lured-by-jobs-sold-into-slavery-indias-crackdown-on-cyber-trafficking-continues.html

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The Expanding Governance Challenge of Artificial Intelligence
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Artificial intelligence (AI) systems are increasingly embedded in economic and social infrastructure. They are being adopted in financial services, healthcare diagnostics, hiring systems, and public administration. But while these systems improve efficiency and decision-making, they also introduce new forms of technological risk. 

Unlike conventional software, AI systems learn patterns from data and continue to evolve as they run. This poses governance issues since risks can arise throughout the AI life cycle, whether at the coding level or in their implementation.

The latest regulatory frameworks, such as the European Union’s AI Act (EU AI Act) and the UNESCO Recommendation on the Ethics of Artificial Intelligence, note that responsible AI governance depends on the realisation of where risks emerge across the development process. 

This article maps the AI system lifecycle, identifies the risks that emerge at each stage and evaluates the policy tools used to mitigate them using the lifecycle framework developed by the Organisation of Economic Co-operation and Development (OECD).
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The Lifecycle of an AI System
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AI systems are developed through a structured process that includes problem definition, dataset collection and preparation, model development, testing and validation, deployment, and monitoring.

The OECD conceptualises this development process as the AI system lifecycle. Each stage entails various technical and administrative procedures, since choices made during these stages will dictate the goals and limits of an AI system. Further, the quality and representativeness of training sets will have a strong effect on the behaviour of models after implementation.

Since this is an iterative and not a linear procedure, risks can be introduced at each stage of the AI lifecycle. New data can be retrained into different models, and systems are regularly updated once they have been deployed, to address performance degradation, model errors, or unintended outputs. This iterative process means governance must address risks across the entire lifecycle, not just at deployment.

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Where AI Risks Emerge
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AI risks usually emerge earlier in the development process, especially in the phases when system objectives are formulated and training data are chosen. The EU AI Act and the UNESCO Recommendation on the Ethics of AI outline the following risks:  bias and discrimination, privacy and data security violations, the absence of transparency in automated decision-making, and risks to fundamental rights.

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AI Governance Risk Landscape: Core Risk Categories Under International Frameworks
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 Risk categories jointly identified by the EU AI Act and UNESCO Recommendation on the Ethics of Artificial Intelligence

Outlining the risks throughout the AI lifecycle helps understand the areas where governance interventions are most necessary. For example, discriminatory outcomes often result from biased or unrepresentative training data, while safety failures are typically linked to inadequate testing before deployment. Risks such as misinformation arise post the development process, when generative AI systems are deployed at scale on digital platforms. 
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AI System Lifecycle: Key Risks at Each Stage
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Risks identified per the EU AI Act and UNESCO Recommendation on the Ethics of AI

Understanding where risks emerge across the lifecycle explains why governance frameworks classify AI systems by risk and apply oversight at multiple stages.
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Policy Tools for Mitigating AI Risks
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Governments and international organisations have developed regulatory tools to help mitigate AI risks in the lifecycle. These tools are meant to make sure that AI technologies are identified as up to standard in safety, accountability and fairness prior to and after deployment. 

For example, the OECD AI Policy Observatory recommends that governments adopt policy instruments such as risk evaluations, algorithmic auditing necessities, regulatory sandboxes, and transparency necessities of AI systems. The European Union’s Artificial Intelligence Act (AI Act) is one of the most comprehensive systems of governance that introduces a risk-oriented regulation strategy. It mandates adherence to requirements concerning data governance, documentation, human oversight, and robustness, and cybersecurity. Such requirements bring regulatory checkpoints to the lifecycle of AI systems.

Mapping these policy tools across the lifecycle illustrates how governance mechanisms can intervene at different stages of AI development. 
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Governance Overlay: Policy Interventions Across the AI Lifecycle
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Regulatory tools mapped at each stage of AI development per the EU AI Act and UNESCO Recommendation on the Ethics of AI

Several policy tools are directed at the risks that occur in the pre-developmental stages. In one example, algorithmic impact assessment has been applied in various jurisdictions to measure the possible consequences of automated decision systems on society before implementation. On the same note, the requirements of dataset documentation, including dataset transparency requirements and model cards, are aimed at enhancing accountability during the training and development stages of the AI systems. Therefore, lifecycle-based policy design allows regulators to intervene before harmful outcomes occur, rather than responding only after AI systems have caused damage in real-world environments.
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The Policy Gap in AI Governance
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The misalignment between risks and governance tools across the AI lifecycle indicates a critical structural gap in existing regulations. Numerous governance processes become activated after AI systems are classified as “high risk” or after they are implemented in the real world. But the most serious sources of damage have their roots in earlier stages of the development procedure.

An example is that prejudiced or unbalanced training data is almost inevitably a source of discriminative results in automated decision systems. When these types of models are applied in areas like staffing, credit rating, or in providing services to the public, such biases can quickly spread to large populations and undermine democratic rights. In the same way, the lack of transparency in model design might result in the fact that the regulator or individuals are affected by the decision-making process. This reflects a broader timing gap in AI governance, where risks originate during design and development, but regulatory intervention typically occurs only after deployment. 

Analysis
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1. Key risks originate before deployment: As depicted in the lifecycle mapping, the data collection and model development phase presents several significant governance risks as opposed to the deployment phase. Structural issues can be entrenched within AI systems even before they are deployed in practice due to bias in data sets, incomplete reporting of training sets, and obscured network designs.

2. Data governance is a primary point of vulnerability: Most of the instances of algorithmic discrimination listed above are associated with training material that is not representative of some population groups or is historical. Since machine learning models are optimisations of patterns that exist in datasets, these biases can be carried through the whole lifecycle and reproduced after deployment. 

3. Regulatory approaches remain mismatched across jurisdictions: Different countries adopt varying approaches to AI governance, ranging from risk-based frameworks such as the EU AI Act to more sector-specific or voluntary guidelines in other regions. This divergence creates inconsistencies in safety, accountability, and enforcement standards, allowing risks to persist across borders and potentially undermining the protection of users in globally deployed AI systems. 

4. Governance interventions remain uneven across the lifecycle: Whereas the various regulatory instruments aim at deployment and monitoring, fewer instruments systematically tackle the risks that are posed by the previous design and development phases.
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Recommendations
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1. Introduce mandatory lifecycle risk assessments: The regulatory systems need to demand systemic risk evaluation at the beginning of AI development, especially at the problem design and dataset selection phases. This would assist in detecting possible harmful applications in advance, before systems are constructed and installed.

2. Strengthen dataset governance standards: Training datasets must be supplemented with documentation as to their provenance, composition and limitations. Standardised documentation frameworks of data sets can assist in the discovery by regulators and auditors of the potential sources of bias or privacy threats.

3. Expand independent algorithmic auditing: AI systems can be assessed by regular third-party audits based on fairness, strength, and security weaknesses. The auditing mechanisms especially apply to high-risk systems employed in employment, finance or the public services.

4. Integrate continuous monitoring requirements: AI systems may be monitored regularly after implementation to identify model drift, unforeseen consequences, or abuse. Reporting systems can facilitate the process where the regulators can see the emerging risks and modify the governance systems.
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Conclusion - The Need for Global AI Governance
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Despite growing regulatory attention, global air governance remains fragmented. Different jurisdictions adopt varying approaches to risk classification, oversight, and enforcement, leading to inconsistencies in safety and accountability standards. Given that AI systems are often developed, deployed, and used across borders, this lack of coordination allows risks to persist beyond national regulatory frameworks.

Addressing these challenges requires a shift towards greater international cooperation and lifecycle-based governance. Developing shared standards, improving cross-border regulatory alignment, and embedding oversight across all stages of AI development will be essential to ensuring that AI systems are safe, transparent, and accountable in a globally interconnected environment.
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References
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• OECD AI lifecycle
• OECD AI system lifecycle description
• OECD AI governance lifecycle framework
• EU AI Act overview
• EU AI Act risk categories
• UNESCO Recommendation on the Ethics of AI
• AI governance lifecycle analysis
• OECD AI policy tools database

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