{"id":5737,"date":"2025-09-28T23:09:52","date_gmt":"2025-09-28T17:39:52","guid":{"rendered":"https:\/\/lawjurist.com\/?p=5737"},"modified":"2025-09-28T23:25:38","modified_gmt":"2025-09-28T17:55:38","slug":"regulating-artificial-intelligence-in-india-legal-challenges-developments-and-the-way-forward","status":"publish","type":"post","link":"https:\/\/lawjurist.com\/index.php\/2025\/09\/28\/regulating-artificial-intelligence-in-india-legal-challenges-developments-and-the-way-forward\/","title":{"rendered":"Regulating Artificial Intelligence in India: Legal Challenges, Developments, And the Way Forward"},"content":{"rendered":"\t\t
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Author: Bachali Sampath Kumar, a student of LL. B Final year at Justice Kumarayya college of law, Karimnagar, Telangana.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Introduction:<\/b>\u00a0\u00a0<\/b><\/p>\n

Artificial Intelligence (AI) is revolutionizing numerous domains: health, education,\u00a0 administration, policing, business, entertainment. Its potential is huge \u2014 enhanced\u00a0 efficiency, predictive power, enhanced decision-making, innovation. But with promise\u00a0 comes risk: algorithmic bias, opacity, privacy breaches, misuse, discrimination,\u00a0 intellectual property concerns, liability, ethical issues. In India, phenomenal AI\u00a0 adoption is now highlighting shortcomings in legal and regulatory systems. As of 2023\u2013 2025, India has made significant legislative (such as the Digital Personal Data\u00a0 Protection Act, 2023) and judicial\/administrative directives, but challenges abound.\u00a0<\/span><\/p>\n

This article discusses the present legal situation in India regarding AI regulation, locates\u00a0 gaps and issues, considers recent trends, and puts forward recommendations for a\u00a0 strong legal framework that is balanced with innovation and protection of rights and\u00a0 harm minimization.\u00a0<\/span><\/p>\n

\u00a0<\/span>I \u00a0 The Legal & Regulatory Landscape in India:\u00a0<\/b><\/p>\n

    \n
  1. Right to Privacy as the Point of Departure :\u00a0<\/b><\/li>\n<\/ol>\n

    The historic Supreme Court ruling in Justice K.S. Puttaswamy (Retd.) & Ors. v. Union of\u00a0 India (2017) declared right to privacy to be a basic right under Article 21 and Part III of\u00a0 the Constitution. This provides constitutional basis for restraining the use of data by\u00a0 the state or private actors, including AI systems, wherever privacy is involved.\u00a0<\/span><\/p>\n

      \n
    1. Digital Personal Data Protection Act, 2023 :\u00a0<\/b><\/li>\n<\/ol>\n

      The DPDP Act (2023) is India’s existing legislative digital personal data protection\u00a0 statute. It provides for regulating processing of digital personal data in a way that\u00a0 balances the requirement of protection of individual rights and the legal need to\u00a0 process such data for permissible purposes. It is, however, not yet operational and\u00a0 there are questions regarding its sufficiency for AI-related issues.\u00a0\u00a0<\/span><\/p>\n

        \n
      1. Information Technology Act, Rules, and Policies:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

        \u00a0<\/b>Current legislation like the Information Technology Act, 2000 (IT Act) and regulations\u00a0 thereunder addresses cybersecurity, intermediary liability, data breach disclosure, etc.\u00a0 However, they were not enacted with AI in their sight. A lot of governmental\u00a0 administrative guidelines and policies by think-tanks are surfacing to tackle AI but often\u00a0 without enforceability or precision.<\/span><\/p>\n

          \n
        1. Judicial \/ Court Guidelines :\u00a0<\/b><\/li>\n<\/ol>\n

          Courts have begun to address AI in certain contexts. For example, the Kerala High\u00a0 Court recently issued guidelines prohibiting use of AI tools for decision-making or\u00a0 legal reasoning in the district judiciary, pointing to risks in transparency, accountability,\u00a0 data security. This shows judicial sensitivity to AI\u2019s potential misuse and the need for\u00a0 safeguards when AI enters the legal and decision-making domain.\u00a0<\/span><\/p>\n

            \n
          1. Sectoral & Emerging Technologies Regulation :\u00a0<\/b><\/li>\n<\/ol>\n

            Aside from pure regulation of AI, there are secondary and allied areas: online gaming\u00a0 regulation (e.g., Promotion and Regulation of Online Gaming Act, 2025) broadcasting\u00a0 regulation (Broadcasting Services Regulation Bill) . Not being AI-related, these are still\u00a0 part of the larger digital regulation ecosystem.\u00a0<\/span><\/p>\n

              \n
            1. Key Legal Challenges in AI Regulation:\u00a0<\/b><\/li>\n<\/ol>\n

              While the law is changing, there are still a number of issues. These are both legal\u00a0 (statutory, jurisprudential) and practical (enforcement, technical, ethical) issues.\u00a0<\/span><\/p>\n

                \n
              1. Absence of AI-Specific Legislation:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                Existing laws cover general data protection, cybersecurity, intermediary liability, etc.,\u00a0 but none are tailored specifically for AI\u2019s unique issues: algorithmic decision-making,\u00a0 opaque models (\u201cblack box\u201d problems), autonomous systems, self-learning systems,\u00a0 deepfakes. India currently lacks a unified, dedicated statute or clear legal standards\u00a0 specifically addressing AI liability, transparency obligations, fairness norms.\u00a0<\/span><\/p>\n

                  \n
                1. Transparency, Explainability, and Algorithmic Bias :\u00a0<\/b><\/li>\n<\/ol>\n

                  AI systems can reinforce or enhance biases in training data (gender, caste, race, socio economic). When algorithms are opaque, it is hard for the affected individuals to\u00a0 contest decisions. Questions of importance: who needs to reveal what goes on inside?\u00a0 How much is needed? Is there a legal recourse if bias is proved? No existing laws\u00a0 explicitly mandate explainability or fairness audits.\u00a0\u00a0<\/span><\/p>\n

                    \n
                  1. Privacy & Data Protection:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                    AI tends to work based on big data sets, which may also contain sensitive personal\u00a0 information, biometric data, etc. Despite the DPDP Act, 2023, there are issues\u00a0 remaining like data minimization, purpose limitation, anonymization v\/s\u00a0 pseudonymization, cross-border data transfers, exceptions in case of the state or law\u00a0 enforcement authority, and the mass surveillance\/misuse possibility. Moreover,\u00a0 occasions like biometric leaks point towards risks in collecting, storing, and governing\u00a0 data.\u00a0<\/span><\/p>\n

                      \n
                    1. Liability & Accountability :\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                      \u00a0<\/b>When AI systems cause harm (e.g., wrongful decision, discrimination, physical harm\u00a0 in autonomous systems), who is responsible? The manufacturer, the deployer, the\u00a0 algorithm designer, or the user? Currently, tort, contract, consumer protection laws\u00a0 may apply, but these were not designed with AI\u2019s complexity. The absence of clarity\u00a0 can deter accountability or lead to relabeling the problem.\u00a0\u00a0<\/span><\/p>\n

                        \n
                      1. Intellectual Property Issues:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                        AI-created content (art, literature, music, code) poses questions: to whom does\u00a0 copyright belong, if created by AI? The training data used for training copyrighted\u00a0 content infringing? Derivative works? Current IP laws in India don’t satisfactorily\u00a0 answer these.\u00a0\u00a0<\/span><\/p>\n

                          \n
                        1. Ethical, Social & Socioeconomic Implications:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                          AI has wider implications: labour displacement, inequality, attacks on democratic\u00a0 debate (through deepfakes, disinformation), surveillance, discrimination. There is also\u00a0 potential for chilling effects if users are ever afraid of being constantly monitored. Laws\u00a0 need to address not only legal liability but also ethical standards.\u00a0\u00a0<\/span><\/p>\n

                            \n
                          1. Enforcement, Technical Capacity, Fragmentation:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                            Regulations are only as good as they can be enforced. Indian regulators might not have\u00a0 technical savvy to audit AI systems, to test for bias, to validate algorithms. Further,\u00a0 patchwork regulation \u2014 various sectors subject to disparate rules (health, finance,\u00a0 telecom) \u2014 can cause inconsistent standards.\u00a0\u00a0<\/span><\/p>\n

                              \n
                            1. Cross-Border and International Law Issues :\u00a0<\/b><\/li>\n<\/ol>\n

                              AI systems & data frequently transcross jurisdictions. Data stored overseas, training on\u00a0 international datasets, output shared worldwide. Which norms hold? How to resolve\u00a0 clashes between legislation? India’s legislation needs to fit in with world norms (e.g.,\u00a0 GDPR, OECD guidelines) for consistency, trade, data flows.\u00a0\u00a0<\/span><\/p>\n

                              \u00a0<\/span>III. Recent Developments & Emerging Trends :\u00a0<\/b><\/p>\n

                              India is dynamic; there are a number of recent legal\/regulatory & policy-trends which\u00a0 indicate progress or reveal tensions.\u00a0<\/span><\/p>\n

                                \n
                              1. DPDP Act Rules & Enforcement :\u00a0<\/b><\/li>\n<\/ol>\n

                                The government has issued (up to September 2025) that the administrative rules of\u00a0 the Digital Personal Data Protection Act will be out (28 September 2025). ([The\u00a0 Economic Times][3]) These rules are likely to help explain key implementation issues.\u00a0<\/span><\/p>\n

                                How consent requirements in AI<\/span>\u2011<\/span>contexts would function, data fiduciary obligations,\u00a0 grievance redressal, retention, erasure, cross<\/span>\u2011<\/span>border transfer, etc.\u00a0<\/span><\/p>\n

                                  \n
                                1. Content Deletion \/ Intermediary Liability Regimes :\u00a0<\/b><\/li>\n<\/ol>\n

                                  Social media companies are being made to meet higher accountability in terms of\u00a0 content takedown. For instance, recently, the Karnataka High Court rejected X’s appeal\u00a0 against the content takedown mechanism launched by the Indian government, holding\u00a0 that social media companies need to be answerable to Indian law. ([Reuters][12]) The\u00a0 balance between free speech and regulation of content (hate speech, fake news etc.)\u00a0 is being dramatized here.\u00a0<\/span><\/p>\n

                                    \n
                                  1. Judicial Directives on AI Application:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                    \u00a0<\/b>Kerala High Court guidelines that district judiciary should not employ AI tools in\u00a0 decision-making or legal reasoning reflect a precautionary approach. The judiciary is\u00a0 acknowledging its dual roles of user and regulator of AI tools, especially in rights influencing decisions.\u00a0<\/span><\/p>\n

                                      \n
                                    1. Leakage of Biometric Data & Privacy Incidents :\u00a0<\/b><\/li>\n<\/ol>\n

                                      The release of huge amounts of police and biometric information of applicants in India\u00a0 (fingerprints, facial scanning etc.) highlights systemic threats. Such events draw public\u00a0 notice and legal call for tighter data protection, safe storage, accountability.\u00a0\u00a0<\/span><\/p>\n

                                        \n
                                      1. AI Misuse & Fraud :\u00a0<\/b><\/li>\n<\/ol>\n

                                        Concern is rising regarding abuse of AI by scammers and its dual<\/span>\u2011<\/span>edged character:\u00a0 boosting services, but also facilitating scams. Experts have called for greater clarity in\u00a0 liability, capacity<\/span>\u2011<\/span>building, and regulation.\u00a0\u00a0<\/span><\/p>\n

                                          \n
                                        1. Analysis: Gaps and Tensions:\u00a0<\/b><\/li>\n<\/ol>\n

                                          Having witnessed these developments, what are the gaps or tensions that remain?\u00a0 Understanding these is essential to be able to suggest rational reforms.\u00a0<\/span><\/p>\n

                                            \n
                                          1. Ambiguities in Definitions and Scope:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n
                                              \n
                                            • What is considered “high<\/span>\u2011<\/span>risk AI”? Are all AI applications subject to equal treatment by law, or do some face more rigorous obligations?\u00a0<\/span><\/li>\n
                                            • Definition of “automated decision<\/span>\u2011<\/span>making,” “algorithmic bias,” “explainability,”\u00a0 “interpretability” etc., are not standardized yet in Indian law.\u00a0<\/span><\/li>\n<\/ul>\n
                                                \n
                                              1. Balancing Innovation with Regulation:\u00a0<\/b><\/li>\n<\/ol>\n

                                                Too much rigid or slow regulation can smother innovation, most notably for startup\u00a0 firms. Under-regulation, by contrast, causes harm. Finding an optimal level of\u00a0 regulatory balance is challenging.\u00a0<\/span><\/p>\n

                                                  \n
                                                1. Enforcement Mechanisms & Regulatory Capacity:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n
                                                    \n
                                                  • \u2219 <\/span>Who will audit AI systems? What technical standards will they utilize? How often\u00a0 will audits occur?\u00a0<\/span><\/li>\n
                                                  • \u2219 <\/span>Institutions need data science expertise, algorithmic fairness expertise, AI safety\u00a0 expertise, etc.\u00a0<\/span><\/li>\n
                                                  • \u2219 <\/span>Sanctions and redress need to be strong enough to deter non<\/span>\u2011<\/span>compliance.<\/span><\/li>\n<\/ul>\n
                                                      \n
                                                    1. Accountability & Attribution of Liability:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n
                                                        \n
                                                      • \u00a0<\/span>When a harmful AI<\/span>\u2011<\/span>driven decision is made, whose error is it? Developers\u00a0 responsible, operators, users, data providers?\u00a0<\/span><\/li>\n
                                                      • \u00a0<\/span>How will courts determine causation when decisions are unclear or emergent\u00a0 characteristics of algorithms?\u00a0<\/span><\/li>\n<\/ul>\n
                                                          \n
                                                        1. Privacy vs Public Interest \/ State Surveillance :\u00a0<\/b><\/li>\n<\/ol>\n
                                                            \n
                                                          • \u2219 <\/span>Legislation should restrict abuse of AI by government agencies in the name of\u00a0 the security. State exemptions or blanket permissions could subvert the Right\u00a0 to Privacy.\u00a0<\/span><\/li>\n
                                                          • \u2219 <\/span>Furthermore, mass surveillance (e.g., facial recognition, predictive policing)\u00a0 needs to be properly regulated.\u00a0<\/span><\/li>\n<\/ul>\n
                                                              \n
                                                            1. IP Rights & AI<\/b>\u2011<\/span>Generated Works:\u00a0<\/b><\/li>\n<\/ol>\n

                                                              Vesting of copyright in a human creator, even if AI created significant material? <\/span>\u2219 <\/span>Are training sets copyrighted materials? Used without a valid license, this can\u00a0 be infringing. Existing jurisprudence and legislation are presently inadequate.\u00a0<\/span><\/p>\n

                                                                \n
                                                              1. Data Quality, Bias, and Fairness :\u00a0<\/b><\/li>\n<\/ol>\n

                                                                Algorithmic decisions based on biased data sets produce discriminatory results.\u00a0 Potential to perpetuate entrenched inequalities.\u00a0<\/span><\/p>\n

                                                                  \n
                                                                1. Transparency and Explainability :\u00a0<\/b><\/li>\n<\/ol>\n

                                                                  \u00a0<\/b>The “black box” of much AI may deprive individuals of the means to contest\u00a0 detrimental decisions. Require legal requirement for explanation, audit trails, rights\u00a0 to know.<\/span><\/p>\n

                                                                    \n
                                                                  1. What a Robust Regulatory Framework Should Include :\u00a0<\/b><\/li>\n<\/ol>\n

                                                                    Based on the above, below are recommendations and best practices for legal\u00a0 reform\/regulation, policy, and practice in India.\u00a0<\/span><\/p>\n

                                                                      \n
                                                                    1. Specific AI Legislation or Amendments :\u00a0<\/b><\/li>\n<\/ol>\n
                                                                        \n
                                                                      • Pass a standalone AI law (or amendment) that is consistent with DPDP but\u00a0 specifically focuses on AI systems. Major points:\u00a0<\/span><\/li>\n
                                                                      • Clarify “AI”, “automated decision-making”, “high<\/span>\u2011<\/span>risk AI”, “algorithmic bias”,\u00a0 etc.\u00a0<\/span><\/li>\n
                                                                      • Requirements for AI design, deployment, regular monitoring.\u00a0 Mandatory risk assessments for high<\/span>\u2011<\/span>risk applications (health, policing, social\u00a0 benefits etc.). Requirements for explainability, transparency, documentation.\u00a0<\/span><\/li>\n<\/ul>\n
                                                                          \n
                                                                        1. Risk<\/b>\u2011<\/span>Based Regulation :\u00a0<\/b><\/li>\n<\/ol>\n

                                                                          \u00a0<\/b>Not all AI is equally risky. Some uses (e.g. benign recommendation systems) require\u00a0 less oversight; others (judicial, policing, health) need much more careful regulation.\u00a0 The law should adopt a tiered risk<\/span>\u2011<\/span>based approach.\u00a0<\/span><\/p>\n

                                                                            \n
                                                                          1. Accountability & Liability Mechanisms:\u00a0<\/b><\/li>\n<\/ol>\n
                                                                              \n
                                                                            • Define clear principles on who bears responsibility for harm inflicted by AI: designer, deployer, data provider, user. May involve joint liability in some\u00a0 instances.\u00a0<\/span><\/li>\n
                                                                            • Provide remedies for persons: right to claim redress, compensation. <\/span>\u2219 <\/span>Supervision or oversight authorities with powers to impose.\u00a0<\/span><\/li>\n<\/ul>\n
                                                                                \n
                                                                              1. Transparency \/ Explainability :\u00a0<\/b><\/li>\n<\/ol>\n
                                                                                  \n
                                                                                • Mandate that automated decision-making involves the provision of explanation\u00a0 accessible to the affected persons.\u00a0<\/span><\/li>\n
                                                                                • Preservation of audit trails, decision-logs, and independent audits. <\/span>\u2219 <\/span>Disclosure requirements on training data sources (as commercially viable).\u00a0<\/span><\/li>\n<\/ul>\n
                                                                                    \n
                                                                                  1. Data Protection Enhancement :\u00a0<\/b><\/li>\n<\/ol>\n
                                                                                      \n
                                                                                    • Facilitate minimization of data, limiting its purpose,\u00a0 anonymization\/pseudonymization where feasible.\u00a0<\/span><\/li>\n
                                                                                    • Tight effective provisions for sensitive and biometric data.\u00a0<\/span><\/li>\n
                                                                                    • Safeguards against mass surveillance, abuse by state or private entities. <\/span>\u2219 <\/span>Secure framework for cross-border data flows.<\/span><\/li>\n<\/ul>\n
                                                                                        \n
                                                                                      1. Ethical Norms & Standards:\u00a0\u00a0<\/b><\/li>\n<\/ol>\n
                                                                                          \n
                                                                                        • Promote adoption of ethical guidelines: e.g., fairness, non-discrimination,\u00a0 inclusivity. These can be codified or made statutory.\u00a0<\/span><\/li>\n
                                                                                        • Mandate impact assessments (both privacy and fairness) prior to deployment\u00a0 of high-risk AI.\u00a0<\/span><\/li>\n<\/ul>\n
                                                                                            \n
                                                                                          1. Capacity Building & Technical Expertise :\u00a0<\/b><\/li>\n<\/ol>\n
                                                                                              \n
                                                                                            • Government agencies, regulatory bodies, courts must develop experience and\u00a0 technical capacity.\u00a0<\/span><\/li>\n
                                                                                            • AI, algorithm, data science training of regulators, judges, law enforcers. <\/span>\u2219 <\/span>Perhaps setting up a specialized agency or bureau to oversee AI regulation.\u00a0<\/span><\/li>\n<\/ul>\n
                                                                                                \n
                                                                                              1. Public Participation, Transparency, and Oversight :\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                Engage civil society, academia, experts in privacy in rulemaking, oversight. <\/span>\u2219 <\/span>Transparency in regulation: public disclosure of government or private sector\u00a0 deployed high-risk AI systems;\u00a0 reporting requirements for serious adverse incidents.\u00a0<\/span><\/p>\n

                                                                                                  \n
                                                                                                1. External Collaboration & Alignment:\u00a0<\/b><\/li>\n<\/ol>\n
                                                                                                    \n
                                                                                                  • Align with worldwide standards (EU AI Act, OECD AI principles, UNESCO\u00a0 guidelines etc.) to be interoperable, enable trade, data exchange\u00a0<\/span><\/li>\n
                                                                                                  • Join standards-setting, collaboration, sharing best practices.\u00a0<\/span><\/li>\n<\/ul>\n
                                                                                                      \n
                                                                                                    1. Enforcement & Remedies:\u00a0<\/b><\/li>\n<\/ol>\n
                                                                                                        \n
                                                                                                      • Severe penalties for non<\/span>\u2011<\/span>adherence: financial penalties; banning use in certain\u00a0 situations; withdrawal of permits.\u00a0<\/span><\/li>\n
                                                                                                      • Prompt and easy grievance redressal mechanisms for parties adversely affected. <\/span>\u2219<\/span><\/li>\n
                                                                                                      • \u00a0<\/span>Judicial review: courts must be given the authority to review AI decisions, even\u00a0 to direct disclosure of pertinent algorithmic information in suitable instances.\u00a0<\/span><\/li>\n<\/ul>\n
                                                                                                          \n
                                                                                                        1. Case Studies \/ Illustrations :\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                          To demonstrate the problems and the ways in which regulation may or has occurred\u00a0 (or should), these are some examples:\u00a0<\/span><\/p>\n

                                                                                                            \n
                                                                                                          1. Kerala High Court Guidelines\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                            The latest Kerala High Court guidelines prohibiting the use of AI tools for legal\u00a0 reasoning in the district judiciary underscore courts’ apprehension regarding due\u00a0 process, natural justice, transparency. It is a cautious interim measure where AI is\u00a0 applied to situations with high stakes.<\/span><\/p>\n

                                                                                                              \n
                                                                                                            1. Biometric Data Leak\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                              The case in which police recruits’ biometric information (fingerprints, facial scans etc.)\u00a0 were leaked highlights the risk in gathering, storing, data safety. This one reveals what\u00a0 occurs when there are no vigorous safeguards, and compels the necessity for legal\u00a0 requirements for security measures, breach disclosure, responsibility.\u00a0\u00a0<\/span><\/p>\n

                                                                                                                \n
                                                                                                              1. AI as Tool for Fraud & Misuse\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                Reports of AI being used by fraudsters to deceive systems or carry out identity\u00a0 theft\/complex scams illuminate technical abuse and loopholes in the law. This indicates\u00a0 that legislation has to include abuse, cybercrime, and ensure remedies are in place.\u00a0<\/span><\/p>\n

                                                                                                                  \n
                                                                                                                1. Content Removal & Free Speech vs Censorship\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                  The instance in which X (ex-Twitter) attempted to defy India’s upgraded content\u00a0 removal process, but there was compliance enforced by courts, in balancing freedom\u00a0 of speech and responsibility. This indicates that online speech, platforms, content\u00a0 moderation are also components of the AI\/digital regulation environment.\u00a0\u00a0<\/span><\/p>\n

                                                                                                                  VII. Policy & Lawmaker Recommendations :\u00a0<\/b><\/p>\n

                                                                                                                  Based on analysis, here are practical recommendations:\u00a0<\/span><\/p>\n

                                                                                                                    \n
                                                                                                                  1. Accelerate Rule<\/b>\u2011<\/span>Making under DPDP Act , with considerations specifically for AI.\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                    The new rules should clearly deal with automated decision<\/span>\u2011<\/span>making, fairness in\u00a0 algorithms, sensitive personal data, anonymization, liability, cross<\/span>\u2011<\/span>border transfers.\u00a0 The consultations for stakeholders should involve tech specialists, civil society,\u00a0 representatives of data subjects.\u00a0<\/span><\/p>\n

                                                                                                                      \n
                                                                                                                    1. Develop an “AI Regulatory Framework \/ Act” which exists in tandem with DPDP Act\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                      \u00a0<\/b>The Act may identify high<\/span>\u2011<\/span>risk types, prescribe responsibilities of transparency and\u00a0 risk analysis, establish oversight bodies, determine penalties, provide redressal.\u00a0<\/span><\/p>\n

                                                                                                                        \n
                                                                                                                      1. Require Impact Assessments, Audits, Certification for High<\/b>\u2011<\/span>Risk AI\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                        \u00a0<\/b>Just as environmental laws tend to mandate environmental impact assessment, AI\u00a0 must have algorithmic \/ ethical \/ human rights impact assessments.\u00a0<\/span><\/p>\n

                                                                                                                          \n
                                                                                                                        1. Create an AI Oversight Authority\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                          \u00a0<\/b>Standalone agency (national or semi<\/span>\u2011<\/span>independent) with technical personnel,\u00a0 regulatory authority, investigative authority, that can impose regulations, certify\u00a0 high<\/span>\u2011<\/span>risk systems, audit compliance, and investigate occurrences.<\/span><\/p>\n

                                                                                                                            \n
                                                                                                                          1. Judicial & Procedural Safeguards\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                            Courts must implement rights to explanation; evidence law might need to adjust to\u00a0 accommodate AI<\/span>\u2011<\/span>created evidence; assure due process in use of AI by government.\u00a0<\/span><\/p>\n

                                                                                                                              \n
                                                                                                                            1. Public Transparency & Disclosure\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                              \u00a0<\/b>Mandatory public disclosure of certain data: which government<\/span>\u2011<\/span>used AI systems,\u00a0 dataset origin, high<\/span>\u2011<\/span>risk systems deployed, incidents, etc.\u00a0<\/span><\/p>\n

                                                                                                                                \n
                                                                                                                              1. Encourage Research & Standards\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                                Facilitate creation of open datasets, bias detection techniques, fairness &\u00a0 interpretability tools; establish technical standards (in coordination with the world) for\u00a0 AI safety, privacy, security.\u00a0<\/span><\/p>\n

                                                                                                                                  \n
                                                                                                                                1. Capacity Building\u00a0\u00a0<\/b><\/li>\n<\/ol>\n

                                                                                                                                  \u00a0<\/b>Legal education incorporating AI law; training regulators; law enforcement; judiciary;\u00a0 also tech developers to know legal responsibilities.\u00a0<\/span><\/p>\n

                                                                                                                                  VIII. Conclusion :\u00a0<\/b><\/p>\n

                                                                                                                                  AI is both a challenge and an opportunity. For India, the stakes are too high: inclusive\u00a0 growth, digital economy development, safeguarding constitutional rights (privacy,\u00a0 equality, freedom of speech) all hang in balance with how well regulation catches up.\u00a0 We already possess robust constitutional foundations, some new legislations (DPDP\u00a0 Act), judicial interventions. Yet much remains to be filled: liability, explainability,\u00a0 enforcement, capacity.\u00a0<\/span><\/p>\n

                                                                                                                                  A balanced regulatory framework that is risk<\/span>\u2011<\/span>based, transparent, enforceable, ethically\u00a0 conscious and technologically informed is indispensable. With the right legal\u00a0 architecture, India can harness AI\u2019s benefits while minimizing its harms \u2014 ensuring\u00a0 justice, fairness, privacy, and innovation go hand in hand.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

                                                                                                                                  Author: Bachali Sampath Kumar, a student of LL. B Final year at Justice Kumarayya college of law, Karimnagar, Telangana. Introduction:\u00a0\u00a0 Artificial Intelligence (AI) is revolutionizing numerous domains: health, education,\u00a0 administration, policing, business, entertainment. Its potential is huge \u2014 enhanced\u00a0 efficiency, predictive power, enhanced decision-making, innovation. But with promise\u00a0 comes risk: algorithmic bias, opacity, privacy breaches, […]<\/p>\n","protected":false},"author":1,"featured_media":5012,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[],"_links":{"self":[{"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/posts\/5737"}],"collection":[{"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/comments?post=5737"}],"version-history":[{"count":7,"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/posts\/5737\/revisions"}],"predecessor-version":[{"id":5746,"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/posts\/5737\/revisions\/5746"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/media\/5012"}],"wp:attachment":[{"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/media?parent=5737"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/categories?post=5737"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lawjurist.com\/index.php\/wp-json\/wp\/v2\/tags?post=5737"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}