Legal Challenges and Opportunities due to Overlapping of AI and IPR

Paper Code: AIJACLAV08RP2025

Category: Research Paper

Date of Publication: May 19, 2025

Citation: Adv Sunil L Kalagi & Mr. Ranjan Kumar Ray, “Legal Challenges and Opportunities due to Overlapping of AI and IPR", 5, AIJACLA, 74, 74-88 (2025), <https://www.aequivic.in/post/legal-challenges-and-opportunities-due-to-overlapping-of-ai-and-ipr>

Author Details: Adv Sunil L Kalagi, LLM, Final Year Student, Kalinga University Naya, Raipur &

Mr. Ranjan Kumar Ray, Asst. Professor, Kalinga University, Faculty of Law, Naya Raipur, Chhattisgarh

Download PDF

Abstract

The rapid advancement of Artificial Intelligence (AI) technologies presents a unique intersection with intellectual property rights (IPR), leading to both legal challenges and opportunities. The integration of AI into creative fields is reshaping traditional Intellectual Property (IP) laws and practices.

The study looks at the ramifications of AI's ability to produce, invent, and imitate human-like results, which frequently prompts questions concerning authorship and ownership in relation to copyright, patents, and trademarks. The inability to assign legal responsibility for works produced by AI, the suitability of current IPR frameworks for dealing with non-human producers, and the possibility of infringement brought on by AI's data-driven processes are some of the main obstacles. Concerns about data privacy and ethical implications are brought up by the application of AI in sectors like healthcare and finance. On the other conjunction, there are several benefits to incorporating AI with IPR systems, including improved enforcement tools, more effective IP portfolio management, and creative license agreement models. The study recommends Reassessing current IPR frameworks and enacting new rules. Amid debates concerning authorship and ownership in the AI era, there is an urgent need for an approach to IPR that is technologically neutral across various sectors. To fully realize AI's potential while ensuring the preservation of artists' rights, it will be crucial as stakeholders should address these concerns through designing and updating new policies and taking references from other countries like USA and European Union.

Keywords: Artificial Intelligence (AI), Intellectual Property Rights (IPR), Sustainable Development Goals (SDGs), Infringement, Legal Liability.

I. INTRODUCTION

‘Artificial Intelligence’ (AI) technology's quick development has revolutionized a wide range of industries, including healthcare, banking, entertainment, and the creative arts. Artificial intelligence (AI) is the emulation of human intelligence in computers that have been designed to think and learn similarly to humans.[1] This covers skills including identifying patterns, comprehending natural language, and solving problems. Important concerns regarding the protection of ‘Intellectual Property Rights’ (IPR) are brought up by AI systems' growing ability to create material, make judgments, and automate procedures.

The legal rights known as Intellectual Property Rights (IPR) give authors and inventors sole authority over their creations, designs, and artistic endeavours. IPR includes a variety of protections, such as trade secrets, patents, trademarks, and copyrights.[2] By guaranteeing that authors can profit from their creations without worrying about unapproved use or duplication, these rights are intended to promote innovation and creativity.

Both opportunities and concerns arise from the junction of AI and IPR, which calls for a review of current legal frameworks to make sure they appropriately handle the special features of AI-generated works. When an AI system, for example, produces a painting, a song, or a software program, the question of who the owner of the creations is—the AI developer, the user who triggered the AI, or the AI itself—comes up.    Additionally, there are many difficulties in training AI models using currently available copyrighted resources. [3]

To strike a balance between the rights of authors and the necessity of innovation and technological growth, the legal ramifications of using copyrighted material for training purposes must be carefully examined.

Harmonized regulations that safeguard artists and creators while encouraging the responsible advancement of AI technology are becoming more and more necessary as various jurisdictions handle these challenges.  To create flexible legal frameworks that consider the reality of artificial intelligence, stakeholders like legislators, legal professionals, engineers, and artists must have a positive conversation.

II. CHALLENGES AND ETHICAL ISSUES DUE TO INTERSECTION OF AI AND IPR.

In India and other nations, the nexus between AI and IPR raises several difficulties and moral dilemmas that are growing more pressing. Fundamental concerns regarding ownership, security, and ethics are brought up by AI technologies as they develop and are increasingly incorporated into economic, creative, and inventive processes. Here are some significant issues and precedent-setting cases:

Key Challenges and Ethical Issues

1. Ownership of AI Created Content:

i) Challenge: One major problem is figuring out who is the rightful owner of works produced by AI systems. Which is it the user, the AI's creator, or the AI itself, if it is seen as an entity? [4]

ii) Ethical Issue: This brings questions regarding how to recognize the achievements of intelligent systems while rewarding human inventors and encouraging innovation.

2. Authorship of Original Works:

i) Challenge: The foundation of traditional IPR systems is human authorship. Because AI systems can produce text, music, art, and more, disagreements regarding authorship and copyright eligibility may arise.

ii) Ethical Issue: If AI generated art is viewed as being on par with human-produced art, there is a chance that human originality will be undermined.[5]

3. Patent Rights on AI Innovations:

i) Challenge: Because of the uncertainty around inventorship and whether AI qualifies as an inventor, innovations created with its assistance may be more difficult to patent.

ii) Ethical Issue: There are problems with the patenting system, which was largely created for human inventors, if AI can produce inventions on its own.

4. Data Privacy and Security:

i) Challenge: Large volumes of data, including copyrighted works or personal information, are frequently used by AI systems, which raises questions with data use, privacy, and rights violation.

ii)  Ethical Issue: Consent and the appropriate use of private or copyrighted information to train AI systems can have serious ethical ramifications.

5. Bias and Fairness:

i) Challenge: Biases in training data can be reinforced by AI systems, producing biased results and violating people's rights.

ii) Ethical Issue: This presents a serious ethical conundrum about equity, representation, and accountability and may lead to unfair treatment or harm to particular groups.

Landmark Cases:

1. India:   Shyam Sunder Co vs State of Bengal (2021): This case focused on the use of software for tracking and monitoring, highlighting concerns about proprietary rights vs public interest in data management and utilization, reflecting a modern concept of IPR in an AI-driven world.[6]

In the case of Google India Pvt. Ltd. v. Vishakha Jagdish (2021), the court evaluated whether protections must be extended to AI-generated work in circumstances involving the technology's role in producing creative output, perhaps suggesting a shift in intellectual property regulations.[7]   In this case, concerns about the usage of copyrighted material and liability were addressed. The ideas discussed regarding sharing and ownership may extend to AI-generated outputs and using current works to generate new content.

2. United States:   - Thaler v. Hirshfeld (2021): An AI system “Device for the autonomous bootstrapping of unified sentience” (DABUS) was listed as the inventor on a patent application that was denied by the U.S. Patent and Trademark Office. The case sparked continuous debates about the ramifications for patent law by raising concerns about whether non-human entities may be acknowledged as inventors.[8]

In terms of Copyright Office's Stance, The U.S. Copyright Office clarified the laws governing the ownership and duplication of AI-generated works by ruling that works produced entirely by AI without human participation are not eligible for copyright protection.

3. UK:   - The most notable case law on AI work recognition is the recent Supreme Court decision in "Thaler v. Comptroller-General of Patents, Designs, and Trade Marks," in which the court unanimously ruled that an AI system cannot be considered an inventor under UK patent law, implying that an AI machine cannot be named as the inventor on a patent application; essentially stating that only a natural person can be recognized as an inventor. The Supreme Court denied Thaler's appeal, confirming that under the UK Patents Act 1977, an AI machine cannot be acknowledged as an inventor. [9]

The UK Copyright, Designs and Patents Act is now being reviewed to see if any changes should be made to allow for AI-generated content. Even though existing guidelines claim that copyright only applies to human authors, it is acknowledged that the law needs to change to reflect AI capabilities.

4. European Union:  Without specifically resolving the issue of copyright for AI-generated products, the Artificial Intelligence Act (2021) seeks to regulate the development and application of AI, addressing ethical considerations and accountability while emphasizing the necessity of alignment with IPR.[10]

The implications for intellectual property rights will only get more intricate and important as AI technology advances. Nations all around the world are shaping their policies and legal systems to safeguard innovation and creativity while tackling the difficulties presented by artificial intelligence.

.

III. OPPORTUNITIES DUE TO INTERSECTION OF AI AND IPR

For Artists, Companies, and Legislators, the nexus of Artificial Intelligence (AI) and Intellectual Property Rights (IPR) is a dynamic field that offers a several opportunities, difficulties, and ramifications.[11] These are a few of the main advantages that come with this intersection.

1. Enhanced Innovation: AI has the potential to accelerate innovation in several sectors by streamlining the research and development process. AI can find patterns, market gaps, and possible locations for new discoveries by analysing enormous amounts of data, which can assist creators in producing intellectual property more effectively.

2. Automation of IP Management: Numerous facets of intellectual property management might be automated by AI technologies, including the following.

i) Trademark searches: AI can help with thorough trademark searches to prevent possible infringements.

ii) Monitoring and enforcement: AI systems can keep an eye out for intellectual property infractions on websites, assisting owners of rights to better safeguard their assets.

iii) Filing and administration: AI can assist in managing portfolios and expediting patent applications to guarantee timely deadline compliance.

3. Improved IP Analysis: AI-powered analytics help improve IP strategy and valuation:

i) Valuation models: By using predictive analytics and taking historical data and market conditions into account, AI can help determine the value of intellectual property assets.

ii) Risk assessment: Based on past trends, AI algorithms can assess the probability of IP conflicts or infringements.

4. Creation of New Types of IP: The proliferation of AI-generated content calls into question ownership and authorship. There are chances to create fresh IPR frameworks that tackle as follows.

i) AI-generated inventions: Investigating whether AIs are considered innovators or if the rights belong to their creators:

ii) Copyright for AI-generated content: Creating rules for who owns works created only by AI, which may result in new business structures.

5. Cross-industry Collaborations: The intersection can encourage cross-sector cooperation.

For example, regarding Entertainment context, AI's capacity to produce art or music may open revenue streams and licensing opportunities.

In the field of Pharmaceuticals, AI in drug research could result in breakthroughs that call for shared ownership structures or new types of patent protection.

6. Global Harmonization of IP Laws: There is a great chance to harmonize worldwide IP regulations pertaining to AI-generated content as AI technology crosses national boundaries. This could make international transactions and interoperability easier.[12]

7. Education and Awareness: Opportunities to inform stakeholders about AI's effects on IPR are presented by the intersection. Workshops and training courses can enable artists, companies, and attorneys to successfully negotiate this challenging environment.

Fig 1: Potential generated by Intersection of IPR and Artificial Intelligence.

8. Sustainability and Ethical IP Practices: By guaranteeing adherence to rules AI can help advance moral IP management practices, lead to more sustainable innovation methods.

The prospects at the nexus of AI and IPR are numerous and diverse as AI develops further. To guarantee that innovation is balanced with protection and equity, it is necessary to carefully assess the legal, ethical, and societal ramifications when navigating these prospects. It will be essential to have discussions amongst technologists, legal professionals, and legislators to create a vibrant and just future in this field.

IV. OVERVIEW OF AI LAW AND POLICY IN THE USA, EU, UK, JAPAN AND INDIA.

In the US, there is no comprehensive federal legislation that expressly addresses AI-generated content, and the approach to AI and IPR is mainly decentralized. Because copyright law usually requires a human author, the U.S. Copyright Office has warned that works produced autonomously by AI may not be eligible for copyright protection. This brings up important issues regarding rights and ownership, especially in the creative industries. Additionally, using copyrighted information to train AI systems is made more difficult by the lack of a federal data protection law, which results in a patchwork of state laws like the California Consumer Privacy Act (CCPA).

With the AI Act, which seeks to provide a legal framework for AI systems based on risk levels, the European Union is leading the way in AI legislation. The goal of this law is to guarantee the safety of AI systems while upholding fundamental rights, such as the right to intellectual property. Strong data protection is offered by the EU's General Data Protection Regulation (GDPR), which has an impact on how AI developers can handle personal information. In terms of IPR, the EU is actively discussing how current copyright regulations relate to works produced by AI, with an emphasis on making sure that authors receive payment for their labors while encouraging AI innovation.

The UK is creating its own AI policy in the wake of Brexit, which involves encouraging research while guaranteeing its ethical and safe application. Like the US, the UK has no firm legal position on AI-generated content and is still investigating how AI may affect copyright laws. The UK GDPR, which is like the EU GDPR but permits certain flexibility, was adopted by the UK. IPR management in respect to AI-generated works is indirectly impacted by the government's published recommendations on ethical AI development, which highlight the significance of public confidence and accountability in AI technologies.

With the National Strategy for Artificial Intelligence presenting a vision for AI development that takes intellectual property rights into account, India is still in the early phases of creating a comprehensive AI strategy. Clarity is still required; however Indian copyright law is presently being examined to address the consequences of AI-generated works. The proposed Personal Data Protection Bill seeks to create a data privacy framework that will have a big influence on the advancement and application of AI. Furthermore, India highlights the importance of ethical AI, emphasizing inclusion and tackling biases in AI systems, which may have an impact on future IPR regulations.

Key areas including regulatory frameworks, intellectual property rights, data protection, and ethical issues were the subject of our study paper, which compared and summarized AI legislation and policy in the USA, EU, UK, Japan, and India:

Fig 2: Understanding Global AI Regulations.

 1. United States of America (USA)

i) Regulatory Framework: The USA regulates AI in a decentralized manner. Although there is no comprehensive federal AI law, several agencies (such as the FTC and NIST) are active in creating recommendations and standards.[13]

ii) Intellectual Property: According to the U.S. Copyright Office, AI-generated content might not qualify for copyright protection, which raises ownership concerns.

iii) Data Protection: There is no such federal data protection statute in the United States. States such as California, however, have passed their own privacy laws (CCPA).[14]

iv) Ethical Considerations: There are several programs and policies in the US that support ethical AI, however they are frequently sector-specific and voluntary.

2. European Union

i)Regulatory Framework: With the AI Act, which seeks to provide a legal framework for AI systems based on risk levels, the EU is leading the way in AI legislation.

ii) Intellectual Property: Although the details are still up for debate, the EU has copyright regulations that might apply to works created by artificial intelligence.

iii)Data Protection: Strong data protection is offered by the General Data Protection Regulation (GDPR), which has an impact on the creation and application of AI.

iv) Ethical Considerations: The EU places a strong emphasis on moral AI values like responsibility, transparency, and non-discrimination.

Fig 3: An Evaluation of AI Governance in USA and EU.

3. United Kingdom

i) Regulatory Framework: The UK is creating its own AI policy after Brexit, which involves encouraging innovation while guaranteeing its ethical and safe application.[15]

ii) Intellectual Property: Like the US, the UK is still investigating how AI may affect copyright laws.

iii) Data Protection: The UK has implemented the GDPR, which is similar to the EU's GDPR but permits some exceptions.

iv) Ethical Considerations: Guidelines for ethical AI development have been released by the UK government, with a focus on public trust and responsibility.

4. Japan

i) Regulatory Framework: Japan advocates the "Society 5.0" concept, which integrates AI into society while guaranteeing its ethical and safe application. AI development rules exist, however there are no all-encompassing legislation.[16]

ii) Intellectual Property: Clarity is still required, but Japan is investigating how current IP regulations relate to AI-generated content.

iii) Data Protection: The GDPR is in line with Japan's Act on the Protection of Personal Information (APPI).[17]

iv) Ethical Considerations: Japan places a strong emphasis on the moral application of AI, emphasizing human-centred methods and the advantages for society.

Fig 4: Worldwide Policy Framework for AI.

5. India: i) Regulatory Framework: India is still in the early phases of creating a thorough AI policy. A vision for AI development is laid out in the National Strategy for Artificial Intelligence.

ii) Intellectual Property: India has not yet created clear guidelines, but it is evaluating its IP laws to cover AI-generated works.

iii) Data Protection: The Personal Data Protection Bill 2023, which seeks to provide a framework for data privacy that will affect AI, is presently being discussed.[18]

iv) Ethical Considerations: India highlights the importance of ethical AI, emphasizing inclusivity and tackling AI system biases.

In India RAISE (Responsible AI for Social Empowerment) 2020 was a significant initiative aimed at leveraging artificial intelligence to address social challenges and promote inclusive growth.[19]  Emphasis was placed on developing AI technologies that are ethical, transparent, and beneficial to society. The event encouraged partnerships between startups, academia, and government to drive innovation in AI while ensuring that social implications are prioritized. The RAISE initiative aims to not only advance technical development in AI but also ensure that these advancements are align with Sustainable Development Goals (SDGs).

Fig 5: International Morality and Policies for AI to align with SDG’s.

Although these regions' approaches to AI law and policy differ greatly, they all share the necessity for strong regulatory frameworks in higher education, emphasizing accountability, human oversight, transparency, and inclusiveness. It advocates for flexible regulatory frameworks and international cooperation to ensure AI policies align with global moral standards and societal benefits.

The following table compares the AI laws and policies of the United States, the European Union, the United Kingdom, Japan, and India:

Aspect	USA	EU	UK	Japan	India
Regulatory Framework	Decentralized; no comprehensive federal law	Proposed AI Act focusing on risk levels	Developing its own AI strategy post-Brexit	"Society 5.0" initiative; guidelines exist	Early stages; National AI Strategy proposed
Intellectual Property	AI-generated works may not be copyrightable	Ongoing debates on AI-generated works	Like the USA; exploring implications	Reviewing IP laws for AI-generated content	Reviewing IP laws; clarity needed
Data Protection	No federal law; state laws like CCPA	GDPR provides robust data protection	UK GDPR mirrors EU GDPR[20]	Act on the Protection of Personal Information (APPI)[21]	Personal Data Protection Bill in discussion
Ethical Considerations	Various voluntary guidelines	Emphasizes transparency and accountability	Government guidelines on ethical AI	Focus on human-centric and societal benefits	Emphasis on inclusivity and bias mitigation

Table 1: This table provides a concise overview of the key aspects of AI law and policy across these regions, highlighting both similarities and differences.

V. DISCUSSION AND CONCLUSION:

The following are some crucial recommendations for legislators looking to strengthen cooperative efforts to weigh the benefits and drawbacks of the junction of AI and IPR.

1. Building a Unified Global Framework: To create a unified framework for intellectual property rights in relation to AI-generated material, it is crucial that stakeholders from different countries collaborate.

It’s important that the key strategy is fostering collaboration between Policymakers, AI developers and IP rights holders. Without this cooperation, disparities in the legislation could cause misunderstandings, arguments, and a climate that inhibits innovation and creativity, which would ultimately impede the very developments that artificial intelligence (AI) can promote.

2. Ensuring Fair Compensation and Protection: Establishing precise rules that safeguard creators' rights while yet taking technology developers' interests into consideration is crucial as AI systems become more and more integrated into creative industries. To secure their livelihoods in an increasingly automated world, stakeholders including legislators, business executives, and legal professionals must endeavour to guarantee that intellectual property laws develop in a way that ensures just compensation for human creators and artists whose works may be produced or influenced by AI.

3. Promoting Innovation and Creativity: Continuous cooperation can result in a well-rounded strategy that fosters innovation while simultaneously defending IP rights. Because their rights and contributions are protected, creators will feel more empowered to experiment with AI technology if a stable legal environment is established. Maintaining a creative culture that has traditionally produced notable breakthroughs in literature, art, and technology depends on this equilibrium.

4. Addressing Ethical Considerations: Addressing the ethical ramifications of AI in IP is becoming more and more crucial as conversations about it grow. The discussion should cover topics such as the societal effects of AI on creative sectors and who is responsible for outputs produced by AI. International dialogue can help establish moral principles that uphold the public good and represent shared ideals.

5. Future-Proofing Legislation: Given how quickly AI technology is developing, it is critical that laws continue to be flexible and progressive. To ensure that policies are both proactive and reactive, ongoing international discussion might aid in anticipating future opportunities and difficulties presented by AI.

6. Fostering Inclusivity in the Global Creative Ecosystem: By acknowledging and considering the diverse perspectives of both wealthy countries and emerging economies like India, international collaboration can lead to more equitable policies that reflect the global nature of innovation and technology. This inclusivity is essential for creating systems that support a wider range of artists and foster a diverse and rich tapestry of human expression.

Fig 6: Importance Guidelines for policymakers to sustainable usage of AI in IPR domain.

Therefore, it is imperative that the frameworks governing intellectual property be modified to reflect the reality of an era in which artificial intelligence (AI) can reproduce, improve, and even create creative works. To ensure that the advantages of technology breakthroughs are distributed fairly and that the rights of individuals who contribute to our collective cultural heritage are upheld, regions can only successfully negotiate the difficulties of AI and IP rights through consistent communication and cooperation. As we go, a collaborative effort to draft considerate, flexible legislation will serve as the foundation for a dynamic, inventive future where creativity and technology can coexist together.

The other important strategy is to develop capacity building in the respective countries for training, education and awareness. This helps stakeholders like AI developers to produce and promote responsible innovation and avoiding legal conflicts. The pressing necessity for a unified global response to evolving AI technologies is reflected in ongoing court proceedings and legislative reviews. To successfully negotiate these obstacles, interdisciplinary discussions including engineers, legal professionals, ethicists, and legislators are essential.[22]

The concepts like ‘Fair Use’ in copyright acts must be re-evaluated and it should adapt to the evolving global scenario. The Acts should be amended accordingly, include new definitions, adapt the global benchmark policies and prevent infringement and provide remedies to the IP right holders by enforcing liabilities.

In the context of artificially intelligent systems , "Strict Liability" implies holding the creator or user of an AI system accountable for any harm the system causes, even if they were not negligent; "Vicarious liability" corresponds to holding a party responsible for the actions of an AI system based on their relationship with it (e.g., an employer to an employee); and "Absolute liability" is the strictest type, holding the developer or user culpable for any harm the AI system causes, even if it was not expected.[23]

Fig 7: Adaption of IP Laws which should be aligned with evolving AI Technology.

In summary, the rapid advancement of AI technology calls for an exhaustive examination of the ways in which these advancements interact with intellectual property rights. The distinct strategies taken across different nations including the US, EU, UK, Japan and India highlight the variety of legal frameworks and interpretations that they have developed in reaction to AI's capacity to create, innovate, and disrupt and in line with evolving AI technologies.

Hence harnessing AI across all sectors of society to fulfil social and economic needs and addressing challenges is key for sustainable development. The legal system should adopt regulatory framework which supports an ecosystem of AI which is healthy and sustainable.

[1] Raj, A. (2024). Artificial Intelligence. International Journal For Science Technology And Engineering, 12(11), 646–655. https://doi.org/10.22214/ijraset.2024.64695

[2] Shadofa, S. (2024). Intellectual Property Rights and Scientific Plagiarism. 31–40. https://doi.org/10.59992/ijlrs.2024.v3n3p3

[3] Torrance, A. W., & Tomlinson, B. (2023). Training Is Everything: Artificial Intelligence, Copyright, and Fair Training. arXiv.Org, abs/2305.03720. https://doi.org/10.48550/arXiv.2305.03720

[4] Pan, Z., Wang, S., & Zhang, C. (2024). The Research On The Ownership Of Copyright Of AI-generated Content. Highlights in Business, Economics and Management, 39, 362–368. https://doi.org/10.54097/wxs9vv67

[5] Feng, Z. (2024). Copyright Issues in the Artworks Generated by Artificial Intelligence. Interdisciplinary Humanities and Communication Studies, 1(9). https://doi.org/10.61173/ceqxk555

[6] Shyam Sundar Roy vs State of West Bengal & Ors,  WPA 9361 of 2021

[7] Google India Pvt. Ltd. v. Vishakha Jagdish (2021).

[8] Buzu, I. (2024). The Inventorship Paradox within Generative AI. Intllectus, 1, 34-47 https://doi.org/10.56329/1810-7087.24.1.03

[9] Matulionytė, R. (2024). ‘AI is not an Inventor’: Thaler v Comptroller of Patents, Designs and Trademarks and the Patentability of AI Inventions. Modern Law Review. https://doi.org/10.1111/1468-2230.12907

[10] Manchev, A. (2024). World’s first law for artificial intelligence. legal, ethical and economic aspects. Obrazovanie i Tehnologii, 15(1), 225–228. https://doi.org/10.26883/2010.241.5985

[11] Kashefi, P., Kashefi, Y., & Ghafouri Mirsaraei, A. (2024). Shaping the future of AI: balancing innovation and ethics in global regulation. Uniform Law Review. https://doi.org/10.1093/ulr/unae040

[12] Marchenko, V., Dombrovska, A., & Prodaivoda, V. (2024). Comparative analysis of regulatory acts of the eu countries on the protection of intellectual property in the conditions of the use of artificial intelligence. Public Administration and Law Review, 3(19), 44–66. https://doi.org/10.36690/2674-5216-2024-3-44-66

[13] Dotan, R. (2024). US regulation of artificial intelligence. 153–178. https://doi.org/10.4337/9781803928241.00015

[14] Aziz, M., & Wilson, C. (2024). Johnny Still Can’t Opt-out: Assessing the IAB CCPA Compliance Framework. Proceedings on Privacy Enhancing Technologies, 2024(4), 349–363. https://doi.org/10.56553/popets-2024-0120

[15] Atkinson-Toal, A., & Guo, C. (2024). Generative Artificial Intelligence (AI) Education Policies of UK Universities. Deleted Journal, 2, 70–94. https://doi.org/10.62512/etlhe.20

[16] Humphrey, D. (2024). Japan’s Society 5.0 and the Organizational Vision of ‘Human-Centric’ AI. Asiascape. https://doi.org/10.1163/22142312-bja10055

[17] Miyashita, H. (2022). Data protection laws in Japan (pp. 128–139). Edward Elgar Publishing eBooks. https://doi.org/10.4337/9781786438515.0001

[18] Wangi Reformasi, T. P., & Buamona, H. (2024). Cybersecurity Law Exploration: Personal Data Protection in 2023. https://doi.org/10.55927/jlca.v3i3.10376

[19] Alkire, L., Bilgihan, A., Bui, M. (Myla), Buoye, A. J., Doğan, S., & Kim, S. (2024). RAISE: leveraging responsible AI for service excellence. Journal of Service Management. https://doi.org/10.1108/josm-11-2023-0448

[20] Between incrementalism and revolution: How the GDPR right to data portability is revamped by the EU and the UK post Brexit. (2022). Edward Elgar Publishing eBooks. https://doi.org/10.4337/9781800371682.00031

[21] The Right to Personal Informational Self-Determination and Balancing Test. (2024). Minsa Beob’hag. https://doi.org/10.52554/kjcl.2024.108.295

[22] Dr. Rahul K Bharati, 2024, International Journal of Law, Justice and Jurisprudence 2024; 4(2): 207-215

[23] Hohma, E. (2024). On the elements and implications of accountability for AI providers. 13–36. https://doi.org/10.4337/9781803928241.00008