A Multidisciplinary Approach to KIIT Horizons, Volume 1

Table of Contents

1. Frontmatter

2. Introduction

   1. Frontmatter

   2. Chapter 1. Addressing Copyright Challenges in the Era of AI-Generated Content: What Are the Legal Implications?

      Pratiti Nayak, Kiymet Tunca Çalıyurt

      Abstract

      As AI progresses quickly, serious concerns arise about protecting the copyright for its products. Each country views AI as an author while maintaining rights differently, resulting in the compelling necessity for an international dialogue on legal standards. The present copyright framework does not provide sufficient solutions for AI authorship intricacies and raises doubts about classic notions of invention and source. The distinctions show an instant demand for a global legal system that can address the particular characteristics of AI-generated content. Investigating legal policies for AI-created works underscores the critical demand for a copyright approach that accounts for human involvement. Recognizing the actual owner and the original creator is complicated when AI operates with substantial control. Present statutes fail to clarify the complexities linked to human artistic contributions. The idea behind developing a single system suggests valuing AI-produced material as a unique category of intellectual property. This initiative might change how we define authorship in digital works by requiring either AI ownership or that of its creators. AI and individuals could collaborate to create projects that connect creativity with established copyright standards. The critical viewpoint is usually overlooked in media reports, and AI's governance is presented without a thorough evaluation of linked laws and ethics. The existing bias may distort the truth for the public and influence choices while ignoring important information. Legal dialogues must also be enhanced as AI becomes more significant in creativity. Designed approaches strive to build improved regulations that represent progress in technology and the basic concepts of copyright. Developing a consistent policy model to confront AI obstacles related to intellectual property demands this investigation and its recommended advice.

3. Exploring Artificial Intelligence Across Disciplines

   1. Frontmatter

   2. Chapter 2. Use of Artificial Intelligence by the Judiciary in Brazil and India

      Kyvalya Garikapati, Faiz Ayat Ansari, Paulo Campanha Santana

      Abstract

      This chapter explores the potential integration of Artificial Intelligence (AI) into the judicial systems of Brazil and India. Both nations face significant caseload challenges, prompting them to consider how AI could enhance the efficiency and accessibility of their legal frameworks.

      In Brazil, AI is already making strides, with over half of the courts utilizing AI tools. Initiatives like Project VICTOR and the ATHOS systems are assisting the Supreme Court and the Superior Court of Justice in conducting preliminary case analyses and legal research. Additionally, AI is streamlining administrative tasks, improving workflow, and facilitating data retrieval.

      India is also beginning to embrace AI technology. The “Judicial Grid” employs AI to assess cases, aiming to reduce backlog preliminarily. Other initiatives include AI-driven chatbots that provide legal information to the public and the development of judgment-prediction tools for judges.

      This chapter assesses the extent and speed of AI adoption in both countries. It compares their approaches and focuses on various applications across different judicial systems, such as case management, legal research, and public access to justice. It also examines AI's legal and ethical implications in judicial decision-making, including bias, accountability, and transparency concerns. By comparing the experiences of Brazil and India, the paper aims to highlight best practices and potential challenges in implementing AI within the judiciary. The chapter concludes with recommendations for AI's responsible and ethical adoption in judicial systems, ultimately striving for more efficient and equitable justice.

   3. Chapter 3. Press Freedom in the AI Era: Global Insights & Indian Data Laws

      Tulishree Pradhan, Chinmayee Nanda

      Abstract

      For journalists working in the contemporary media environment, combining artificial intelligence (AI) technology with data protection laws presents both possibilities and challenges. This study focuses on data privacy laws’ role in upholding journalistic freedom in India. India’s Data Protection Law, passed in 2023, is a crucial component in ensuring the confidentiality and security of personal data. This Act protects people’s fundamental rights in the digital realm by establishing guidelines for data collection, processing, storage, and sharing. Building trust between the public, media organizations, and media professionals requires strong data privacy policies. Furthermore, the Data Protection Law is crucial to preserving press freedom since it provides a foundation for moral journalistic practices. Artificial intelligence (AI) applications facilitate media professionals’ collection, analysis, and dissemination of news in the complex world of data-driven reporting. Adherence to data protection rules and ethical concerns is essential for preventing privacy abuses and upholding journalistic integrity. Thus, the Data Protection Law promotes investigative journalism and transparency in public discourse by providing journalists with the means to protect their sources and personal data. By promoting accountability and openness in data processing, this legislation upholds people’s right to privacy while bolstering journalists’ function as democratic watchdogs. The practical implementation of India’s Data Protection Law is essential to promoting journalism and upholding press freedom in AI-driven media. Achieving an equilibrium between technological advancements, ethical commitments, and legal constraints is necessary to preserve citizens’ trust and democratic values in mass communication operations.

   4. Chapter 4. Can the Digital Data Protection Act Bridge the Gap Between Privacy and Competition Law in the Age of Artificial Intelligence? Exploring the Confluence of Regulatory Domains Amidst Data Harvesting

      Akash Bag, Bhavya Tandon, Anant V. Maria

      Abstract

      The Digital Data Protection Act of 2023 marks a significant development in safeguarding user data privacy in India and simultaneously emerges as a critical instrument in the anti-trust domain. Recognizing the transformative impact of artificial intelligence on data processing, this paper explores the inadequacies of addressing anti-competitive data practices exclusively under the Competition Act. It highlights the Competition Commission of India’s acknowledgment of the challenges ‘Data Harvesting’ poses to competition law. The analysis extends beyond conventional regulatory frameworks by arguing for an integrated approach considering the intersection of privacy and anti-trust issues. The paper advocates for responsible and mandatory data-sharing provisions under the Competition Act and segmented consent strategies under the Digital Data Protection Act. This dual approach addresses the legal complexities of rapid technological advancements, urging a cohesive policy response that spans multiple regulatory perspectives.

   5. Chapter 5. Artificial Intelligence-Powered Sustainability Reporting: A Policy Analysis of Opportunities and Challenges for Non-governmental Organizations

      Shashwata Sahu, Ramesh Chandra Sethi

      Abstract

      With the growing significanceof environmental sustainability, organizations are expected to be more transparent and accountable. NGOs (Non-Governmental Organizations) have a sustainable ecological component, but their sustainability reporting processes often lag due to the absence of artificial intelligence (AI) technology. Thus, this has been an influential game changer, enhancing the potential of Sustainability Reporting. This discussion paper analyzes the advantages and limitations of AI-powered sustainability reporting for NGOs. It aims to explore the potential benefits that AI may provide in increasing the accuracy, efficiency, and transparency of NGO sustainability reporting and highlight salient policy implications to encourage ethical usage of AI in NGO sustainability reporting. This study employs a qualitative research approach and utilizes secondary data sources. It discusses the potential of AI technologies to ease data collection and automate data analysis and reporting, which can help NGOs generate a more comprehensive picture of their environmental impact. Moreover, AI can enhance transparency by making data verification and investor participation in the development process in real-time. However, scrutiny of policy issues such as data privacy, data security, and bias in AI systems is needed. Through this study, the researcher aims to explore possibilities for NGOs to adopt AI in preparing more rigorous and credible sustainability reports. It explores these challenges and the lack of regulatory frameworks that allow for responsible and effective AI adoption in the non-governmental sector. By embracing AI-powered sustainability reporting, the average NGO can increase stakeholder trust and will, therefore, drastically enhance transparency and accountability and recruit the required resources for their environmental endeavors. This study provides critical information to governments and NGO leaders seeking to harness the capabilities of AI for a greener tomorrow.

   6. Chapter 6. A Study on Agricultural Innovations to Improve Social Enterprises in Crop Irrigation Through an Integrated Artificial Intelligence Driven Approach

      Monalisha Chakraborty, Prasanta Parida, Subhomita Chakraborty

      Abstract

      The use of AI-driven agricultural innovations in India to improve social enterprises is highlighted here in the research paper with a focus on the identification and classification of crops and optimal irrigation. The study uses various machine learning algorithms including Convolutional Neural Networks, RNN, Decision Trees, K-Means Clustering, and GBM among others to identify the best performing algorithms over various iterations. The average accuracy across all CNN models was 92.4%, with precision and recall values between 90.5% and 93.5%. In the case of RNN models, the Mean Absolute Percentage Error was 3.4% and Root Mean Squared Error. For Decision Trees, Gini Impurity and Information Gain values were similarly high, suggesting effective classification performance. The K-Means Clustering method resulted in an average Silhouette Score of 0.61 and an average Inertia of 350 in Crop Irrigation Optimization. Low scores were also demonstrated by the GBM model, with Mean Squared Error averaging 0.12, and Log Loss score averaging 0.32. These results indicate that AI-based innovations have the potential to enhance agricultural productivity, sustainability, and resilience in India, helping smallholders and social enterprises.

   7. Chapter 7. Artificial Intelligence Tools: Flipped and Blended Teaching–Learning Dynamics in English Language Classroom

      Zeenat Taher, Rakesh Kumar Tripathi, Sharda Acharya

      Abstract

      The role of ‘Artificial Intelligence’ (AI) in English Language Teaching and Learning is still a thought-provoking question. In the twenty-first century, we cannot deny the assistance of ‘Artificial Intelligence’ (AI) in our day-to-day lives. As human beings, we are gradually becoming more and more dependent on ‘AI’ to a large extent. But, when the question is about ‘AI’ being used in the field of education, we are still in a dilemma, especially with the thought that ‘Is it ethical to use AI in our classroom teaching’? Do the English language teachers need to expose the students to the ‘AI’ form of learning? Is learning the English language through ‘AI’ tools more beneficial for the students? If it is then what should be the role of a teacher in the English language classes? These are some of the questions that the researcher will discuss in this article in context with the pedagogy of a ‘Flipped and Blended’ classroom teaching with the assistance of ‘AI’ in the context of the ‘Legal English’ subject of the 1st Semester, LL.B. students of a university. The current study will illustrate the use of ‘AI’ in a flipped and blended classroom teaching experience through a lesson plan on “Communication Skills” by integrating the online English language learning platform ‘Nearpod’ with real-time or in-person classroom teaching. The theory of the concept was taught through a lecture and discussion method using a PowerPoint presentation. The class exercises were conducted on the ‘Nearpod’ platform which included class exercises such as quizzes, match the following exercises, fill in the blanks, board discussion, and video clipping. The current study will also provide feedback from the students on their learning experience through ‘AI’ in flipped or blended mode of instruction. The researcher has used a survey questionnaire to collect feedback from the students, sharing their experience of the ‘flipped’ class with the AI’ assisted classroom learning. Finally, the teacher will state a brief reflection of the teacher about the teaching experience using ‘AI.’

   8. Chapter 8. Unravelling AI’s Impact on Women’s Safety and Empowerment in Urban India: An Empirical Analysis

      Ipsita Das, Debadeepti Jagaty, Shrabani Kar

      Abstract

      Artificial Intelligence (AI) has become a potent instrument capable of revolutionizing multiple facets of civilization. Researchers attempt to determine how artificial intelligence affects women's safety and empowerment in this paper. The different facets of women's empowerment in urban India are covered in this paper. It highlights the significant behaviours of women empowerment in the socio-economic context. The paper also does an empirical analysis to establish a corelation of AI with woman empowerment effectiveness and women safety. The researchers have tried to highlight the safety measures which can be taken with the help of deep technologies like AI. The paper explores into the ways in which AI technology can contribute to the empowerment of women, with a particular emphasis on enhancing safety, reducing violence, and promoting gender equality. By examining the potential benefits of AI in these areas, the paper sheds light on the ways in which technology can help to address some of the challenges that women face in today's world.

   9. Chapter 9. Policy and Legal Regulatory Landscape for Artificial Intelligence in Carbon Management

      Aranya Nath, Srishti Roy Barman, Rasika Pramod Bangre

      Abstract

      As we observed, various parts of India are facing “heatwaves” owing to abrupt climate change that takes place due to massive usage of carbon emissions leading to the Indian Meteorological Department (IMD) focusing on “carbon neutrality”. As a result, the paper will explore the evolving policy and legal regulatory landscape governing the deployment of AI in carbon management practices. Authors in this paper seek to discuss the functionality of AI in carbon reduction and sequestration by delving into the intricacies of policy frameworks at international, regional, and national levels. The paper will begin with the authors analyzing the key directives, agreements, and initiatives shaping AI integration into carbon management strategies, emphasizing the alignment with global climate goals such as the Paris Agreement. It would help the readers to understand the burning issue since its known significant inception. Additionally, the authors also contemplate the legal challenges and ethical considerations accompanying AI applications in carbon management. It explores pertinent issues of data privacy, algorithm transparency, accountability, and liability, offering insights into the evolving juris-prudence surrounding these matters. Authors have considered drawing on case studies and best practices; the research highlights successful regulatory approaches and identifies areas requiring further development. Its under-scores the importance of interdisciplinary collaboration among policymakers, legal experts, technologists, and environmental stakeholders to navigate the complex terrain of AI-enabled carbon management responsibly and sustain-ably. Finally, while concluding the chapter, the authors have taken the liber-ty to gauge the feasibility and accuracy of understanding the policy and legal frameworks necessary to harness the full potential of AI in addressing the pressing challenges of carbon emissions and climate change mitigation.

   10. Chapter 10. Examining the Efficacy and Ethical Implications of Predictive Policing Deployment in Indian Law Enforcement: A Critical Inquiry

       Nilanjan Chakraborty, Susmita Priyadarshini Mishra, Yogesh Mishra

       Abstract

       This research article examines the integration of predictive policing technologies within Indian law enforcement, analyzing its effectiveness in crime prevention, and its implications on community trust and civil liberties. Utilizing interdisciplinary approaches from criminology, data science, and legal studies, the paper evaluates the performance of predictive algorithms in detecting crime patterns and optimizing resource distribution. It places a significant emphasis on the ethical challenges posed by these technologies, especially concerns related to bias, discrimination, and privacy violations that disproportionately impact marginalized communities. The study also critically assesses the alignment of predictive policing practices with social justice and civil rights, interrogating the implications for constitutional rights and procedural fairness. Furthermore, it investigates the legal frameworks governing the use of predictive policing in India, comparing local regulations with international best practices to suggest regulatory pathways that ensure responsible technology deployment. This article seeks to offer thorough insights into the use of predictive policing in Indian law enforcement, helping stakeholders, including lawmakers and police officers, to understand how to navigate the intricate terrain of contemporary policing while protecting citizens’ rights and safety.

   11. Chapter 11. AI Tools Adoption and Utilization Impact: Extending TAM Framework and Exploring Relevance to Job Performance Among Bengaluru IT Professionals

       Samuel Mores Geddam, A. Ameer Hussian, N. Nethravathi

       Abstract

       This study explores how IT professionals in Bengaluru adopts and integrate AI tools into their professional lives. It examines the key factors that influence their attitudes towards these technologies, their intentions to adopt them, and the extent of their actual usage. The findings reveal a nuanced and interconnected relationship between these variables. Findings indicate that perceived usefulness significantly impacts attitudes and intentions towards AI tool adoption, emphasizing the importance of highlighting practical benefits in training initiatives. User-friendly design is important, but perceived ease of use alone may not strongly affect behavioural intentions. Interestingly, professionals who perceive their job performance as already high may show less willingness to embrace new technological tools. This underscores the importance of framing these tools as supportive aids that complement and enhance human capabilities rather than substitutes. Confidence in using such tools, often referred to as perceived self-efficacy, plays a crucial role in shaping both the intention to adopt them and their actual implementation. This emphasises the value of providing focused training and support to boost professionals’ confidence. Finally, recognizing and rewarding instances of AI tool contributions to job performance can further drive adoption and utilization. Overall, the study underscores the complex nature of AI adoption in Bengaluru's IT sector, offering valuable insights to cultivate a culture of innovation and enhance competitiveness.

   12. Chapter 12. Ethical and Legal Implications of AI-Based Doping Detection Systems in Sports

       Prathyusha Samvedam, Hiranmaya Nanda

       Abstract

       In the new era of Artificial intelligence (AI) the world has shifted to a completely new dimension with changes in every sector and also in the daily life of mankind. So is the change in the sports. It further reached the detection of sports doping landscape. The AI based technologies are a blessing to the world. they are further much more accurate and efficient as compared to traditional methods of sports doping detection. However, it is not to be ignored that they bring up difficult moral and legal issues. After a lot of analysis over the years, collecting facts and researching the authors in this article have tried to explore the ethical and legal aspects of AI-based doping detection systems in sports. The usage of AI-based doping uncovering technologies in sports are examined in this research by the authors along with their ethical and legal aspects. The article discusses the opportunities and problems of modern technologies, taking into account how they can affect different aspects such as privacy, athlete rights, and equality and fairness of sporting events.

       The article starts with an analysis of ethical issues that are present in development of AI-based systems, highlighting the consequence of fairness equity, and respect for the autonomy of athletes. The article also analyses the legal framework that is governing anti-doping initiatives including national laws, international regulations like the World Anti-Doping Code (WADC), and the case law of the Court of Arbitration for Sport (CAS). Further, the study examines various case studies that highlight moral and legal conundrums brought on by the application of AI to doping detection, offering insights into practical applications and difficulties associated it with it.

       Finally, the article concludes with various suggestions to help with resolving moral and legal issues related to AI-based doping detection. The article emphasises on the significance of various moral standards, best legal frameworks, its responsibility, and finally protecting the rights and privacy of athletes.

4. Backmatter