Current Issue

The emergence of Artificial Intelligence (AI) and Machine Learning (ML) has fundamentally transformed the creation, management, and commercialization of intellectual property (IP), presenting unprecedented legal and regulatory challenges. AI-powered systems are now capable of generating literary works, artistic creations, software programs, inventions, designs, music, and other forms of intellectual output with minimal human intervention. While these technological advancements have accelerated innovation and enhanced productivity across various sectors, they have also challenged the traditional principles of Intellectual Property Rights (IPR), which are primarily based on human creativity, authorship, and inventorship. Existing legal frameworks often struggle to determine ownership, authorship, patent eligibility, copyright protection, liability for infringement, and the lawful use of copyrighted data in AI training processes. Furthermore, issues relating to trade secrets, trademark protection, algorithmic transparency, licensing, fair use, and cross-border enforcement have become increasingly significant in the global digital economy. This study examines the evolving relationship between AI, ML, and Intellectual Property Rights by analyzing the legal implications of AI-generated works, patentability of AI-assisted inventions, protection of training datasets, and emerging judicial and regulatory responses in major jurisdictions. It also evaluates the role of international organizations in promoting harmonized legal standards that balance technological innovation with the protection of creators' rights and public interest. The study concludes that modernizing intellectual property laws through adaptive, technology-neutral, and internationally coordinated legal frameworks is essential for fostering innovation, ensuring legal certainty, protecting human creativity, and supporting sustainable development in the rapidly evolving AI-driven digital ecosystem.

The rapid advancement of digital technologies has fundamentally transformed labour markets, employment relationships, and the regulation of work across the globe. Digital platforms, artificial intelligence, automation, cloud computing, and algorithm-driven management systems have facilitated the emergence of the gig economy, enabling flexible, on-demand employment through platforms such as Uber, Swiggy, Zomato, Amazon Mechanical Turk, and Upwork. While these innovations have expanded employment opportunities and increased economic efficiency, they have also created significant legal challenges concerning worker classification, social security, fair wages, occupational safety, collective bargaining, data privacy, algorithmic decision-making, and employment rights. Traditional labour laws, primarily designed for standard employer-employee relationships, often fail to adequately protect gig workers who are frequently classified as independent contractors rather than employees. This classification limits their access to statutory benefits including minimum wages, paid leave, health insurance, pensions, maternity protection, and workplace safety. International organizations, including the International Labour Organization (ILO), have emphasized the need to modernize labour regulations to address evolving forms of digital employment. This paper critically examines the legal implications of digital technologies on labour laws through a comparative analysis of international labour standards and selected national legal frameworks. It explores the challenges associated with platform work, artificial intelligence, algorithmic management, and cross-border digital labour while evaluating recent judicial developments and legislative reforms. The study concludes that ensuring fair labour conditions in the digital economy requires adaptive legal frameworks, stronger social protection systems, algorithmic transparency, effective platform accountability, and international cooperation to safeguard workers' rights without hindering technological innovation and economic growth.

The present study examines how people understand, accept, and respond to the growing use of artificial intelligence in modern society. Artificial intelligence technologies are increasingly used in education, healthcare, banking, transport, communication, agriculture, security, business, entertainment, and public services. These technologies have created new opportunities for efficiency, innovation, automation, decision-making, and problem-solving. The study focuses on public awareness, attitudes, trust, expectations, and concerns regarding artificial intelligence. It examines whether people perceive AI as a useful tool for social and economic progress or as a source of risk related to job loss, privacy, data misuse, bias, surveillance, misinformation, and reduced human control. The study also explores the influence of factors such as age, education, occupation, digital literacy, income, media exposure, and personal experience with technology on public perception. In contemporary communities, artificial intelligence has both positive and negative societal implications. On one hand, it can improve healthcare diagnosis, personalized education, smart governance, financial services, disaster management, and accessibility for differently abled persons. On the other hand, it may create ethical challenges, social inequality, digital divide, algorithmic discrimination, and dependence on machines. The study is significant because public perception plays an important role in the acceptance and responsible use of artificial intelligence. The findings may help policymakers, educators, technology developers, social researchers, and community organizations design awareness programmes, ethical guidelines, and inclusive AI policies for the benefit of society.

Artificial Intelligence (AI) and automation are transforming the global labour market by reshaping employment patterns, redefining workforce skill requirements, and creating new career opportunities across diverse industries. The integration of intelligent technologies such as machine learning, robotics, natural language processing, computer vision, and intelligent automation has significantly improved productivity, operational efficiency, and innovation while simultaneously altering traditional job roles and organizational structures. This study examines the impact of Artificial Intelligence and automation on employment patterns, workforce skills, and future career opportunities. It explores how technological advancements are replacing repetitive and routine tasks while increasing demand for highly skilled professionals capable of working alongside intelligent systems. The study further investigates the importance of digital literacy, analytical thinking, creativity, emotional intelligence, adaptability, critical thinking, and lifelong learning in preparing the workforce for the evolving employment landscape. Additionally, it identifies major challenges associated with AI adoption, including job displacement, skill gaps, technological inequality, ethical concerns, workforce reskilling, and policy adaptation. The study emphasizes the role of higher education institutions, governments, industries, and training organizations in promoting continuous learning, competency-based education, digital upskilling, and human-centred AI implementation. It concludes that although Artificial Intelligence and automation will significantly transform employment structures, they will also generate new occupations, entrepreneurial opportunities, and innovation-driven careers. Developing future-ready skills and embracing lifelong learning will therefore remain essential for ensuring sustainable employment, economic growth, workforce resilience, and inclusive development in the rapidly evolving digital economy.