ChatGPT in Oncology Diagnosis and Treatment: Applications, Legal and Ethical Challenges.

Introduction: Clinical research is a key area in which the use of AI in healthcare data seen a significant increase, even though met with great ethical, legal and regulatory challenges. Artificial Intelligence (AI) concerns the ability of algorithms encoded in technology to learn from data, to be able to perform automated tasks without every step in the process being explicitly to be programmed by a human. AI development relies on big data collected from clinical trials to train algorithms, that requires careful consideration of consent, data origin and ethical standards. When data is acquired from third-party sources, transparency about collection methods, geographic origin and anonymization standards becomes critical. While consent forms used in clinical trials can offer clearer terms for data use, ambiguity remains about how this data can be reused for AI purposes after the trial ends. There are very few or no laws on the use of AI especially in developing countries. Also, there are a lot of misconceptions on the global use of AI. Statement of Objectives: Artificial intelligence as an innovative technology has contributed to a shift in paradigm in conducting clinical research. Unfortunately, AI faces ethical, and regulatory challenges especially in limited resource countries where the technology is still to be consolidated. One of the main concerns of AI involves data re-identification, in which anonymized data can potentially be traced back to individuals, especially when linked with other datasets. Data ownership is also a complex and often controversial area within the healthcare sector. AI developers needs to clearly explain the value of data collection to hospitals and cybersecurity teams to ensure that they understand how the data will be secured and used ethically Methodology: The World Health Organization (WHO) recognizes that AI holds great promise for clinical health research and in the practice of medicine, biomedical and pharmaceutical sciences. WHO also recognizes that, to fully maximize the contribution of AI, there is the need to address the ethical, legal and regulatory challenges for the health care systems, practitioners and beneficiaries of medical and public health services. In this study we have pulled data from accessible websites, peered reviewed open-access publications that deal with the ethical and regulatory concerns of AI, that we have discussed in this writeup. We have attempted to place our focus on the development of AI and applications with particular bias in the ethical and regulatory concerns. We have discussed and given an insight on whether AI can advance the interests of patients and communities within the framework of collective effort to design and implement ethically defensible laws and policies and ethically designed AI technologies. Finally, we have investigated the potential serious negative consequences of ethical principles and human rights obligations if they are not prioritized by those who fund, design, regulate or use AI technologies for health research. Results: From our data mining and access to multiple documentations, vital information has been pooled together by a systematic online search to show that AI is contributing significantly in the growth of global clinical research and advancement of medicine. However, we observed many ethical and regulatory challenges that has impacted health research in developing economies. Ethical challenges include AI and human rights, patient’s privacy, safety and liability, informed consent and data ownership, bias and fairness. For the legal and regulatory challenges, we observed issues with data security compliance, data monitoring and maintenance, transparency and accountability, data collection, data storage and use. The role of third-party vendors in AI healthcare solutions and finally AI development and integration into the health systems has also been reviewed. Conclusion: The advancement of AI, coupled with the innovative digital health technology has made a significant contribution to address some challenges in clinical research, within the domain of medicine, biomedical and pharmaceutical products development. Despite the challenging ethical and regulatory challenges AI has impacted significant innovation and technology in clinical research, especially within the domain of drug discovery and development, and clinical trials studies.

The development of Artificial Intelligence (AI) has significantly transformed state administration by enhancing efficiency and transparency in decision-making processes. However, its implementation also raises legal and ethical challenges, particularly concerning accountability, algorithmic bias, and human rights protection. This study employs a normative legal research method with statutory and philosophical approaches to analyze regulations governing AI in state administration. The findings indicate that while AI can improve public service quality, existing regulations have not fully addressed emerging challenges. Therefore, strict policies are necessary to ensure that AI operates in accordance with the principles of transparency, fairness, and public rights protection, aligning with constitutional law and democratic values.

This study aims to explore and analyze the ethical and legal challenges posed by the use of artificial intelligence (AI) in digital businesses, highlighting the need for robust guidelines and frameworks to guide responsible AI implementation. Adopting a qualitative research approach, data were collected through semi-structured interviews with 20 experts from diverse fields related to digital businesses and AI. The content analysis method was employed to identify main themes, categories, and concepts within the ethical and legal realms of AI usage. Two main themes emerged: ethical challenges and legal challenges. Ethical challenges encompassed categories such as privacy violations, discriminatory practices, and AI accountability. Legal challenges included intellectual property rights, data regulations, and surveillance and control issues. The analysis revealed a complex landscape of ethical dilemmas and legal uncertainties that digital businesses face when implementing AI technologies. The study concludes that navigating the ethical and legal challenges of AI in digital businesses requires a multi-faceted approach, emphasizing the importance of developing comprehensive ethical guidelines and legal frameworks. These measures should ensure AI technologies are used in ways that respect human rights and promote fairness and transparency in the digital economy.

Background: Artificial Intelligence (AI) is increasingly being integrated into the criminal justice system, promising to enhance efficiency, accuracy, and decision-making. However, the use of AI also raises significant ethical and legal challenges, including concerns about bias, fairness, transparency, and accountability. These challenges necessitate a thorough examination of AI's impact on the criminal justice system to ensure its benefits are realized without compromising ethical and legal standards. Objective: This study aims to evaluate the impact of AI on the criminal justice system, focusing on the ethical and legal challenges it presents. The research seeks to understand how AI technologies are being implemented, their effects on decision-making processes, and the extent to which they adhere to ethical and legal principles. The goal is to identify best practices and propose solutions to mitigate potential risks. Methods: A mixed-methods approach was employed, combining quantitative surveys and qualitative interviews. Quantitative data were collected from 250 criminal justice professionals, measuring their perceptions of AI's impact on various aspects of the justice system. Qualitative interviews with 40 key stakeholders provided deeper insights into the ethical and legal challenges associated with AI integration. Data were analyzed using statistical methods for the surveys and thematic analysis for the interviews. Results: Findings indicate that AI can significantly enhance the efficiency and accuracy of the criminal justice system but also presents substantial ethical and legal challenges. Issues such as algorithmic bias, lack of transparency, and accountability were frequently highlighted. Best practices identified include implementing rigorous validation processes, ensuring transparency in AI decision-making, and establishing clear accountability frameworks. Conclusion: While AI holds significant promise for improving the criminal justice system, addressing ethical and legal challenges is crucial for its successful integration. Implementing best practices can mitigate risks and ensure that AI technologies are used responsibly. Future research should focus on developing comprehensive guidelines and policies to govern the use of AI in the criminal justice system.

The development of artificial intelligence (AI) presents society with not only technological but also legal and ethical challenges. This article offers an interdisciplinary analysis of the impact of AI development on legal and ethical issues, with particular emphasis on the Polish context. The analysis focuses on constitutional principles that may soon face challenges due to the advancement of artificial intelligence. The article explores how AI development affects the freedoms, rights, and obligations of individuals and citizens guaranteed in the Constitution of the Republic of Poland. It also examines how national courts, tribunals, public oversight bodies, and human rights institutions interpret, understand, and modify or reinterpret the law in response to AI progress. Furthermore, the article analyzes the ethical implications of using artificial technologies in the context of increasing automation. It outlines possible legal and policy solutions that may help ensure a balance between AI development and the protection of human and civil rights. The article is intended not only to contribute to the discussion on legal challenges related to AI development but also to emphasize the need to adapt constitutional principles to the realities shaped by this progress. The constructive legislative and political proposals included herein may support the achievement of harmony between human freedoms, rights, and responsibilities and the development of artificial intelligence, while preserving fundamental principles of equality, social justice, and the democratic rule of law. It should be noted that artificial technology does not pose a threat – if used responsibly.

Ethical and Legal Challenges of Artificial Intelligence in Nuclear Medicine

In the era of big data, text-based medical data, such as electronic health records (EHR) and electronic medical records (EMR), are growing rapidly. EHR and EMR are collected from patients to record their basic information, lab tests, vital signs, clinical notes, and reports. EHR and EMR contain the helpful information to assist oncologists in computer-aided diagnosis and decision making. However, it is time consuming for doctors to extract the valuable information they need and analyze the information from the EHR and EMR data. Recently, more and more research works have applied natural language processing (NLP) techniques, i.e., rule-based, machine learning-based, and deep learning-based techniques, on the EHR and EMR data for computer-aided diagnosis in oncology. The objective of this review is to narratively review the recent progress in the area of NLP applications for computer-aided diagnosis in oncology. Moreover, we intend to reduce the research gap between artificial intelligence (AI) experts and clinical specialists to design better NLP applications. We originally identified 295 articles from the three electronic databases: PubMed, Google Scholar, and ACL Anthology; then, we removed the duplicated papers and manually screened the irrelevant papers based on the content of the abstract; finally, we included a total of 23 articles after the screening process of the literature review. Furthermore, we provided an in-depth analysis and categorized these studies into seven cancer types: breast cancer, lung cancer, liver cancer, prostate cancer, pancreatic cancer, colorectal cancer, and brain tumors. Additionally, we identified the current limitations of NLP applications on supporting the clinical practices and we suggest some promising future research directions in this paper.

This paper explores the legal and regulatory challenges posed by AI's role in cybersecurity, specifically focusing on AI-driven cyber defense and offense mechanisms. It examines the current legal frameworks, highlights gaps, and proposes recommendations for regulating AI technologies in the cybersecurity domain. As artificial intelligence (AI) continues to revolutionize cybersecurity, it introduces both opportunities and legal challenges, particularly in AI-driven cyber defense and offense mechanisms. This article explores the legal implications of AI’s use in cybersecurity, examining the sufficiency of existing frameworks, the ethical concerns in AI-operated cyber attacks, and the accountability issues surrounding AI’s autonomous decisions. By analyzing current laws and identifying key gaps, this research highlights the need for updated legal frameworks to address the rapid advancements in AI-driven cybersecurity.

Artificial intelligence (AI) and global governance are an inclusive platform to discover the policy challenges worldwide augmented by artificial intelligence. The platform has three predominant subjects: AI and the global order, governance of AI, insights on the platform consider for mapping of AI futures. AI has great impact in revolution of geopolitical order and the reaction of multifaceted organizations which minimize AI risks and unpremeditated significances and its social aids are maximized through governance structures. It focusses on setups, collaborations, and tensions between different actors responsible for plan, deployment, support and governance of AI. AI improves the benefit for human well-being, productivity, social good, and safety with substantial risks for workers, developers, firms, and governments. The actors and organization begin to realize the ethical, legal, and regulatory challenges associated with AI.KeywordsArtificial intelligenceEthicsEconomic challengesGovernanceRegulation

The digital transformation in modern libraries employs Artificial Intelligence (AI) to enhance scientific literacy. However, the implementation of AI presents various legal and ethical challenges that must be addressed to ensure its responsible and fair use. This study utilizes a narrative literature review method, analyzing and synthesizing various relevant sources. This method is flexible, covering diverse types of literature, and is useful for developing theoretical or conceptual models. Regulations for AI in Indonesia are still incomplete, although some aspects are regulated by existing laws. Key challenges include privacy, bias, discrimination, and AI regulation. Ethical principles such as transparency, honesty, and accountability are crucial in AI utilization. Ethical guidelines and regulations must be implemented to ensure fairness and accountability. Librarians play a vital role in enhancing users' scientific literacy through training and digital resource curation. AI implementation can improve library service efficiency and quality but also requires careful attention to ethical and privacy issues. AI holds significant potential for enhancing scientific literacy and operational efficiency in libraries, but the existing legal and ethical challenges must be addressed seriously. More specific regulations and clear ethical guidelines are essential to ensure the safe and responsible application of AI. The application of AI in libraries can significantly enhance scientific literacy and service efficiency, but stricter regulations and the implementation of ethical guidelines are needed to address the existing legal and ethical challenges. This study provides guidance for libraries in adopting AI technology safely and ethically.

Almost no one today doubts that AI systems will increasingly affect our lives in the near future. Growing interactions of humans with non-human intelligent systems are both a source of threats and a source of hopes. In this paper, some ethical challenges in the development and application of weak and strong AI systems are analyzed. Then, legal challenges that appear when legislators attempt to regulate uncertain and unpredictable phenomena such as AI are discussed. Here we show that despite these challenges, an appropriate law is the most optimal response to threats and hopes related to AI. We also point out that the development of AI will be a major political challenge. Politicians will have to find a difficult compromise between, on the one hand, consenting to the inevitable and essentially beneficial technological development for humanity and, on the other hand, certain risks and dangers, probably also inherent in the specificity of AI functioning.

The metaverse, a pioneering digital realm merging virtual and augmented realities with Artificial Intelligence (AI), represents a transformative environment where digital and physical realities converge seamlessly. Generative AI (GenAI) is indispensable in powering the metaverse's dynamic and immersive experiences, enabling the autonomous generation of diverse digital content. Large Language Models (LLMs), as a component of GenAI, play a critical role by facilitating real-time communication, multilingual translation, and personalized interactions, enhancing user engagement in shared virtual spaces. This scoping review explores the interdependence between GenAI and the metaverse and the unique ethical and legal challenges that emerge from their integration. It identifies key ethical and legal issues, such as bias in AI-generated content, misinformation, and data privacy concerns, related to the deployment of GenAI and LLMs, and offers strategic recommendations for addressing these challenges responsibly. Emphasizing the transformative potential of these technologies, this review highlights the necessity of developing tailored ethical and legal frameworks to manage their convergence responsibly, ensuring equitable and sustainable growth within the metaverse.

This paper is the introduction to the special issue entitled: 'Governing artificial intelligence: ethical, legal and technical opportunities and challenges'. Artificial intelligence (AI) increasingly permeates every aspect of our society, from the critical, like urban infrastructure, law enforcement, banking, healthcare and humanitarian aid, to the mundane like dating. AI, including embodied AI in robotics and techniques like machine learning, can improve economic, social welfare and the exercise of human rights. Owing to the proliferation of AI in high-risk areas, the pressure is mounting to design and govern AI to be accountable, fair and transparent. How can this be achieved and through which frameworks? This is one of the central questions addressed in this special issue, in which eight authors present in-depth analyses of the ethical, legal-regulatory and technical challenges posed by developing governance regimes for AI systems. It also gives a brief overview of recent developments in AI governance, how much of the agenda for defining AI regulation, ethical frameworks and technical approaches is set, as well as providing some concrete suggestions to further the debate on AI governance.This article is part of the theme issue 'Governing artificial intelligence: ethical, legal, and technical opportunities and challenges'.

The rapid integration of Artificial Intelligence (AI) into digital ecosystems presents a host of legal and ethical challenges that require urgent attention within the framework of cyber law. AI’s increasing presence across industries such as healthcare, finance, transportation, and governance has introduced a myriad of complex issues, particularly concerning liability, data protection, privacy, intellectual property, and ethical decision-making. From a legal perspective, one of the most pressing concerns is determining accountability for AI-driven decisions, especially when systems operate autonomously without human oversight. Issues of data privacy and protection are also critical, as AI systems rely on vast amounts of personal data, raising concerns about consent, data ownership, and the risk of data breaches. Furthermore, intellectual property rights related to AI-generated content remain uncertain, particularly regarding the ownership of creations produced by AI systems. Ethical considerations, including the potential for AI to perpetuate or exacerbate biases, discrimination, and unequal treatment, pose significant concerns about fairness, justice, and transparency. This paper delves into the intersection of AI and cyber law, analyzing the regulatory approaches taken in various jurisdictions, such as the European Union's General Data Protection Regulation (GDPR) and emerging AI-specific legislation. By reviewing current legal standards, ethical frameworks, and the evolving nature of AI technology, this analysis seeks to propose a balanced and comprehensive legal approach that fosters innovation while safeguarding human rights, fairness, and transparency. Ultimately, it calls for the development of adaptive legal and ethical guidelines that can ensure responsible AI deployment within digital ecosystems while preventing misuse or harm.

This article explores the research problem that investigates how the implementation of artificial intelligence (AI) systems in competency management impacts legal compliance and people management practices in organizations, considering the associated ethical and legal challenges. Initially, it discusses the relevance of AI in organizations, addressing its definition, trends, innovations and the positive impact on operational efficiency. It then analyzes skills and people management, emphasizing the integration of AI to identify and develop talents. The article also delves into aspects of business law, including regulations pertaining to AI, the importance of compliance, and the liability of companies in the event of legal violations. Additionally, it proposes practical contributions to the development of internal policies that integrate AI and competency-based management, highlighting the importance of continuous training. Finally, it addresses ethical and legal challenges such as algorithmic discrimination, privacy, transparency and the need for future regulation, allowing for a comprehensive discussion on the interactions between technology, management and law in the organizational context.