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The rapid advancement of generative artificial intelligence (AI) has brought about significant ethical challenges. As machines become more adept at creating human-like content, concerns about misuse, bias, privacy, and accountability have emerged. Without clear guidelines and regulations, there is a risk of unethical use, such as creating deepfake videos or disseminating misinformation, which could have severe societal consequences. Additionally, questions about intellectual property rights and the ownership of AI-generated creations still need to be solved, further complicating the ethical landscape. The book, Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices, comprehensively solves these ethical challenges. By providing insights into the historical development and key milestones of Generative AI, the book lays a foundation for understanding its complex ethical implications. It examines existing ethical frameworks and proposes new ones tailored to AI's unique characteristics, helping readers apply traditional ethics to AI development and deployment.
Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]
An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.
The author investigates how to produce realistic and workable ethical codes or regulations in this rapidly developing field to address the immediate and realistic longer-term issues facing us. She spells out the key ethical debates concisely, exposing all sides of the arguments, and addresses how codes of ethics or other regulations might feasibly be developed, looking for pitfalls and opportunities, drawing on lessons learned in other fields, and explaining key points of professional ethics. The book provides a useful resource for those aiming to address the ethical challenges of AI research in meaningful and practical ways.
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Generative Artificial Intelligence (AI), an ever-evolving technology, holds immense promise across various industries, from healthcare to content generation. However, its rapid advancement has also given rise to profound ethical concerns. Illicit black-market industries exploit generative AI for counterfeit imagery, and in educational settings, biases and misinformation perpetuate. These issues underscore the need to grapple with the risks accompanying generative AI integration. Exploring the Ethical Implications of Generative AI emerges as a wellspring of insight for discerning academic scholars. It sets the stage by acknowledging generative AI's multifaceted potential and its capacity to reshape industries. The book addresses these complex ethical concerns, offering a comprehensive analysis and providing a roadmap for responsible AI development and usage. Its intended audience spans business leaders, policymakers, scholars, and individuals passionate about the ethical dimensions of AI.
The rapid development of Artificial Intelligence (AI) technologies has been nothing less of awe-inspiring. Policymakers are put in a bind as debates over how the deployment of these AI systems is to be managed—with good governance and ethical considerations in mind, and without stifling innovation. ASEAN’s response has been the formulation of the ASEAN Guide on AI Governance and Ethics, or the ASEAN AI Guide. This Guide serves more as a “practical guide” for organizations involved in the development and deployment of AI for commercial and non-military or dual-use applications, as opposed to a policy playbook for governments. Though voluntary in application, it does have some positive attributes including laying out the groundwork for regionwide discussions around AI governance and ethics issues, promoting human involvement in AI system management and having an ecosystem approach to policy. For the implementation of the Guide to be effective, certain notable aspects should be taken into consideration. Firstly, the additional costs organizations will bear in putting into place the checks and balances premised by the guide should be reassessed, especially the disproportionate impact these will have on MSMEs. Additionally, labour availability for these suggested governance mechanisms may be lacking, with rising skills and human resource gaps in integral areas such as cybersecurity. Moreover, on a national level, policymakers should be wary of potential disparities between institutional and regulatory maturity for AI system implementation relative to business readiness for implementation on the ground. For the ASEAN AI Guide to translate into actionable outcomes, some public policy areas warrant additional consideration. Firstly, some focus will need to be redirected to ex-post regulations, such as legal recourse for AI-generated Intellectual Property (IP) infringement. Furthermore, how new technologies and human capital can be leveraged to better manage potential ill-effects of AI system deployment should be given more focus, along with keeping tabs on psychological changes among different segments of society with greater AI system usage. Lastly, the ASEAN AI Guide should be used as a basis for greater regional engagement in this integral area.