Ethical AI and Data Science : Building Trustworthy and Transparent Systems (Data Analytics Applications)

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  • 予約

Ethical AI and Data Science : Building Trustworthy and Transparent Systems (Data Analytics Applications)

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  • 製本 Hardcover:ハードカバー版/ページ数 256 p.
  • 言語 ENG
  • 商品コード 9781041109297

Full Description

As AI permeates day-to-day life—influencing who is granted what type of healthcare, determining who is granted an employment interview or academic enrollment, or delivering what information to whom—it frames individuals and society. AI has far-reaching powers to improve lives, but it is not without risks. Due to its limitations, AI may prevent a person from receiving needed healthcare, block a deserving candidate from employment, or present fake and inaccurate information. How to trust that AI systems will improve lives and not create greater inequality and strife? How to foster the benefits of AI and mitigate the harms from AI? Ethical AI and Data Science: Building Trustworthy and Transparent Systems contributes answers to these questions.

A vital and ongoing dialogue surrounding data, accessibility, and the multifaceted challenges posed by AI in ethics, safety, and societal impact, the book features diverse perspectives and practical approaches written by a panel of experts. Highlights of the book include:

Ensuring safety in agentic AI through decision traceability
Promoting responsible and ethical AI in financial services
Bridging human-machine knowledge for responsible AI
Responsible agentic AI for effective cybersecurity and ethical safety

The book offers valuable insights into navigating the complexities of developing AI systems that are not only innovative but also transparent, equitable, and secure. This volume aims to advance understanding and foster collaboration among researchers, practitioners, and policymakers, helping to shape AI technologies that responsibly serve society while addressing critical concerns around fairness, accountability, and human well-being.

Contents

1. Transparent by Design: Ensuring Safety in Agentic AI through Decision Traceability 2. AI Transparency 3. Foundation of Trustworthy AI 4. AI Ethics in STEM Education: Promoting Student Awareness through a Reflective-Collaborative Approach 5. Navigating the AI Epoch: A Critical Examination of Student Voice and Agency through the Lens of Foucault and Freire 6. Beyond the Standard Prompt: The Duality of Generative AI Between Reproduction and Emancipation from a Freirean Perspective 7. Responsible AI/AI Ethics as Related to Financial Services which would Interest the Readership. 8. Intelligent Digital Twins and Ethical Decision-Making Support 9. Assessing AI Algorithms 10. Bridging Human-Machine Knowledge for Responsible AI 11. Generative AI, Emerging Technology, and Political Communication: Examples, Methods of Study, and Implications for Democracy 12. Responsible Agentic AI for Effective Cyber-Defense and Ethical Safety

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