The Frontlines of Artificial Intelligence Ethics: Human-Centric Perspectives on Technology's Advance

This foundational text examines the intersection of AI, psychology, and ethics, highlighting the importance of ethical considerations in the design and implementation of technologically supported education, decision support, and leadership training. It offers a unique perspective on the emerging social relationships between people and AI agents and systems, exploring the history of data science, technology in education, and combatting machine learning bias.

Format: Paperback / softback
Length: 212 pages
Publication date: 30 June 2022
Publisher: Taylor & Francis Ltd

This foundational text delves into the intricate intersection of AI, psychology, and ethics, establishing the critical importance of ethical considerations in the design and implementation of technologically supported education, decision support, and leadership training. As AI continues to reshape our lives, both in mundane and remarkable ways, it is essential to examine its broader humanistic impact. While much academic and industrial attention has been focused on the technical and economic aspects of this AI revolution, the personal, emotional toll of these changes has often been relegated to anecdotal evidence. In this groundbreaking work, Hampton and DeFalco offer a unique perspective on the emerging social dynamics between humans and AI agents and systems. Drawing from the expertise of leading academics, professionals, and policy advocates, the book explores the historical context of data science, the role of technology in education, and the challenges of combating machine learning bias. Moreover, it provides insights into the future directions of this rapidly evolving field, urging those in positions of authority to actively engage with the research.

Part One: The History of Data Science
In the first part of the book, Hampton and DeFalco trace the historical development of data science, highlighting its origins in statistics, computer science, and psychology. They explore how data science has evolved to become a powerful tool for analyzing and interpreting complex data sets, enabling researchers to make informed decisions based on empirical evidence. The authors also discuss the ethical implications of data collection, storage, and analysis, emphasizing the need for transparency, privacy, and responsible use of data.

Part Two: Technology in Education
The second part of the book focuses on the role of technology in education, particularly in the context of AI. The authors discuss how AI can be used to enhance learning outcomes, personalize education, and facilitate lifelong learning. They explore the potential benefits and challenges of AI-powered educational systems, such as automated grading, personalized learning paths, and virtual tutoring. However, they also raise concerns about the potential risks associated with AI, such as the potential for bias, the loss of human interaction, and the need for ethical training and supervision.

Part Three: Combatting Machine Learning Bias
The third part of the book addresses the critical issue of combating machine learning bias. The authors discuss how bias can manifest in AI systems and the potential consequences of biased decision-making. They explore various strategies for mitigating bias, such as using diverse data sets, designing fair algorithms, and incorporating ethical considerations into the design and training process. The authors also emphasize the importance of transparency and accountability in AI development, ensuring that decision-making processes are fair, transparent, and explainable.

Conclusion
In conclusion, this foundational text provides a comprehensive exploration of the intersection of AI, psychology, and ethics. It offers valuable insights into the psychological impact of the AI revolution, the role of technology in education, and the challenges of combating machine learning bias. By presenting cutting-edge research from leading academics, professionals, and policy advocates, the book encourages those in positions of authority
This foundational text delves into the intricate intersection of AI, psychology, and ethics, establishing the critical importance of ethical considerations in the design and implementation of technologically supported education, decision support, and leadership training. As AI continues to reshape our lives, both in mundane and remarkable ways, it is essential to examine its broader humanistic impact. While much academic and industrial attention has been focused on the technical and economic aspects of this AI revolution, the personal, emotional toll of these changes has often been relegated to anecdotal evidence. In this groundbreaking work, Hampton and DeFalco offer a unique perspective on the emerging social dynamics between humans and AI agents and systems. Drawing from the expertise of leading academics, professionals, and policy advocates, the book explores the historical context of data science, the role of technology in education, and the challenges of combating machine learning bias. Moreover, it provides insights into the future directions of this rapidly evolving field, urging those in positions of authority to actively engage with the research.

Part One: The History of Data Science
In the first part of the book, Hampton and DeFalco trace the historical development of data science, highlighting its origins in statistics, computer science, and psychology. They explore how data science has evolved to become a powerful tool for analyzing and interpreting complex data sets, enabling researchers to make informed decisions based on empirical evidence. The authors also discuss the ethical implications of data collection, storage, and analysis, emphasizing the need for transparency, privacy, and responsible use of data.

Part Two: Technology in Education
The second part of the book focuses on the role of technology in education, particularly in the context of AI. The authors discuss how AI can be used to enhance learning outcomes, personalize education, and facilitate lifelong learning. They explore the potential benefits and challenges of AI-powered educational systems, such as automated grading, personalized learning paths, and virtual tutoring. However, they also raise concerns about the potential risks associated with AI, such as the potential for bias, the loss of human interaction, and the need for ethical training and supervision.

Part Three: Combatting Machine Learning Bias
The third part of the book addresses the critical issue of combating machine learning bias. The authors discuss how bias can manifest in AI systems and the potential consequences of biased decision-making. They explore various strategies for mitigating bias, such as using diverse data sets, designing fair algorithms, and incorporating ethical considerations into the design and training process. The authors also emphasize the importance of transparency and accountability in AI development, ensuring that decision-making processes are fair, transparent, and explainable.

Conclusion
In conclusion, this foundational text provides a comprehensive exploration of the intersection of AI, psychology, and ethics. It offers valuable insights into the psychological impact of the AI revolution, the role of technology in education, and the challenges of combating machine learning bias. By presenting cutting-edge research from leading academics, professionals, and policy advocates, the book encourages those in positions of authority
This foundational text delves into the intricate intersection of AI, psychology, and ethics, establishing the critical importance of ethical considerations in the design and implementation of technologically supported education, decision support, and leadership training. As AI continues to reshape our lives, both in mundane and remarkable ways, it is essential to examine its broader humanistic impact. While much academic and industrial attention has been focused on the technical and economic aspects of this AI revolution, the personal, emotional toll of these changes has often been relegated to anecdotal evidence. In this groundbreaking work, Hampton and DeFalco offer a unique perspective on the emerging social dynamics between humans and AI agents and systems. Drawing from the expertise of leading academics, professionals, and policy advocates, the book explores the historical context of data science, the role of technology in education, and the challenges of combating machine learning bias. Moreover, it provides insights into the future directions of this rapidly evolving field, urging those in positions of authority, to actively engage with the research.

Part One: The History of Data Science
In the first part of the book, Hampton and DeFalco trace the historical development of data science, highlighting its origins in statistics, computer science, and psychology. They explore how data science has evolved to become a powerful tool for analyzing and interpreting complex data sets, enabling researchers to make informed decisions based on empirical evidence. The authors also discuss the ethical implications of data collection, storage, and analysis, emphasizing the need for transparency, privacy, and responsible use of data.

Part Two: Technology in Education
The second part of the book focuses on the role of technology in education, particularly in the context of AI. The authors discuss how AI can be used to enhance learning outcomes, personalize education, and facilitate lifelong learning. They explore the potential benefits and challenges of AI-powered educational systems, such as automated grading, personalized learning paths, and virtual tutoring. However, they also raise concerns about the potential risks associated with AI, such as the potential for bias, the loss of human interaction, and the need for ethical training and supervision.

Part Three: Combatting Machine Learning Bias
The third part of the book addresses the critical issue of combating machine learning bias. The authors discuss how bias can manifest in AI systems and the potential consequences of biased decision-making. They explore various strategies for mitigating bias, such as using diverse data sets, designing fair algorithms, and incorporating ethical considerations into the design and training process. The authors also emphasize the importance of transparency and accountability in AI development, ensuring that decision-making processes are fair, transparent, and explainable.

Conclusion
In conclusion, this foundational text provides a comprehensive exploration of the intersection of AI, psychology, and ethics. It offers valuable insights into the psychological impact of the AI revolution, the role of technology in education, and the challenges of combating machine learning bias. By presenting cutting-edge research from leading academics, professionals, and policy advocates, the book encourages those in positions of authority to actively engage with the research.

Weight: 336g
Dimension: 152 x 228 x 18 (mm)
ISBN-13: 9780367467678