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What is Explainability

Chapter 7
Creative AI Tools and Ethical Implications in Teaching and Learning
The ability to provide understandable explanations for the decisions and recommendations generated by AI models.
Published in Chapter:
ChatGPT and Other Generative AI Tools in Education: Transformative Potential and Ethical Considerations
C. V. Suresh Babu (Hindustan Institute of Technology and Science, India) and S. Adhithya (Hindustan Institute of Technology and Science, India)
Copyright: © 2023 |Pages: 18
DOI: 10.4018/979-8-3693-0205-7.ch007
Abstract
This chapter presents a comprehensive exploration of the transformative influence of generative AI tools in education. It examines the personalized learning experience enabled by AI, the role of AI tools as virtual tutors, content creation aids for educators, and their application in language learning and communication enhancement. Additionally, the chapter delves into the ethical implications associated with AI integration, including data privacy, fairness, and transparency. Practical strategies for responsible AI adoption are proposed, encompassing guidelines for ethical usage and educator training. The chapter concludes by highlighting the vast potential of AI-powered education while underscoring the significance of ethical considerations in its implementation. It encapsulates the evolution of AI in education and foresees a future where learners are empowered through dynamic and personalized educational experiences.
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Chapter 30
Effects of Human-Machine Integration on the Construction of Identity
One of the most important concepts of the Ethnomethodology of Discourse. It relates the objectification of social knowledge needed to develop daily habits with how individuals justify their actions socially when interacting with technology. This affects directly on the construction of psychosocial identity.
Published in Chapter: Effects of Human-Machine Integration on the Construction of Identity; From: Handbook of Research on Technoself: Identity in a Technological Society
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Chapter 5
Synthetic Data Generation: Methods, Applications, and Multidisciplinary Use Cases
The degree to which synthetic data generation processes and models can be understood and justified, fostering trust and transparency in their use.
Published in Chapter: Synthetic Data Generation: Methods, Applications, and Multidisciplinary Use Cases; From: Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency
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Chapter 3
Ethical Considerations for Artificial Intelligence in Educational Assessments
This ethics principle relates to the lowering of opacity relating to data, AI algorithms and AI-driven decisions, the justification of its use, and the communication of details in a non-technical easy-to-understand manner to relevant stakeholders.
Published in Chapter: Ethical Considerations for Artificial Intelligence in Educational Assessments; From: Creative AI Tools and Ethical Implications in Teaching and Learning
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Chapter 100
Explainable Artificial Intelligence
Degree to which an observer or user can understand the cause of a decision by formulating an explanation.
Published in Chapter: Explainable Artificial Intelligence; From: Encyclopedia of Data Science and Machine Learning
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Chapter 5
Ethical Rationality in AI: On the Prospect of Becoming a Full Ethical Agent
Research paradigm which prioritizes making AI intelligible and interpretable in order to promote safety, transparency, and trust.
Published in Chapter: Ethical Rationality in AI: On the Prospect of Becoming a Full Ethical Agent; From: Machine Law, Ethics, and Morality in the Age of Artificial Intelligence
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Chapter 18
Futuristic Chatbots: Expectations and Directions for Accomplishment
AI systems must offer lucid and comprehensible rationales for their judgments to improve transparency and user understanding of the technology's operations.
Published in Chapter: Futuristic Chatbots: Expectations and Directions for Accomplishment; From: Design and Development of Emerging Chatbot Technology
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