Del i serien Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

AI for People, Democratizing AI

Second EAI International Conference, CAIP 2023, Bologna, Italy, November 24-26, 2023, Proceedings

Häftad, Engelska, 2024

AvMarta Ziosi,Giovanni Sartor,João Miguel Cunha,Angelo Trotta,Philipp Wicke

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This book constitutes the refereed post-conference proceedings of the Second EAI International Conference on AI for People, Democratizing AI, CAIP 2023, held in Bologna, Italy, during November 24-26, 2023. The 11 regular papers were carefully reviewed and selected from 27 submissions.

Produktinformation

Utgivningsdatum2024-10-03
Mått155 x 235 x 9 mm
Vikt230 g
FormatHäftad
SpråkEngelska
SerieLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Antal sidor131
FörlagSpringer International Publishing AG
ISBN9783031713033

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Tillämpad datateknik inom Data och IT
Systemvetenskap och AI inom Data och IT

.- Ethical AI and innovation..- A Human-Centered Decision Support System in Customer Support..- An AI-based Remote Rehabilitation System to Promote Access to Physical Rehabilitation..- Democratization of AI and Governance..- Democratization is a process, not a destination: Operationalizing ethics and democratization in a cyberinfrastructure for AI project..- (Im)possibilities in the Ethics of AI: Biometric Surveillance, Complicity, and Refusal in India and Beyond..- Research methods of the impact of AI on elections systematic review..- AI in Society and Legal Aspects..- On the Legal Aspects of Responsible AI: Algorithmic Change, Human Oversight, and Societal Outcomes..- Limitations of Transparency in Democratising and Regulating Algorithmic Management..- Breaking the Filtered Lens: A Feminist Examination of Beauty Ideals in Augmented Reality Filters..- Data Privacy and Technology Ethics..- Your body should not belong to the internet: online bodily integrity in the world of deepfake pornography..- The Promise and Peril of Responsible AI Principles..- Accelerating Machine Learning Primitives on Commodity Hardware.