What AI Can Do : Strengths and Limitations of Artificial Intelligence

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What AI Can Do : Strengths and Limitations of Artificial Intelligence

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 444 p.
  • 言語 ENG
  • 商品コード 9781032395999
  • DDC分類 006.3

Full Description

The philosopher Spinoza once asserted that no one knows what a body can do, conceiving an intrinsic bodily power with unknown limits. Similarly, we can ask ourselves about Artificial Intelligence (AI): To what extent is the development of intelligence limited by its technical and material substrate? In other words, what can AI do? The answer is analogous to Spinoza's: Nobody knows the limit of AI.

Critically considering this issue from philosophical, interdisciplinary, and engineering perspectives, respectively, this book assesses the scope and pertinence of AI technology and explores how it could bring about both a better and more unpredictable future.

What AI Can Do highlights, at both the theoretical and practical levels, the cross-cutting relevance that AI is having on society, appealing to students of engineering, computer science, and philosophy, as well as all who hold a practical interest in the technology.

Contents

Conceptual Framework of AI Ethics. Philosophical Roots for AI Ethics Controversy. AI and Ethics: A Feminist Decolonial Critique. Algorithm as an Assemblage. Algorithms and Everyday. Auntiebot: Indigenous Protocols and AI in Practice. AI as a way to improve educational practices. Using AI for Educational Research in Multimodal Learning Analytics. The Dark Side of Smart Cities. AI in Biomedical Research and Clinical Practice. AI in Music. Violence control between the machine and the human. AI in the future of education. AI in Neuroscience: Helping to Understand How the Brain Represents Word Meanings. Building predictive models to efficiently generate new nanomaterials with antimicrobial activity. AI in Construction 4.0. Towards an automatic screening system to detect anomalies in retina images. Deep learning for energy savings in electric devices. Artificial Intelligence in Industry 4.0: a review of challenges. Artificial intelligence for mental health: Possibilities for accessible
massive therapy in the future. Classification Machine Learning applications for Energy Management Systems in Distribution Systems.

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