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Responsible AI : (Record no. 141064)

MARC details
000 -LEADER
fixed length control field 02052nam a22002537a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260609125819.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 260609s2024 |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780138073923
040 ## - CATALOGING SOURCE
Transcribing agency PK-LaUMT
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Item number RES-
245 00 - TITLE STATEMENT
Title Responsible AI :
Remainder of title best practices for creating trustworthy AI systems /
Statement of responsibility, etc Qinghua Lu . . . [et al.]
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Boston :
Name of publisher, distributor, etc Addison-Wesley,
Date of publication, distribution, etc 2024
300 ## - PHYSICAL DESCRIPTION
Extent xix, 291 p.
500 ## - GENERAL NOTE
General note Index present
520 ## - SUMMARY, ETC.
Summary, etc AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levels Development process perspectives, including software engineering best practices for AI System perspectives, including quality attributes, architecture styles, and patterns Techniques for connecting code with data and models, including key tradeoffs Principle-specific techniques for fairness, privacy, and explainability A preview of the future of responsible AI
546 ## - LANGUAGE NOTE
Language note Eng
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence-social aspects
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lu, Qinghua
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Zhu, Liming
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Whittle, Jon
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Xu, Xiwei
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Home library Current library Date acquired Full call number Barcode Date last seen Price effective from Koha item type Copy number
      UMT Main Campus UMT Main Campus 2026-06-09 006.3 RES- 152896 2026-06-09 2026-06-09 Books  
      UMT Main Campus UMT Main Campus 2026-07-20 006.3 RES- 153518 2026-07-20 2026-07-20 Books C.2