商品描述
This book enables readers to understand the challenges and opportunities of developing human-centered AI with commonsense reasoning abilities. Despite apparent accuracy improvements brought by large neural models across task benchmarks, common sense is still lacking. The lack of common sense affects many tasks, including story understanding, decision-making, and question answering. Commonsense knowledge and reasoning have long been considered the "black matter" of AI, raising concerns about the trustworthiness and applicability of AI methods in both autonomous and hybrid applications. This book describes how to design a more robust, collaborative, explainable, and responsible AI through incorporating neuro-symbolic commonsense reasoning. In addition, the book provides examples of how these properties of AI can facilitate a wide range of social-good applications in digital democracy, traffic monitoring, education, and robotics. What makes commonsense reasoning such a unique and impactful challenge? What can we learn from cognitive research when designing and developing AI systems? How can we approach building responsible, robust, collaborative, and explainable AI with common sense? And finally, what is the impact of this work on human-AI teaming? This book provides an accessible introduction and exploration of these topics.
商品描述(中文翻譯)
本書使讀者能夠理解開發具有人本中心的人工智慧（AI）及其常識推理能力所面臨的挑戰與機會。儘管大型神經模型在各項任務基準測試中顯示出明顯的準確性提升，但常識仍然不足。常識的缺乏影響了許多任務，包括故事理解、決策和問題回答。常識知識和推理長期以來被視為AI的「黑暗物質」，引發了對AI方法在自主和混合應用中可信度和適用性的擔憂。本書描述了如何通過整合神經符號常識推理來設計更具韌性、協作性、可解釋性和負責任的AI。此外，本書提供了這些AI特性如何促進數位民主、交通監控、教育和機器人等廣泛社會公益應用的範例。常識推理為何是一個如此獨特且具影響力的挑戰？在設計和開發AI系統時，我們可以從認知研究中學到什麼？我們如何能夠以常識來構建負責任、穩健、協作和可解釋的AI？最後，這項工作對人類與AI團隊合作有何影響？本書提供了這些主題的易懂介紹和探索。
作者簡介
Filip Ilievski, Ph.D., is a Senior Assistant Professor of Commonsense AI at the VrijeUniversiteit (VU) Amsterdam's Computer Science department. Dr. Ilievski is an affiliated scientist at the USC Information Sciences Institute (ISI), where he was previously a Research Lead and played a key role in a team within the DARPAMachine Common Sense (MCS) program. Dr. Ilievski holds a Ph.D. in Natural Language Processing. His research focuses on developing robust and explainable neuro-symbolic technology with positive real-world impact, based on neural methods and high-quality knowledge. Dr. Ilievski has also made extensive contributions in identifying long-tail entities in text, interpretation of internet memes, and enabling access to large-scale knowledge resources.
作者簡介(中文翻譯)
Filip Ilievski 博士是阿姆斯特丹自由大學（Vrije Universiteit, VU）計算機科學系的常識人工智慧高級助理教授。Ilievski 博士是南加州大學資訊科學研究所（USC Information Sciences Institute, ISI）的附屬科學家，之前擔任研究負責人，並在 DARPAMachine Common Sense (MCS) 計畫中的一個團隊中扮演了關鍵角色。Ilievski 博士擁有自然語言處理的博士學位。他的研究專注於開發基於神經方法和高品質知識的穩健且可解釋的神經符號技術，以實現正面的現實世界影響。Ilievski 博士在識別文本中的長尾實體、解釋網路迷因以及促進對大規模知識資源的訪問方面也做出了廣泛的貢獻。
