Approaches to Corporate Social Responsibility: Knowledge, Values, and Actions 2024 (Routledge Studies in Business Ethics)

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Following recent growth of ethical consumerism, customers and other stakeholders increasingly pressure organizations to be socially responsible and minimize their negative impact on the environment. Accordingly, a plethora of firms have integrated corporate social responsibility (CSR) at the center of their business strategies and actions. Whilst this has resulted in many firms meeting their broader responsibilities toward society and the environment, some firms have used CSR in a manipulative and insincere way. As stakeholders become aware of such misuse of CSR, largely thanks to the rapid evolution of information technologies, they start to penalize firms by spreading negative word of mouth about them, and specifically about their CSR knowledge, values, and actions. Now, more than ever before, stakeholders are increasingly critical and cautious in their assessments of firms’ CSR knowledge, values, and actions. On this background, this edited volume sheds light on different internal and external perspectives spanning CSR knowledge, values, and actions. It shares theoretical, practical, and case-based insights on the broader topic and can be of interest to researchers, academics, practitioners, and advanced students in the fields of CSR and business ethics, knowledge management, strategy, and marketing.

Computational Approaches to Conscious Artificial Intelligence

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Artificial Intelligence (AI) has seen rapid advancements in recent years, particularly in the areas of deep learning and the ability to generalize from concrete objects to abstract concepts. Meanwhile, in the study of machine consciousness, a universally agreed definition among scientists and philosophers is still lacking. This book raises a number of issues surrounding the nature and implications of conscious artificial intelligence: How might concepts developed through research in machine consciousness enhance the functionality of AI systems, making them fully autonomous? If self-explanatory information is related to qualia, does this imply that machines using self-explanatory information are conscious? How is the interpretation of intelligence related to a system's ability to generate accurate predictions? Is machine consciousness ultimately possible? And how might it be examined from an ethical standpoint? This edited volume consists of 10 chapters that highlight the prospects of machine consciousness and study the subject from several perspectives. The issues are wide-ranging and include topics such as the metaverse, a computational approach to pain and suffering, universal cognitive intelligence, intentional action, the categorization of conscious machines, and more. The volume is designed as a reference guide for researchers, practitioners, and students interested in the intersection of AI and consciousness. Sample Chapter(s) Preface Chapter 1: The Conscious Machine Contents: The Conscious Machine (Yan H Ng and Antonio Chellaa) The Category of Machines that Become Conscious: An Example of Memory Modelling (Igor Aleksander) A Constructive Explanation of Consciousness and its Implementation (Pei Wang) On Artificial Intelligence, Consciousness and Robots (Pentti O A Haikonen) Universal Cognitive Intelligence, from Cognitive Consciousness, and Lambda (Λ) (Selmer Bringsjord, Naveen Sundar Govindarajulu and James Oswald) Intelligence and Consciousness in Natural and Artificial Systems (David Gamez) Attention and Consciousness in Intentional Action: Steps Toward Rich Artificial Agency (Paul Bello and Will Bridewell) Artificial Conscious Intelligence: Why Machine Consciousness Matters to AI (JJames A Reggia, Garrett E Katz and Gregory P Davis) Will Conscious Digital Creatures Roam the Metaverse? (Owen Holland) On the Ethics of Constructing Conscious AI (Shimon Edelman) Readership: Researchers, practitioners, students, informed readers interested in the intersection of Artificial Intelligence and Consciousness.