Ethics

Giving Voice to Values (GVV) is a rehearsal and case-based approach to business ethics education that is designed to develop moral competence and that emphasizes self-assessment, peer coaching and prescriptive ethics. It is built on the premise that many businesspeople want to act on their values but lack the know-how and experience for doing so. The focus is on action rather than developing ethical awareness or analytical constructs for determining what is right and the epistemology behind knowing that it is right, while acknowledging that existing and well-established approaches to these questions are also important. The GVV rubric for acting on one’s values is based upon the following three questions: (1) What’s at stake? (2) What are the reasons and rationalizations you are trying to counter? and (3) What levers can be used to influence those who disagree? Taken together, the answers to these questions constitute a script for constructing a persuasive argument for effecting values-based change and an action plan for implementation. This approach is based on the idea, supported by research and experience, that pre-scripting and “rehearsal” can encourage action. GVV is meant to be complementary to traditional approaches to business ethics that focus on the methodology of moral judgment. GVV cases are post-decision-making in that they begin with a presumed right answer and students are invited to engage in the “GVV Thought Experiment,” answering the questions: “What if you were going to act on this values-based position? How could you be effective?” This implies a shift in focus towards values-based action in ways that recognize the pressures of the business world. As a consequence of this shift, GVV addresses fundamental questions about what, to whom, and how business ethics is taught. The answers to these questions have led to widespread adoption of GVV in business schools, universities, corporations, and beyond.

Artificial intelligence (AI), commonly defined as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation,” can be classified into analytical, human-inspired, and humanized AI depending upon its application of cognitive, emotional, and social intelligence. AI’s foundations took place in the 1950s. A sequence of vicissitudes of funding, interest in, and support for AI followed subsequently. In 2015 AlphaGo, Google’s AI-driven system, won against the human grandmaster in the highly complex board game Go. This is considered one of the most significant milestones in the development of AI and marks the starting of a new period, enabling several AI innovations in a variety of sectors and industries. Higher education, the fashion industry, and the arts serve as illustrations of areas wherein ample innovation based on AI occurs. Using these domains, various angles of innovation in AI can be presented and decrypted. AI innovation in higher education, for example, indicates that at some point, AI-powered robots might take over the role of human teachers. For the moment, however, AI in academia is solely used to support human beings, not to replace them. The apparel industry, specifically fast fashion—one of the planet’s biggest polluters—shows how innovation in AI can help the sector move toward sustainability and eco-responsibility through, among other ways, improved forecasting, increased customer satisfaction, and more efficient supply chain management. An analysis of AI-driven novelty in the arts, notably in museums, shows that developing highly innovative, AI-based solutions might be a necessity for the survival of a strongly declining cultural sector. These examples all show the role AI already plays in these sectors and its likely importance in their respective futures. While AI applications imply many improvements for academia, the apparel industry, and the arts, it should come as no surprise that it also has several drawbacks. Enforcing laws and regulations concerning AI is critical in order to avoid its adverse effects. Ethics and the ethical behavior of managers and leaders in various sectors and industries is likewise crucial. Education will play an additional significant role in helping AI positively influence economies and societies worldwide. Finally, international entente (i.e., the cooperation of the world’s biggest economies and nations) must take place to ensure AI’s benefit to humanity and civilization. Therefore, these challenges and areas (i.e., enforcement, ethics, education, and entente) can be summarized as the four summons of AI.