Abstract
Although Artificial Intelligence (AI) has existed since the 1950’s, it has experienced a series of expansions and declines over the years. Currently, AI is on an upward trajectory and has prompted the fourth industrial revolution as many scientists have noted. Some firms have rapidly embraced this technology and experienced growth while others have been slow to adopt. Naturally, this expansion often has societal impacts. The aim of this study is to explore ethical considerations that arise during the adoption of this technology. This research addressed three questions: 1. How do market and regulatory forces reportedly shape Artificial Intelligence adoptions? 2. What ethical principles/perspectives do managers follow when adopting Artificial Intelligence and Machine Learning systems? and 3.What ethical issues exist within the firms that adopt Artificial Intelligence and Machine Learning systems? Since the research in this area was limited, I decided to use a qualitative exploratory approach. This dissertation contained three primary components: an industry analysis, a discussion case study along with a supporting instructor’s manual, and a grounded theory study. Through the industry analysis, I identified key actors operating within this market, determined power dynamics, and prepared an AI Stakeholder Power/Interest Matrix. This tool provided managers with strategies they can use to prioritize their internal resources and manage relationships with these stakeholders. The discussion case study and instructor’s manual focused on a company, Vectra Digital, that designed its own AI in-house and explored the ethical and operational aspects of this decision. Faculty can use this package – discussion case study and instructor’s manual – to prepare a highly engaging learning experience for business students. Finally, the grounded theory study included industry expert interviews and proposed a new approach, an Ethics Integrated AI Adoption Framework with AI Trust functioning as an antecedent to these leader behaviors. From a theoretical standpoint, this study served as a bridge between AI trust and ethics, as well as AI trust and AI-Human job design, along with ethics and AI-Human job design.