AI-enabled information systems (AI-enabled IS) offer enhanced utility and efficiency due to their knowledge-based endowments, enabling human agents to assign and receive tasks from AI-enabled IS. As a result, this leads to improved decision-making, ability to manage laborious jobs, and a decrease in human errors. Despite the performance-based endowments and efficiencies, there are significant ethical concerns regarding the use of and delegation to AI-enabled IS, which have been extensively addressed in the literature on the dark side of artificial intelligence (AI). Notable concerns include bias and discrimination, fairness, transparency, privacy, accountability, and autonomy. However, the Information Systems (IS) literature does not have a delegation framework that incorporates ethics in the delegation mechanism. This work seeks to integrate a mixed deontological-teleological ethical system into the delegation mechanism to (and from) AI-enabled IS. To that end, I present a testable model to ethically appraise various AI-enabled IS as well as ethically evaluate delegation to (and from) AI-enabled IS in various settings and situations.

Supply chain transparency is principally focused on a company's efforts toward disclosing information about their products, and their supply chain operations to the public. Essay 1 is a conceptual paper that examines the risks of disclosing supply chain mapping information to consumers and proposes an approach to developing risk mitigation strategies. This essay also develops a set of supply chain mapping conventions that support the development of an agility-focused supply chain map. Essay 2 employs an experimental design methodology to examine the impact of disclosing the ethnicity of a supplier on consumers' behaviors, while also capturing the extent to which a consumers' ethnic identity and prosocial disposition influence their behaviors. Finally, also using an experimental design, Essay 3 analyzes consumer outcomes based on disclosing no, partial, and full supply chain transparency information, and accounts for heterogenous consumer traits such as the importance of information to a consumer and their perceived quality of information. Collectively, these essays advance the body of knowledge that seeks to understand the risks and benefits of supply chain transparency, by conceptually identifying risks and proposing an approach to minimize the risks associated with supply chain transparency, and by illuminating the conditions that prompt favorable consumer outcomes.