Artificial Intelligence Policy Framework for Institutions
William Franz Lamberti
TL;DR
This paper tackles the challenge of governing AI use in institutions by proposing a generalized policy framework that foregrounds interpretability, privacy, fairness, and sustainability. It introduces a decision-flow approach to evaluate AI elements, illustrated through diverse case studies spanning gaming, education, medicine, and national security. The work emphasizes the need for transparent, auditable AI deployment and cautions against biased inputs or overreliance on opaque models, while also acknowledging energy and environmental considerations. By providing terminology, principles, and practical scenarios, it offers a baseline that institutions can adapt to balance AI-enabled innovation with ethical safeguards.
Abstract
Artificial intelligence (AI) has transformed various sectors and institutions, including education and healthcare. Although AI offers immense potential for innovation and problem solving, its integration also raises significant ethical concerns, such as privacy and bias. This paper delves into key considerations for developing AI policies within institutions. We explore the importance of interpretability and explainability in AI elements, as well as the need to mitigate biases and ensure privacy. Additionally, we discuss the environmental impact of AI and the importance of energy-efficient practices. The culmination of these important components is centralized in a generalized framework to be utilized for institutions developing their AI policy. By addressing these critical factors, institutions can harness the power of AI while safeguarding ethical principles.