Responsible AI Principles in Product Management Practices

Abstract

In the wake of rapid advancements and investments in AI technologies, integrating AI into software products has become widespread. Product Manager, also called “Mini-CEO”, plays a crucial role in driving this innovation. However, as ethical considerations gain prominence, it is imperative for Product Managers to incorporate responsible AI principles into their product management practices for “responsible innovation”. Ethical issues of AI are well-documented, but there is a notable scarcity of research on integrating responsible AI into product management. This gap leaves Product Managers ill-equipped to ensure ethical and sustainable AI development, risking unintended consequences for users and society. This study aims to fill this gap by answering two research questions: 1. How do organizations currently integrate responsible AI into their product management? 2. What are the challenges of integrating responsible AI into product management? For this purpose, a semi-systematic review of the literature is conducted. A conceptual framework is also developed, incorporating the Responsible Innovation and ISPMA SPM frameworks. For data collection, 20 semi-structured interviews were conducted with AI product managers, consultants, and researchers in responsible AI space. A thematic analysis of interviews was conducted to gain insights from the experiences and perspectives of the interviewees. Research findings indicate that understanding market needs for ethical values, incorporating responsible AI into practices such as roadmapping and product lifecycle management, and continuous performance and risk assessments are crucial for ethical AI products. Effective stakeholder coordination and comprehensive documentation to meet ethical standards are also essential for ensuring AI products align with regulatory requirements and user expectations. The study also identified several challenges in responsible AI integration, such as increased overheads, unrealistic customer expectations, complexity, skill shortages, and negligence in the early stages. Strategies to address these include automated risk assessments, effective customer communication, thinking beyond regulations, forming dedicated RAI teams, adopting holistic approaches, and engaging in external collaboration. This research provides insights for AI product managers to integrate responsible AI and for researchers and policymakers to develop informed regulations and policies for safer AI products.

Colophon: This page is part of the AAU Student Projects portal, which is run by Aalborg University. Here, you can find and download publicly available bachelor's theses and master's projects from across the university dating from 2008 onwards. Student projects from before 2008 are available in printed form at Aalborg University Library.

If you have any questions about AAU Student Projects or the research registration, dissemination and analysis at Aalborg University, please feel free to contact the VBN team. You can also find more information in the AAU Student Projects FAQs.

A master thesis from Aalborg University

Responsible AI Principles in Product Management Practices