Augmenting Human Judgment in AI-Powered Project Management: A Framework for Collaborative Decision-Making

Abstract

This paper explores the transformative role of artificial intelligence (AI) in project management, emphasizing the importance of integrating AI capabilities with human judgment to enhance decision-making processes. The focus is on three key areas: representation learning for deeper insights, cognitive bias mitigation, and ethical AI design. Representation learning techniques, such as natural language processing (NLP) and deep learning, enable AI systems to analyze complex project data, providing actionable insights that support informed decision-making. Additionally, AI can help mitigate common cognitive biases like overconfidence and the sunk-cost fallacy by offering real-time feedback and objective analysis. Ethical considerations are paramount, necessitating transparent, accountable, and fair AI systems. Strategies such as explainable AI (XAI), human-in-the-loop governance, and bias auditing are essential to ensure responsible AI deployment. By combining AI's analytical strengths with human contextual knowledge and ethics, this collaborative framework aims to maximize project success while addressing the limitations of purely automated systems. Looking ahead, emerging technologies like reinforcement learning and generative AI hold great potential but also present new ethical and regulatory challenges that must be proactively addressed. This paper underscores the need for a balanced approach that leverages AI to augment human judgment, fostering innovation and sustainable practices in project management.