Participatory Management Can Help Artificial Intelligence Ethics Adhere to Social Consensus

Artificial Intelligence (AI) is rapidly becoming pervasive, reshaping social structures, cultural dynamics, and labor markets. This rapid growth has ignited global discussions surrounding AI's challenges, including its tendency to perpetuate biases and social inequalities, ignoring societal values, and affect diverse sectors such as genetics, drug production, defense, and democratic processes. This study examines AI ethics within the framework of social consensus, advocating for participatory management as a crucial approach to address these challenges. The proposed methodology includes the entire AI lifecycle, promoting inclusive practices from initial design through implementation, monitoring, and control. The participatory management model is structured in three phases: Stakeholder Engagement, which advocates for the active involvement of diverse stakeholders in the development of AI systems to ensure a range of perspectives in design, modeling, and implementation; Monitoring and Alignment, which emphasizes the continual observation of AI systems' interaction with their environments; and Macro Level Impact Analysis, which evaluates the broader societal impacts of the AI ecosystem across domains such as education, culture, health, and safety. This study underscores the importance of a collaborative, inclusive approach in AI development and management, emphasizing the need to align AI advancements with ethical principles and societal well-being.