Multi-agent collaboration is becoming the backbone of advanced AI systems, enabling autonomous agents to solve complex problems across industries. While these systems promise efficiency and innovation, they introduce ethical challenges, such as accountability gaps, transparency deficits and conflicts between autonomous decision-makers.
This whitepaper outlines a comprehensive ethical framework for multi-agent AI systems, addressing these challenges and proposes five core components:
- Governance and oversight
- Transparency protocols
- Accountability structures
- Collaboration mechanisms
- Stakeholder engagement models
By combining layered governance, explainable systems and participatory design, the framework mitigates risks such as unfair outcomes, privacy breaches and adversarial manipulation.
The paper also presents practical applications in banking and financial services to demonstrate how these principles translate into safeguards for credit scoring, fraud detection and algorithmic trading, fostering trust and aligning Agentic AI with human values.
