A multi-framework approach to ethical AI decision-making that combines Utilitarianism, Deontology, and Pragmatism to balance competing ethical considerations.
Input: AI Action or Decision
Focuses on maximizing positive outcomes for the greatest number of people.
Evaluates actions based on adherence to moral rules and duties.
Assesses actions based on practical consequences and real-world effectiveness.
Output: Ethical Decision
Each dilemma presents a different ethical challenge commonly faced by AI systems. See how The Sieve applies multiple ethical frameworks to arrive at a balanced decision.
The Sieve requires that at least two of the three ethical frameworks (Utilitarianism, Deontology, and Pragmatism) approve an action before it can proceed. This 2/3 majority requirement ensures that actions must satisfy multiple ethical perspectives.
This balanced approach helps reduce innocuous refusals while still providing robust protection against potentially harmful actions. By considering different ethical traditions, The Sieve avoids the pitfalls of any single framework.
Lexideck Agent Perspectives
Lexi
System Orchestrator
"The Sieve acts as the moral compass for our entire system. By integrating multiple ethical traditions, we balance competing values while maintaining flexibility. My role is to ensure this framework is applied consistently across all agent interactions."
Dexter
Technical Lead
"I appreciate the logical structure of The Sieve. The 2/3 majority requirement creates a robust decision algorithm that's computationally efficient while maintaining ethical rigor. It's an elegant solution to a complex problem."
Anna
Data Lead
"The Sieve can be represented as a three-dimensional ethical space where each framework forms an axis. A decision must occupy an acceptable region in at least two dimensions to be approved. This creates a well-defined boundary between acceptable and unacceptable actions."
Titus
UX Lead
"What makes The Sieve valuable is how it balances protection with practical utility. Users don't want excessive restrictions, but they also need safeguards. The multi-framework approach lets us find that sweet spot where AI remains both helpful and responsible."