A proposed framework by Ashwin Singh
Synthetic Inheritance AI
Investigating what present decisions leave for future generations.
Definition
Synthetic Inheritance AI (SIAI) is a proposed AI-assisted framework developed by Ashwin Singh for investigating how today's decisions, actions and omissions affect future generations.
It examines the original decisions, immediate outcomes, overlooked factors and long-term economic, social, environmental and institutional consequences inherited by future generations. Through evidence-based analysis and accountability, it aims to improve present-day decision-making.
What are we leaving behind for people who have not yet been born?
What the framework examines
- The decision: who acted, when, with what stated purpose and available evidence.
- The immediate result: what changed and who benefited or bore a cost.
- The omissions: risks, people, alternatives or evidence that were left out.
- The inheritance: effects that persist in institutions, communities, economies or the environment.
- The lesson: what a future decision-maker can verify and improve.
How to use it
Start with a documented decision or policy. Build a timeline of actions and outcomes, distinguish evidence from claims and inference, and test competing explanations. Trace both intended effects and neglected consequences across generations. Human judgment remains responsible for interpretation and accountability; AI assists with organising and examining the evidence.
Framework developed by Ashwin Singh · SENLAROS CORPORATION (PTY) LTD