Permissions-then-goals based AI user interfaces and legal accountability: First law of robotics and a possible definition of robot safety
This document contains a general overview of the principles.
The principles are based mainly on the idea of competence-based whitelisting and preserving reversibility (keeping the future options open) as the primary goal of AI, while all task-based goals are secondary.
Human-manageable user interface for goal structures, which consists of (in the order of decreasing priority):
1. Whitelist-based permissions for: actions, changes, or results.
2. Implicitly forbidden actions (everything that is not permitted in (1)).
3. Optional: additional blacklist of forbidden actions, changes, or results.
4. Goals (main targets and tasks).
5. Suggestions (optimisation goals).
Can make use of the concepts of reversibility and irreversibility.
Similarity to competence-based permissions of public sector officials (in contrast to the private sector, where everything that is not explicitly forbidden, is permitted — in public sector, everything that is not explicitly permitted, is forbidden. Due to high demands on responsibility, the permissions are given based on specific certifications of competences, and certifiers in turn have their associated responsibility).
Legal aspect: Enables accountability mechanisms for the mistakes of the AI-based agent (accountability of users, owners, manufacturers, etc — based on the entries in the above list and resulting actions of the agent).