Human empowerment and control - revisited

In the original post on the topic from 6 month ago, I wrote about human control of AI systems in terms of the three categories in-the-loop, on-the-loop and out of-the-loop.

Upon further reflection, I think there's a fourth category: conditional-on-the-loop.

The idea of conditional-on-the-loop is that one (potential black box) algorithm is producing a decision (the decider)  which is checked against another algorithms which provides full transparency (the checker), for example a rule based system implementing a policy statement.

If the checker agrees with the decider than the system would go ahead with implementing the decision. If, however, there's a conflict between the decider and the checker, the final decision would be delegated to a human decision maker.

The advantage of this approach is its scalability. Routine cases can be automated at low risk and the scarce human resource can be focused on the critical cases.

The approach is of limited use if time-to-decision is of the essence, e.g. in automated weapon systems, autonomous transportation, equity trading or other applications where decision have to be made in extremely short time frames.

Human empowerment and control

A goal often stated for AI systems is the empowerment and augmentation of the users of such systems.

Empowerment implies control. Paul Scharre discusses different levels of control in his book "Army of None: Autonomous Weapons and the Future of War” which I discussed in an earlier post. This three-level categorization can, however, be applied to AI systems in general.

·       in-the-loop

the AI recommends, and the human decides

This is the strongest form of control and empowerment.

There is, however, the potential that a human is just an actuator and not a decider because the AI makes a suggestion which cannot be investigated and validated by the human decision maker for various reasons, e.g. the time for making a decision is too short,  the large numbers of decisions to be made overwhelms the decider, there's a lack of transparency of the recommendation process.

The human in-the-loop could have also developed a blind trust in the AI recommendations.

·       on-the-loop

the system decides, but the human can take over control at any moment

Essentially the human has control over the on/off switch of the AI systems which is very coarse grain level of control yet ultimately very powerful.

·       out-of-the-loop

this is a fully autonomous system; the human controller has no power.

There can be reasonable use cases for each of these levels of human empowerment.

When developing a AI system, all stake holders including product owners, data scientist, legal and senior executives need to carefully assess which level of human control and empowerment should be implemented.

An important consideration is the reversibility of a decision. If the decision is reversible, a possible mitigation is the possibility to challenge a decision by a person who is subjected to it as discussed in a previous post.