educating boards on AI

AI is fundamentally an augmentation of the human factor. I once designed a framework for organisations where the three main classes of stakeholder ( or in ISO terms, "interested party" / IP ) are 

• 1. investors : moves first with capital, gets paid last
• 2a. staff : the first supplier, gets paid first, closes loop
• 3. customers : pays first

Depending on business model of course, there are other IPs, like 

• 0. the government,
• 2. suppliers ( superset of staff ), 
• 4. neighbours,
• 5. competitors, 
• 6. criminals

etc. 

It becomes interesting to run brief simulations over a cup of coffee about what happens when the cost of doing business for each of those parties gets impacted by AI. Basically if the cost of thought drops for everyone, the government is going to want a higher standard of compliance, investors are going to allocate capital differently, staff either get lazier or more productive, suppliers are expected to increase performance, customers have different behaviours depending on their own operating models, competitors are simply trying to leverage off the same thing in different dimensions, and thieves are getting sneakier.

I generally say that most business problems are talent management problems - and that the only long-term difference between machine and human intelligences is legal personhood. In the pathology of behaviour, we again a simple framework is to determine if the problematic party is (a) stupid, (b) lazy, or (c) malicious - there being various formulations of reduction and expansion about this. So much fun to think about, but more fun to think about as an educator of students who don't understand this thoroughly.

( Someone was looking for board-level non-technical AI-subject-matter training the other day, so I dropped a random comment and buggered off. Thought about it a bit more over the week. )