It combines different types of decision logic, including artificial intelligence, decision rules, regulations, and human judgement, with measurements and logic minimizing decision noise and cognitive bias.
It combines different types of decision logic, including artificial intelligence, decision rules, regulations, and human judgement, with measurements and logic minimizing decision noise and cognitive bias.
CONTEXT
Imagine buying a house.
People will rarely take decisions without context, but so far we
expected computers to do so.
You wouldn’t simply look through the window and say, “This will be my new home”. You would open the door and walk in, look at all the rooms and assess the condition, the roof, plumbing, electrics, windows, and heating – this is the 'internal data'.
You would then walk and drive around the neighborhood, the local schools, shops, sport facilities, public transport, the value of properties in the area, and you probably even will have a chat with the neighbors – this is the 'external data'.
The combination of 'internal' and 'external data' and the insights from it against certain decision criteria, is key in making optimal decisions and is what we call 'context'.
✔ Provides a framework for best practices in decision-making and processes for deploying enterprise AI.
✔ Acts as a coach and empowers people to make the best decisions
✔ Gartner has tipped decision intelligence as the near future of corporate decision-making.