Keynote by Dr. Babak Hodjat: Creating an AI-Powered Organization

What’s the Problem With Analytics?

Most companies are focused on preliminary analytics, but this doesn’t do business impact justice.

  • Models become obsolete faster than we expect — changes in customer habits, regulations, even unpredictable events like natural disasters alter the course of AI models.

What’s the State of AI Now?

AI doesn’t entirely cover decision-making the way humans do. Three significant obstacles keep computers from making decisions on the human scale as well as we do:

  • not robust to unexpected states (i.e., states not in training models)
  • not robust if the rules change (i.e., must learn everything from scratch each time.)

Understand Decision Making

Humans make decisions by taking context and applying strategies that optimize our objectives for making that decision. We create the plan through experience, but also mental models. We try out different choices within the virtual world of our minds and make the decisions. The outcome of our final decision is added to our historical data for future decisions.

  • The space is too large. Too many variables create noise.
  • The space is too high-dimensional. Single tweaks don’t yield enough improvement for the next course of action.

Enter Evolutionary Computation

Evolutionary computation began at the dawn of computers with Turing. Instead of using one “climber,” it uses population search. Multiple variables are optimized at once, and multiple objectives and novelty can get around deception. You can remove the options that aren’t doing well, keeping the ones that are, and allowing them to talk to each other.

So Why Do We Need AI-driven Decision Making in AI-Powered Organizations?

Decisions are multi-objective, always. Dr. Babak Hodjatis clear that we must be able to use data to make the best possible decision. A lot is on the line for businesses to rely on intuition.

  • What would that look like driven by AI-decision making?



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