Two kinds of software: It’s time to take world modeling seriously

It’s time to get serious about world modeling.  Here’s why:

  1. There are two kinds of software in the world. (1) Tools (like Microsoft word) and (2) software that depends on a model of the world as its core capability
  2. Examples of the second category are fraud detection systems, churn analysis, google ads, recommender systems like amazon and Netflix, and more
  3. These systems depend on the degree to which their internal, “cartoon” model reflects the world

    In recent years, we’ve learned how to build these models automatically from a stream of data (e.g. fraud data, churn data, click data)

  4. But if you think about these cartoon models (we might call them “world models”), there are more ways to obtain them than from just data
  5. When we do interactive data visualization, what we’re doing is substituting a human brain, *informed* by data, for the “world modeling” capability.
  6. Essentially, we’re substituting ourselves for this capability, in situations / use cases where we recognize that the data isn’t perfect.
  7. There is an unmet need here, because as Mark Zangari describes in his talk at SFU last fall, it’s asking too much of our brains to do effectively in many complex situations.
  8. In particular, this is the source of a lot of cognitive bias, and leads to unintended consequences in many situations
  9. So, we need to think beyond the use of historical data for “world modeling”.
    In particular, we need to combine a) the data; b) good interactive data visualization (as with Tableau, Excel, or Qlikview; and c) a good systems model.
  10. (c)  has been missing until recently. This is what World Modeler™ software does, and Decision Intelligence helps us to do, and what Decision Engineers build for a living.

Lorien Pratt

Pratt has been delivering AI and DI solutions for her clients for over 30 years. These include the Human Genome Project, the Colorado Bureau of Investigation, the US Department of Energy, and the Administrative Office of the US Courts. Formerly a computer science professor, Pratt is a popular international speaker and has given two TEDx talks. Her Quantellia team offers AI, DI, and full-stack software solutions to clients worldwide. Previously a leading technology analyst, Pratt has also authored dozens of academic papers, co-edited the book: Learning to Learn, and co-authored the Decision Engineering Primer. Her next book: Link: How Decision Intelligence makes the Invisible Visible (Emerald Press), is in production. With media appearances such as on TechEmergence and GigaOm, Pratt is also listed on the Women Inventors and Innovator’s Mural. Pratt blogs at www.lorienpratt.com.

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