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Artificial Intelligence Complex Systems Environment Machine Learning Simulation Wicked Problems
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From maker space to solver space

Conferences are for meetings.  Project teams build deliverables.  Data is for data scientists.  Online communities are for social contact.

Until now, when a new mix is emerging.  Can we solve difficult problems in a short-term conference setting?  Is there a new way to run a workshop, which is dynamic, data-driven, visual, collaborative?

I wrote a few months back about the Silicon Valley Sim Center: an initiative to bring a new way to solve “wicked” problems to Silicon valley.  And in an article in this month’s Wired called “Hey Silicon Valley, Buckminster Fuller has a lot to teach you“ by Sarah Fallon, she interviews Jonathon Keats about his new book on what Bucky has to say to Silicon Valley.*

And from “maker spaces” to “solver spaces”, a new way of working together to solve difficult problems is emerging.

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Guest Post Innovation Leadership for decision makers
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Guest post: Mindset GPS: Navigating New Realities

Great leaders make the right call at the right time to deliver outstanding results. They avoid relying on outdated mindsets and practices in a complex and changing environment. Leaders today must be willing to help others to think strategically, question past practices, and explore new alternatives.

Relying on old habits, acquiescing to group think, and depending on obsolete assumptions limits individual careers and reduces organizational viability.  A painful example: in the 1990s, mortgage bankers granted 95% mortgages based on the wrong assumption that home prices never fall more than 5%. They paid a high price for their narrow thinking. Additionally, they ignored expert warnings about a real estate bubble. One bank executive stated that he knew it would blow up, but as long as the music was playing, he had to keep dancing. Instead of searching for a new melody, he went along for the ride.

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Artificial Intelligence Decision engineering Decision intelligence
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Decision: I do not think it means what you think it means

We use the word “decision” to mean two very different things.  If I say “I’ve decided that the moon is made of green cheese”, or “I’ve decided that the economy will deteriorate next year”, these statements aren’t necessarily about actions I’m going to take.  If, instead, I say, “I’ve decided to go to go to graduate school” or “I’ve decided to institute a new policy”, that’s fundamentally different.

How?  The first kind of decision leads to a fact, either well-supported or not.  It is, essentially, using data and expertise, following its implications (deductively, inductively, or otherwise), and leading to a conclusion (which may have more or less justification: to fit this category it doesn’t have to be right). Continue reading

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Decision engineering Decision intelligence Guest Post Introduction
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Guest Post: What is Decision Intelligence (DI), anyway?

Decision Intelligence: An easy and pedagogical way to make Informed Decisions using collective intelligence

Have you sometimes had the feeling that you missed important aspects in your decision making which make you feel somewhat uneasy?

Did you perhaps forget to take certain facts into consideration or did you misjudge the relative importance of an influencing factor? Did you realize the unintended consequences of the decision taken?

You know there is a tacit cause-and-effect mechanism under the surface, but maybe you did not capture it, or even not understood it.

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