Building Teams of People (and Machines?)

The way I build a human team depends upon the purpose of the team.

Sometimes I need a team with skills nearly-identical to my own.  Sometimes I need a team with widely varying skills.  Sometimes I need a little bit of both – I need subject matter experts with deep knowledge in a specific area who also have other skills and insights acquired through different professional experiences.

Sometimes I like to include a totally new perspective – perhaps a new hire or trainee or novice or someone from an entirely unrelated discipline because they may see things in a way that the rest of us can’t see or ask a question that the rest of us wouldn’t ask.

Would I do the same things if I were building teams of people plus machines?  For example, would I select multiple machine-learning systems that were written by different programming teams and that implement differing algorithms in order to gain diverse machine insights?

The Evolving Concept of “Working in Teams”

Technology changes the nature of work. It always has in one way or another. And now it is changing the nature of what we mean by “working in teams.”

We are in a new era where many human workers have, or soon will have, cognitive co-workers (i.e., machine learning applications).  This pairing of person and technology creates a human-technology team that will work problems together.  The effect that such teaming has on the human team member is something to be studied.

Beyond that, there will also be teams of such teams, i.e., my cognitive co-worker and I will work with your cognitive co-worker and you to achieve mutual goals.  Is there anything to that dynamic that might create teamwork challenges?

It’s something to think about.

 

 

Good Book – “Complexity: A Guided Tour” by Melanie Mitchell

For any of my students looking for an introduction to “complexity,” I recommend Complexity – A Guided Tour by systems scientist Melanie Mitchell.  I pulled it off my shelf this morning to re-read Chapter 19, “The Past and Future of the Sciences of Complexity.”

Dr. Mitchell’s Ph.D. advisor was Dr. Douglas Hofstadter, author of the Pulitzer Prize-winning classic Godel, Escher, and Bach: An Eternal Golden Braid.  For a thought-provoking interview with Dr. Hofstadter, see the following interview in The Atlantic magazine:

https://www.theatlantic.com/magazine/archive/2013/11/the-man-who-would-teach-machines-to-think/309529/