Monday, September 21, 2015

Tipping Point(s)?

       In some ways, at least 40 or so pages in, Geoff Colvin's Humans Are Underrated: What High Achievers Know That Brilliant Machines Never Will, doesn't offer anything particularly new. The basic premise is one that has been repeated in many places by many voices over the past 20-25 years: technology is forcing changes at an incredibly accelerating rate, and humans have to adapt. I've written and spoken about it over and over and over. The cries have accelerated right along with the technology...well, honestly, behind the technology. After all, most of us have better hindsight than foresight. I'm sure the book will become more interesting once Colvin starts to address the part of the title following the colon.
       One snippet, though, did jump out and give me some pause for thought. Colvin quotes economist Tyler Cowen from a 2013 book: "But it takes more and more time for you to improve on the computer each year. And then one day...poof! ZMP for you." Colvin explains that "'ZMP' means 'zero marginal product'--the economists' term for when you add no value at all." Maybe it was the bluntness of the line; maybe it was a person being reduced to a product. Whatever the reason--and it's not absolutely logical--it made me wonder if we've reached a key tipping point or two.
       I've always contended that we remain in control of our machines. In a simple example, we can decide how tethered we remain to our machines. Do we respond to every enticing ping from the phone no matter what? But when I think about some of the work machines are now doing and likely will be doing soon, I wonder if we've ceded a much higher degree of control that we realize. Actually, I don't wonder. I know. In large part this is because, while formerly humans and machines often complemented each other, that is less often the case. Consider chess. It was considered remarkable when a computer first beat a human. Then humans and computers could pair up and play chess most effectively. Now the computer alone has the edge. Studies also chow how computers analyzing data in abstract situations often reach better conclusions when analyzed over time. That's the first tipping point.
       If that sounds rather dire, the second one is more hopeful. Yes, we still put too much emphasis on standardized testing, too much faith in packaged curricula. Yes, in some ways we've simply repackaged tired pedagogy in new technology. Still, I hear more and more tales of change. Of different models. Of more student-driven, active learning centers. Of greater focus not on providing simply answers, but on posing complex questions. Of school becoming more clearly relevant, flexible, meaningful. Of educators more aware of the need to help our students become, to play off the title, the high achievers who know what brilliant machines never will.
       We're not nearly where we need to be yet, and we have many hurdles to overcome. But finally we seem to be not only hearing the message, but also listening and responding.

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