AI's Promise -- Augmenting Human Creativity


         I am convinced that I am an artificial intelligence alarmist for the same reason that I like dystopian and apocalyptic literature. What I don’t understand is why the secret hope for catastrophe. The current pandemic has certainly called my bluff. Be careful what you wish for, I suppose.

         So when a good friend recommended that I read a book on artificial intelligence by the Chief Technology Officer at Microsoft, I readily agreed.

         Kevin Scott’s “Reprogramming The American Dream: From Rural America to Silicon Valley – Making AI Serve Us All” is an odd and hopeful book. Scott’s a rural boy, from West Virginia, who fell in love with computers and found his way to Microsoft, where, apparently, he has the freedom to direct policy and research goals for the software giant. The book is part biography, part walking tour, as he revisits boyhood haunts to see what artificial intelligence can do to improve the lives of folks in rural communities.

         It’s no mystery that the book’s forward is written by J.V. Vance, author of the wildly popular “Hillbilly Elegy.” Both men share a love and deep commitment to what coastal dwellers refer to as “flyover” country, the vast interior of the United States that has been transformed generally for the worse as a result of changes in the technology and manufacturing.

         Scott doesn’t write in the vein of Elon Musk, who regards artificial intelligence as an existential threat to humankind. You won’t find dark foreboding about Hal’s progeny taking control, or Skynet terminators seeking to destroy pesky humans. In fact, Scott doesn’t discuss whether, and if so when, artificial intelligence might reach the point of superintelligence, exceeding the powers of humankind. The distant future doesn’t concern him, at least not in this book.

         But I’ve assumed in this review that you know what I mean when I refer to artificial intelligence. As I take understand Scott, artificial intelligence is a form of machine learning, the ability to program a device to perform tasks more efficiently and reliably than humans. It’s not mere automation, mind you, but the ability of a machine to process data, lots of data – “big data” – in order to find relationships between variables that permit the machine to discover new ways of doing things.

         As Scott reminds us, artificial intelligence, the machines doing the learning, don’t replace us. Left to their own devices the machines would have no role. In order to find the relationships among data points necessary to do things, machines have to be programmed. The machine has to be taught what to look for – purposed, if you will – to do anything of value.

         Machines don’t replace human effort, they augment human creativity, performing the simpler tasks of which we are capable with fewer errors, freeing us from the mundane to do better and more creative things.

         Consider radiology, the interpretation of X-rays. No one is saying that interpreting a radiograph is simple. It takes years of training to learn to do that. But once the basic skills have been mastered, there are routine diagnostic interpretations that don’t tax a specialist. Freeing the specialist to look at more interesting cases, outliers, if you will, might improve radiology in general, permitting physicians to focus on finding cures for less common illnesses.

         Scott makes a convincing case.

         Oddly, Scott’s work called to mind Shoshana Zuboff’s “Age of Surveillance Capitalism,” a book about how social media harvests the metadata we leave behind each time we interact on the internet, in order to aggregate ever larger pools of data, the better to search for secret relationship among variables that yield the power to predict what we consumers will do next.

         Zuboff hammers home the point that the algorithms yielding predictive data are controlled by individuals: who decides who gets to decide what’s important, she asked.

When I first read, and understood, Zuboff, I was so infuriated I quit social media, logging off Facebook and Twitter in January 2019.

         Scott shamed me into rethinking my Luddite reaction. Ignoring social media won’t make it go away anymore than destroying machinery during the industrial revolution would stop the transformation of household manufacturing.

Who decides who decides? We do. (Or, at least, Microsoft does.) Refusing to try to harness the power of AI for the common good guarantees that someone else makes the decision.

         AI is here to stay. We can harness its potential to augment ours. Scott’s book shows how as he travels through rural communities to examine how small companies are using it to transform devastated labor markets.

         I was persuaded by his optimistic challenge. So much so, that I decided I reengage with social media and try to learn to harness it, and the AI algorithms it uses, to serve purposes I recognize as good.

         Will we ultimately lose to the machines? Will a superintelligence enslave us to a hidden Matrix? Maybe. But we ought at least to fight to make AI serve our purposes before it’s too late. Apocalypse be damned, I say; a livable future requires realistic use of the tools at hand.

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