I recently added a fascinating book titled Technology Trap to my Book Library. Author Carl Benedikt Frey has done some important work in partnership with Michael A. Osborne evaluating the impact of automation on the Future of Work. In this new work of applied history, Frey draws on past revolutions to look at possible corollaries. It was Winston Churchill that said: The further Backward you Look, the Further Forward you can See. That quote has stuck with me, prompting my Looking back to see Ahead. Here is the book abstract:
This Recent Article is the result of a collaborative effort between TCS and the Clayton Christensen Institute. The article examines the strategic choices faced by various players in the emerging Mobility Ecosystem – viewed through the lens of the Theory of Disruptive Innovation. It outlines the best course of action for achieving long-term profitability in the ride-hailing market.
As with any future scenario, the variables that must be considered in determining the path of the scenario can be overwhelming – There is Peril in Predicting. However, inaction is not an option. Strategic choices must be explored.
Maurice Conti is the Chief Innovation Officer at Alpha focused on what he calls the Augmented Age. He talks about it this way: We’re heading for a future where our natural human capabilities are going to be radically augmented in three ways: Computational systems will help us think. Robotic systems will help us make. And a digital nervous system will connect us to the world far beyond what our natural nervous system can offer.
Take a look at the picture above. Can you guess what it is? It is an example of what you get when a design tool intersects with the augmented age. Take a look at the short Ted Talk below for the answer.
I recently ran into a TCS colleague at a forum in which I presented. Ryan Metz is a Data Scientist working at our Cornell Innovation Lab. Ryan mentioned an Article he had written about the short term impact of AI – versus the long term concerns voiced by the likes of Elon Musk and Stephen Hawking. As he states in the article, the long term concern is that we will produce machines so intelligent that we lose control over them. They will become a new form of life that rules over us as we do the the animal kingdom.
In the article, Ryan uses story telling to articulate the short term impacts of artificial intelligence – a very effective way to raise awareness. The key message: The technology that already exists, or is about to exist, is dangerous enough on its own. Ryan focuses on two artificial neural networks (algorithms modeled after a rough approximation of how groups of neurons in your brain operate): Generative Adversarial Networks (GANs) and Recurrent Neural Networks (RNNs). A quick example of each from the article: