Fast Future Research provides a glimpse into possible futures through a series of recently published books that focus on our Our Emerging Future and accelerate our learning and dialog. As with his previous books, Rohit Talwar enlists several authors in a new book just launched titled A Very Human future. An abstract for the book reads as follows:
A popular question these days is: Will a robot take my job? That question is as popular as: what should my child study in school? At the heart of both questions is the fear that we as a society will automate anything that can be automated. This website may help bring some clarity – at least in the context of automation risk level. It’s very quick, simply enter your job and an automation risk level expressed as a percentage will be returned.
Ultimately, these questions are difficult to answer, as we cannot predict the jobs of the future – and required skill levels could be a moving target. The progression of automation can be viewed on a spectrum from augmenting humans to fully conscious machines. There are arguments being made on both ends of this spectrum – time will tell.
In late 2016, having just finished reading The Rise and Fall of American Growth, I was thinking about an underlying theme of the book – the views of techno-optimists versus those of techno-pessimist. In the context of the books narrative, the techno-optimist believes that future innovations will indeed drive a resurgence of growth – albeit at the expense of jobs. The pessimist sees no return to growth and believes our best innovations are behind us. Two years ago, I posed a question via a Post: Are you a techno-optimist or techno-pessimist?
The brain is clearly one of the next great frontiers. In this World Economic Forum Article on reading minds, we get a glimpse into the exponential progression of brain science. The author cites research published by AI experts in China, the US and Japan showing that computers can replicate what people are thinking by using functional magnetic resonance imaging (fMRI) machines that measure brain activity – linked to deep neural networks that replicate human brain functions.
In their now popular book on The Second Machine Age Andrew McAfee and Eric Brynjolfsson describe one of the forces behind our accelerating pace. This force could be key to understanding the dynamics of our environment; the number of potentially valuable building blocks is exploding around the world, and the possibilities are multiplying like never before.
The illiterate of the 21st century will not be those that can’t read or write, but those who cannot learn, unlearn, and relearn – Alvin Tofler, Rethinking the Future.
As we all become life long learners, unlearning could be our biggest challenge. Our mental models prevent us from seeing the need for change. We are creatures of the only world we have individually known. Even if you are one hundred years old, the mental models established after humanities second Tipping Point dominate your thinking. They form our intuitions and belief systems.
Yesterday on Coffee Break with Game Changers, Bonnie D. Graham hosted a show focused on designing the future of humanity. You can listen to the rebroadcast here. The session abstract is included below. The show participants included: Bonnie, Masha Krol, Ian Gertler, Maricel Cabahug and myself.
In her opening monologue, Bonnie said:
The first impact of AI will be that more and more non-designers develop their creativity and social intelligence skills to bolster their employability – in the future, everyone will be a designer
With all the talk of AI and its potential negative impact on humanity, we lose sight of the positive. As an engine for augmentation, artificial intelligence is likely to advance our human potential. The effectiveness of what we do stands to improve – whether its creativity and design, or oriented in analytics. Some would prefer to call it “Augmented Intelligence” versus artificial intelligence. If we view the progression of AI on a spectrum, we could indeed reach the place of augmentation and never approach the other end of the spectrum. This lies at the heart of the artificial intelligence debate.