In the 1990s John Koza, a professor at Stanford University carried out a series of experiments involving new ways to create electrical circuits. He designed a programme which created thousands of random circuit designs. These were measured against desired outcomes. Most were terrible and were eliminated. Those closest to a solution were combined and rerun. This process was repeated many times with the poor performers being eliminated at each stage.

The real threat is much more obvious and interesting. We've all heard the prophetic apocalyptic predictions for AI's future. Elon Musk has said that it's our "biggest existential threat" and has likened it to "summoning the demon." Other great minds are similarly vocal about their fears. The late Stephen Hawking said that AI could wipe out human race.

The Personal Computer and the Internet have, without a doubt, revolutionized business in the last 25 years. For most of us, it's now impossible to think of the business world without all of the technology and the services built on top of these two innovations. Yet, what if these innovations are just teaser of what is to come in the next couple of decades? While it's certainly true that innovation isn't always a purely positive force, technological innovation has still been the biggest factor in driving long-term economic growth and improving the quality of life since the dawn of mankind. The agricultural and industrial revolutions, as well as the adoption of electricity have clearly been huge drivers of productivity for our society.

Biomedical AIntrepreneurship describes the practice of creating AI products and services to solve bioscience (drugs and devices) and clinical problems. As such, it is the pursuit of opportunity under conditions of uncertainty with the goal of creating user defined value through the design, development and deployment of biomedical innovations that use a predominantly AI backbone, platform or foundation that have a VAST business model. It is a subsegment of digital health products and services. The use of AI in medicine is evolving rapidly. Management of chronic diseases – Companies are using machine learning to monitor patients using sensors and to automate the delivery of treatment using connected mobile apps (Example: Diabetes and automated insulin delivery).

When IBM first debuted its Watson system on the game show Jeopardy! in 2011, it was like something out of science fiction. Here was a computer that could not only understand spoken questions, but answer them faster and more accurately than the best human players. Nobody had ever seen anything even remotely like it before. Today, less than a decade later, artificial intelligence has been transformed from the incredible to something approaching the mundane. Not only do we have capabilities that are similar to the original Watson system on our phones, we can access top-notch resources from a number of companies, often for free.

The greatest unfair competitive advantage for your small business is leveraging this critical shift in how you view the drivers of the future. As I was growing up I'd often quip that my grandmother, who had been born at the start of the 20th Century in a Greek village and lived to nearly the age of 100, saw more change in her lifetime than I'd ever possibly see. Turns out I couldn't have been more wrong because my future math was a few exponents short. A recent webcast (below) by Peter Diamandis and Ray Kurzweil (co-founders of Singularity University) drove that point home and provided insight into how the future will be even more radically disruptive than anything we've already experienced and more so that what we can today predict. I've followed Peter and Ray for many years now and their ability to capture our imagination and stretch our minds is extraordinary.

If you've been following the work of Boston Dynamics (currently owned by Softbank) you've probably seen some of their four legged and wheeled robots which are able to navigate all sorts of obstacles and remain standing after being kicked, shoved, and pushed. While some of these robots, such as their BigDog, WildCat, and Spot appear to have an amazing ability to mimic an animal's gait. However, last year they introduced a two-legged anthropomorphic robot called Atlas, which was based on a more primitive biped called Petman. When I first saw Atlas I was impressed by its (his?) ability to perform some basic human-like tasks, such as picking up objects and resisting a human's attempts to knock it over. Still, it most often looked as though it would have a tough time passing a field sobriety test when it attempted to traverse even moderately rough terrain.

At Siemens ConneCTs 2018 I had the opportunity to sit down with Dr. Norbert Gaus, Head of R&D in Digitalization and Automation, and Barbara Humpton, Chief Executive Officer of Siemens USA and one of the topics of conversation that emerged was a collision of different insights and aspects surrounding the future of work. A couple of topics that come up quite frequently in relation to the future of work is whether or not the younger generations have the same work ethic as previous generations (Baby Boomers and Greatest Generation) and whether or innovation requires organizations to become more open. Dr. Nortbert Gaus doesn't think the work ethic of the new generation is lower than ours, but their expectations of work are different (the environment). Changing expectations will force employers to re-think how they engage with their workforce, build their work spaces, and structure teams, time schedules and compensation plans. "The ideal characteristics for future employees are curiosity and initiative."

Recently I had the opportunity to attend Siemens ConneCTs 2018 in Princeton, New Jersey, an event billed as a science fair for adults with a theme this year of AI & the Rise of Autonomous Systems. Dr. Kurt Bettenhausen, the Senior Vice President of Corporate Technology for Siemens US, opened the event and introduced a future of manufacturing automation challenge they were embarking upon with Princeton University. At the core of the challenge is a pair of robot arms developed by researchers at Siemens that, with the help of artificial intelligence and machine learning, can manufacture products without having to be programmed. The robot's arms autonomously divide tasks and work together as one and have the ability to detect when the work product has shifted out of the expected position and to adjust the performance of subsequent manufacturing steps. To help advance the research and the technology towards increased capabilities and commercial application, Siemens has tasked Princeton with a test case that's a little more fun than your typical proof of concept.

Every discussion about artificial intelligence seems to alternate between utopia and dystopia. Some believe that the productivity unleashed through automation will lift up all of society, creating a world of superabundance and more meaningful work, while others see robots taking our jobs and an acceleration of trends favoring capital over labor. In fact, in an article in Harvard Business Review, Accenture's Mark Knickrehm describes five distinct schools of thought, ranging from both extremes to various shades of gray in between. He suggests that leaders need to reinvent operating models, redefine jobs and include employees in the process of transformation. Yet that's easier said than done.