AI from its beginning has been plagued with duality. Success in AI has always been accompanied by increased responsibility, social responsibilities, educational challenges and impact that decision makers and the general public vaguely understand. Considerable progress has been made in understanding the how and what of AI, including common modes of reasoning. Research shows, that combinations of deductive, case based, inductive, uncertainty, and default reasoning are just a few of the aspects of intelligence that need to be incorporated into successful AI systems. The duality between the role of humans in the universe and what role machines will play is only beginning to play out. AI offers humans benefits, including less boring repetitive workplaces, safer manufacturing, better travel, increased security, and smarter decisions that may help preserve a volatile habitat (Buchanan, 2006). Since the beginning, AI has been concerned with creating intelligent machines that formalize reasoning and understanding in all areas of the human experience. The direction has always been toward formalizing knowledge in a way that makes working with computers easier and more helpful. The impact of AI on living has the potential to meet and or exceed the impact of any prior technologies. Exploring psychology, reasoning, decision science and behavior puts AI in the position to solve intellectual problems, control robot motions, interpret human language, learn new skills and acquire knowledge by continually analyzing data.
Both AI and ML are terms that ascribe to a variety of meanings. The near-term future indicates that a technology that has been coming for decades and has finally tipped, will continue to grow. Fueled by the very familiar Moore’s Law, which states that the capacity of computer chips will double every year while the costs decrease by half, along with new innovations such as quantum computing, assures the continued exploration and integration of AI and ML in many workplaces.
Fueled by rapid expansion in computing power, the IBM 360/75, the mainframe computer of its day, in 1969 helped to land our first astronauts on the moon. It had 6 megabytes of computing power. Today that equates to 10% of the computing power needed for the game Candy Crush. On the factory floor, robots are likely to replace humans in redundant tasks and repetitive jobs. This relative fast grow in an expansion of power has led to the factory floor being populated by robots and not just at Tesla. Apples’ supplier Foxconn replaced 60,000 workers in a factory in China with robots in 2017. Amazon continues to rollout robot staffed warehouse and distribution centers and most of the shipping from ports like Los Angeles to Baltimore is now conducted by robots. Even law enforcement has gone robotic. Knightscope security robots patrol the parking lot, while high speed bots, like the Cheetah, chase down criminals at speed in excess of 28 MPH. Robots are building houses, aiding the military, delivering pizza and making meals at McDonalds. They are helping to drive cars and soon trucks, play music and turn lights off and on.
Smart chabots and vocally activated technologies are everywhere. Some good, some not so good but always more prevalent and getting better. These devices are helping hire babysitters and acting as lawyers. They are and will continue to take the jobs they can take. They pretend a massive impact on jobs, the workplace and employment. Although they offer the potential of opening up new positions and roles, what and how this will all play out has yet to be determined. Undoubtable there will be upheaval and redefinition of workplace performance. Certainly, it is the agile workplace that will have the best chance of surviving and thriving into the future (Hirsch, 2017).