Occupations accounting for 47 percent of all U.S. employment are at risk of computerization.\u00a0 And, according to the Oxford economists who conducted the research, this isn\u2019t decades away: it could happen over the next 10 to 20 years. So, are we finally at the point of \u201cThe Brain\u2019s Last Stand,\u201d as Newsweek declared after chess master Garry Kasparov lost to an IBM computer 20 years ago? \u00a0\n\n\nWe don\u2019t have to be. Not if leaders in business and government invest in human-centered automation, a solution that holds the potential to offer the best of both worlds \u2013 combining the efficiencies of computerization and the flexibility and creativity of skilled workers.\n\n\nTo understand the threat, consider author Nicholas Carr\u2019s warning that smart machines could de-skill work in a way that creates long-term difficulties. He points to the way in which automatic systems have replaced much of the work of airline pilots, whose role today is largely to be available in case of emergencies.\u00a0 But, as their skills deteriorate from lack of use, pilots are increasingly reacting inappropriately in emergency circumstances, doing such things as lifting a plane\u2019s nose and reducing its air speed in the event of a stall, when the correct action is to tip the craft down and gain velocity.\n\n\nBut what if we view automation not as a replacement for humans, but an opportunity to maximize human potential? As described by IBM data scientists, in the era of cognitive systems, humans and machines will \u201cneed to collaborate to produce better results, each bringing their own superior skills to the partnership. The machines will be more rational and analytic -- and, of course, possess encyclopedic memories and tremendous computational abilities. People will provide expertise, judgment, intuition, empathy, a moral compass, and human creativity.\u201d\n\n\nCarr calls for this \u201chuman-centered automation\u201d to \u201cdivide roles and responsibilities in a way that not only capitalizes on the computer\u2019s speed and precision but also keeps workers engaged, active, and alert -- in the loop rather than out of it.\u201d\n\n\nOf course, getting to the point of true human-machine collaboration is no simple task. Companies and management consultants will need to examine how job redesign and process reengineering can make full use of skilled human resources while taking advantage of the efficiencies of machine learning. Integrating AI-systems into complex professions such as medicine will involve breaking traditional tasks into simplified, discrete parts, changing the requirements for human skills and increasing human-computer interdependence. But, done right, AI-based computer medical systems will help physicians make diagnoses and identify treatment options for patients without de-skilling the medical profession.\n\n\nGiven the enormity of this challenge, public policy has an important role to play in pursuing a collaborative future.\u00a0 It might, for instance, encourage the right mix of human and digital labor that pairs humans to work with machines, instead of against them.\u00a0 In The Second Machine Age, MIT\u2019s Erik Brynjolfsson and Andrew McAfee recommend that policymakers, \u201cUse taxes, regulation, contests, grand challenges, or other incentives to try to direct technical change toward machines that augment human ability rather than substitute for it...\u201d\n\n\nThe National Science Foundation\u2019s (NSF) National Robotics Initiative is a step in this direction.\u00a0 It provides support for systems that work alongside or cooperatively with workers. According to NSF, the idea is that the next generation of robotic systems should be designed \u201cto establish a symbiotic relationship with their human partners, each leveraging their relative strengths in the planning and performance of tasks.\u201d\n\n\nNot everyone believes that government should focus on the integration of humans and machines.\u00a0 One high profile organization objected to the NSF\u2019s initiative over a concern that it \u201cprecludes opportunities to develop AI systems that could replace workers, which history has shown to produce greater economic benefits in the moderate and long run.\u201d\n\n\nBut there is plenty of evidence supporting the idea that co-robots can be more efficient. Garry Kasparov, who has continued to examine AI since his headline-making loss in the 1990s, argues that pairing humans with computers offers the opportunity to get the intuition and insight of the human and the processing power of the machine.\u00a0 In chess tournaments \u201cthe teams of human plus machine dominated even the strongest computers.\u201d\n\n\nCollaboration holds tremendous promise, enough so to justify government investment in a dedicated research initiative designed to see how far it can be developed. To be clear, this pursuit shouldn\u2019t be viewed as a humanist exercise -- the goal is to seek the genuine efficiencies. In doing so, we need to be open to the idea that, over time, collaboration will fail to outperform machines acting alone. \u00a0But at this stage, it would be dangerously short-sighted to believe that the role of humans must inevitably be diminished.