In gig-economy there is a tremendous opportunity to leverage the full potential of digital disruption including AI, Gamification, and Automation paving path to next-gen educational methods and job reorientation. Firstly, finding ways on how AI technologies could aid education methods, augment human skills in professional jobs and there by the challenges posed by AI. We commonly hear news like – an artificially intelligent computer system built by Google has just beaten the world’s best human, Lee Sedol of South Korea, at an ancient strategy game called Go. The Google program Alpha Go, actually learned the game without much human help. It started by studying a database of about 100,000 human matches, and then continued by playing against itself millions of times. As it evolved, it reprogrammed itself and improved. This self-learning program is based on a neural network, and theories of how the human brain works. Another classic example is Pearson – the world’s leading Education Company tapping IBM’s Watson as a virtual tutor for college students. With continued impact of AI on education and gig-economy, analysts are estimating a net reductions in jobs/workforce between 4% and 7% across various industries. It is simultaneously creating demand for high skilled digital workforce. Likewise AI and advance machine learning is paving new paths to education methods and future focus areas to complement and supersede machines to take full advantage of AI.
Second focus area is Gamification that has become the frontier of training, capitalizing on a new generation born into a computerized world. The idea behind the concept is to take elements of game design and logic and apply it to a work situation. One of the biggest companies to utilize gamification is McDonald’s, which introduced a new till system using a simulation game. Employees were asked to engage customers and use the till while under time restraints. Air Cargo Netherlands also used gamification when they needed to train employees on a specific utility. They created a game version of a new logistic system called Smartgate. They used the game to develop employees’ “chain thinking” and help them realize the consequences of their decisions in a risk-free environment.
Lastly, driving the automation agenda leveraging advances in robotics, artificial intelligence, and machine learning as machines match or outperform human performance in a range of work activities, including ones requiring cognitive capabilities. Examples include guiding customer service representatives to more quickly resolve customer problems and anticipate future purchases, quickly and securely reconciling mass overnight transactions for financial institutions, or giving time back to HR professionals by managing the time consuming on-boarding processes for new hires. Technical, economic, and social factors will determine the pace and extent of automation. Continued technical progress, for example in areas such as natural language processing, is a key factor. Beyond technical feasibility, the cost of technology, competition with labor including skills and supply and demand dynamics, performance benefits including and beyond labor cost savings, and social and regulatory acceptance will affect the pace and scope of automation. Hence the next-gen education should focus on learning futuristic competencies with an aim to complement realizing full potential of automation.