For the marketplace to blossom, India needs a future-ready workforce. According to the World Economic Forum, 85% of 2030’s jobs do not exist today. We need to change the way we teach in schools, focusing on “why” instead of “what”. For instance, a 14-year-old girl at the tinkering lab in Delhi had built a prototype of “Lord Ganesha” who offered blessings and prasāda using motion sensors.
In colleges and vocational training institutes, we need to create a stronger connection with industry, to manage the unemployability challenge that many Indian graduates face. We live in times of tectonic change. The curriculum that incoming college students are introduced to, may become irrelevant by the time they graduate. This can be deeply unsettling, and we need to arm our students with emotional resilience. Unfortunately, no university in the world has a course that teaches AI and emotional resilience. Maybe India can take leadership in creating such a course. It will be much needed at a time when the media constantly reports that robots are coming for our jobs.
CUSTOMISED MASS PRODUCTION
A newly emerging trend is the increasing demand of consumers for customized, tailor-made, and individualized products. Such trends are reflected, among others, in the growth of the craft and artisan economy or the rising demand for luxury goods, e.g. in the high price segments of car, watches, or textile industries. Large firms respond to this growing demand for customization by developing a “hybrid” production process of “customized” mass production. Mobile robots are used to perform a variety of tasks as opposed to the large, industrial robots which perform the same tasks repeatedly (Winfrey, 2014). Low-cost collaborative robots are a boon to small and medium-sized companies that compete with firms from low-cost markets. Collaborative robots augment human tasks and allow workers to increase productivity by focusing on the more sophisticated non-routine tasks. For example, Mercedes factories are replacing heavy industrial robots with smaller and flexible robots (e.g. producing the Class S 2018, the most expensive model), and BMW and Audi are testing lightweight, sensor-equipped robots to respond to the demand for individualized cars. Since “the flexibility and dexterity of human workers are reclaiming space on Mercedes’ assembly lines”, new and more sophisticated jobs in middle occupations are created (Behrwald and Rauwald, 2016).
Automation will enhance the sophistication of mass production systems in the industry, agriculture, and the service sector. Such systems are enabled by IoT or the Internet of Things. IoT advantages lie in the low costs to generate, transfer and analyze high quantities of data, which firms can collect in real-time and communicate to a network of computers for analysis and coordination of activities and flow of goods, cash, and information.In manufacturing, many countries launched initiatives to develop Industry 4.0 in Germany, advanced manufacturing in the US, or Usine/Industrie de la Future in France. The goal is to increase productivity by automating the full value chain in manufacturing and integrating autonomous robots and computers into a data network that connects companies, departments, and functions.
Skills requirements for Industries 4.0 are more interdisciplinary than those for basic digital literacy. Industries 4.0 creates new operational and organizational structures relying on decision making, coordination, control, and support services, a much more complex environment. There is also a need to coordinate between virtual and real machines and plants in production management systems. Employment will decrease in occupations comprising tasks that can be automated and will increase in occupations where human labor is complementary to robots. The balance between substitution and complementarity effects depends on the robots’ field of applications, with employment falling in some areas and growing in others. Robots can substitute for low value, routine tasks and increase the value of those skills necessary to the performance of more “abstract” tasks
RESKILLING IS THE ANSWER
Each job loss due to automation will lead to five new jobs, requiring different skill sets. Re-skilling is challenging, but it is possible, with a combination of a national mentoring program, decentralized content-delivery mechanisms, and community-based learning models. Last, but by no means least, is the issue of ethics. Consider the driverless car conundrum explained beautifully by the MIT Moral Machine. If a driverless car meets with an accident and has a choice between killing two passengers or five pedestrians, what should it do? This is a difficult question. Most people answer that the car should kill the two passengers, as long as they are not one of them. Exploring the contours of debates like this requires our artists, philosophers, lawyers, activists, politicians, technologists, and business leaders to come together. As the saying goes, technology is far too important to be left to the technologists alone.
In conclusion, the key to excel for humans, later on, will be versatility. We being homo sapiens are comfortable with changes in their environmental factors. We are fit for transformation; more than we might suspect we truly are. We have vital, natural social abilities, robots don’t have. Hence focusing more on the cognitive, behavioral, and emotional domains will no doubt provide an edge. It is also essential to discover and cultivate new financial ways to deal with these issues to manage the impending difficulties machines will foist on our general public.