The subtlety and complexity of human brain is reflected in the vast range of reactions that we exhibit in response to emotional and intellectual stimuli. Scientists and thinkers, who have come up with myriad ground-breaking discoveries in the past, have skillfully tapped into the vast power of inter-connected neural networks in their brains, which seem to be otherwise unattainable achievements.
However, waves of technological advancements and innovation have led to the emergence of what can be termed as “End of Work”( term coined by US economist Jeremy Rifkin in 1995) scenario. Indirectly, it means that a vast number of people aross the world can become unemployed, thanks to the overwhelming force of automation, which has begun to outperform manual labor in a number of tasks, thereby resulting in labor displacement. Although the risk is offset by growth in productivity through capital accumulation and creation of new jobs, the fact that automation can improve the speed , quality and cost of available goods and services across many domains, makes it an obvious alternative for human work.
In the context of 21st century, at the heart of automation, lie two path breaking technologies by the name of Artificial Intelligence and Machine Learning. Although there are key differences between the two terms, the actual relationship between them is more of complementation. Simply put, artificial intelligence can provide a machine with an ability to learn through various experiences from multiple task executions. These experiences train a machine to learn from various kinds of inputs and maximize its performance on a task, thereby enriching its knowledge base. Artificial intelligence, demonstrated through machine learning, has the ability to dramatically improve our world, in terms of simplifying or even handling complex tasks.
Automatable tasks such as those related to transportation, data processing and collection and back-office work, have already started witnessing skills on artificial intelligence, being brought to the table. The potential of artificial intelligence and machine learning in driving in driving a change in the socio-economic system, has been exhibited in the from of some path-breaking innovations such as autonomous vehicles, computer-aided material design systems, robots and other devices that run on artificial intelligence (AI) enabled softwares designed to provide effective solutions for various concerns.
The impact of AI differs across sectors, with certain tasks and roles being more prone to automation, as compared to others. Given the complex interplay of commercial, social and legal factors that determine the nature and extent of impact of AI, the likelihood of tasks offering wide scope for improved outcomes under a certain set of conditions , increases.
While adoption of AI has emerged as one of the most overwhelming forces driving societal change, there are different perspectives with respect to the nature of occupations that come under the umbrella of automation by AI. While a general idea exists that routine tasks performed in highly structured and predictable environments can be easily moved to an AI enabled execution platform, a recent incident of a news article being created a machine leaning algorithm without human guidance, compels experts to look into more that AI can offer. The change enabled by the adoption of AI in industrial services can be defined as a sequence of events, starts off with displacement of work-force and dampening of wage growth for less educated workers. Eventually, this culminates into a certain proportion of work getting displaced by automation and emergence of new job oppurtunities which demand expertise in tasks such as data analysis and interpretation ans sound working knowledge of machine learning tools. These experts include data scientists, machine learning enginners and research scientists. The competencies on data analysis and interpretation software are of great value in development of business intelligence.
Apart from bringing to the table, benefits of learning from newly created job roles, AI also promotes employee engagement in organizations, thereby making them rise meteorically in their workplaces. Communication in the corporate landscape can be analyzed using AI driven softwares, which enable companies to identify behavioural cues that give an insight into employee efficiency, work satisfaction ndex and their ability to work in teams. Overall, this gives an understanding of the employee communication in real-time, which also brings forth missing links that need to be sorted out, in order to boost the productivity of employee and organization.
While a certain group of experts seems to be increduluous about the impact of automation technologies on employment, other experts have their brows knitted in concern for the displaced workers, who deserve to receive assistance for their healthcare and education, even if they are unemployed. With increasing competition for non-routine manual labour coming into picture due to workforce displacement , AI enabled technologies are introducing a work culture, which is characterized by less secure and legally uncertain jobs. However, on the contrary, looking at the way humans are outperformed by AI based working models in many aspects of productivity, one cannot overlook the response of employment and economy to technology enabled automation. Additionally, with changes in working-earning patterns and shifts in income distribution across demographics coming into force, its hard to be oblivious to the impact that AI is creating on the global economy.
However, the impacts of AI and automation differ across countries, with certain regions facing specific type of effect as compared to others. While many studies have been conducted to study the nature of this impact, one expectation seems to be common among all of them. They definitely foresee a future equipped with capabilities offered by artificial intelligence , with the likelihood of it becoming an indispensable functional tool in the lives of people. Tech-giants like Microsoft have already started conducting training programs in AI and cloud technologies for students from across the country. A recce is also being done on the ethical implications of using AI, by institutes like TUM (Technical University of Munich). Therefore, one is most likely to witness fair, transparent and powerful technologies under the umbrella of AI and automation, in the near future.