Rapid advancements in the field of artificial intelligence (AI) are uniquely poised to transform entire occupations and industries, changing the way work will be done in the future. It is imperative to understand the extent and nature of the changes so that we can prepare today for the jobs of tomorrow. New empirical work from the MIT-IBM Watson AI Lab uncovers how jobs will transform as AI and new technologies continue to scale across business and industries. We created a novel dataset using machine learning techniques on 170 million U.S. job postings. The dataset and research, The Future of Work: How New Technologies Are Transforming Tasks, allow us to extract key insights into how AI is shaping the future of work.
AI and machine learning are already changing the way that businesses operate. In the financial services sector, the technology is being used in everything from customer service to credit decisioning to fighting fraud. Earlier this year research from IHS Markit warned that banks piling into AI could spell tens of millions of job losses but the new IBM report suggests this is mistaken. The MIT-IBM Watson AI Lab used machine learning to analyse 170 million online job postings in the US between 2010 and 2017, finding that task are shifting between people and machines - but the change is slow. The overall demand for tasks that make up occupations are down between 2010 and 2017.
Artificial intelligence is likely to change how every job is performed, eliminating work related to repetitive tasks but increasing the need for creative thinkers, according to a new study. These findings are contained in a report released this week by the MIT-IBM Watson AI Lab called "The Future of Work: How New Technologies Are Transforming Tasks." The study found signs that AI is beginning to slowly redefine the nature of tasks performed in certain jobs as automation gains ground. "As new technologies continue to scale within businesses and across industries, it is our responsibility as innovators to understand not only the business process implications, but also the societal impact," said Martin Fleming, vice president and chief economist of IBM, in a statement. "To that end, this empirical research from the MIT-IBM Watson AI Lab sheds new light on how tasks are reorganizing between people and machines as a result of AI and new technologies."
As AI is increasingly incorporated into our workplaces and daily lives, it is poised to fundamentally upend the way we live and work. Concern over this looming shift is widespread. A recent survey of 5,700 Harvard Business School alumni found that 52% of even this elite group believe the typical company will employ fewer workers three years from now. The advent of AI poses new and unique challenges for business leaders. They must continue to deliver financial performance, while simultaneously making significant investments in hiring, workforce training, and new technologies that support productivity and growth.
The recent wave of AI and automation has been argued to differ from previous General Purpose Technologies (GPTs), in that it may lead to rapid change in occupations' underlying task requirements and persistent technological unemployment. In this paper, we apply a novel methodology of dynamic task shares to a large dataset of online job postings to explore how exactly occupational task demands have changed over the past decade of AI innovation, especially across high, mid and low wage occupations. Notably, big data and AI have risen significantly among high wage occupations since 2012 and 2016, respectively. We built an ARIMA model to predict future occupational task demands and showcase several relevant examples in Healthcare, Administration, and IT. Such task demands predictions across occupations will play a pivotal role in retraining the workforce of the future.