Artificial intelligence

The term “artificial intelligence” was coined by computer scientists in the 1950s who set out to develop computers that could mimic human intelligence with skills such as reasoning, problem-solving, learning new tasks and communicating using natural language. Since the 2010s, advances in computing technology and the availability of troves of data from the internet have led to significant advances in artificial intelligence, particularly machine learning, which uses algorithms to enable systems to learn and make predictions based on data.

In the world of work, there are two distinct types of application of AI technology in the workplace. The first is directed at automating tasks that workers perform. When AI is used to automate tasks, it doesn’t necessarily lead to redundancies, as the technology can also complement human labour when certain tasks are automated. Whether technological adoption leads to automation (job loss) or augmentation (job complementarity) depends on the centrality of the automated task to the occupation, how the technology is integrated into work processes and management’s desire to retain humans to perform or oversee some of the tasks, despite automation’s potential.

The second is to use AI-based analytics and algorithms for management functions: hiring, monitoring, supervising, and training workers, as well as scheduling hours and breaks – or what is commonly referred to as “algorithmic management”. 

Both task automation and algorithmic management have implications for job quantity (the number of jobs) and job quality, including respect for fundamental principles and rights at work.