As the coronavirus has swept across the globe, the swathes of redundancies that have followed in its wake have relegated the "robots are taking our jobs" narrative into the background. It was a narrative with a somewhat mixed logic at the best of times. For instance, research from the London School of Economics (LSE) found that the introduction of industrial robots has actually increased wages for employees while also increasing the number of job opportunities for highly skilled people. The researchers conducted a comprehensive analysis of the economic impact of industrial robots over 17 countries between 1993 and 2007 across 14 different industries. The period of analysis corresponded with a huge rise in the use of industrial robots, with the price of such machinery also falling by approximately 80%.

This is part 2 of a three-part series examining the effects of robots and automation on employment, based on new research from economist and Institute Professor Daron Acemoglu. Overall, adding robots to manufacturing reduces jobs -- by more than three per robot, in fact. But a new study co-authored by an MIT professor reveals an important pattern: Firms that move quickly to use robots tend to add workers to their payroll, while industry job losses are more concentrated in firms that make this change more slowly. The study, by MIT economist Daron Acemoglu, examines the introduction of robots to French manufacturing in recent decades, illuminating the business dynamics and labor implications in granular detail. "When you look at use of robots at the firm level, it is really interesting because there is an additional dimension," says Acemoglu.

Recent surveys, studies, forecasts and other quantitative assessments of the progress of AI highlighted US consumers' interest in AI working alongside their physicians, the current porn-heavy state of deepfakes, the potential business benefits of Robotic Process Automation (RPA), and the impact of automation on incomes and employment. The internet is home to at least 14,678 deepfakes, according to a new report by DeepTrace. Funds run by computers that follow rules set by humans account for 35% of America's stockmarket, 60% of institutional equity assets and 60% of trading activity. Exchange-traded funds (etfs) and mutual funds automatically track indices of shares and bonds--in September 2019 these vehicles had $4.3trn invested in American equities, exceeding the sums actively run by humans for the first time [The Economist] Only 16% expect to reduce training budgets; 52% of the U.S. employees surveyed believe they have the necessary skills to be successful in an AI-enabled workplace, 20% saying they do not possess the right skills, and 28% reporting they aren't sure; 25% of employers and 20% of employees see a definite gap in workers' skills; 63% of U.S. employees expressed willingness to use a virtual or digital assistant to help them self-manage tasks and deadlines [Genesys surveys of 303 employers and 1,001 employees] Only 29% of finance departments that have deployed Robotic Process Automation (RPA) have utilized the technology for financial reporting; the average amount of avoidable rework in accounting departments can take up to 30% of a full-time employee's overall time. The first comprehensive review of studies published since 2012 comparing analysis of medical images by healthcare professionals and deep learning systems found humans and machines are on a par.

Robots are taking wages from American workers. A new study from the Federal Reserve Bank has found that the portion of national income give to human employees has dramatically decreased as automation continues to increase. The study suggests that employees that employees feel they have lost their bargaining power when it comes to asking for a raise out of fear they may be replaced by a robot. A new study from the Federal Reserve Bank has found that the portion of national income has dramatically decreased as automation continues to increase. 'Businesses have more options to automate hard-to-fill positions now than in the past,' the study authors write.

This has given rise to an extreme theory that either AI or robots will replace humans in many jobs, pushing the unemployment rate close to 50 percent. Although the jobless rate reaching 50 percent may be an exaggeration, it appears all but certain that the rate of technological unemployment -- loss of employment caused by technological progress -- will reach 10 to 20 percent. This means that unless some steps are taken, the Fourth Industrial Revolution driven by AI, the "internet of things" and big data will lead the human race to a dystopia rather than to a utopia. What measures could be taken to lead us to an utopia instead? Gross domestic product, the total value of income earned in a country over a given period of time, is distributed to capital and labor.

I'm skeptical of arguments that technology will have severe detrimental effects on employment for many reasons. But one reason is this: If artificial intelligence (AI) turns out to be as powerful as the worriers say, won't it be good at finding new nonobvious tasks for humans and also training them for these new occupations? An artificial Intelligence project utilizing a humanoid robot from French company Aldebaran and reprogramed for their specific campus makes its debut as an assistant for students attending Palomar College in San Marcos, California, REUTERS. Long before we cross such a science fiction threshold, however, we are beginning to see how technology will improve employment opportunities. For example, in the latest in a long series of reports on the topic,Michael Mandel shows yet again how technology usually helps workers.

These changes are called "Industry 4.0" or the fourth industrial revolution. It is an industrial revolution that uses artificial intelligence and robots in such a way that manufacturing plants will become unmanned and a majority of office jobs will be made unnecessary. In March, an AI player of the board game go, developed by Google and named AlphaGo, defeated the world's leading professional go player 4 games to 1. The pro lost the first three games, and although he won the fourth, he was defeated in the fifth round. The decisive factor that led to the victory for AlphaGo was its "deep learning" capability.