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Job loss due to AI -- How bad is it going to be?

#artificialintelligence

Displaced workers transition to new jobs, some of which are created by automation. The government helps to facilitate this transition via investments in training and education. Increased productivity raises incomes, lowers work hours (average work time in the U.S. has fallen more than 50% since the early 1900s5), and lowers prices, creating more demand for goods and services, leading to more jobs and broader economic growth. How well do we expect this pattern to hold with AI-enabled automation in the near future, and will they replace jobs faster than they create them?


How to automate the enterprise: Your guide to getting started

ZDNet

The deluge of stories about artificial intelligence and robots has sparked a renewed interest in the capacity of machines to work better, smarter and longer than humans. Fuelled by the well-publicised examples of smart systems winning gameshows and trouncing a world-champion in the notoriously complex game of Go, many businesses are considering the potential of automation. But away from the speculation about the capabilities of near-future AI and robots, what are the practical considerations for any firm thinking of going down the automation route? The first rather obvious question for a business to ask is whether it is technically feasible to automate a particular activity, or will be in the near future, according to the consultancy McKinsey. This question shouldn't be drawn too broadly, and should focus on individual aspects of a person's role rather than their job in its entirety.


Automation and anxiety

#artificialintelligence

SITTING IN AN office in San Francisco, Igor Barani calls up some medical scans on his screen. He is the chief executive of Enlitic, one of a host of startups applying deep learning to medicine, starting with the analysis of images such as X-rays and CT scans. It is an obvious use of the technology. Deep learning is renowned for its superhuman prowess at certain forms of image recognition; there are large sets of labelled training data to crunch; and there is tremendous potential to make health care more accurate and efficient. Dr Barani (who used to be an oncologist) points to some CT scans of a patient's lungs, taken from three different angles.


Automation and anxiety

#artificialintelligence

SITTING IN AN office in San Francisco, Igor Barani calls up some medical scans on his screen. He is the chief executive of Enlitic, one of a host of startups applying deep learning to medicine, starting with the analysis of images such as X-rays and CT scans. It is an obvious use of the technology. Deep learning is renowned for its superhuman prowess at certain forms of image recognition; there are large sets of labelled training data to crunch; and there is tremendous potential to make health care more accurate and efficient. Dr Barani (who used to be an oncologist) points to some CT scans of a patient's lungs, taken from three different angles.


Do Not Be Alarmed by Wild Predictions of Robots Taking Everyone's Jobs

Slate

In February, McKinsey Global Institute predicted that 45 million Americans--one-quarter of the workforce--would lose their jobs to automation by 2030. That was up from its 2017 estimate that 39 million would be automated out of work, due to the economic dislocation of COVID-19. Historically, firms tend to replace some of the workers they fire during recessions with machines. Fear of robot-driven mass unemployment has become increasingly mainstream. Andrew Yang, who is currently leading the polls for the Democratic nomination to be the next mayor of New York City, made it a pillar of his unorthodox 2020 presidential campaign.