WASHINGTON - The use of robots in U.S. manufacturing has more than tripled over the two decades, and has doubled in the rest of the world, replacing certain categories of worker, according to a report published Monday. As of 2017, automation in the United States had risen to 1.8 robots for every 1,000 workers from just 0.5 recorded 22 years earlier, according to research by the Federal Reserve Bank of St. Louis. The report found the highest prevalence of robots in the auto sector, with France in the lead, followed by the United States and Germany. Automation has eroded the number of intermediate "middle-skill" occupations, while the share of high-skill and low-skill positions has grown, it said. France leads the way in employing robots to build cars, using 148 robots for every 1,000 workers, compared to 136 in the United States, while Italy and Germany each use about 120, the study found.
Amazon announced last week that it will spend $700 million to train about 100,000 workers in the US by 2025, helping them move into more highly skilled jobs. The New York Times observed that with this program Amazon is acknowledging that "advances in automation technology will handle many tasks now done by people." The number of jobs which AI and machines will displace in the future has been the subject of numerous studies and surveys and op-eds and policy papers since 2013, when a pair of Oxford academics, Carl Benedikt Frey and Michael Osborne, estimated that 47% of American jobs are at high risk of automation by the mid-2030s. McKinsey Global Institute: between 40 million and 160 million women worldwide may need to transition between occupations by 2030, often into higher-skilled roles. Clerical work, done by secretaries, schedulers and bookkeepers, is an area especially susceptible to automation, and 72% of those jobs in advanced economies are held by women.
Apple Park, the corporate HQ of Apple Inc., located in California. Digitalization is evolving from an economic challenge to a governance and political problem. Some studies suggest that by 2030, Artificial Intelligence (AI) might contribute up to EUR 13.33 trillion to the global economy (more than the current output of China and India combined). The essence of the political conflict that raises the issue of global governance is what type of actor (a state or a digital corporation) will lead this process, creating global asymmetry in terms of trade, information flows, social structures and political power. This means challenging the international system as we know it.
What are the differences between econometrics, statistics, and machine learning? I discovered this myself a couple years ago, through an analysis of the economics literature that required the research team to classify articles into economics fields (like labor and macro) and research styles (like theory and econometrics). The project was motivated by frustration with complaints lodged against academic economics in the wake of the Great Recession (perhaps you've seen the movie version: Inside Job). I thought: "What's with all the whining? "Economics has never been better!"
One of the biggest impacts may be on jobs, not only on the nature of work itself, but on the availability of work. Some crystal ball gazers are predicting that AI (working in concert with its older sibling, automation) will trigger massive job losses; others see AI producing a net gain in employment . Both views can be supported both logically and empirically; but they both can't be right. As Andy Kessler put it in a June 17 Wall Street Journal column, "The future happens, just not the way most people think." Kessler then walked readers through a shopping list of past predictions that turned out to be way off the mark: "megamistakes," he called them.
Artificial intelligence (AI) is set to play a key role in the future of financial services and more broadly in what UBS and the World Economic Forum refer to as the "Fourth Industrial Revolution." The global economy is on the cusp of profound changes driven by "extreme automation" and "extreme connectivity." In this changing economic landscape, AI is expected to be a pervasive feature, allowing to automate some of the skills that formerly only humans possessed. In the financial services industry in particular, there has been a lot of noise around the potential of AI and data supports that investors are excited about the impact the technology could have across the industry. VC-backed fintech AI companies raised approximately US$2.22 billion in funding in 2018, nearly twice as much as 2017's record.
The use of artificial intelligence (AI), cognitive technologies, and robotics to automate and augment work is on the rise, prompting the redesign of jobs in a growing number of domains. The jobs of today are more machine-powered and data-driven than in the past, and they also require more human skills in problem-solving, communication, interpretation, and design. As machines take over repeatable tasks and the work people do becomes less routine, many jobs will rapidly evolve into what we call "superjobs"--the newest job category that changes the landscape of how organizations think about work. During the last few years, many have been alarmed by studies predicting that AI and robotics will do away with jobs. In 2019, this topic remains very much a concern among our Global Human Capital Trends survey respondents.
A key strength of NLP (natural language processing) is being able to process large amounts of texts and then summarise them to extract meaningful insights. In this example, a selection of economic bulletins in PDF format from 2018 to 2019 are analysed in order to gauge economic sentiment. The bulletins in question are sourced from the European Central Bank website. As a disclaimer, the below examples are used solely to illustrate the use of natural language processing techniques for educational purposes. This is not intended as a formal economic summary in any business context.
I've been thinking a lot recently about the many ways in which artificial intelligence may change our lives. One of the biggest impacts may be on jobs, not only on the nature of work itself, but on the availability of work. Some crystal ball gazers are predicting that AI (working in concert with its older sibling, automation) will trigger massive job losses; others see AI producing a net gain in employment. Both views can be supported both logically and empirically; but they both can't be right. As Andy Kessler put it in a June 17 Wall Street Journal column, "The future happens, just not the way most people think."
Robots helped build your car and pack your latest online shopping order. A chatbot might help you figure out your credit card balance. A computer program might scan and process your resume when you apply for work. What will work in America look like a decade for now? A team of economists at the McKinsey Global Institute set off to figure out in a new report out Thursday.