Preparing the Global Workforce for AI Disruption


Within the next decade, the world will see a major disruption of the workforce due to advances in artificial intelligence (AI) technology. According to a McKinsey Global Institute report, 375 million workers, or about 14 percent of the global workforce, may be required to shift occupations as digitization, automation, and AI technologies start to take over the workspace. In a separate 2018 report by the Organization for Economic Cooperation and Development (OECD), half of the global workforce is expected to be impacted one way or another by machine-learning technologies. AI technology will be at the forefront of the Fourth Industrial Revolution, and it will prove to be a far greater challenge than the ones that preceded it. If the world does not prepare, robots and technology could cause mass unemployment.

The case for placing AI at the heart of digitally robust financial regulation


"Data is the new oil." Originally coined in 2006 by the British mathematician Clive Humby, this phrase is arguably more apt today than it was then, as smartphones rival automobiles for relevance and the technology giants know more about us than we would like to admit. Just as it does for the financial services industry, the hyper-digitization of the economy presents both opportunity and potential peril for financial regulators. On the upside, reams of information are newly within their reach, filled with signals about financial system risks that regulators spend their days trying to understand. The explosion of data sheds light on global money movement, economic trends, customer onboarding decisions, quality of loan underwriting, noncompliance with regulations, financial institutions' efforts to reach the underserved, and much more. Importantly, it also contains the answers to regulators' questions about the risks of new technology itself. Digitization of finance generates novel kinds of hazards and accelerates their development. Problems can flare up between scheduled regulatory examinations and can accumulate imperceptibly beneath the surface of information reflected in traditional reports. Thanks to digitization, regulators today have a chance to gather and analyze much more data and to see much of it in something close to real time. The potential for peril arises from the concern that the regulators' current technology framework lacks the capacity to synthesize the data. The irony is that this flood of information is too much for them to handle.

How to Tackle the Global Supply Chain Crisis


For more than 50 years, Davos, the annual meeting of the World Economic Forum, has been an important barometer of economic, political, social, and environmental issues affecting the future of the world. So, what topics are driving the agenda for Davos 2022? The global supply chain crisis has taken on a new meaning. As the pandemic spread rapidly in 2020 and lingered in 2021, the general consensus was that disruptions to the global supply chain would be temporary albeit costly. But in 2022, it is clear that fragile supply chain may exist in a perpetual state of disruption for quite some time. In fact, the global supply chain was always in a fragile state; the pandemic laid bare just how vulnerable it was all along.

The Problem with Blaming Robots For Taking Our Jobs

The New Yorker

In the late nineteen-forties, Delmar Harder, a vice-president at Ford, popularized the term "automation"--a "nickname," he said, for the increased mechanization at the company's Detroit factory. Harder was mostly talking about the automatic transfer of car parts between machines, but the concept soon grew legs--and sometimes a robotic arm--to encompass a range of practices and possibilities. From the immediate postwar years to the late nineteen-sixties, America underwent what we might call an automation boom, not only in the automotive sector but in most heavy-manufacturing industries. As new technology made factory work more efficient, it also rendered factory workers redundant, often displacing them into a growing service sector. Automation looks a little different these days, but the rhetoric around it remains basically the same.

Blockchain + AI in Finance: How Opposites Attract


FinTech as we know it now is highly specialized and centralized. Blockchain and AI can be catalysts for FinTech 2.0 focusing on holistic solutions with increased transaction speeds, transparency, and security. Furthermore, DeFi may mean a larger pool of investors as more and more people gain access to financial markets. The more investors there are, the more data there will be that would be impossible to process without AI. Blockchain provides the foundation for smart contracts to improve transparency and data management, while AI may be leveraged to scale processes, accelerate transactions, and extract insights from large volumes of data.

La veille de la cybersécurité


There is no disputing the privacy trend. And it is one of the few issues in American life that crosses party lines. Data shows that 86% of people care about privacy for themselves and others -- with 79% willing to act on it by spending time and money to protect their data. And to those cynics who say people moan about privacy and do nothing, the same study found that 47% have taken action because of a company's data policies. What does this mean for the trillions of dollars that flow through the U.S. economy as a result of the very same privacy violations that are enraging consumers?

China's COVID lockdowns are a symptom of deeper problems

FOX News

Gatestone Institute senior fellow Gordon Chang weighs in on Shanghai residents protesting COVID lockdowns on'Fox News Live.' In the spring of 2021, China was reporting only a few dozen COVID cases each day and celebrating a return to steady economic growth. The United States, meanwhile, reeled from its worst death wave of the pandemic. Media outlets around the world, from the Chinese Ministry of Propaganda to the New York Times, were quick to declare that China had "won" the pandemic, having decisively defeated the virus and demonstrated the virtues of unbridled autocracy. Xi Jinping was set to use China's apparent COVID success as a central argument for enshrining himself, at the upcoming Communist Party Congress in October 2022, as emperor-for-life.

Automation Isn't the Biggest Threat to US Factory Jobs


The number of American workers who quit their jobs during the pandemic--over a fifth of the workforce--may constitute one of the largest American labor movements in recent history. Workers demanded higher pay and better conditions, spurred by rising inflation and the pandemic realization that employers expected them to risk their lives for low wages, mediocre benefits, and few protections from abusive customers--often while corporate stock prices soared. At the same time, automation has become cheaper and smarter than ever. Robot adoption hit record highs in 2021. This wasn't a surprise, given prior trends in robotics, but it was likely accelerated by pandemic-related worker shortages and Covid-19 safety requirements.

Forecasting Recessions With Scikit-Learn


It is no secret that everybody wants to predict recessions. Many economists and finance firms have attempted this with limited success, but by and large there are several well known leading indicators for recessions in the US economy. However, when presented to the general public these indicators are typically taken alone, and are not framed in a way that can give probability statements associated with an upcoming recession. In this project, I have taken several of those economic indicators and built a classification model to generate probabilistic statements. Here, the actual classification ('recession' or'no recession') is not as important as the probability of a recession, since this probability will be used to determine a basic portfolio scheme which I will describe later on.

Could ethical AI help underrepresented groups get ahead at work?


Artificial intelligence (AI) can be a powerful tool to help build a more inclusive economy.ljubaphoto It's no secret that the pandemic resulted in women and marginalized communities being ousted from the work force in record numbers. Though many demographic sectors have since bounced back, the gains remain unequal among traditionally under-represented groups. For example, employment in the accommodation and food service industries, which are traditionally staffed primarily by women, are still 17 per cent below pre-pandemic levels. And while the unemployment rate for racialized workers has returned to pre-pandemic levels, it's still higher than that of non-racialized workers.