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It's Time to Rethink Machine Learning Models in Financial Services

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Richard Harmon, Managing Director of Financial Services at Cloudera, discusses the importance of relevant machine learning models in today's age, and how the financial sector can prepare for future changes. The past six months have been turbulent. Business disruptions and closures are happening at an unprecedented scale and impacting the economy in a profound way. In the financial services sector, S&P Global estimates that this year could quadruple UK bank credit losses. The economic uncertainty in the UK is heightened by Brexit, which will see the UK leave the European Union in 2021.


The impact of machine learning and AI on the UK economy

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A recent virtual event addressed another such issue: the potential impact machines, imbued with artificial intelligence, may have on the economy and the financial system. The event was organised by the Bank of England, in collaboration with CEPR and the Brevan Howard Centre for Financial Analysis at Imperial College. What follows is a summary of some of the recorded presentations. The full catalogue of videos are available on the Bank of England's website. In his presentation, Stuart Russell (University of California, Berkeley), author of the leading textbook on artificial intelligence (AI), gives a broad historical overview of the field since its emergence in the 1950s, followed by insight into more recent developments.


Europe and AI: Leading, Lagging Behind, or Carving Its Own Way?

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For its AI ecosystem to thrive, Europe needs to find a way to protect its research base, encourage governments to be early adopters, foster its startup ecosystem, expand international links, and develop AI technologies as well as leverage their use efficiently.


Artificial intelligence as a central banker – IAM Network

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Artificial intelligence, such as the Bank of England Bot, is set to take over an increasing number of central bank functions. Billionaire John Catsimatidis uses artificial intelligence to research daughter's date


Artificial intelligence as a central banker

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Artificial intelligence (AI) is increasingly useful for central banks. While it may be used only in low-level roles today, technological advances and cost savings will likely embed AI deeper and deeper into core central bank functions. Maybe each central bank will have their own AI engine, maybe a future'BoB' (the Bank of England Bot). What will be the impact of BoB and its counterparts? BoB could today, or soon, help with many central bank tasks, such as information gathering, data analysis, forecasting, risk management, financial supervision, and monetary policy analysis.


133 million jobs could be created globally by the rise of AI

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There is no question that the rise of AI (Artificial Intelligence) is gaining strength as industries across the globe look towards the revolutionary technology to change how work and with the introduction of the new 5G network. Transcending into all industry sectors from Manufacturing and Engineering to Retail and Wholesale, the rise of AI could ignite the biggest shake up on industry sectors and job reform since the introduction of the desktop computer. It is anticipated that the rise of AI is set to replace some methods of working whilst it is estimated that it could create 133 million jobs globally. Explaining the preconceptions of AI and its future, Microsoft believes that every company will be an AI company in the next 5 years; however, due to concerns that people do not fully understand the technology and therefore could be left behind. In the last 12 months Microsoft have set up a pilot AI business school here in the UK to focus on education, discussion and R&D so that they may deliver AI skills development to individuals and business.


Soon a Robot Will Be Writing This Headline

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Fearing that a newfangled technology would put them out of work, neighbors broke into the house of James Hargreaves, the inventor of the spinning jenny, and destroyed the machine and also his furniture in 18th-century England. Queen Elizabeth I denied an English priest a patent for an invention that knitted wool, arguing that it would turn her subjects into unemployed beggars. A city council dictated that Anton Möller, who invented the ribbon loom in the 16th century, should be strangled for his efforts. But centuries of predictions that machines would put humans out of work for good -- a scenario that economists call "technological unemployment" -- have always turned out to be wrong. Technology eliminated some jobs, but new work arose, and it was often less grueling or dangerous than the old.


Industry, academia and government are joining forces to drive AI education

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In the engine room of the economy, artificial intelligence (AI) is being heralded as a driver of productivity and commercial growth. With an ability to process huge quantities of data quickly, the technology can increase efficiency, improve the decision-making process by introducing new insights and speed up delivery. AI changes the definition of "production" and promises to transform how we measure economic growth for countries across the world. Research by Accenture shows that, by 2035, AI could double annual global economic growth rates by creating a new virtual workforce to boost productivity, enhancing the skills and ability of existing staff and driving innovations in the economy. Over time, companies using AI will not only do things differently, they will also do different things.


Digital Bulletin UiPath - Software Robots: the answer to a more productive, engaged workforce

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The business landscape is currently facing a period of uncertainty and unrest. Ongoing Brexit tensions have cut the productivity of UK companies and created a crucial need for increased productivity – which Robotic Process Automation (RPA) could help provide. New technologies like RPA are becoming more common in offices, resulting in an increase in business process efficiency. Specifically, RPA's ability to execute rules-based office tasks is resulting in employee time being freed up for more meaningful, strategic tasks, ultimately helping boost engagement, productivity and happiness. RPA and new technologies are also ushering in a new world of work: according to the World Economic Forum, 65% of children now entering primary school will hold jobs that currently don't exist.


Robots Can Do Our Jobs? No: That's Algorithmic Pseudoscience at Work

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Ironically, algorithms are telling us that machines will soon be able to do most of our jobs, but those conclusions perfectly illustrate what's non-scientific about turning human reasoning over to computers. Barely a month passes without a news story about how robots and artificial intelligence (AI) are going to devastate a significant number of the jobs in the workplace, sweeping away solid salary paying employment for factory workers and white-collar clerks alike. Just this month, the UK Parliament reported on the future of work in the face of automation, declaring that over 70% of jobs were at medium to high risk of displacement. While the report draws on a "more optimistic" study by the ONS to arrive at this prediction, the ONS used methods inspired by the even-more-frightening results in a 2013 paper by Oxford economist Carl Frey and machine learning expert Michael Osbourne, which found that almost half of jobs were at high risk, and two-thirds at medium risk. The paper was so important that in addition to shaping the methodologies of later reports (like those of the ONS, the OECD, and others), it informed a speech of the Bank of England's Chief Economist to the Trades Union Congress in 2015, prompted the "Fourth Industrial Revolution" theme of the 2016 Davos Forum, provided the basis of the WEF "Future of Jobs" report, and generated a subsequent sea of articles by journalists who rarely questioned the numbers.