The last 15 years have brought what Stanford University professor Erik Brynjolfsson calls the "productivity paradox." While there's been continuing advances in technology, such as artificial intelligence, automation, and teleconferencing tools, the U.S. and other countries have seen flagging productivity. But a productivity boom is coming soon, Brynjolfsson said at the recent EmTech Next conference hosted by MIT Technology Review. He pointed to advances in technology, particularly artificial intelligence programs that are as good as -- or better -- than humans at some things. Businesses should now focus on incorporating the technology into work processes and preparing employees, he said, and policymakers should make sure its adoption doesn't contribute to inequality.
The direction of AI development is not preordained. It can be altered to increase human productivity, create jobs and shared prosperity, and protect and bolster democratic freedoms--if we modify our approach. The direction of AI development is not preordained. It can be altered to increase human productivity, create jobs and shared prosperity, and protect and bolster democratic freedoms--if we modify our approach. Artificial Intelligence (AI) is not likely to make humans redundant. Nor will it create superintelligence anytime soon. But like it or not, AI technologies and intelligent systems will make huge advances in the next two decades--revolutionizing medicine, entertainment, and transport; transforming jobs and markets; enabling many new products and tools; and vastly increasing the amount of information that governments and companies have about individuals. Should we cherish and look forward to these developments, or fear them? Current AI research is too narrowly focused on making advances in a limited set of domains and pays insufficient attention to its disruptive effects on the very fabric of society. There are reasons to be concerned. Current AI research is too narrowly focused on making advances in a limited set of domains and pays insufficient attention to its disruptive effects on the very fabric of society. If AI technology continues to develop along its current path, it is likely to create social upheaval for at least two reasons. For one, AI will affect the future of jobs. Our current trajectory automates work to an excessive degree while refusing to invest in human productivity; further advances will displace workers and fail to create new opportunities (and, in the process, miss out on AI's full potential to enhance productivity). For another, AI may undermine democracy and individual freedoms. Each of these directions is alarming, and the two together are ominous. Shared prosperity and democratic political participation do not just critically reinforce each other: they are the two backbones of our modern society.
Identifying the optimal level of taxation is quite complex. Human behaviour is highly unpredictable and gathering data can be time consuming. Despite decades of economic research being put into finding the optimal tax rate, it remains an open problem. But, scientists at the US business technology company, Salesforce, believe they may have found the key to solving the problem – Artificial Intelligence. The team has developed an AI system called the AI Economist, which uses reinforcement learning technology to identify the optimal level of taxation to make reduce inequality.
This research work deals with Natural Language Processing (NLP) and extraction of essential information in an explicit form. The most common among the information management strategies is Document Retrieval (DR) and Information Filtering. DR systems may work as combine harvesters, which bring back useful material from the vast fields of raw material. With large amount of potentially useful information in hand, an Information Extraction (IE) system can then transform the raw material by refining and reducing it to a germ of original text. A Document Retrieval system collects the relevant documents carrying the required information, from the repository of texts. An IE system then transforms them into information that is more readily digested and analyzed. It isolates relevant text fragments, extracts relevant information from the fragments, and then arranges together the targeted information in a coherent framework. The thesis presents a new approach for Word Sense Disambiguation using thesaurus. The illustrative examples supports the effectiveness of this approach for speedy and effective disambiguation. A Document Retrieval method, based on Fuzzy Logic has been described and its application is illustrated. A question-answering system describes the operation of information extraction from the retrieved text documents. The process of information extraction for answering a query is considerably simplified by using a Structured Description Language (SDL) which is based on cardinals of queries in the form of who, what, when, where and why. The thesis concludes with the presentation of a novel strategy based on Dempster-Shafer theory of evidential reasoning, for document retrieval and information extraction. This strategy permits relaxation of many limitations, which are inherent in Bayesian probabilistic approach.
Stephen Chen investigates major research projects in China, a new power house of scientific and technological innovation. He has worked for the Post since 2006. He is an alumnus of Shantou University, the Hong Kong University of Science and Technology, and the Semester at Sea programme which he attended with a full scholarship from the Seawise Foundation.
There is now widespread anxiety over the future of work, often accompanied by calls for a basic income to protect those displaced by automation and other technological changes. As a labour economist, I am in favour of more efficient redistributive taxation through the application of refundable tax credits, which amounts to an income-tested basic income or negative income tax. But I am more skeptical about the spectre of a future without work. And if the future isn't scarred by massive, widespread technological unemployment, a basic income would be neither outrageously expensive nor the be-all and end-all of the policy measures that society needs. The reasons for my skepticism about a future without work rests in the evidence to date.
What was perhaps most fascinating, however, was how complex the problem at hand seems to be, and how varied the proposed solutions were. Commenting on why the current automation trend appears to be so strong, Daron Acemoglu (MIT Professor of Economics and coauthor of the New York Times 2012 best-selling book Why Nations Fail) spoke about how many of the most highly compensated professionals in the workplace today are turning their creative talents to "automate, automate, automate" all available technologies, which tends to adversely affect lower-wage workers. And when asked what they would do if given a "magic wand" to protect the current workforce against automation, speakers proposed making the U.S. tax code more favorable to workers by taxing capital gains at a higher rate; dramatically expanding educational opportunities, particularly alternatives to traditional four-year college degrees; and in the developing world, making social security benefits portable. Secretary Acosta, who delivered the keynote address, declared that in a rapidly automating world, "it is critical that we adapt the culture of lifelong learning," at both the personal and policy levels. Having worked in the technology sector for the six years between my undergraduate career and joining Erb, I have personally experienced the incredible rate of current technological change, and I absolutely agree with Acosta's sentiment.
But if this is to happen, the Cambridge University Professor believes a political rethink is required: "As to whether that will happen or not will depend on whether this county's politicians are prepared to learn from Scandinavian countries instead of the US. "Scandinavia has a good welfare state and high taxation, the opposite to the US, with its very inadequate welfare state and low taxes. "The present government seems to admire the US system more." The celebrated cosmologist and astrophysicist does however foresee a difficulty with collecting taxes from these multinational tech giants, based on current controversies over their tax arrangements. Facebook's UK tax bill, for example, is 0.62 percent of their £1.3billion
Republicans argue that the lower taxes for corporations and wealthy individuals promised in the tax bill currently before Congress will result in new investment in businesses and more jobs. But in the age of artificial intelligence and automation, trickle-down economics won't create employment. What corporations and the US economy at large need most in this emerging era is not more free cash, but a new approach to machine-assisted human productivity and purpose.
Erik Brynjolfsson, MIT Sloan School professor, explains how rapid advances in machine learning are presenting new opportunities for businesses. He breaks down how the technology works and what it can and can't do (yet). He also discusses the potential impact of AI on the economy, how workforces will interact with it in the future, and suggests managers start experimenting now. Brynjolfsson is the co-author, with Andrew McAfee, of the HBR Big Idea article, "The Business of Artificial Intelligence." SARAH GREEN CARMICHAEL: Welcome to the HBR IdeaCast from Harvard Business Review. It's a pretty sad photo when you look at it. A robot, just over a meter tall and shaped kind of like a pudgy rocket ship, laying on its side in a shallow pool in the courtyard of a Washington, D.C. office building. Workers – human ones – stand around, trying to figure out how to rescue it. The security robot had just been on the job for a few days when the mishap occurred. One entrepreneur who works in the office complex wrote: "We were promised flying cars.