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How artificial intelligence is transforming the world

#artificialintelligence

Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it.1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations. Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance. In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values.2 Although there is no uniformly agreed upon definition, AI generally is thought to refer to "machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention."3 According to researchers Shubhendu and Vijay, these software systems "make decisions which normally require [a] human level of expertise" and help people anticipate problems or deal with issues as they come up.4 As such, they operate in an intentional, intelligent, and adaptive manner. Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. With massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decisionmaking.


Commentary: Why the U.S. Could Fall Behind in the Global AI Race

#artificialintelligence

The country that wins the global race for dominance in artificial intelligence stands to capture enormous economic benefits, including potentially doubling its economic growth rates by 2035. Unfortunately, the United States is getting bad advice about how to compete. Over the past year, Canada, China, France, India, Japan, and the United Kingdom have all launched major government-backed initiatives to compete in AI. While the Trump administration has begun to focus on how to advance the technology, it has not developed a cohesive national strategy to match that of other countries. This has allowed the conversation about how policymakers in the United States should support AI to be dominated by proposals from advocates primarily concerned with staving off potential harms of AI by imposing restrictive regulations on the technology, rather than supporting its growth.


Government Should Remove Barriers to Deploying AI, Report Says – MeriTalk

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Government and policy-makers shouldn't put up unnecessary barriers to deploying artificial intelligence (AI) over concern of any perceived risks associated with the technology. Instead, policymakers should encourage innovation while crafting targeted solutions for specific problems if they occur, according to a report by the Information Technology Innovation Foundation, a science and technology policy think tank. There are a vast and diverse array of uses for AI, from rapidly analyzing large amounts of data to detecting abnormalities and patterns in transactions to extracting insights from datasets such as the link between a gene and a disease. AI is a field of computer science devoted to creating computer systems that perform operations characteristic of human intelligence, such as learning and decision making. Policy debates around AI are dividing into two positions: those that want to enable innovation, and those who want to slow or stop it, according to the report "Ten Ways the Precautionary Principle Undermines Progress in Artificial Intelligence."


Assured Autonomy: Path Toward Living With Autonomous Systems We Can Trust

arXiv.org Artificial Intelligence

The challenge of establishing assurance in autonomy is rapidly attracting increasing interest in the industry, government, and academia. Autonomy is a broad and expansive capability that enables systems to behave without direct control by a human operator. To that end, it is expected to be present in a wide variety of systems and applications. A vast range of industrial sectors, including (but by no means limited to) defense, mobility, health care, manufacturing, and civilian infrastructure, are embracing the opportunities in autonomy yet face the similar barriers toward establishing the necessary level of assurance sooner or later. Numerous government agencies are poised to tackle the challenges in assured autonomy. Given the already immense interest and investment in autonomy, a series of workshops on Assured Autonomy was convened to facilitate dialogs and increase awareness among the stakeholders in the academia, industry, and government. This series of three workshops aimed to help create a unified understanding of the goals for assured autonomy, the research trends and needs, and a strategy that will facilitate sustained progress in autonomy. The first workshop, held in October 2019, focused on current and anticipated challenges and problems in assuring autonomous systems within and across applications and sectors. The second workshop held in February 2020, focused on existing capabilities, current research, and research trends that could address the challenges and problems identified in workshop. The third event was dedicated to a discussion of a draft of the major findings from the previous two workshops and the recommendations.