【正文】 rences, and may be applied to detect, remove, or reduce human bias, rather than reinforcing it. Social and political decisions are likewise at play in AI‘s influences on Employment and Workplace trends, such as the safety s needed to protect people from structural changes in the economy. AI is poised to replace people in certain kinds of jobs, such as in the driving of taxis and trucks. However, in many realms, AI will likely replace tasks rather than jobs in the near term, and will also create new kinds of jobs. But the new jobs that will emerge are harder to imagine in advance than the existing jobs that will likely be lost. AI will also lower the cost of many goods and services, effectively making everyone better off. Longer term, AI may be thought of as a radically different mechanism for wealth creation in which everyone should be entitled to a portion of the world‘s AIproduced treasures. It is not too soon for social debate on how the economic fruits of AI technologies should be shared. Entertainment has been transformed by social works and other platforms for sharing and browsing blogs, videos, and photos, which rely on techniques actively developed in NLP, information retrieval, image processing, crowdsourcing, and machine learning. Some traditional sources of entertainment have also embraced AI to pose music, create stage performances, and even to generate 3D scenes from natural language text. The enthusiasm with which people have already responded to AIdriven entertainment has been surprising. As with many aspects of AI, there is ongoing debate about the extent to which the technology replaces or enhances sociability. AI will increasingly enable entertainment that is more interactive, personalized, and engaging. Research should be directed toward understanding how to leverage these attributes for individuals‘ and society‘s benefit. What’s next for AI research? The research that fuels the AI revolution has also seen rapid changes. Foremost among them is the maturation of machine learning, stimulated in part by the rise of the digital economy, which both provides and leverages large amounts of data. Other factors include the rise of cloud puting resources and consumer demand for widespread access to services such as speech recognition and navigation support. Machine learning has been propelled dramatically forward by impressive empirical successes of artificial neural works, which can now be trained with huge data sets and largescale puting. This approach has been e to be known as ―deep learning.‖ The leap in the performance of information processing algorithms has been acpanied by significant progress in hardware technology for basic operations such as sensing, perception, and object recognition. New platforms and markets for datadriven products, and the economic incentives to find new prod。 public safety and security。 service robots。 20xx by Stanford University. Artificial Intelligence and Life in 2030 is made available under a Creative Commons AttributionNoDerivatives License (International): /licenses/bynd/3 Substantial increases in the future uses of AI applications, including more selfdriving cars, healthcare diagnostics and targeted treatment, and physical assistance for elder care can be expected. 4 EXECUTIVE SUMMARY Artificial Intelligence (AI) is a science and a set of putational technologies that are inspired by—but typically operate quite differently from—the ways people use their nervous systems and bodies to sense, learn, reason, and take action. While the rate of progress in AI has been patchy and unpredictable, there have been significant advances since the field‘s inception sixty years ago. Once a mostly academic area of study, twentyfirst century AI enables a constellation of mainstream technologies that are having a substantial impact on everyday lives. Computer vision and AI planning, for example, drive the video games that are now a bigger entertainment industry than Hollywood. Deep learning, a form of machine learning based on layered representations of variables referred to as neural works, has made speechunderstanding practical on our phones and in our kitchens, and its algorithms can be applied widely to an array of applications that rely on pattern recognition. Natural Language Processing (NLP) and knowledge representation and reasoning have enabled a machine to beat the Jeopardy champion and are bringing new power to Web searches. While impressive, these technologies are highly tailored to particular tasks. Each application typically requires years of specialized research and careful, unique construction. In similarly targeted applications, substantial increases in the future uses of AI technologies, including more selfdriving cars, healthcare diagnostics and targeted treatments, and physical assistance for elder care can be expected. AI and robotics will also be applied across the globe in industries struggling to attract younger workers, such as agriculture, food processing, fulfillment centers, and factories. They will facilitate delivery of online purchases through flying drones, selfdriving trucks, or robots that can get up the stairs to the front door. This report is the first in a series to be issued at regular intervals as a part of the One Hundred Year Study on Artificial Intelligence (AI100). Starting from a charge given by the AI100 Standing Committee to consider the likely influences of AI in a typical North American city by the year 2030, the 20xx Study Panel, prising experts in AI and other relevant areas focused their attention on eight domains they considered most salient: transportation。 lowresource munit