【正文】 changes: ―Some examples: Banks. Today banks provide loans based on very inplete data. It is true that many people who today qualify for loans would not get them in the future. However, many people – and arguably many more people – will be able to obtain loans in the future, as banks turn away from using such factors as race, socioeconomic background, postal code and the like to assess fit. Moreover, with more data (and with a more interactive relationship between bank and client) banks can reduce their risk, thus providing more loans, while at the same time providing a range of services individually directed to actually help a person‘s financial state. “Health care providers. Health care is a significant and growing expense not because people are being less healthy (in fact, societywide, the opposite is true) but because of the significant overhead required to support increasingly plex systems, including prescriptions, insurance, facilities and more. New technologies will enable health providers to shift a significant percentage of that load to the individual, who will (with the aid of personal support systems) manage their health better, coordinate and manage their own care, and create less of a burden on the system. As the overall cost of health care declines, it bees increasingly feasible to provide singlepayer health insurance for the entire population, which has known beneficial health outes and efficiencies. “Governments. A significant proportion of government is based on regulation and monitoring, which will no longer be required with the deployment of automated production and transportation systems, along with sensor works. This includes many of the daily (and often unpleasant) interactions we have with government today, from traffic offenses, manifestation of civil discontent, unfair treatment in mercial and legal processes, and the like. A simple example: One of the most persistent political problems in the United States is the gerrymandering of political boundaries to benefit incumbents. Electoral divisions created by an algorithm to a large degree eliminate gerrymandering (and when open and debatable, can be modified to improve on that result).‖ A sampling of additional answers, from anonymous respondents: ? ―Algorithms find knowledge in an automated way much faster than traditionally feasible.‖ 9 PEW RESEARCH CENTER g ? ―Algorithms can crunch databases quickly enough to alleviate some of the red tape and bureaucracy that currently slows progress down.‖ ? ―We will see less pollution, improved human health, less economic waste.‖ ? ―Algorithms have the potential to equalize access to information.‖ ? ―The efficiencies of algorithms will lead to more creativity and selfexpression.‖ ? ―Algorithms can diminish transportation issues。 however, as with all great technological revolutions, this trend has a dark side. Most respondents pointed out concerns, chief among them the final five overarching themes of this report。 and . social and demographic trends. All of the center‘s reports are available at . Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. For this project, Pew Research Center worked with Elon University‘ s Imagining the Inter Center, which helped conceive the research, collect, and analyze the data. 169。 journalism and media。 ethical issues are being worked out “Algorithms don?t have to be perfect。 the fact that it results in perpetual injustices toward the very minority classes it creates will be ignored. The Common Good has bee a discredited, obsolete relic of The Past.‖ ? ―In an economy increasingly dominated by a tiny, very privileged and insulated portion of the population, it will largely reproduce inequality for their benefit. Criticism will be belittled and dismissed because of the veneer of digital ?logic‘ over the process.‖ ? ―Algorithms are the new gold, and it‘s hard to explain why the average ?good‘ is at odds with the individual ?good.‘‖ ? ―We will interpret the negative individual impact as the necessary collateral damage of ?progress.‘‖ ? ―This will kill local intelligence, local skills, minority languages, local entrepreneurship because most of the available resources will be drained out by the global petitors.‖ ? ―Algorithms in the past have been created by a programmer. In the future they will likely be evolved by intelligent/learning machines …. Humans will lose their agency in the world.‖ ? ―It will only get worse because there‘s no ?crisis‘ to respond to, and hence, not only no motivation to change, but every reason to keep it going – especially by the powerful interests involved. We are heading for a nightmare.‖ ? ―Web provides more convenience for citizens who need to get a ride home, but at the same time – and it‘s naive to think this is a coincidence – it‘s also a moized, corporatized, disempowering, cannibalizing harbinger of the End Times. (I exaggerate for effect. But not by much.)‖ Theme 4: Biases exist in algorithmicallyanized systems Two strands of thinking tie together here. One is that the algorithm creators (code writers), even if they strive for inclusiveness, objectivity and neutrality, build into their creations their own perspectives and values. The other is that the datasets to which algorithms are applied have their own limits and deficiencies. Even datasets with billions of pieces of information do not capture the fullness of people‘s lives and the diversity of their experiences. Moreover, the datasets themselves are imperfect because they do not contain inputs from everyone or a representative sample of everyone. The two themes are advanced in these answers: g 12 PEW RESEARCH CENTER Justin Reich, executive director at the MIT Teaching Systems Lab, observed,