【正文】 igence or thinking manipulation is added to processes and objects that previously did not have that layer. So prediction possibilities follow us around like a pet. The result: As information tools and predictive dynamics are more widely adopted, our lives will be increasingly affected by their inherent conclusions and the narratives they spawn.‖ ―The overall impact of ubiquitous algorithms is presently incalculable because the presence of algorithms in everyday processes and transactions is now so great, and is mostly hidden from public view. All of our extended thinking systems (algorithms fuel the software and connectivity that create extended thinking systems) demand more thinking – not less – and a more global perspective than we have previously managed. The expanding collection and analysis of data and the resulting application of this information can cure diseases, decrease poverty, bring timely solutions to people and places where need is greatest, and dispel millennia of prejudice, illfounded conclusions, inhumane practice and ignorance of all kinds. Our algorithms are now redefining what we think, how we think and what we know. We need to ask them to think about their thinking – to look out for pitfalls and inherent biases before those are baked in and harder to remove. ―To create oversight that would assess the impact of algorithms, first we need to see and understand them in the context for which they were developed. That, by itself, is a tall order that requires impartial experts backtracking through the technology development process to find the models and formulae that originated the algorithms. Then, keeping all that learning at hand, the experts need to soberly assess the benefits and deficits or risks the algorithms create. Who is prepared to do this? Who has the time, the budget and resources to investigate and remend useful courses of action? This is a 21stcentury job description – and market niche – in search of real people and panies. In order to make algorithms more transparent, products and product information circulars might include an outline of algorithmic assumptions, akin to the nutritional sidebar now found on many packaged food products, that would inform users of how algorithms drive intelligence in a given product and a reasonable outline of the implications inherent in those assumptions.‖ Theme 2: Good things lie ahead A number of respondents noted the many ways in which algorithms will help make sense of massive amounts of data, noting that this will spark breakthroughs in science, new conveniences and human capacities in everyday life, and an everbetter capacity to link people to the 8 PEW RESEARCH CENTER g information that will help them. They perform seemingly miraculous tasks humans cannot and they will continue to greatly augment human intelligence and assist in acplishing great things. A representative proponent of this view is Stephen Downes, a researcher at the National Research Council of Canada, who listed the following as positive 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 selfe