{"id":93736,"date":"2017-02-08T13:46:21","date_gmt":"2017-02-08T18:46:21","guid":{"rendered":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/2017\/02\/08\/theme-1-algorithms-will-continue-to-spread-everywhere\/"},"modified":"2024-04-14T04:17:10","modified_gmt":"2024-04-14T09:17:10","slug":"theme-1-algorithms-will-continue-to-spread-everywhere","status":"publish","type":"post","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/internet\/2017\/02\/08\/theme-1-algorithms-will-continue-to-spread-everywhere\/","title":{"rendered":"Theme 1: Algorithms will continue to spread everywhere"},"content":{"rendered":"

Nearly all of these respondents see the great advantages of the algorithms that are already changing how connected institutions and people live and work. A significant majority expects them to continue to proliferate \u2013 mostly invisibly \u2013 and expects that there will be an exponential rise in their influence. They say this will bring many benefits and some challenges.<\/p>\n\n

Jim Warren<\/strong>, longtime technology entrepreneur and activist, described algorithms: \u201cAny sequence of instructions for how to do something (or how a machine that can understand said instructions can do it) is \u2013 by definition \u2013 an \u2018algorithm.\u2019 All sides \u2013 great and small, benevolent and malevolent \u2013 have always<\/em> created and exercised such algorithms (recipes for accomplishing a desired function), and always will. Almost all of the \u2018good\u2019 that humankind has created \u2013 as well as all the harm (sometimes only in the eye of the beholder) \u2013 has been from discovering how to do something, and then repeating that process. And more often than not, sharing it with others. Like all-powerful but double-edged tools, algorithms are. ;-)\u201d<\/p>\n\n

Terry Langendoen<\/strong>, a U.S. National Science Foundation expert whose job is to support research on algorithms, is enthusiastic about what lies ahead. \u201cThe technological improvements in the past 50 years in such areas as speech-recognition and synthesis, machine translation and information retrieval have had profound beneficial impacts \u2026,\u201d he said. \u201cThe field is poised to make significant advances in the near future.\u201d<\/p>\n\n

The benefits will be visible and invisible and can lead to greater human insight into the world<\/h3>\n\n

Patrick Tucker<\/strong>, author and technology editor at Defense One, pointed out how today\u2019s networked communications amplify the impacts of algorithms. \u201cThe internet is turning prediction into an equation,\u201d he commented. \u201cFrom programs that chart potential flu outbreaks to expensive (yet imperfect) \u2018quant\u2019 algorithms that anticipate bursts of stock market volatility, computer-aided prediction is everywhere. As I write in The Naked Future<\/em><\/a>, in the next two decades, as a function of machine learning and big data, we will be able to predict huge areas of the future with far greater accuracy than ever before in human history, including events long thought to be beyond the realm of human inference. That will have an impact in all areas including health care, consumer choice, educational opportunities, etc. The rate by which we can extrapolate meaningful patterns from the data of the present is quickening as rapidly as is the spread of the internet because the two are inexorably linked.\u201d<\/p>\n\n

Code, flexible and open code, can make you free \u2013 or at least a bit freer.\nPaul Jones<\/cite><\/p><\/blockquote>\n\n

Paul Jones<\/strong>, clinical professor at the University of North Carolina-Chapel Hill and director of ibiblio.org, was optimistic. \u201cThe promise of standardization of best practices into code is a promise of stronger best practices and a hope of larger space for human insight,\u201d he predicted. \u201cCode, flexible and open code, can make you free \u2013 or at least a bit freer.\u201d<\/p>\n\n

David Krieger<\/strong>, director of the Institute for Communication & Leadership IKF, predicted, \u201cData-driven algorithmic cognition and agency will characterize all aspects of society. Humans and non-humans will become partners such that identity(ies) will be distributed and collective. Individualism will become anachronistic. The network is the actor. It is the network that learns, produces, decides, much like the family or clan in collective societies of the past, but now on the basis of big data, AI and transparency. Algorithmic auditing, accountability, benchmarking procedures in machine learning, etc., will play an important role in network governance frameworks that will replace hierarchical, bureaucratic government. Not government, but governance.\u201d<\/p>\n\n

An anonymous software security consultant noted, \u201cThere will be many positive impacts that aren\u2019t even noticed. Having an \u2018intelligent\u2019 routing system for cars may mean most people won\u2019t notice when everyone gets to their destination as fast as they used to even with twice the traffic. Automated decisions will indeed have significant impacts upon lots of people, most of the time in ways they won\u2019t ever recognize. Already they\u2019re being used heavily in financial situations, but most people don\u2019t see a significant difference between \u2018a VP at the bank denied my loan\u2019 and \u2018software at the bank denied my loan\u2019 (and in practice, the main difference is an inability to appeal the decision).\u201d<\/p>\n\n

Another anonymous respondent wrote, \u201cAlgorithms in general enable people to benefit from the results of the synthesis of large volumes of information where such synthesis was not available in any form before \u2013 or at least only to those with significant resources. This will be increasingly positive in terms of enabling better-informed choices. As algorithms scale and become more complex, unintended consequences become harder to predict and harder to fix if they are detected, but the positive benefit above seems so dramatic it should outweigh this effect. Particularly if there are algorithms designed to detect unintended discriminatory or other consequences of other algorithms.\u201d<\/p>\n\n

The many upsides of algorithms are accompanied by challenges<\/h3>\n\n

Respondents often hailed the positives while noting the need to address the downsides.<\/p>\n\n

If we guard the core values of civil society (like equality, respect, transparency), the most valuable algorithms will be those that help the greatest numbers of people.\nGalen Hunt<\/cite><\/p><\/blockquote>\n\n

Galen Hunt<\/strong>, partner research manager at Microsoft Research NExT, reflected the hopes of many when he wrote, \u201cAlgorithms will accelerate in their impact on society. If we guard the core values of civil society (like equality, respect, transparency), the most valuable algorithms will be those that help the greatest numbers of people.\u201d<\/p>\n\n

Alf Rehn<\/strong>, professor and chair of management and organization at \u00c5bo Akademi University in Finland, commented, \u201cNew algorithmic thinking will be a great boon for many people. They will make life easier, shopping less arduous, banking a breeze and a hundred other great things besides. But a shaved monkey can see the upsides. The important thing is to realize the threats, major and minor, of a world run by algorithms. They can enhance filter bubbles for both individuals and companies, limit our view of the world, create more passive consumers, and create a new kind of segregation \u2013 think algorithmic haves and have-nots. In addition, for an old hacker like me, as algorithmic logics get more and more prevalent in more and more places, they also increase the number of attack vectors for people who want to pervert their logic, for profit, for more nefarious purposes, or just for the lulz.\u201d<\/p>\n\n

Andrew Nachison<\/strong>, founder at We Media, observed, \u201cThe positives will be enormous \u2013 better shopping experiences, better medical experience, even better experiences with government agencies. Algorithms could even make \u2018bureaucrat\u2019 a friendlier word. But the dark sides of the \u2018optimized\u2019 culture will be profound, obscure and difficult to regulate \u2013 including pervasive surveillance of individuals and predictive analytics that will do some people great harm (\u2018Sorry, you\u2019re pre-disqualified from a loan.\u2019 \u2018Sorry, we\u2019re unable to sell you a train ticket at this time.\u2019). Advances in computing, tracking and embedded technology will herald a quantified culture that will be ever more efficient, magical and terrifying.\u201d<\/p>\n\n

Luis Lach<\/strong>, president of the Sociedad Mexicana de Computaci\u00f3n en la Educaci\u00f3n, A.C., said, \u201cOn the negative side we will see huge threats to security, data privacy and attacks to individuals, by governments, private entities and other social actors. And on the positive we will have the huge opportunity for collective and massive collaboration across the entire planet. Of course the science will rise and we will see marvelous advances. Of course we will have a continuum between positive and negative scenarios. What we will do depends on individuals, governments, private companies, nonprofits, academia, etc.\u201d<\/p>\n\n

Frank Pasquale<\/strong>, author of The Black Box Society: The Secret Algorithms That Control Money and Information<\/em> and professor of law at the University of Maryland, wrote, \u201cAlgorithms are increasingly important because businesses rarely thought of as high-tech have learned the lessons of the internet giants\u2019 successes. Following the advice of Jeff Jarvis\u2019 What Would Google Do<\/em><\/a>, they are collecting data from both workers and customers, using algorithmic tools to make decisions, to sort the desirable from the disposable. Companies may be parsing your voice and credit record when you call them, to determine whether you match up to \u2018ideal customer\u2019 status, or are simply \u2018waste\u2019 who can be treated with disdain. Epagogix advises movie studios on what scripts to buy based on how closely they match past, successful scripts. Even winemakers make algorithmic judgments, based on statistical analyses of the weather and other characteristics of good and bad vintage years. For wines or films, the stakes are not terribly high. But when algorithms start affecting critical opportunities for employment, career advancement, health, credit and education, they deserve more scrutiny. U.S. hospitals are using big data-driven systems to determine which patients are high-risk \u2013 and data far outside traditional health records is informing those determinations. IBM now uses algorithmic assessment tools to sort employees worldwide on criteria of cost-effectiveness, but spares top managers the same invasive surveillance and ranking. In government, too, algorithmic assessments of dangerousness can lead to longer sentences for convicts, or no-fly lists for travelers. Credit scoring drives billions of dollars in lending, but the scorers\u2019 methods remain opaque. The average borrower could lose tens of thousands of dollars over a lifetime, thanks to wrong or unfairly processed data. It took a combination of computational, legal and social scientific skills to unearth each of the examples discussed above \u2013 troubling collection, bad or biased analysis, and discriminatory use. Collaboration among experts in different fields is likely to yield even more important work. Grounded in well-established empirical social science methods, their models can and should inform the regulation of firms and governments using algorithms.\u201d<\/p>\n\n

Cindy Cohn<\/strong>, executive director at the Electronic Frontier Foundation, wrote, \u201cThe lack of critical thinking among the people embracing these tools is shocking and can lead to some horrible civil liberties outcomes \u2026. I don\u2019t think it\u2019s possible to assign an overall \u2018good\u2019 or \u2018bad\u2019 to the use of algorithms, honestly. As they say on Facebook, \u2018It\u2019s complicated.\u2019\u201d<\/p>\n\n

Bernardo A. Huberman<\/strong>, senior fellow and director of the Mechanisms and Design Lab at HPE Labs, Hewlett Packard Enterprise, said, \u201cAlgorithms do lead to the creation of filters through which people see the world and are informed about it. This will continue to increase. If the negative aspects eventually overtake the positive ones, people will stop resorting to interactions with institutions, media, etc. People\u2019s lives are going to continue to be affected by the collection of data about them, but I can also see a future where they won\u2019t care as much or will be compensated every time their data is used for money-making purposes.\u201d<\/p>\n\n

Marcel Bullinga<\/strong>, trend watcher and keynote speaker, commented, \u201cAI will conquer the world, like the internet and the mobile phone once did. It will end the era of apps. Millions of useless apps (because there are way too many for any individual) will become useful on a personal level if they are integrated and handled by AI. For healthy robots\/AI, we must have transparent, open source AI. The era of closed is over. If we stick to closed AI, we will see the rise of more and more tech monopolies dominating our world as Facebook and Google and Uber do now.\u201d<\/p>\n\n

In today\u2019s market economy, driven by profit and shareholder value, the possibility of widespread abuse is quite high.\nMichael Rogers<\/cite><\/p><\/blockquote>\n\n

Michael Rogers<\/strong>, author and futurist at Practical Futurist, said, \u201cIn a sense, we\u2019re building a powerful nervous system for society. Big data, real-time analytics, smart software could add great value to our lives and communities. But at the same time they will be powerful levers of social control, many in corporate hands. In today\u2019s market economy, driven by profit and shareholder value, the possibility of widespread abuse is quite high. Hopefully society as a whole will be able to use these tools to advance more humanistic values. But whether that is the case lies not in the technology, but in the economic system and our politics.\u201d<\/p>\n\n

An anonymous principal engineer commented, \u201cThe effect will depend on the situation. In areas where human judgment is required, I foresee negative effects. In areas where human judgment is a hindrance it could be beneficial. For example, I don\u2019t see any reason for there to be train accidents (head-on collisions, speeding around a curve) with the correct design of an intelligent train system. Positive and negative effects will also depend on the perception of the person involved. For example, an intelligent road system could relieve congestion and reduce accidents, but also could restrict freedom of people to drive their cars as they wish (e.g., fast). This could be generalized to a reduction in freedom in general, which could be beneficial to some but detrimental to others.\u201d<\/p>","protected":false},"excerpt":{"rendered":"

Nearly all of these respondents see the great advantages of the algorithms that are already changing how connected institutions and people live and work. A significant majority expects them to continue to proliferate \u2013 mostly invisibly \u2013 and expects that there will be an exponential rise in their influence. They say this will bring many 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