BiblioVault - Books about Algorithms

Algorithmic Regimes

Methods, Interactions, and Politics

Juliane Jarke

Amsterdam University Press, 2024

Algorithms have risen to become one, if not the central technology for producing, circulating, and evaluating knowledge in multiple societal arenas. In this book, scholars from the social sciences, humanities, and computer science argue that this shift has, and will continue to have, profound implications for how knowledge is produced and what and whose knowledge is valued and deemed valid. To attend to this fundamental change, the authors propose the concept of algorithmic regimes and demonstrate how they transform the epistemological, methodological, and political foundations of knowledge production, sensemaking, and decision-making in contemporary societies. Across sixteen chapters, the volume offers a diverse collection of contributions along three perspectives on algorithmic regimes: the methods necessary to research and design algorithmic regimes, the ways in which algorithmic regimes reconfigure sociotechnical interactions, and the politics engrained in algorithmic regimes.

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Algorithms of Education

How Datafication and Artificial Intelligence Shape Policy

Kalervo N. Gulson

University of Minnesota Press, 2022

A critique of what lies behind the use of data in contemporary education policy

While the science fiction tales of artificial intelligence eclipsing humanity are still very much fantasies, in Algorithms of Education the authors tell real stories of how algorithms and machines are transforming education governance, providing a fascinating discussion and critique of data and its role in education policy.

Algorithms of Education explores how, for policy makers, today’s ever-growing amount of data creates the illusion of greater control over the educational futures of students and the work of school leaders and teachers. In fact, the increased datafication of education, the authors argue, offers less and less control, as algorithms and artificial intelligence further abstract the educational experience and distance policy makers from teaching and learning. Focusing on the changing conditions for education policy and governance, Algorithms of Education proposes that schools and governments are increasingly turning to “synthetic governance”—a governance where what is human and machine becomes less clear—as a strategy for optimizing education.

Exploring case studies of data infrastructures, facial recognition, and the growing use of data science in education, Algorithms of Education draws on a wide variety of fields—from critical theory and media studies to science and technology studies and education policy studies—mapping the political and methodological directions for engaging with datafication and artificial intelligence in education governance. According to the authors, we must go beyond the debates that separate humans and machines in order to develop new strategies for, and a new politics of, education.

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The Anthology in Digital Culture

Forms and Affordances

Giulia Taurino

Amsterdam University Press, 2023

As a cultural form, media practice and organizational model, the anthology has represented an important editorial framework in the development, preservation and retrieval of narratives, from paper-based media to machine-generated content, all throughout a series of discontinued analog and digital technologies. Over time, anthologies became part of the “metaphors we live by” (Lakoff and Johnson 2008), figurative lenses through which we read, navigate, interpret stories and organize human thoughts for better understanding. By providing an overview on the role of the anthology on streaming platform environments, this book examines how traditional editorial practices of anthologization intersect with data-driven content classification and sorting in the context of both pre- and post-digital culture. The author ultimately proposes to insert “anthology” in a vocabulary of digital culture that accounts for new curatorial and algorithmic processes of content filtering, in the attempt to expand the critical “keywords” (Williams 1983; Striphas 2015; Thylstrup et al. 2021) for the study of culture, society, data.

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Automating the News

How Algorithms Are Rewriting the Media

Nicholas Diakopoulos

Harvard University Press, 2019

From hidden connections in big data to bots spreading fake news, journalism is increasingly computer-generated. An expert in computer science and media explains the present and future of a world in which news is created by algorithm.

Amid the push for self-driving cars and the roboticization of industrial economies, automation has proven one of the biggest news stories of our time. Yet the wide-scale automation of the news itself has largely escaped attention. In this lively exposé of that rapidly shifting terrain, Nicholas Diakopoulos focuses on the people who tell the stories—increasingly with the help of computer algorithms that are fundamentally changing the creation, dissemination, and reception of the news.

Diakopoulos reveals how machine learning and data mining have transformed investigative journalism. Newsbots converse with social media audiences, distributing stories and receiving feedback. Online media has become a platform for A/B testing of content, helping journalists to better understand what moves audiences. Algorithms can even draft certain kinds of stories. These techniques enable media organizations to take advantage of experiments and economies of scale, enhancing the sustainability of the fourth estate. But they also place pressure on editorial decision-making, because they allow journalists to produce more stories, sometimes better ones, but rarely both.

Automating the News responds to hype and fears surrounding journalistic algorithms by exploring the human influence embedded in automation. Though the effects of automation are deep, Diakopoulos shows that journalists are at little risk of being displaced. With algorithms at their fingertips, they may work differently and tell different stories than they otherwise would, but their values remain the driving force behind the news. The human–algorithm hybrid thus emerges as the latest embodiment of an age-old tension between commercial imperatives and journalistic principles.

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Big Data Recommender Systems

Algorithms, Architectures, Big Data, Security and Trust, Volume 1

Osman Khalid

The Institution of Engineering and Technology, 2019

First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users’ data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges.

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Cloud Ethics

Algorithms and the Attributes of Ourselves and Others

Louise Amoore

Duke University Press, 2020

In Cloud Ethics Louise Amoore examines how machine learning algorithms are transforming the ethics and politics of contemporary society. Conceptualizing algorithms as ethicopolitical entities that are entangled with the data attributes of people, Amoore outlines how algorithms give incomplete accounts of themselves, learn through relationships with human practices, and exist in the world in ways that exceed their source code. In these ways, algorithms and their relations to people cannot be understood by simply examining their code, nor can ethics be encoded into algorithms. Instead, Amoore locates the ethical responsibility of algorithms in the conditions of partiality and opacity that haunt both human and algorithmic decisions. To this end, she proposes what she calls cloud ethics—an approach to holding algorithms accountable by engaging with the social and technical conditions under which they emerge and operate.

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Computing Taste

Algorithms and the Makers of Music Recommendation

Nick Seaver

University of Chicago Press, 2022

Meet the people who design the algorithms that capture our musical tastes.

The people who make music recommender systems have lofty goals: they want to broaden listeners’ horizons and help obscure musicians find audiences, taking advantage of the enormous catalogs offered by companies like Spotify, Apple Music, and Pandora. But for their critics, recommender systems seem to embody all the potential harms of algorithms: they flatten culture into numbers, they normalize ever-broadening data collection, and they profile their users for commercial ends. Drawing on years of ethnographic fieldwork, anthropologist Nick Seaver describes how the makers of music recommendation navigate these tensions: how product managers understand their relationship with the users they want to help and to capture; how scientists conceive of listening itself as a kind of data processing; and how engineers imagine the geography of the world of music as a space they care for and control.

Computing Taste rehumanizes the algorithmic systems that shape our world, drawing attention to the people who build and maintain them. In this vividly theorized book, Seaver brings the thinking of programmers into conversation with the discipline of anthropology, opening up the cultural world of computation in a wide-ranging exploration that travels from cosmology to calculation, myth to machine learning, and captivation to care.

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Data Fusion in Wireless Sensor Networks

A statistical signal processing perspective

Domenico Ciuonzo

The Institution of Engineering and Technology, 2019

The role of data fusion has been expanding in recent years through the incorporation of pervasive applications, where the physical infrastructure is coupled with information and communication technologies, such as wireless sensor networks for the internet of things (IoT), e-health and Industry 4.0. In this edited reference, the authors provide advanced tools for the design, analysis and implementation of inference algorithms in wireless sensor networks.

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Data Power

Radical Geographies of Control and Resistance

Jim E. Thatcher

Pluto Press, 2021

In recent years, popular media has inundated audiences with sensationalized headlines recounting data breaches, new forms of surveillance and other dangers of our digital age. Despite their regularity, such accounts treat each case as unprecedented and unique. This book proposes a radical rethinking of the history, present and future of our relations with the digital, spatial technologies that increasingly mediate our everyday lives.

From smartphones to surveillance cameras, to navigational satellites, these new technologies offer visions of integrated, smooth and efficient societies, even as they directly conflict with the ways users experience them. Recognizing the potential for both control and liberation, the authors argue against both acquiescence to and rejection of these technologies.

Through intentional use of the very systems that monitor them, activists from Charlottesville to Hong Kong are subverting, resisting and repurposing geographic technologies. Using examples as varied as writings on the first telephones to the experiences of a feminist collective for migrant women in Spain, the authors present a revolution of everyday technologies. In the face of the seemingly inevitable circumstances, these technologies allow us to create new spaces of affinity, and a new politics of change.

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Engines of Order

A Mechanology of Algorithmic Techniques

Bernhard Rieder

Amsterdam University Press, 2020

Software has become a key component of contemporary life and algorithmic techniques that rank, classify, or recommend anything that fits into digital form are everywhere. This book approaches the field of information ordering conceptually as well as historically. Building on the philosophy of Gilbert Simondon and the cultural techniques tradition, it first examines the constructive and cumulative character of software and shows how software-making constantly draws on large reservoirs of existing knowledge and techniques. It then reconstructs the historical trajectories of a series of algorithmic techniques that have indeed become the building blocks for contemporary practices of ordering. Developed in opposition to centuries of library tradition, coordinate indexing, text processing, machine learning, and network algorithms instantiate dynamic, perspectivist, and interested forms of arranging information, ideas, or people. Embedded in technical infrastructures and economic logics, these techniques have become engines of order that transform the spaces they act upon.

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Geographic Medicine for the Practitioner

Algorithms in the Diagnosis and Management of Exotic Diseases

Kenneth D. Warren and Adel A. F. Mahmoud

University of Chicago Press, 1978

"The many diseases that are endemic in most of the developing nations of the world (and that may also affect travelers to these regions) are, at world levels, the most important sources of morbidity that affect the entire human race. The change in morbidity patterns in the more developed nations should not be permitted to blind the more affluent countries to the implications of this simple statement. Thus, direct and useful guides are needed to assure efficient and economical diagnosis and treatment of those infections that are endemic to the less affluent two-thirds of the earth.

"The algorithms in this book have been developed by Drs. Warren and Mahmoud, as the result of a systematic effort to produce such guides. The book is presented as another in the series "Studies in Infectious Disease Research" and is a most welcome addition, certain to supply a major and hitherto inadequately fulfilled need."—from the Foreword, by Edward H. Kass, M. D., Ph.D

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An Intelligence in Our Image

The Risks of Bias and Errors in Artificial Intelligence

Osonde A. Osoba

RAND Corporation, 2017

Machine learning algorithms and artificial intelligence influence many aspects of life today and have gained an aura of objectivity and infallibility. The use of these tools introduces a new level of risk and complexity in policy. This report illustrates some of the shortcomings of algorithmic decisionmaking, identifies key themes around the problem of algorithmic errors and bias, and examines some approaches for combating these problems.

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Language and the Rise of the Algorithm

Jeffrey M. Binder

University of Chicago Press, 2022

A wide-ranging history of the algorithm.

Bringing together the histories of mathematics, computer science, and linguistic thought, Language and the Rise of the Algorithm reveals how recent developments in artificial intelligence are reopening an issue that troubled mathematicians well before the computer age: How do you draw the line between computational rules and the complexities of making systems comprehensible to people? By attending to this question, we come to see that the modern idea of the algorithm is implicated in a long history of attempts to maintain a disciplinary boundary separating technical knowledge from the languages people speak day to day.

Here Jeffrey M. Binder offers a compelling tour of four visions of universal computation that addressed this issue in very different ways: G. W. Leibniz’s calculus ratiocinator; a universal algebra scheme Nicolas de Condorcet designed during the French Revolution; George Boole’s nineteenth-century logic system; and the early programming language ALGOL, short for algorithmic language. These episodes show that symbolic computation has repeatedly become entangled in debates about the nature of communication. Machine learning, in its increasing dependence on words, erodes the line between technical and everyday language, revealing the urgent stakes underlying this boundary.

The idea of the algorithm is a levee holding back the social complexity of language, and it is about to break. This book is about the flood that inspired its construction.

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Scripted Culture

Digitalization and the Cultural Public Sphere

Edited by Ruedi Widmer and Ines Kleesattel

Diaphanes, 2018

When we look at the cultural public sphere through the lens of digitalization, a paradoxical picture emerges. In some ways, the digital age seems to have brought the goals of the Enlightenment to their fullest fruition, giving us boundless and instantaneous access to every kind of knowledge and art. But the internet and its platforms also frequently bring chaos, immersing us in a sphere of often unverified information whose scope is unimaginable. This book takes a tour through the current debates on digital culture, bringing together a wide array of perspectives from aesthetic theory, cultural studies, electronic media, and the arts.

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Selected Papers on Analysis of Algorithms

Donald E. Knuth

CSLI, 2000

Analysis of Algorithms is the fourth in a series of collected works by world-renowned computer scientist Donald Knuth. This volume is devoted to an important subfield of Computer Science that Knuth founded in the 1960s and still considers his main life's work. This field, to which he gave the name Analysis of Algorithms, deals with quantitative studies of computer techniques, leading to methods for understanding and predicting the efficiency of computer programs. Analysis of Algorithms, which has grown to be a thriving international discipline, is the unifying theme underlying Knuth's well known book The Art of Computer Programming. More than 30 of the fundamental papers that helped to shape this field are reprinted and updated in the present collection, together with historical material that has not previously been published. Although many ideas come and go in the rapidly changing world of computer science, the basic concepts and techniques of algorithmic analysis will remain important as long as computers are used.

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Swarm Intelligence

Applications, Volume 3

Ying Tan

The Institution of Engineering and Technology, 2018

Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions.

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Swarm Intelligence

Innovation, new algorithms and methods, Volume 2

Ying Tan

The Institution of Engineering and Technology, 2018

Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions.

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Swarm Intelligence

Principles, current algorithms and methods, Volume 1

Ying Tan

The Institution of Engineering and Technology, 2018

Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions.

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Voices in the Code

A Story about People, Their Values, and the Algorithm They Made

David G. Robinson

Russell Sage Foundation, 2022

Algorithms—rules written into software—shape key moments in our lives: from who gets hired or admitted to a top public school, to who should go to jail or receive scarce public benefits. Such decisions are both technical and moral. Today, the logic of high stakes software is rarely open to scrutiny, and central moral questions are often left for the technical experts to answer. Policymakers and scholars are seeking better ways to share the moral decisionmaking within high stakes software—exploring ideas like public participation, transparency, forecasting, and algorithmic audits. But there are few real examples of those techniques in use.

In Voices in the Code, scholar David G. Robinson tells the story of how one community built a life-and-death algorithm in an inclusive, accountable way. Between 2004 and 2014, a diverse group of patients, surgeons, clinicians, data scientists, public officials and advocates collaborated and compromised to build a new kidney transplant matching algorithm—a system to offer donated kidneys to particular patients from the U.S. national waiting list. Drawing on interviews with key stakeholders, unpublished archives, and a wide scholarly literature, Robinson shows how this new Kidney Allocation System emerged and evolved over time, as participants gradually built a shared understanding both of what was possible, and of what would be fair. Robinson finds much to criticize, but also much to admire, in this story. It ultimately illustrates both the promise and the limits of participation, transparency, forecasting and auditing of high stakes software. The book’s final chapter draws out lessons for the broader struggle to build technology in a democratic and accountable way.

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Whoosh Goes the Market

Algorithms, Automation, and Alienation

Daniel Scott Souleles

University of Chicago Press, 2024

A vivid, fast-paced inside look at financial markets, the people who work on them, and how technology is changing their world (and ours).

Markets are messy, and no one knows this better than traders who work tirelessly to predict what they will do next. In Whoosh Goes the Market, Daniel Scott Souleles takes us into the day-to-day experiences of a team at a large trading firm, revealing what it’s actually like to make and lose money on contemporary capital markets.

The traders Souleles shadows have mostly moved out of the pits and now work with automated, glitch-prone computer systems. They remember the days of trading manually, and they are suspicious of algorithmically driven machine-learning systems. Openly musing about their own potential extinction, they spend their time expressing fear and frustration in profanity-laced language. With Souleles as our guide, we learn about everything from betting strategies to inflated valuations, trading swings, and market manipulation. This crash course in contemporary finance vividly reveals the existential anxiety at the evolving front lines of American capitalism.

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