Algorithms: Technology, Culture, Politics develops a relational, situated approach to algorithms. It takes a middle ground between theories that give the algorithm a singular and stable meaning in using it as a central analytic category for contemporary society and theories that dissolve the term into the details of empirical studies. The book discusses algorithms in relation to hardware and material conditions, code, data, and subjects such as users, programmers, but also “data doubles”. The individual chapters bridge critical discussions on bias, exclusion, or responsibility with the necessary detail on the contemporary state of information technology. The examples include state-of-the-art applications of machine learning, such as self-driving cars, and large language models such as GPT. The book will be of interest for everyone engaging critically with algorithms, particularly in the social sciences, media studies, STS, political theory, or philosophy. With its broad scope it can serve as a high-level introduction that picks up and builds on more than two decades of critical research on algorithms.

The study of the effect of "exceptional" experiences and beliefs on health--including anomalous, placebo, or hypnotic healing and mystical, religious, transpersonal, and creative experiences--is attracting increasing academic and public interest. This collection of essays explores the nature of mind, its impact on the body, and the relationship between "exceptional" experiences and physical health, mental health, and the potential for other types of perception. Examining the influence of spiritual practices, mental imagery, and alternative healing methods such as Reiki and Johrei, the essays encourage the expansion of mental health practice to include the full range of exceptional experiences. By normalizing experiences that are often pathologized, this book recognizes that exceptional human experiences can and do have value for physical and mental health.

A nuanced account from a user perspective of what it’s like to live in a datafied world. We live in a media-saturated society that increasingly transforms our experiences, relations, and identities into data others can analyze and monetize. Algorithms are key to this process, surveilling our most mundane practices, and to many, their control over our lives seems absolute. In Living with Algorithms, Ignacio Siles critically challenges this view by surveying user dynamics in the global south across three algorithmic platforms—Netflix, Spotify, and TikTok—and finds, surprisingly, a more balanced relationship. Drawing on a wealth of empirical evidence that privileges the user over the corporate, Siles examines the personal relationships that have formed between users and algorithms as Latin Americans have integrated these systems into the structures of everyday life, enacted them ritually, participated in public with and through them, and thwarted them. Sometimes users follow algorithms, Siles finds, and sometimes users resist them. At times, users do both. Agency lies in the navigation of the spaces in-between. By analyzing what we do with algorithms rather than what algorithms do to us, Living with Algorithms clarifies the debate over the future of datafication and whether we have a say in its development. Concentrating on an understudied region of the global south, the book provides a new perspective on the commonalities and differences among users within a global ecology of technologies.

Children's Creative Music-Making with Reflexive Interactive Technology discusses pioneering experiments conducted with young children using a new generation of music software for improvising and composing. Using artificial intelligence techniques, this software captures the children’s musical style and interactively reflects it in its responses. The book describes the potential of these applications to enhance children’s agency and musical identity by reflecting players’ musical inputs, storing and creating variations on them. Set in the broader context of current music education research, it addresses the benefits and challenges of incorporating music technologies in primary and pre-school education. It is comprised of six main chapters, which cover the creation of children's own music and their musical selves, critical thinking skills and learner agency, musical language development, and emotional intent during creative music-making. The authors provide a range of straight-forward techniques and strategies, which challenge conceptions of ‘difficult-to-use music technologies’ in formal music education. These are supported by an informative collection of practitioner vignettes written by teachers who have used the software in their classrooms. Not only are the teachers’ voices heard here, but also those of children as they discover some of the creative possibilities of music making. The book also provides free access to a companion website with teacher forums and a large bank of activities to explore. A toolkit serves as a database of the teaching activities in which MIROR applications have been used and provides a set of useful ideas regarding its future use in a variety of settings. This book demonstrates that music applications based on artificial intelligence techniques can make an important contribution to music education within primary and pre-school education. It will be of key interest to academics, researchers and postgraduate students in the fields of music education, music technology, early years and primary education, teaching and learning, and teacher educators. It will also serve as an important point of reference for Early Years and Primary practitioners.

This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Conference on Inductive Logic Programming, ILP 2014, held in Nancy, France, in September 2014. The 14 revised papers presented were carefully reviewed and selected from 41 submissions. The papers focus on topics such as the inducing of logic programs, learning from data represented with logic, multi-relational machine learning, learning from graphs, and applications of these techniques to important problems in fields like bioinformatics, medicine, and text mining.

How computational methods can expand how we see, read, and listen to Holocaust testimony The Holocaust is one of the most documented—and now digitized—events in human history. Institutions and archives hold hundreds of thousands of hours of audio and video testimony, composed of more than a billion words in dozens of languages, with millions of pieces of descriptive metadata. It would take several lifetimes to engage with these testimonies one at a time. Computational methods could be used to analyze an entire archive—but what are the ethical implications of “listening” to Holocaust testimonies by means of an algorithm? In this book, Todd Presner explores how the digital humanities can provide both new insights and humanizing perspectives for Holocaust memory and history. Presner suggests that it is possible to develop an “ethics of the algorithm” that mediates between the ethical demands of listening to individual testimonies and the interpretative possibilities of computational methods. He delves into thousands of testimonies and witness accounts, focusing on the analysis of trauma, language, voice, genre, and the archive itself. Tracing the affordances of digital tools that range from early, proto-computational approaches to more recent uses of automatic speech recognition and natural language processing, Presner introduces readers to what may be the ultimate expression of these methods: AI-driven testimonies that use machine learning to process responses to questions, offering a user experience that seems to replicate an actual conversation with a Holocaust survivor. With Ethics of the Algorithm, Presner presents a digital humanities argument for how big data models and computational methods can be used to preserve and perpetuate cultural memory.

The individual consumer now wields more power than ever before, with increased exposure to global cultures and media. This means that customer perception is now critically important and as such must occupy the heart of any brand. This provides a wealth of opportunities to work with and adapt to customers' motivations, but at the same time presents a series of challenges around retaining their attention and fostering positive relationships with them. The secret of a brand's success often lies in its ability to respond nimbly to the unexpected adoption of its products or services - essentially its ability to surprise its consumers. To all intents and purposes, brands must continue to introduce innovative and intriguing experiences to customers so that they can remain differentiated from the herd and deliver a human message amongst increasingly automated and unremarkable communications. Developed from experience at the forefront of new branding developments at market-leading companies, and drawing on the lessons learned by cultivating start-ups with sponsors including Google, Customer Experience Branding expertly reviews the key considerations when devising brand strategy to introduce an element of newness and interest into customer interactions. Case studies are delivered from major brands that continually achieve this, including Apple, Starbucks, Virgin, LEGO, Google, GoPro, Uber, Instagram, KLM and Handelsbanken, and the Foreword has been provided by Sir Richard Branson, who has himself unfailingly responded to consumer need and overseen a remarkable portfolio over the years as a result.

As the power and sophistication of of 'big data' and predictive analytics has continued to expand, so too has policy and public concern about the use of algorithms in contemporary life. This is hardly surprising given our increasing reliance on algorithms in daily life, touching policy sectors from healthcare, transport, finance, consumer retail, manufacturing education, and employment through to public service provision and the operation of the criminal justice system. This has prompted concerns about the need and importance of holding algorithmic power to account, yet it is far from clear that existing legal and other oversight mechanisms are up to the task. This collection of essays, edited by two leading regulatory governance scholars, offers a critical exploration of 'algorithmic regulation', understood both as a means for co-ordinating and regulating social action and decision-making, as well as the need for institutional mechanisms through which the power of algorithms and algorithmic systems might themselves be regulated. It offers a unique perspective that is likely to become a significant reference point for the ever-growing debates about the power of algorithms in daily life in the worlds of research, policy and practice. The range of contributors are drawn from a broad range of disciplinary perspectives including law, public administration, applied philosophy, data science and artificial intelligence. Taken together, they highlight the rise of algorithmic power, the potential benefits and risks associated with this power, the way in which Sheila Jasanoff's long-standing claim that 'technology is politics' has been thrown into sharp relief by the speed and scale at which algorithmic systems are proliferating, and the urgent need for wider public debate and engagement of their underlying values and value trade-offs, the way in which they affect individual and collective decision-making and action, and effective and legitimate mechanisms by and through which algorithmic power is held to account.

Algorithmic Institutionalism is the first book to conceive algorithms as institutions in contemporary societies, focusing on different dimensions of how they structure decision-making and enact power relations. In many situations in contemporary societies, algorithms structure social interactions, resulting in patterns of action and human behavior in collective contexts. Almeida, Filgueiras, and Mendonca discuss how algorithms are gradually occupying an institutional space in societies, deciding on different aspects of social life and shaping collective and individual human behaviors. As institutions, algorithms work as decision systems that define what is allowed, hindered, facilitated, or made impossible as well as positions within society's organizational structures. Algorithmic institutionalism uses the perspective of institutional theories to explain the functioning of these decision systems and how they establish patterns and norms that affect human behavior and lead to deep changes in contemporary society. The book points to the challenges of political orders that are gradually institutionalized with algorithms, comprising new dynamics of interaction between humans and machines. These disruptive dynamics of interaction between humans and machines create new challenges related to the democratization of algorithms and the impasses that emerge with technological advancement through digital technologies. Providing an analytical framework for an adequate comprehension of the social and political implications of algorithmic systems, Algorithmic institutionalism applies this framework to make sense of recommendation systems, the platformization of governments, and the deployment of algorithms in security. It then addresses the challenge of developing approaches to democratize the new political order influenced by the global expansion of algorithmic decision-making, pointing to key democratic values that are relevant once we consider the construction of legitimate decisions in contemporary societies.