This paper explores how accountability might make otherwise obscure and inaccessible algorithms available for governance. The potential import and difficulty of accountability is made clear in the compelling narrative reproduced across recent popular and academic reports. Through this narrative we are told that algorithms trap us and control our lives, undermine our privacy, have power and an independent agential impact, at the same time as being inaccessible, reducing our opportunities for critical engagement. The paper suggests that STS sensibilities can provide (...) a basis for scrutinizing the terms of the compelling narrative, disturbing the notion that algorithms have a single, essential characteristic and a predictable power or agency. In place of taking for granted the terms of the compelling narrative, ethnomethodological work on sense-making accounts is drawn together with more conventional approaches to accountability focused on openness and transparency. The paper uses empirical material from a study of the development of an “ethical,” “smart” algorithmic videosurveillance system. The paper introduces the “ethical” algorithmic surveillance system, the approach to accountability developed, and some of the challenges of attempting algorithmic accountability in action. The paper concludes with reflections on future questions of algorithms and accountability. (shrink)

Feyerabrend argues that intellectual progress relies on the creativity of the scientist, against the authority of science.

Part of understanding the meaning and power of algorithms means asking what new demands they might make of ethical frameworks, and how they might be held accountable to ethical standards. I develop a definition of networked information algorithms as assemblages of institutionally situated code, practices, and norms with the power to create, sustain, and signify relationships among people and data through minimally observable, semiautonomous action. Starting from Merrill’s prompt to see ethics as the study of “what we ought to do,” (...) I examine ethical dimensions of contemporary NIAs. Specifically, in an effort to sketch an empirically grounded, pragmatic ethics of algorithms, I trace an algorithmic assemblage’s power to convene constituents, suggest actions based on perceived similarity and probability, and govern the timing and timeframes of ethical action. (shrink)

Latour is a world famous and widely published French sociologist who has written with great eloquence and perception about the relationship between people, science, and technology. He is also closely associated with the school of thought known as Actor Network Theory. In this book he sets out for the first time in one place his own ideas about Actor Network Theory and its relevance to management and organization theory.

_Computational thinking cisely. Stating the difficulty of a problem accounts builds on the power and for the underlying power of the machine—the com- limits of computing puting device that will run the solution. We must processes, whether they are exe- consider the machine’s instruction set, its resource cuted by a human or by a constraints, and its operating environment. machine. Computational In solving a problem efficiently,, we might further methods and models give us ask whether an approximate solution is good (...) the courage to solve prob- enough, whether we can use randomization to our lems and design systems that no one of us would advantage, and whether false positives or false nega- be capable of tackling alone. Computational think- tives are allowed. Computational thinking is refor- ing confronts the riddle of machine intelligence: mulating a seemingly difficult problem into one we What can humans do better than computers? and know how to solve, perhaps by reduction, embed- What can computers do better than humans? Most ding, transformation, or simulation. fundamentally it addresses the question: What is Computational thinking is thinking recursively. It computable? Today, we know only parts of the is parallel processing. It is interpreting code as data answers to such questions. and data as code. It is type checking as the general- Computational thinking is a fundamental skill for ization of dimensional analysis. It is recognizing everyone, not just for computer scientists. To read- both the virtues and the dangers of aliasing, or giv- ing, writing, and arithmetic, we should add compu- ing someone or something more than one name. It tational thinking to every child’s analytical ability. is recognizing both the cost and power of indirect Just as the printing press facilitated the spread of the addressing and procedure call. It is judging a pro- three Rs, what is appropriately incestuous about this gram not just for correctness and efficiency but for vision is that computing and computers facilitate the aesthetics, and a system’s design for simplicity and spread of computational thinking. (shrink)