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Thinking critically about and researching algorithms

机译：批判性思考和研究算法

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More and more aspects of our everyday lives are being mediated, augmented, produced and regulated by software-enabled technologies. Software is fundamentally composed of algorithms: sets of defined steps structured to process instructions/data to produce an output. This paper synthesises and extends emerging critical thinking about algorithms and considers how best to research them in practice. Four main arguments are developed. First, there is a pressing need to focus critical and empirical attention on algorithms and the work that they do given their increasing importance in shaping social and economic life. Second, algorithms can be conceived in a number of ways -technically, computationally, mathematically, politically, culturally, economically, contextually, materially, philosophically, ethically -but are best understood as being contingent, ontogenetic and performative in nature, and embedded in wider socio-technical assemblages. Third, there are three main challenges that hinder research about algorithms (gaining access to their formulation; they are heterogeneous and embedded in wider systems; their work unfolds contextually and contingently), which require practical and epistemological attention. Fourth, the constitution and work of algorithms can be empirically studied in a number of ways, each of which has strengths and weaknesses that need to be systematically evaluated. Six methodological approaches designed to produce insights into the nature and work of algorithms are critically appraised. It is contended that these methods are best used in combination in order to help overcome epistemological and practical challenges.
机译：越来越多的日常生活被软件支持的技术调节，增强，产生和调节。软件从根本上由算法组成：一组定义的步骤，这些步骤构造为处理指令/数据以产生输出。本文综合并扩展了关于算法的新兴批判性思维，并考虑了如何在实践中对其进行最佳研究。提出了四个主要论点。首先，迫切需要将关键的和经验性的注意力集中在算法上，并且由于算法在塑造社会和经济生活中的重要性日益提高，它们所做的工作也越来越重要。其次，算法可以通过多种方式来构想-从技术，计算，数学，政治，文化，经济，语境，物质，哲学，伦理等方面来考虑-但最好理解为偶然性，本体论和执行性，并广泛地嵌入社会技术组合。第三，存在三个主要挑战，阻碍了对算法的研究（获得对它们的表达的访问权；它们是异构的并且被嵌入更广泛的系统中；它们的工作在上下文和情况上不断地展开），这需要实际和认识论的关注。第四，可以通过多种方法对算法的组成和工作进行经验研究，每种方法都有其优缺点，需要系统地评估。严格评估了六种方法方法，这些方法旨在深入了解算法的性质和工作。认为最好将这些方法结合使用，以帮助克服认识论和实际挑战。

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