Georas analyzes different dilemmas that arise when we use robots to serve humans living in the digital age. She focuses on the design and deployment of carebots in particular, to explore how they are embedded in more general multifaceted material and discursive configurations, and how they are implicated in the construction of humanness in socio-technical spaces. In doing so, she delves into the "fog of technology," arguing that this fog is always also a fog of inequality since the emerging architectures of our digitized lives will connect with pre-existing forms of domination. In this context, resistive struggles are premised upon our capacity to dissent, which is what ultimately enables us to express our humanity and at the same time makes us unpredictable. What it means to be human in the digital world is thus never fixed, but, Georas argues, must always be strategically reinvented and reclaimed, since there always will be people living on the “wrong side of the digital train tracks” who will be unjustly treated.

In Chapter1, it was explained how linear approximations can be used to set up key-recovery attacks using Matsui’s Algorithm 1 or 2. This chapter takes a closer look at Algorithm 2 and its improvements. The most important improvement, and the main topic of this chapter, is the “fast Fourier transformation method.”

Millar and Gray argue that mobility shaping is raising a set of unresolved ethical, political, and legal issues that have significant consequences for shaping human experience in the future. By way of analogy, they unpack how these emerging issues in mobility echo those that have been asked in the more familiar context of net neutrality. They then apply some of the ethical and legal reasoning surrounding net neutrality to the newly relevant algorithmically controlled mobility space. They conclude that we can establish and ensure a just set of principles and rules for shaping mobility in ways that promote human flourishing by extending some of the legal and regulatory framework around net neutrality to mobility providers.

Chapter 11 reconstructs the theory of linear cryptanalysis from a more general point of view. To do this, we need to cover some mathematical ground. We first discuss linear algebra over the field of complex numbers, and then turn to the Fourier analysis of functions on a finite Abelian group. Both of these topics play a central role in Chapter 11.

Determining the effectiveness of linear cryptanalysis is an application of statistical theory. In this chapter, we review some basic concepts from statistics and discuss how they are used to estimate the cost of linear attacks, and Matsui’s second algorithm in particular.

Traditionally, linear cryptanalysis exploits linear approximations with atypically high absolute correlation. In this chapter, we discuss instead how linear approximations with correlation zero can be used. This variant of linear cryptanalysis is called zero-correlation linear cryptanalysis.

If more than one good linear approximation is available, then it is natural to try to exploit all of them simultaneously. This is called multiple linear cryptanalysis. The first part of this chapter discusses multiple linear cryptanalysis in general. The second part focuses on the special case with a set of masks that forms a vector space, which is called multidimensional linear cryptanalysis.

Finding linear trails with high absolute correlation quickly becomes tedious work, especially for ciphers with a more complicated structure than the example that we have worked with so far. Since the total number of trails is finite, finding linear trails with a maximal absolute correlation is an example of a combinatorial optimization problem. This chapter discusses three commonly used optimization methods: Matsui’s branch and bound method, mixed-integer linear programming, and satisfiability or satisfiability modulo theories. At the same time, the chapter introduces two additional example ciphers that follow a different design strategy.

Lyon uses the COVID epidemic to think about the instrumentalizing role of surveillance capitalism in digital society. He argues that the tech solutionism proffered by tech companies during the pandemic too often implied that democratic practices and social justice are at least temporarily dispensable for some greater good, with disastrous consequences for human flourishing. As a counterpoint, Lyon uses the notion of an ethics of care as a way to refocus on the importance of articulating the conditions that will enable the humans who live in datafied societies to live meaningful lives. He then offers Eric Stoddart’s notion of the “common gaze” to begin to imagine what those conditions might be. From this perspective, surveillance can be conceptualized as a gaze for the common good with a “preferential optic” focused on the conditions that will alleviate the suffering of the marginalized.

Murakami Wood makes both an empirical and a theoretical contribution by analysing the discourses contained in smart city marketing materials to create a detailed description of the kind of human that smart city developers and promoters envision as smart city residents. The resulting portrait of the “platform human” – a being whose entrepreneurial and libertarian needs are seamlessly enabled by technology built into the lived environment – is informed by a technologically-enabled notion of class, a particular and specific political identity of smart citizens as property-owning, entrepreneurial, and libertarian, and a generic environmental ‘goodness’ associated with smart platforms. The combination of these three elements resonates strongly with transhumanist speciation where humans are imagined as data-driven, surveillant, and robotic.