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The desirability of computers making moral decisions poses an array of future dangers that are difficult to anticipate but will, nevertheless, need to be monitored and managed. Public policy and mechanisms of social and business liability management will both play a role in the safety, direction, and speed in which artificial intelligent systems are developed. Fear is not likely to stop scientific research, but it is likely that various fears will slow it down. Mechanisms for distinguishing real dangers from speculation and hype fueled by science fiction are needed. This chapter surveys ways of addressing issues of rights and accountability for (ro)bots and touches on topics such as legal personhood, self‐replicating robots, the possibility of a “singularity” at which AI outstrips human intelligence, and the transhumanist movement that sees the future of humanity itself as an inevitable (and desirable) march toward cyborg beings.

The classical view of viruses as intracellular parasites requiring available molecular machinery to replicate themselves suggests that they can be considered as some sort of program. In this context, viruses would mainly be considered as encapsulated pieces of software, to be executed by the cellular host hardware. The function that is being executed is a computation, and using this concept will be extremely useful in the exploration of viruses as computational objects. The notion of a general machine capable of performing computations was formalized in theoretical terms by British mathematician Alan Turing. This chapter discusses viruses as replicating machines, viruses as phases of matter, evolving genome reduction, the space of replicators, adaptation at high-mutation rates, viral quasispecies, and critical genome size.

The complexity of the living world can be described as a series of evolutionary transitions. A subset of these are the ETIs (evolutionary transitions in individuality), the theory of which explains how individuals of one kind go through cycles of conflict, conflict mediation and cooperation to eventually become individuals of another kind. The theory of ETIs and multilevel selection can be applied to the origin of life. The interpretive view expanded on in this chapter, is not only of epistemic value but it is helpful to explain the increase in genetic information that was essential for more complex life to evolve. At the origin of life, lower-level replicating units (LRUs) cooperated to form higher-level replicating units (HRUs) from which the simplest proto-cells emerged. Trade-offs in reproduction and viability and task allocation between individuals at the lower level facilitated the transfer of fitness to higher level individuals. Where possible, exemplars of LRUs (like mobile genetic elements) and HRUs (primitive, but functionally integrated groups of ribozymes and/or genes) are used for explanatory purposes.

DNA metabarcoding generates huge amounts of data containing noise introduced by molecular methods. Chapter 8 “DNA metabarcoding data analysis” discusses the analytic steps and available software to curate and evaluate DNA metabarcoding data prior to final ecological analyses. It provides command lines to perform primary analyses of Illumina sequencing data with the OBITools, ranging from read assignment to samples to the formation of molecular operational taxonomic units (MOTUs) and their assignment to a taxon through comparison against reference databases. Chapter 8 also develops several methods to further curate sequencing data from contaminants or dysfunctional PCRs by using DNA extraction, PCR, and sequencing blank controls as well as PCR/biological replicates. It also presents several classical analyses to ensure that the diversity of the sample or the study site is appropriately covered. Finally, this chapter considers what conclusions on biodiversity and ecological processes can be really drawn from metabarcoding data.

This chapter discusses an in-depth example of an Artificial Chemistry. This algorithmic chemistry is based on the matrix calculus of Mathematics and is used to explore the simplicity of AC formalisms, together with the rich complexity of the resulting chemistry. It starts with the general formalism and then discusses the most simple non-trivial example of a chemistry based on 2x2 matrices of the N=4 system. Next is the considerably more complex 3x3 matrices N=9 system, with already 511 different species. After introducing higher N systems, including a mutation operation, the chapter concludes with an summary.

This chapter examines the battle for control between patent owners and purchasers of patented devices. By proclaiming users who violated the use restrictions as patent infringers, patent owners impose various kinds of conditions on purchasers’ use of their devices. The Supreme Court adhered to the principle of patent exhaustion and held in an 1852 case that once a patented good was sold, the patent owner could not interfere with the rights of purchasers to use it in the “ordinary pursuits of life.” While the Court stood firmly behind this principle for over 150 years, in recent years, with technological innovations like self-replicating technologies and with the development of international commerce, the common law principle of patent exhaustion is under attack. It remains to be seen how the Supreme Court will address the issue of patent exhaustion in future cases.

This chapter discusses the assembly of a minimal self-replicating protocell. It centers on the minimal thermodynamic coupling between the three functional structures: container, metabolism, and genes. The potential practical applications of minimal protocells are also discussed.

This chapter examines the development of non-enzymatic self-replicating systems based on nucleotidic and nonnucleotidic precursors. It discusses issues concerning nucleic acid replicators, chemical ligation to self-replication, competition and cooperation in nonenzymatic self-replicating systems, and replication in non-nucleotidic model systems. The chapter concludes with an outlook toward exponential replication.

This chapter looks at the ethological relations of digital culture and software through an example of feminist media art, Lynn Hershman-Leeson’s film Teknolust (2002). This film is an unusual intervention into the practices and representations of biodigitality in the 1990s. It depicts scientist Rosetta Stone and her creation of three self-replicating automatons (SRAs) modeled on her image. The theme of biodigitality is buried in a micro-level analysis of relations, affects, and “cuddling,” which is a repeated feature of the film. The SRAs can be seen as similar to exploration machines that analyze the gaps and undefined spaces between humans, machines, and biological life in general. The film works through a certain network of sexuality that shifts from human-centric reproduction to “bacterial sex,” with emphasis on sexuality as an effort towards the becoming-insect and becoming-machinic ideas included in Gilles Deleuze’s feminism.

Research in urban evolution requires that the features of cities are accurately captured for input into evolutionary models. Until recently, the evolutionary effects of cities have often been addressed using single sites, dichotomous urban–rural contrasts or, to a lesser extent, using urban gradients. However, urbanization does not produce a homogenous spatial continuum: cities are highly heterogeneous environments, with sharp and often non-linear environmental changes related to the amount of impervious surface, green vegetation, air pollution, light, noise, or contrasted temperature profiles. The comprehensive quantification of urban heterogeneity in space and time is essential for exploring the origins of organismal variation and adaptation in cities, and to best identify the strength and directionality of selective pressures and neutral processes occurring in populations of urban organisms. This chapter reviews frameworks that can be used to describe and quantify urbanization—these include classical ecological frameworks, the understudied temporal dimension of urban evolutionary biology, and the concept of replicated insight into urban-driven evolutionary processes. The chapter further discusses how axes of variation capturing the urban environment can be quantified with univariate and multivariate approaches, and presents quantitative results on how urbanization is captured in published studies of urban evolution. Finally, it discusses study design and statistical approaches of interest when testing for urban evolution: these include the question of model selection and variable fitting, spatial autocorrelation, and appropriate scale use in studies of urban evolution.