The emergence of large-scale social media systems, such as Wikipedia, Facebook, and Twitter, has given rise to a new multi-disciplinary effort based around the concept of social machines. For the most part, this research effort has limited its attention to the study of Web-based systems. It has also, perhaps unsurprisingly, tended to highlight the social scientific relevance of such systems. The present paper seeks to expand the scope of the social machine research effort to encompass the Internet of Things. One (...) advantage of this expansion is that it helps to reveal some of the links between the science of social machines and the sciences of the mind. A second advantage is that it furthers our conceptual understanding of social machines and supports the quest to derive a philosophically-robust definition of the term “social machine.” The results of the present analysis suggest that social machines are best conceived as systems in which a combination of social and technological elements play a role in the mechanistic realization of system-level phenomena. The analysis also highlights the relevance of cognitive science and the philosophy of mind to our general understanding of systems that transcend the cyber, physical, and social domains. (shrink)

Social machines are a prominent focus of attention for those who work in the field of Web and Internet science. Although a number of online systems have been described as social machines, there is, as yet, little consensus as to the precise meaning of the term “social machine.” This presents a problem for the scientific study of social machines, especially when it comes to the provision of a theoretical framework that directs, informs, and explicates the scientific and engineering activities of (...) the social machine community. The present paper outlines an approach to understanding social machines that draws on recent work in the philosophy of science, especially work in so-called mechanical philosophy. This is what might be called a mechanistic view of social machines. According to this view, social machines are systems whose phenomena are explained via an appeal to socio-technical mechanisms. We show how this account is able to accommodate a number of existing attempts to define the social machine concept, thereby yielding an important opportunity for theoretical integration. (shrink)

In the age of ubiquitous computing and artificially intelligent applications, social machines serves as a powerful framework for understanding and interpreting interactions in socio-algorithmic ecosystems. Although researchers have largely used it to analyze the interactions of individuals and algorithms, limited attempts have been made to investigate the politics in social machines. In this study, I claim that social machines are per se political machines, and introduce a five-point framework for classifying influence processes in socio-algorithmic ecosystems. By drawing from scholars from (...) political theory, I use a notion of influence that functions as a meta-concept for connecting and comparing different conceptions of politics. In this way, I can associate multiple political aspects of social machines from a cybernetic perspective. I show that the framework efficiently categorizes dimensions of influence that shape interactions between individuals and algorithms. These categories are symbolic influence, political conduct, algorithmic influence, design, and regulatory influence. Using case studies, I describe how they interact with each other on online social networks and in algorithmic decision-making systems and illustrate how the framework is able to guide scientists in further research. (shrink)

Massive Open Online Courses (MOOCs) have, in recent years, become increasingly popular. An important challenge facing MOOCs is the ‘teacher bandwidth problem’: In the MOOC environment, where there are potentially hundreds of thousands of students, it is impossible for a few teachers to interact with individual students—there is not enough ‘teacher bandwidth’. According to Siemens and Downes’s theory of ‘connectivism’ (Siemens, 2004) one can make up for the lack of teacher bandwidth by relying on collaboration between students; philosophically speaking, however, (...) this theory is underdeveloped. In this paper, we consider the question of learner collaboration in online courses, and the theory of connectivism, from the perspective of social epistemology. We note the similarities between Siemens and Downes’s theory and virtue reliabilist theories of epistemic collaboration more broadly. Our paper has two main aims. First, we offer an illustration of how it is possible to conceptualise learner collaboration in online settings as analogous to collaboration between scientists. Second, we attempt to expand on and clarify what Siemens and Downes had in mind when they proposed the theory of connectivism. (shrink)

Within analytic philosophy, the existence of collective knowledge has been motivated by means of two apparently distinct, and in direct competition with one another, theoretical approaches: (i) the commitment model and (ii) the distributed model. This paper agues, however, that to fully account for collaborative knowledge—i.e., a special kind of collective knowledge—both models are required. In other words, there is at least one kind of collective knowledge, the account of which requires treating the two models not as competitors but as (...) complementary to each other. If that’s correct, not only can we gain a deeper understanding of the specifics surrounding collaborative knowledge but also a clearer picture of the broader debate surrounding collective knowledge. (shrink)

Memory technologies are cultural artifacts that scaffold, transform, and are interwoven with human biological memory systems. The goal of this article is to provide a systematic and integrative survey of their philosophical dimensions, including their metaphysical, epistemological and ethical dimensions, drawing together debates across the humanities, cognitive sciences, and social sciences. Metaphysical dimensions of memory technologies include their function, the nature of their informational properties, ways of classifying them, and their ontological status. Epistemological dimensions include the truth-conduciveness of external memory, (...) the conditions under which external memory counts as knowledge, and the metacognitive monitoring of external memory processes. And lastly, ethical and normative dimensions include the desirability of the effects memory technologies have on biological memory, their effects on self and culture, and their moral status. Whilst the focus in the article is largely philosophical and conceptual, empirical issues such as the way we interact with memory technologies in various contexts are also discussed. We thus take a naturalistic approach in which philosophical and empirical concepts and approaches are seen as continuous. (shrink)

In this philosophical exploration, we investigate the concept of robotic moral environment interaction. The common view understands moral interaction to occur between agents endowed with ethical and interactive capacities. However, recent developments in moral philosophy argue that moral interaction also occurs in relation to the environment. Here conditions and situations of the environment contribute to human moral cognition and the formation of our moral experiences. Based on this philosophical position, we imagine robots interacting as moral environments—a novel conceptualization of human–robot (...) moral interaction with an inherent capacity for moral augmentation. To explicate this idea, we first define moral environments as moral systems providing moral affordances. We then intuit and explicate two constitutive conditions of moral environments: the environment’s moral ambiance and its moral atmosphere and compare them with real-life cases of moral environments—the moral landmarks. Based on these explications, we construct several explanatory cases to illustrate robots interacting as moral environments. Lastly, we set to evaluate the ethical challenges and wider social ramifications of using moral environment robots in the public space. (shrink)

One can know how to ride a bicycle, play the cello, or collect experimental data. But who can know how to properly ride a tandem bicycle, perform a symphony, or run a high-energy physics experiment? Reductionist analyses fail to account for these cases strictly in terms of the individual know-how involved. Nevertheless, it doesn't follow from non-reductionism that groups possess this know-how. One must first show that epistemic extension cannot obtain. This is the idea that individuals can possess knowledge even (...) when others possess some of the epistemic materials generating it. I show that only knowledge-that can be epistemically extended, not knowledge-how. Appeal to epistemic extension is a viable way of avoiding group knowledge-that ascriptions but not group knowledge-how ascriptions. Therefore, groups can know how. (shrink)

I connect two increasingly popular ideas in social epistemology—group knowledge and epistemic extension—both departures from mainstream epistemological tradition. In doing so, I generate a framework for conceptualizing and organizing contemporary epistemology along several core axes. This, in turn, allows me to delineate a largely unexplored frontier in group epistemology. The bulk of extant work in group epistemology can be dubbed intra-group epistemology: the study of epistemically salient happenings within groups. I delineate and attempt to motivate what I dub inter-group epistemology: (...) the study of epistemically salient happenings between groups and other subjects and entities. (shrink)