In Weaving the Web (2000), Berners-Lee defines Social Machines as biotechnologically hybrid Web-processes on the basis of which, “high-level activities, which have occurred just within one human’s brain, will occur among even larger more interconnected groups of people acting as if the shared a larger intuitive brain” (201–202). The analysis and design of Social Machines has already started attracting considerable attention both within the industry and academia. Web science, however, is still missing a clear definition of what a Social Machine is, which has in turn resulted in several calls for a “philosophical engineering” (Halpin 2013; Hendler & Berners-Lee 2010); Halpin et al. 2010). This paper is a first attempt to respond to this call, by combining contemporary philosophy of mind and cognitive science with epistemology. The idea of philosophical engineering implies that a sufficiently good conception of Social Machines should be of both theoretical and practical advantage. To demonstrate how the present approach can satisfy both objectives it will be used in order to address one of Wikipedia’s (the most famous Social Machine to date) most worrying concerns—i.e., the current and ongoing decline in the number of its active contributors (Halfacker et al. 2012).
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Remarks to the same effect can be found in several passages throughout the book. See for example pp. 63 and 169.
Take for example SOCIAM (http://sociam.org)--a collaboration between Southampton, Oxford and Edinburgh universities, set to explore the nature of Social Machines. Or consider the Smart Society Project (http://www.smart-society-project.eu)--a collaboaration between the University of Trento, University of Edinburgh, U-Hopper s.r.l., German Research Centre for Artificial Intelligence, University of Oxford, Ben-Gurion University of the Negev, Imaginary s.r.l, University of Karlstad, Vienna University of Technology and University of Southampton, whose goal is to understand and design hybrid systems where people and machines can work tightly together to build smarter societies.
Facebook, mySpace and twitter are social networking websites where users can post, share and ‘like’ comments and online content. Galaxy Zoo is a citizen science project that enlists members of the public to assist with the morphological classification of large number of galaxies. Wikipedia is a free online encyclopedia that allows its users to edit almost any article accessible. Intellipedia is an online system for collaborative data sharing used by the United States Intelligence Community.
See also (Shani 2013), whose view—viz., moderate active externalism—is similar to what we here call the hypothesis of extended cognition (though note that Shani’s arguments do not so heavily rely on DST, and his view is stronger than the hypothesis of extended cognition in that it denies—instead of remaining silent on the matter—the extension of (common-sense functionalist) mental states. For more details on why common-sense functionalism is necessary for the extended mind thesis, but not the extended and distributed cognition hypotheses, see (Palermos 2014a and (Palermos 2016). Though note, again, that the hypotheses of extended and distributed cognition are neither incompatible with common-sense functionalism, nor anti-functionalist on the whole. In so far as a cognitive process is a function, these two hypotheses are compatible with functionalism.
To preempt a possible worry, here, the relevant reciprocal interactions need only be continuous during the operation of the relevant coupled cognitive system and the unfolding of any processes related to it. For example, if, as part of her job and during normal working hours, individual S participates in distributed cognitive system X, S does not need to continuously interact with the other members of X, when she is at home. However, whenever X is in operation, S must continuously and reciprocally interact with the rest of the X-members. For a detailed explanation of why the existence of non-linear relations that arise out of reciprocal interactions between agents and their artifacts ensures the existence of distributed cognitive systems see Palermos 2016.
An anonymous referee worries that the criterion of mutual interactivity on the basis of feedback loops cannot deal with the ‘cognitive bloat’ worry. That is, if that’s all that is required for extended and distributed cognition to arise then we will end up with a cognitive bloat whereby cognition will seem like leaking in implausibly many directions—i.e., we will have to postulate an implausible number of extended and distributed cognitive systems. To solve this problem the referee suggests reintroducing the common sense functionalist criteria of trust, reliability, availability and past endorsement as introduced by Clark and Chalmers (1998). The following paragraph and fn. 7 demonstrate how the ongoing feedback loops criterion can handle the cognitive bloat worry within the context of the hypothesis of distributed cognition without such additional criteria. In (Palermos 2014a) there is also a detailed analysis on how the feedback loops criterion suffices, on its own, to overcome the cognitive bloat worry, by providing a clear distinction between the hypothesis of extended cognition and the hypothesis of embedded cognition.
This may raise a possible concern with other forms of interpersonal communication that potentially involve dense mutual interactivity between the involved parties, such as in the case of dialogue. Could such cases of interpersonal communication qualify as instances of collective cognition? Interestingly, a number of authors (Fusaroli, Gangopadhyay and Tylen, 2013; Fusaroli, Raczaszek-Leonardi and Tylen 2013) have recently suggested that dialogue between two individuals can, many times, qualify as a case of distributed cognition. This could potentially lead to a cognitive bloat (Rowlands 2009) whereby any form of communication between two individuals would qualify as giving rise to a distributed cognitive system. As noted above, however, not all instances of interpersonal communication will satisfy the criterion of mutual interactivity. Put simply, not all interpersonal communication is a form of dialogue. In their paper, Fusaroli, Gangopadhyay and Tylen provide essentially the same response:
"Not all conversational arrays automatically come to constitute interpersonal synergies. This requires a certain level of skillful linguistic engagement. As evident from the empirical studies reviewed, synergy effects can be achieved to a lower or higher degree. In other words, interlocutors can become more or less close to an ideal model of dialogical mind according to the dymanics at play. Importantly, we also suggest a possible mechanism for the creation and maintenance of dialogical minds: the co-construction of interactional routines, such as the context-sensitive alignment of expressive behavior" (Fusaroli, Gangopadhyay and Tylen, 2013).
For a detailed defense of group properties and entities on the basis of a naturalized version of emergence, see Palermos 2016.
This is the main tenet of what is known within contemporary epistemology as ‘virtue reliabilism.’ A historically prior but weaker alternative is ‘process reliabilism’ according to which in order for a belief-forming process to count as knowledge conducive, it only needs to be reliable, independently of whether it may count as a cognitive ability or not (for an overview of reliabilism see Goldman and Beddor 2015). Given that process reliabilism is not concerned with whether the relevant process may count as a cognitive ability, it also neglects the concept of cognitive integration, which is the present paper’s main philosophical focus and key for designing Social Machines that could qualify as distributed cognitive systems (see also fn. 13).
Elsewhere (Palermos 2011, Palermos 2014b), it has been argued that both theories also put forward the same broad, common sense functionalist intuitions on what is required from a process to count as a cognitive ability. Briefly, both views state that the process must be (a) normal and reliable, (b) one of the agent’s habits/dispositions and (c) integrated into the rest of the agent’s cognitive character/system.
Recently there has been a number of process reliabilist attempts to account for knowledge that is produced on the basis of epistemic artifacts or in a socially distributed fashion. For example Goldberg (2010) has put forward the extendedness hypothesis, Goldman (2014) has proposed social process reliabilism and Michaelian and Arango Muñioz (Michaelian 2014; Michaelian and S. Arango-Muñoz 2016 have offered the alternative of distributed reliabilism. An anonymous referee therefore wonders why I here choose to focus on virtue reliabilism as opposed to process reliabilism. The main reason has to do with the paper’s main claim that there is a way to design Social Machines such that their socio-epistemic properties can be viewed as the cognitive properties of a distributed cognitive system. In contrast to virtue reliabilism, traditional forms of process reliabilism (and presumably the above derivative accounts) explicitly state that cognition resides strictly within the head or organism of individual agents. Accordingly, it would be hard to motivate, on the basis of process reliabilism, the claim that TMSs or Social Machines are cognitive systems in Berners-Lee’s sense. The contrast between the above process reliabilist accounts and virtue reliabilism, when it comes to explaining extended and distributed knowledge, becomes most evident with respect to the issue of epistemic responsibility. Michaelian and Muñoz write for example: Assignments of credit and responsibility for cognitive success and failure “presuppose a richer notion of agency: what we might refer to as responsible cognitive agency, where responsible cognitive agency requires cognitive agency, plus responsibility. There is no clear sense in which a TMS, for example, might be assigned responsibility for its cognitive success and failures, and it is in this sense we have suggested that extended and distributed memory systems do not qualify as cognitive agents.” Process reliabilism therefore can’t account for distributed epistemic responsibility, which is a reason to suggest that the relevant distributed system cannot qualify as a cognitive agent. In contrast, as the above indicates, virtue reliablism employs the notion of cognitive integration in order to not only account for epistemic responsibility but also explain how the resulting epistemic responsibility belongs to an extended or even distributed cognitive system as a whole. This renders virtue reliabilism a significantly more promising candidate for explaining how Social Machines can be designed in order to qualify as epistemic cognitive systems in themselves. Perhaps, however, a modified version of distributed process reliabilism along the lines suggested by (Michaelian 2014; Michaelian and S. Arango-Muñoz 2016) could provide the resources for conceptualizing distributed agents as proper cognitive—qua responsible—agents, but such an approach would require departing from the more traditional accounts of process reliabilism that restrict cognition within the head of individual cognitive agents.
For a recent review on TVSS, see Bach-y-Rita and Kercel (2003). For a full account of how sensorimotor knowledge is constitutive of perception see (Noë 2004). “The basic claim of the enactive approach is that the perceiver’s ability to perceive is constituted (in part) by sensorimotor knowledge (i.e. by practical grasp of the way sensory stimulation varies as the perceiver moves).” (Noë 2004, 12) “What the perception is, however, is not a process in the brain, but a kind of skillful activity on the part of the animal as a whole”. (Noë 2004, 2). “Perception is not something that happens to us or in us, it is something we do”. (Noë 2004, 1). Sensorimotor dependencies are relations between movements or change and sensory stimulation. It is the practical knowledge of loops relating external objects and their properties with recurring patterns of change in sensory stimulation. These patterns of change may be caused by the moving subject, the moving object, the ambient environment (changes in illumination) and so on.
The above points regarding the emergence of TMSs may create the impression that distributed cognitive systems need time to develop a sufficiently integrated structure. Nevertheless, any of the above preconditions to cognitive integration may in principle be very quickly realized within a group, provided that the appropriate socio-technical system is in place. It is true, however, that as time goes by, self-organising systems, such as distributed cognitive systems, can increase their efficiency by adapting to the conditions of the dynamic environments in which they operate. Currently, most distributed cognitive systems would need some time before achieving an appropriate degree of integration, but this does not mean that we could not possibly design socio-technical systems that would be very quick to achieve the required state or even start with it by default.
At least with respect to a wide range of scientific topics. See (Giles 2005). See also encyclopedia Britannica’s response (http://corporate.britannica.com/britannica_nature_response.pdf) and Nature’s counter response (http://www.nature.com/press_releases/Britannica_response.pdf).
All numbers refer to English Wikipedia alone.
Contrary to what I claim above it may be thought that Wikipedia can keep its quality high merely on the basis of bots. But this is overly optimistic as to what bots can do and underestimates the difficulty and degree of understanding what is required for completing the task. For example, while a bot can detect that an entry lacks a sufficient amount of references, it could not possibly assess the reliability and the appropriateness of the references provided. Indicatively see Metz’s article ‘Wikipedia Deploys AI to Expand its Ranks of Human Editors’, published at WIRED: http://www.wired.com/2015/12/wikipedia-is-using-ai-to-expand-the-ranks-of-human-editors/?mbid=social_fb
These points can help disambiguate what may constitute the distributed cognitive system of Wikipedia. An anonymous referee worries that we may have to accept that Wikipedia and all of its creators and users across time constitute a single distributed cognitive system. This seems to be rather implausible and unlike the paradigm distributed cognitive system in the literature—i.e., the crew-members of a ship as it performs near land manoeuvres (Hutchins 1995). In contrast to the navy ship, where all members are involved in the on-going process of navigating the ship, not all of Wikipedia’s creators and users are involved in Wikipedia’s on-going processes. To address this worry, we need to keep in mind that systems are individuated on the basis of the processes we are interested in (for more details on system individuation see (Palermos 2014a) and (Palermos 2016)). In order to figure out what sort of system Wikipedia really is we need to look at what components are currently giving rise to the Wikipedia processes/properties that we are interested in, such as its overall reliability. Whatever components currently contribute to this process in a constitutive fashion (by mutually interacting with each other) can be considered as proper parts of Wikipedia’s distributed cognitive system. As indicated in the main text, this will primarily consist by the socio-techinical system that comprises of Wikipedia’s algorithm and its active contributors. As time goes by, different parts of this socio-technical system might be substituted with others (e.g., active contributors may come and go), but whatever (biological and technological) components give rise to Wikipedia’s reliability (by mutually interacting with each other) at any given time, they can be considered as constitutive parts of Wikipedia’s cognitive system at that time.
An anonymous referee raises the question of how Wikipedia could implement the suggested change in the way it operates. As Halfaker et al. (2012) report, Wikipedia is currently working on the basis of enforced formal policies. Most of them are decided by the board and stuff members of Wikimedia Foundation. A change in Wikipedia’s software, such as the one suggested here, would also require to go through Wikimedia’s system administrators https://meta.wikimedia.org/wiki/System_administrators.
Digg and reddit are entertainment, social news networking services. Their members can submit content, such as text posts or direct links. Registered users can then vote submissions up or down to organize the posts and determine their position on the sites’ pages.
Planet Hunters is another citizen science project that enlists members of the public to assist with finding planets.
To say that some cases of the available open innovation software do not qualify as Social Machines is not to deny that they are social systems. Moreover, some open innovation software may occasionally qualify as Social Machines, provided that the criterion of mutual interactions between the contributing members is satisfied. One such a case may well be the discovery of a new type of galaxies known as Green Pea galaxies, which started as a discussion in the internet forums of Galaxy Zoo, with he name "Give peas a chance", and in which various green objects were posted.
As Shadbolt et al. (2013) put it, “the key difference between social machines and open innovation is at the level of interaction between the social and the machine-driven processing components” (3).
Adams, F., & Aizawa, K. (2001). The bounds of cognition. Philosophical Psychology, 14(1), 43–64.
Adams, F., & Aizawa, K. (2010). The bounds of cognition (1st ed.). Malden, MA: Wiley-Blackwell.
Bach-y-Rita, P., & Kercel, S. W. (2003). Sensory substitution and the human-machine interface. Trends in Cognitive Science, 7(12), 541–6.
Barnier, A. J., Sutton, J., Harris, C. B., & Wilson, R. A. (2008). A conceptual and empirical framework for the social distribution of cognition: the case of memory. Cognitive Systems Research, 9(1–2), 33–51.
Berners-Lee, T., Fischetti, M., & Foreword By-Dertouzos, M. L. (2000). Weaving the Web: The original design and ultimate destiny of the World Wide Web by its inventor. Harper Information.
Berners-Lee, T., Hall, W., Hendler, J. A., O'Hara, K., Shadbolt, N., & Weitzner, D. J. (2006). A framework for web science. Foundations and trends in Web Science, 1(1), 1–130.
Black, P., Delaney, H., & Fitzgerald, B. (2007). Legal issues for wikis: the challenge of user-generated and peer-produces knowledge, content and culture. eLaw Journal, 14, 245.
BonJour, L. (1985). The Structure of Empirical Knowledge. Harvard University Press.
Braddon-Mitchell, D., & Jackson, F. (2006). Philosophy of mind and cognition: an introduction (2nd ed.). Malden, MA: Wiley-Blackwell.
Chemero, A. (2009). Radical embodied cognitive science. Cambridge: MIT Press.
Chi, E. H. (2008). The social web: research and opportunity. IEEE Computer, 41(9), 88–91.
Chisholm, R. M. (1977). Theory of knowledge. Prentice-Hall.
Clark, A. (1997). Being there: putting brain, body and world together again. Cambridge, Massachusetts, USA: MIT Press.
Clark, A. (2007). Curing cognitive hiccups: a defense of the extended mind. The Journal of Philosophy, 104, 163–192.
Clark, A. (2008). Supersizing the mind. Oxford University Press.
Clark, A., & Chalmers, D. (1998). The extended mind. Ananlysis, 58(1), 7–19.
Doan, A., Ramakrishnan, R., & Halevy, A. Y. (2011). Crowdsourcing systems on the world-wide web. Communications of the ACM, 54(4), 86–96.
Froese, T., Gershenson, C., & Rosenblueth, D.A. (2013). The dynamically extended mind. Retrieved http://arxiv.org/abs/1305.1958.
Giere, R. (2002a). Scientific cognition as distributed cognition. In P. Carruthers, S. Stitch, & M. Siegal (Eds.), Cognitive bases of science. Cambridge: Cambridge University Press.
Giere, R. (2002a). ‘Discussion Note: Distributed Cognition in Epistemic Cultures’. Philosophy of Science, 69.
Giere, R. (2006). The role of agency in distributed cognitive systems. Philosophy of Science, 73, 710–719.
Giere, R. (2007). Distributed cognition without distributed knowing. Social Epistemology, 21(3), 313–320.
Giere, R., & Moffat, B. (2003). Distributed cognition: where the cognitive and the social merge. Social Studies of Science, 33(2), 1–10.
Giles, J. (2005). Internet encyclopaedias go head to head. Nature, 438(7070), 900–901.
Goldberg, S. (2010). Relying on others: an essay in epistemology. Oxford: Oxford University Press.
Goldman, A. I. (2014). Social Process Reliabilism. In: Essays in Collective Epistemology, Lackey, J. (ed.), Oxford University Press.
Goldman, A. and Beddor, B. (2015). “Reliabilist Epistemology”, The Stanford Encyclopedia of Philosophy (Winter 2015 Edition), Edward N. Zalta (ed.), URL = <http://plato.stanford.edu/archives/win2015/entries/reliabilism/>.
Greco, J. (1999). Agent reliabilism. In J. Tomberlin (Ed.), Philosophical perspectives 13: Epistemology (pp. 273–296). Atascadero, CA: Ridgeview Press.
Greco, J. (2004). Knowledge as credit for true belief. In M. DePaul & L. Zagzebski (Eds.), Intellectual virtue: perspectives from ethics and epistemology. Oxford: Oxford University Press.
Greco, J. (2007). The nature of ability and the purpose of knowledge. Philosophical Issues, 17, 57–69.
Greco, J. (2010). Achieving knowledge: a virtue-theoretic account of epistemic normativity. Cambridge: Cambridge University Press.
Halfaker, A., Geiger, R. S., Morgan, J. T., & Riedl, J. (2012). The rise and decline of an open collaboration system: How Wikipedia’s reaction to popularity is causing its decline. American Behavioral Scientist, DOI: 0002764212469365.
Halpin, H. (2013). Does the web extend the mind? In: Proceedings of the 5th annual ACM web science conference (pp. 139–147). ACM.
Halpin, H., Clark, A., & Wheeler, M. (2010). Towards a philosophy of the web: representation, enaction, collective intelligence. In: Proceedings of the WebSci10: Extending the Frontiers of Society On-Line.
Hendler, J., & Berners-Lee, T. (2010). From the semantic Web to social machines: a research challenge for AI on the World Wide Web. Artificial Intelligence, 174(2), 156–161.
Heylighen, F., Heath, M., & Van Overwalle, F. (2007). The emergence of distributed cognition: Aconceptual framework. In Proceedings of collective intentionality IV (2004), Vol. IV. University of Siena.
Hutchins, E. (1995). Cognition in the wild. Cambridge: MIT Press.
Knorr, K. K. (1999). Epistemic cultures: how the sciences make knowledge. Cambridge, Mass: Harvard University Press.
Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: The University of Chicago Press.
Menary, R. (2007). Cognitive integration: mind and cognition unbound. Basingstoke: Palgrave McMillan.
Michaelian, K. (2014). JFGI: from distributed cognition to distributed reliabilism. Philosophical Issues, 24(1), 314–346.
Michaelian, K, & Arango-Muñoz, S. (2016). Collaborative memory knowlege: A distributed reliabilist perspective. In M. Meade, A. Barnier, P. Van Bergen, C. Harris, and J. Sutton (Eds.), Collaborative Remembering: How Remembering with Others Influences Memory. Oxford University Press, forthcoming.
Nersessian, N. J. (2005). Interpreting scientific and engineering practices: Integrating the cognitive, social, and cultural dimensions. In: Scientific and Technological Thinking, M. Gorman, R. Tweney, D. Gooding, & A. Kincannon, eds. (Erlbaum). pp. 17–56.
Nersessian, N. J. (2006). The cognitive-cultural systems of the research laboratory. Organization Studies, 27(1), 125–145.
Nersessian, N. J., Newstetter, W. C., Kurz-Milcke, E. & Davies, J. (2003). A Mixed-method Approach to Studying Distributed Cognition in Evolving Environments. Proceedings of the International Conference on Learning Sciences. pp. 307–314.
Nersessian, N. J., Kurz-Milcke, E., Newstetter, W. C., & Davies, J. (2003).Research laboratories as evolving distributed cognitive systems. Proceedings of The 25th Annual Conference of the Cognitive Science Society. pp. 857–862.
Noë, A. (2004). Action in perception. Cambridge, MA: MIT Press.
Noveck, B. S. (2007). Wikipedia and the future of legal education. Journal of Legal Education, 57, 3.
O’Hara, K. and Hall, W. (2008) Trust on the web: Some web science research challenges. UoC Papers: E-Journal on the Knowledge Society, 7.
Palermos, S. O. (2011). Belief-forming processes, extended. Review of Philosophy and Psychology, 2(4), 741–765.
Palermos, S. O. (2014a). Loops, constitution, and cognitive extension. Cognitive systems research, 27, 25–41.
Palermos, S. O. (2014b). Knowledge and cognitive integration. Synthese, 19(18), 1931–1951.
Palermos, S. O. (2015). Active externalism, virtue reliabilism and scientific knowledge. Synthese 192(9), 2955–2986
Palermos, S. O. (2016). The Dynamics of Group Cognition. Minds and Machines, forthcoming.
Papineau, David (2015). Naturalism. The Stanford Encyclopedia of Philosophy (Fall 2015 Edition), Edward N. Zalta (ed.), URL = <http://plato.stanford.edu/archives/fall2015/entries/naturalism/>.
Plantinga, A. (1993a). Warrant and proper function. New York: Oxford University Press.
Plantinga, A. (1993b). Warrant: the current debate. Oxford: Oxford University Press.
Pritchard, D. H. (2009). Knowledge. London: Palgrave Macmillan.
Pritchard, D. H. (2010a). Knowledge and understanding. In A. Haddock, A. Millar, & D. H. Pritchard (Eds.), The nature and value of knowledge: three investigations. Oxford: Oxford University Press.
Pritchard, D. H. (2010b). ‘Anti-Luck Virtue Epistemology’, manuscript, available at http://www.philosophy.ed.ac.uk/people/full-academic/duncan-pritchard.html.
Pritchard, D. (2010b). Cognitive ability and the extended cognition thesis. Synthese, 175, 133–151.
Rowlands, M. (1999). The body in mind: understanding cognitive processes. New York: Cambridge University Press.
Rowlands, M. (2009). Extended cognition and the mark of the cognitive. Philosophical Psychology, 22(1), 1–19.
Rupert, R. D. (2004). Challenges to the hypothesis of extended cognition. Journal of Philosophy, 101(8), 389–428.
Rupert, R. D. (2009). Cognitive systems and the extended mind (1st ed.). Oxford: OUP USA.
Shadbolt, N. R., Smith, D. A., Simperl, E., Van Kleek, M., Yang, Y., & Hall, W. (2013). Towards a classification framework for social machines. In Proceedings of the 22nd international conference on World Wide Web companion (pp. 905–912). International World Wide Web Conferences Steering Committee.
Shani, I. (2013). Making it mental: in search for the golden mean of the extended cognition controversy. Phenomenology and the Cognitive Sciences, 12(1), 1–26.
Smart, P. R. (2012). The web-extended mind. Metaphilosophy, 43(4), 446–463.
Smart, P. R. (2014). Embodiment, cognition and the World Wide Web. In L. Shapiro (Ed.), The Routlege handbook of embodied cognition. New York: Routlege.
Smart, P. R., & Shadbolt, N. R. (2014). Social machines. In M. Khosrow-Pour (Ed.), Encyclopedia of information science and technology (pp. 6855–6862). Hershey, Pennsylvania, USA: IGI Global.
Smart, P., Heersmink, R. & Clowes, R. (forthcoming). The Cognitive Ecology of the Internet. In: S. Cowley & F. Vallée-Tourangeau (eds.), Cognition Beyond the Brain: Computation, Interactivity and Human Artifice (2nd ed.). Dordrecht: Springer.
Sparrow, B., & Chatman, L. (2013). Social cognition in the internet age: same as it ever was? Psychological Inquiry, 24(4), 273–292.
Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: cognitive consequences of having information at our fingertips. Science, 333(6043), 776–778.
Steup, M. (1999). A Defense of Internalism. In: The Theory of Knowledge: Classical and Contemporary Readings, 2nd edition. Wadsworth Publishing.
Sutton, J. (2008). Between individual and collective memory: coordination, interaction, distribution. Social Research, 75(1), 23–48.
Sutton, J., Harris, C. B., Keil, P. G., & Barnier, A. J. (2010). The psychology of memory, extended cognition, and socially distributed remembering. Phenomenology and the Cognitive Sciences, 9(4), 521–560. doi:10.1007/s11097-010-9182-y.
Thagard, P. (1993). Societies of minds: science as distributed computing. Studies in History and Philosophy of Science Part A, 24(1), 49–67. doi:10.1016/0039-3681(93)90024-E.
Thagard, P. (1994). Mind, society, and the growth of knowledge. Philosophy of Science, 61(4), 629–645.
Thagard, P. (1997). Collaborative knowledge. Noûs, 31(2), 242–261. doi:10.1111/0029-4624.00044.
Theiner, G., & O’Connor, T. (2010). The emergence of group cognition. In A. Corradini & T. O’Connor (Eds.), Emergence in science and philosophy (pp. 6–78). London: Routledge.
Theiner, G., Allen, C., & Goldstone, R. (2010). Recognizing group cognition. Cognitive Systems Research, 11(4), 378–395.
Tollefsen, D. (2006). From extendedmind to collective mind. Cognitive Systems Research, 7(2–3), 140–150.
Tollefsen, D., & Dale, R. (2011). Naturalizing joint action: a process-based approach. Philosophical Psychology, 25, 385–407.
Wegner, D. (1986). Transactive memory: a contemporary analysis of the group mind. In B. Mullen & G. R. Goethals (Eds.), Theories of group behavior. New York: Springer.
Wegner, D., Giuliano, T., & Hertel, P. (1985). Cognitive interdependence in close relationships. In W. J. Ickes (Ed.), Compatible and incompatible relationships (pp. 253–276). New York: Springer.
Wilson, R. A. (2000). The mind beyond itself. In D. Sperber (Ed.), Metarepresentations: a multidisciplinary perspective (pp. 31–52). New York: Oxford University Press.
Wilson, R. (2004). Boundaries of the mind: the individual in the fragile sciences: cognition. New York: Cambridge University Press.
Wilson, R. (2005). Collective memory, group minds, and the extended mind thesis. Cognitive Processing, 6(4), 227–236.
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Palermos, S.O. Social machines: a philosophical engineering. Phenom Cogn Sci 16, 953–978 (2017). https://doi.org/10.1007/s11097-016-9489-4
- Social Machines
- Distributed cognition
- Active externalism
- Web science