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Social Machines Paradigm

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Keynote talk at the Web Science Summer School, Singapore, 8 December 2014. Today we see the rise of Social Machines, like Twitter, Wikipedia and Galaxy Zoo—where communities identify and solve their own problems, harnessing commitment, local knowledge and embedded skills, without having to rely on experts or governments.
The Social Machines paradigm provides a lens onto the interacting sociotechnical systems of our hybrid digital-physical world, citizen-centric and at scale—emphasising empowerment and sociality in a world of pervasive technology adoption and automation.
This talk will present the Social Machines paradigm as an approach to social media analytics and a rethinking of our scholarly practices and knowledge infrastructure.

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Social Machines Paradigm

  1. 1. The Social Machines Paradigm David De Roure
  2. 2. Overview 1. Shifts in scholarship 2. Social Machines 3. Knowledge Infrastructure
  3. 3. The Big Picture More people More machines Big Data Big Compute Conventional Computation “Big Social” Social Networks e-infrastructure Online R&D (Science 2.0) Social Machines @dder
  4. 4. Edwards, P. N., et al. (2013) Knowledge Infrastructures: Intellectual Frameworks and Research Challenges. Ann Arbor: Deep Blue. http://hdl.handle.net/2027.42/97552
  5. 5. Christine Borgman
  6. 6. theODI.org
  7. 7. F i r s t
  8. 8. http://www.parliament.uk/business/committees/committees-a-z/commons-select/science-and-technology-committee/news/report-responsible-use-of-data/
  9. 9. New Social Processes http://www.theguardian.com/uk/series/reading-the-riots
  10. 10. www.zooniverse.org
  11. 11. Talk Forum Scientists Image Classification Citizen Scientists data reduction
  12. 12. http://www.climateprediction.net/ http://onlinelibrary.wiley.com/doi/10.1002/qj.2455/abstract
  13. 13. Digital Music Collections Student-sourced ground truth Community Software Supercomputer Linked Data Repositories 23,000 hours of recorded music Music Information Retrieval Community SALAMI
  14. 14. Notifications and automatic re-runs Autonomic Curation Self-repair New research? Machines are users too
  15. 15. “In it” not “On it” In it not on it
  16. 16. 1. Shifts in scholarship 2. Social Machines 3. Knowledge Infrastructure
  17. 17. Social Machines Principles of Empowerment Real life is and must be full of all kinds of social constraint – the very processes from which society arises. Computers can help if we use them to create abstract social machines on the Web: processes in which the people do the creative work and the machine does the administration... The stage is set for an evolutionary growth of new social engines. The ability to create new forms of social process would be given to the world at large, and development would be rapid. 1 2 Berners-Lee, Weaving the Web, 1999 (pp. 172–175)
  18. 18. SOCIAM: The Theory and Practice of Social Machines is funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EPJ017728/1 and comprises the Universities of Southampton, Oxford and Edinburgh. See sociam.org
  19. 19. SOCIAM - Social Machines - will research into pioneering methods of supporting purposeful human interaction on the World Wide Web, of the kind exemplified by phenomena such as Wikipedia and Galaxy Zoo. These collaborations are empowering, as communities identify and solve their own problems, harnessing their commitment, local knowledge and embedded skills, without having to rely on remote experts or governments. http://sociam.org/
  20. 20. “Yet Wikipedia and its stated ambition to “compile the sum of all human knowledge” are in trouble. The volunteer workforce that built the project’s flagship, the English-language Wikipedia—and must defend it against vandalism, hoaxes, and manipulation— has shrunk by more than a third since 2007 and is still shrinking… The main source of those problems is not mysterious. The loose collective running the site today, estimated to be 90 percent male, operates a crushing bureaucracy with an often abrasive atmosphere that deters newcomers who might increase participation in Wikipedia and broaden its coverage…” http://www.technologyreview.com/featuredstory/520446/the-decline-of-wikipedia/
  21. 21. Pip Willcox
  22. 22. PRAISE: Performance and pRactice Agents Inspiring Social Education Mark d’Inverno http://goldsmiths.musiccircleproject.com/
  23. 23. http://socialmachines.media.mit.edu/ Digital networks have radically increased the speed and scope with which individuals can effect social change, transforming the relationship between people and institutions. But the impact to date of this transformation has been more disruptive and ad hoc, as opposed to constructive and systematic. Existing tools and practices for harnessing the potential of digital networks have failed to sustain a public sphere where institutions and individuals can come together to understand, learn and act constructively on societal problems. By building “social machines” that bring system solutions to such critical global challenges as gender equality and literacy learning, the Laboratory for Social Machines seeks to contribute to the creation of the next generation of the public sphere.
  24. 24. http://sociam.org/socm2015/
  25. 25. Trajectories... distinguished by purpose Trajectories through Social Machines https://sites.google.com/site/bwebobs13/
  26. 26. Kuhn cycle Normal Science – computer science is a puzzle-solving activity under our current paradigm, inspired by great achievements (in the left quadrants). Successful social machines, like Wikipedia, are the anomaly. They do not yield to standard techniques despite attempts to extend those techniques and fit social machines in as machines. cf Newtonian mechanics. We are in the period of crisis, where the failure of established methods permits us to experiment with new methods to crack the anomaly. We experiment with social machines as an underpinning model. If successful, social machines become the new paradigm and scientific revolution has occurred. This is evidenced by the papers and books that train the next generation.
  27. 27. 1. Shifts in scholarship 2. Social Machines 3. Knowledge Infrastructure
  28. 28. Web as lens Web as artefact Web Observatories http://www.w3.org/community/webobservatory/
  29. 29. A computationally-enabled sense-making network of expertise, data, software, models and narratives Iain Buchan
  30. 30. Towards interoperable observatories Technical and social interface http://www.w3.org/community/webobservatory/
  31. 31. The Web Observatory Tiropanis, T., Hall, W., Shadbolt, N., De Roure, D., Contractor, N., and Hendler, J. The web science observatory. IEEE Intelligent Systems 28, 2 (2013), 100–104.
  32. 32. The R Dimensions Research Objects facilitate research that is reproducible, repeatable, replicable, reusable, referenceable, retrievable, reviewable, replayable, re-interpretable, reprocessable, recomposable, reconstructable, repurposable, reliable, respectful, reputable, revealable, recoverable, restorable, reparable, refreshable?” @dder 14 April 2014 sci method access understand new use social curation Research Object Principles
  33. 33. Scholarly Machines David De Roure, JCDL 2013 Ecosystem
  34. 34. Richard O’Bierne
  35. 35. STORYTELLING AS A STETHOSCOPE FOR SOCIAL MACHINES 1. Sociality through storytelling potential and realization Zooniverse is a highly storified Social Machine 2. Sustainability through reactivity and interactivity Facebook doesn’t allow for improvisation 3. Emergence through collaborative authorship and mixed authority Wikipedia assigns authority rights rigidly Ségolène Tarte, David De Roure and Pip Willcox, (2014). Working out the plot: the role of stories in social machines http://ora.ox.ac.uk/objects/ora:8033
  36. 36. social machines social machines social machines Not just machines —try calling them socials
  37. 37. 1. Shifts in scholarship beyond the fourth paradigm – Crowd + Machines, and our automated future 2. Social Machines – Humans are empowered, creative, subversive, curious Ludere humanum est* – A lens, a pattern, … and a new paradigm? – You are designers of social machines 3. Knowledge Infrastructure – Sensemaking network of Scholarly Social Machines – Observatories, Social Objects, r* research – Don’t forget it is fundamentally social * Pip Willcox
  38. 38. rstl.royalsocietypublishing.org
  39. 39. The FORCE2015 Research Communication and e-Scholarship Conference brings together researchers, scholars, librarians, archivists, information scientists, publishers, and research funders in a lively forum – to broaden awareness of current efforts across disciplines, but also to define the future through discussions, challenge projects, demonstrations, and the seeding of new partnerships and collaborations.
  40. 40. Pip Willcox
  41. 41. Thanks to Christine Borgman, Iain Buchan, Mark d’Inverno, Chris Lintott, Richard O’Bierne, Kevin Page, Rob Simpson, Ségolène Tarte, Pip Willcox; FORCE11, SOCIAM; Andrew W. Mellon Foundation, EPSRC, ESRC, AHRC. david.deroure@oerc.ox.ac.uk www.oerc.ox.ac.uk/people/dder @dder http://www.slideshare.net/davidderoure/social-machines-paradigm www.oerc.ox.ac.uk www.force11.org sociam.org EPSRC EP/J017728/1
  42. 42. www.oerc.ox.ac.uk david.deroure@oerc.ox.ac.uk @dder
  43. 43. Abstract Today we see the rise of Social Machines, like Twitter, Wikipedia and Galaxy Zoo—where communities identify and solve their own problems, harnessing commitment, local knowledge and embedded skills, without having to rely on experts or governments. The Social Machines paradigm provides a lens onto the interacting sociotechnical systems of our hybrid digital-physical world, citizen-centric and at scale—emphasising empowerment and sociality in a world of pervasive technology adoption and automation. This talk will present the Social Machines paradigm as an approach to social media analytics and a rethinking of our scholarly practices and knowledge infrastructure.

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