Social Machines and how to study them
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Keynote at HUMANE workshop, organised by OII, 21 March 2017, Oxford UK
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Social Machines and how to study them
- 1. David De Roure @dder Social Machines and how to study them DIRECTOR, OXFORD E-RESEARCH CENTRE
- 3. Empowered Citizens Studying Social Machines Scholarly Social Machines Social Platforms Internet of Things Sociam GO!
- 8. https://twitter.com/CR_UK/status/446223117841494016/ Some people's smartphones had autocorrected the word "BEAT" to instead read "BEAR". "Thank you for choosing an adorable polar bear," the reply from the WWF said. "We will call you today to set up your adoption." http://www.bbc.com/news/technology-26723457
- 12. Gradus[n_] := Plus @@ (Flatten[Table[#1, {#2}] & @@@ FactorInteger[n]] - 1) + 1 a(n) = A001414(n) - A001222(n) + 1 where A001414 = sum of primes dividing n (with repetition) A001222 = Number of prime divisors of n counted with multiplicity https://oeis.org/A275314
- 15. 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
- 16. Ecosystem Perspective • We see a community of living, hybrid organisms, rather than a set of machines which happen to have humans amongst their components • Their successes and failures inform the design and construction of their offspring and successors
- 17. time Social Machine instances @dder
- 18. Social Media Triangle social media data and analytics social media for engagement with research social media as a subject of research Sam McGregor
- 19. The Web Observatory Tiropanis, T., Hall, W., Shadbolt, N., De Roure, D., Contractor, N. and Hendler, J. 2013. The Web Science Observatory, IEEE Intelligent Systems 28(2) pp 100–104.
- 20. Observer of one social machine Observers using third party observatory Observer of multiple social machines Human participants in Social Machine Human participants in multiple Social Machines Observer of Social Machine infrastructure 1 4 2 3 5 6 SM SM SM Social Machine Observing Social Machines 7 @dder
- 21. By Ségolène Tarte, David De Roure and Pip Willcox Working out the Plot The Role of Stories in Social Machines Tarte, S.M., De Roure, D. and Willcox, P. 2014. Working out the Plot: the Role of Stories in Social Machines. SOCM2014: The Theory and Practice of Social Machines, Seoul, Korea, International World Wide Web Conferences pp. 909–914
- 22. STORYTELLING AS A STETHOSCOPE FOR SOCIAL MACHINES 1. Sociality through storytelling potential and realization 2. Sustainability through reactivity and interactivity 3. Emergence through collaborative authorship and mixed authority Zooniverse is a highly storified Social Machine Facebook doesn’t allow for improvisa/on Wikipedia assigns authority rights rigidly http://ora.ox.ac.uk/objects/ora:8033
- 23. Pip Willcox
- 24. Tarte, S. Willcox, P., Glaser, H. and De Roure, D. 2015. Archetypal Narratives in Social Machines: Approaching Sociality through Prosopography. ACM Web Science 2015. SégolèneTarte
- 25. The Macroscope
- 26. Max Van Cleek
- 28. Scholarly Machines EcosystemDavid De Roure, JCDL 2013 https://www.force11.org
- 29. Richard O’Bierne
- 30. Pip Willcox
- 31. Thanks to Graham Klyne for assistance in capturing and encoding the First Folio provenance Pip Willcox
- 32. The Printing and Proof-Reading of the First Folio of Shakespeare by Hinman makes the case for compositors A to E http://collation.folger.edu/2016/03/fallen-type/ http://internetshakespeare.uvic.ca/doc/JC_TextIntro/section/1/ Pip Willcox
- 33. Normal Science – computer science is a puzzle-solving activity under our current paradigm, inspired by great achievements. 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. Kuhn cycle 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. De Roure, D. 2014. The Emerging Paradigm of Social Machines, Digital Enlightenment Yearbook 2014 227 K. O’Hara et al. (Eds.) IOS Press, 2014. pp 227-234.
- 35. Social Platforms
- 40. Living in the Internet of Things
- 41. New Forms of Data ▶ Internet data, derived from social media and other online interactions (including data gathered by connected people and devices, eg mobile devices, wearable technology, Internet of Things) ▶ Tracking data, monitoring the movement of people and objects (including GPS/geolocation data, traffic and other transport sensor data, CCTV images etc) ▶ Satellite and aerial imagery (eg Google Earth, Landsat, infrared, radar mapping etc) http://www.oecd.org/sti/sci-tech/new-data-for- understanding-the-human-condition.htm
- 42. Seizing the tiger by the tail ▶ The Internet of Things describes a world in which everyday objects are connected to a network so that data can be shared ▶ But it is really as much about people as the inanimate object ▶ It is impossible to anticipate all the social changes that could be created by connecting billions of devices https://www.gov.uk/government/publications/internet-of-things-blackett-review
- 45. There is no such thing as a closed system Humans are creative and subversive The Rise of the Bots A Swarm of Drones Accidents happen (in the lab, bin) Holding machines to account Software vulnerability Where are the throttle points? @dder
- 46. Normal Accidents Small events cascade through the system, with catastrophic consequences, when: • The system is complex • The system is /ghtly coupled • The system has catastrophic poten/al doi:10.1016/B0-08-043076-7/04509-5
- 47. Sociam GO!
- 50. evolve power up Collecting Training Grinding Pokéstop Backpack Pokédex Gym Candy Stardust Poké Ball egg incubator revive catch Free to play, but pay for more balls, incubators, etc.
- 51. • An exergame (and cultural heritage app) with massive takeup – A behavioural intervention – Leads to real-world social interactions (also see Death Tracker) • What is it about the design pattern that makes it so successful? – Appeals to collector instinct – Appeals to gaming/training instinct – “The pokes are quite cute” cf soft toys • Compare with – Zooniverse, e.g. Galaxy Zoo, Snapshot Serengeti (gotta catch ‘em all) – Linked in (seriously!) • Do we create games in our own image?
- 52. In the Beginning, There Is the Designer The Designer Creates an Experience The Experience Takes Place in a Venue The Experience Rises Out of a Game The Game Consists of Elements The Elements Support a Theme The Game Begins with an Idea The Game Improves through Iteration The Game Is Made for a Player The Experience Is in the Player’s Mind The Player’s Mind Is Driven by the Player’s Motivation Some Elements Are Game Mechanics Game Mechanics Must Be in Balance Game Mechanics Support Puzzles Players Play Games through an Interface Experiences Can Be Judged by Their Interest Curves One Kind of Experience Is the Story Story and Game Structures Can Be Artfully Merged with Indirect Control Stories and Games Take Place in Worlds Worlds Contain Characters Worlds Contain Spaces The Look and Feel of a World Is Defined by Its Aesthetics Some Games Are Played with Other Players The Designer Usually Works with a Team The Team Sometimes Communicates through Documents Good Games Are Created through Playtesting The Team Builds a Game with Technology Your Game Will Probably Have a Client The Designer Gives the Client a Pitch The Designer and Client Want the Game to Make a Profit Games Transform Their Players Designers Have Certain Responsibilities Each Designer Has a Purpose
- 53. Closing thoughts
- 55. Nigel Shadbolt David De Roure Tim Berners-Lee Ursula Martin Grant Miller Jason Nurse Petar Radanliev Ségolène Tarte Max Van Kleek Pip Willcox Wendy Hall Luc Moreau Leslie Carr Kieron O'Hara Aastha Madaan Elena Simperl Ramine Tinati Thanassis Tiropanis Dave Robertson Peter Buneman Stuart Anderson Amy Guy David Murray-Rust Claudia Pagliari Michael Rovatsos
- 56. david.deroure@oerc.ox.ac.uk @dder Supported by SOCIAM: The Theory and Practice of Social Machines, funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/J017728/1, also Cyber Security of the Internet of Things EP/N02334X/1, and Smart Society: Hybrid and Diversity-Aware Collective Adaptive Systems: When People Meet Machines to Build a Smarter Society, funded under the European Commission FP7-ICT FET Proactive Initiative: Fundamentals of Collective Adaptive Systems (FOCAS), Project Reference 600854.