Jim Hendler discusses social machines, which he defines as networks of machines supporting networks of people working together in ways that impact the real world. He argues that social networking consumes huge amounts of human time and that this time could be harnessed through social machines to solve problems like curing disease and feeding the hungry. Examples of early social machines include games with a purpose that harness human computation and citizen science projects like Galaxy Zoo. Moving forward, social machines may blend more with artificial intelligence, and their study requires multidisciplinary perspectives from computing, social science, and other fields. Realizing their potential faces both social challenges around online communities and technical challenges in platform design.

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Social Machines:
The Coming Collision of Artificial
Intelligence, Social Networking
and Humanity
Jim Hendler
Tetherless World Professor of Computer, Web and Cognitive Sciences
Director, Institute for Data Exploration and Applications
Rensselaer Polytechnic Institute
http://www.cs.rpi.edu/~hendler
@jahendler (twitter)

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(Shameless Plug)

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What is a social machine?
• 3 definitions of “Social Machine”
– Cooler name than social media analytics

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What is a social machine?
• 3 definitions of “Social Machine”
– Cooler name than social media analytics
– Machines increasingly entering our
social sphere
1968 2010 Today

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What is a social machine?
• 3 definitions of “Social Machine”
– Cooler name than social media analytics
– Machines increasingly entering our
social sphere
– Networks of machines supporting
networks of people working together in
ways that impact the real world

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What is a social machine?
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.. Berners-Lee, Weaving the Web, 1999
Combination of all three

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Social networking consumes huge amounts
of human (humanity’s!) time

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Time spent online

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Time spent online
Economist, 2014

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Using this time
Imagine
• Hundreds of millions of people
• Effectively able to network together
• Working with the data archives of science, govts,
NGOs, etc.
Working together on the Web
to cure disease,
to feed the hungry,
and to empower the powerless…
How could we do this?

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Idea 1, do this by “accident”
Being explored, but how do we make this purposeful?

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Harnessing the power for “fun”
Von Ahn, 06

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GWAP (ESP ca. 2006)

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Harnessing this power “unknowlingly”
You have likely
helped to make
Optical
Character
Recognition
better!
Von Ahn et al, 08

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Duolingo (2012)

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Harnessing human knowledge for problem solving
Raddick et al, 07

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Millions of galaxies classified

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16: Hanny’s Voorwerp
(A digression or maybe the whole point)

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The Zooniverse

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Social machines for Social Good

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Social machines for Social Good

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AI and Social Machines

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Today: We gain benefit from AI

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But, the machines still need us…

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But, the machines still need us…

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The “AI revolution” needs Social Machines!

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Embracing the blur

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Embracing the blur

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Embracing the blur

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Wikipedia Needs humans (enabled by technology)

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Wikipedia needs technology (enabled by humans)
How do you prevent people from ruining articles? (Defacement or vandalism)
Software robots automatically reverse obvious defacement immediately.
Moreover, there are hundreds of people who spend a little time each day
watching the list of recent changes on Wikipedia (see Wikipedia:Recent changes
patrol)... (Wikipedia FAQ, 2010)

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Studying Social Machines
is Inherently Multidisciplinary

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Distribution Statement
Wikipedia as Social Mechanism

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Distribution Statement
Slashdot (viz. Reddit) mechanism

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Galaxy Zoo communities
Bipana Bantawa, OII

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“Self Organizing” social machines

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Different network dynamics in different SMs

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22: Social Challenges include
• Keys to understanding on-line communities
include
– dynamics of online communities
• Incentives unclear
• Information flows between online and offline are largely
unstudied
• We can no longer assume an expert -> novice
continuum, but what replaces it?
– Trust (and distrust) on Web-based communities
• Goal is to share information, not hide it – but how do we
prevent abuses?
• Who do you trust (really)?
– Governance is a critical factor
• HFS is “self organizing,” which limits its scale

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Example: Governance
• Wikipedia includes a lot of rules and
privileged people to adjudicate/enforce
them
– Study in 2008
(Butler etal, CHI, 08)
• 44 policies (now 51)
• 248 guidelines (now over 400)

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23: Technical Challenges include
• Heavy programming burden
– Costs a lot to build/support a scalable, governed
platform
• Compare Wikipedia to HFS
– Designing a successful GWAP still a black art
• And a large programming challenge
– How can we create tools that a community can use by
itself?
• 80% solution for everyone >> 99% for some
• Underlying models
– How do we define Social Machines more rigorously?

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Engineering challenges
• Creating tools that allow groups of users to create, share
and evolve a new generation of open and interacting social
machines
– Declarative mechanism for sharing
– Read/write mechanism for both information and “governance”
• Creating the underlying architectural principles to guide the
design and efficient engineering of new Web infrastructure
components for this new generation of social software
– Distributed, open and dynamic (aka Web-like)
• Creating mechanisms to guarantee that use protocols are
explicit and conform to the relevant social policy
expectations of the users.
– Transparency, accountability, policy awareness

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Social Machines
• We are on developingnew technologies to create
Web-based systems that will transform society
by:
– Creating new systems that allow large numbers of
users to interact over the Web to collectively solve
problems.
– Creating and disseminating new Web application
development technologies aimed at letting
communities build and run their own social machines
• AI may be an important part of this
• There are some important examples out there
– But there’s a lot of important science to be done
• This is a truly interdisciplinary challenge in which
computing, social science, informatics and
communications work is all required

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Questions