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Collaborative eLearning Assistant Network. Caring agents are conscious agents. Introduction. The team: Patrick Parslow, Shirley Williams, Will Browne Contact details: [email protected] My Background – Cybernetics, Computer Science, Civil Engineering(!). Participation!. - PowerPoint PPT Presentation
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© University of Reading 2007 www.reading.ac.uk
School of Systems Engineering
2 December 2007
Collaborative eLearning Assistant NetworkCaring agents are conscious agents
Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
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Introduction• The team:
Patrick Parslow, Shirley Williams, Will Browne
• Contact details:
• My Background – – Cybernetics, Computer Science, Civil Engineering(!)
Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Participation!
• Huge topic - Machine Consciousness (MC) & eLearning
– Philosophy, Pedagogy, Computer Science, Psychology, Sociology, Ethics, Communities of Practice…
• Controversy about :– Whether MC is possible?– Whether MC is desirable?– Would MC improve an eLearning Assistant?– What is consciousness anyway?
• So – I will be asking for your opinions during the presentation.
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
What do I mean, ‘Consciousness’?
• It is hard to gain a consensus on what is meant by Consciousness – and hard to describe
• Features of a conscious system, by my working definition:
– Aware of surroundings– Aware of self (an autonomous entity distinct from
environment)– Aware of others (as autonomous agents in the
environment)– Holding a Theory of Mind of others– Having a Theory of Mind of self
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
How conscious can a computer be?
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1. Not at all2. Aware of surroundings3. Aware of self4. Aware of others5. Fully
Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Why a conscious Assistant?
• Self (1999) advocated caring intelligent tutoring systems– Learner models– Prediction– Adaptive
• Conscious systems have– Theories of mind (models of the ‘other’)– Prediction– Adaptation– ‘Self’ awareness (!)
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Hypothesis – consciousness is an emergent property
• Based on a certain minimum functionality – Machine Consciousness Capable (MCC)– can recognise, classify, model, communicate and predict
• Community– exist in an environment with others like them
• Advantage– there is an ‘evolutionary’ advantage to modelling the
‘other’
• Model of self is a ‘freebie’– A result of associating one’s own being with other similar
agents– Using same processes that model ‘other’ to model ‘self’
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Is it ethical?
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1. No2. If it can be proven
safe3. Human rights come
first4. If the MC has rights5. Yes
Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Motivation• Motivation to use in eLearning
– Caring agents need to be able to model and predict• Thus they need to perceive, recognise, classify
– Learners exist in communities• Thus paired eLearning companions can exist in
communities
– The eLearning assistant works in a ‘symbiotic’ relationship
• Benefits from providing the best advantage to its partner
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Complications
• Multiple strands of thought through different neural pathways– Only aware of one at a time
• Multiple interests– Like to keep on top of them all
• Multiple roles– In different contexts, family, social, academic,
professional
• Multiple domains means multiple ontologies– Or does it? Folksonomies and context awareness…
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Complexity
• To deal with the complicated, use complexity.
• Not multiple MC agents, but multiple agents making up the machine consciousness– Accessing the same internal models
• Communicating with the ‘user’ or learning partner
• But also with other MC agents in a network– Bringing experience from other learners – Building and exploiting a trust network– Generating meaning through folksonomical activity
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
In pictures
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Supporting Connectivism…
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Would a Machine ConsciouseLearning agent help?
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1. No2. Only some people3. Many, but not all
people4. Yes
Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Context, Meaning, Community
• First the “Alternative” view – Identity– Our roles in communities are given meaning by their
context– Our identity is the aggregation of the meaning created– We define ourselves in the context of community
• Our sense of ‘self’, – the conscious feeling we are who we– defined and refined through continuous comparison,
evaluation
– Consciousness takes time to develop
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Context, Meaning, Community
• All things our MCC agent needs to be able to model– All embodied to some extent in a folksonomy if :
• it records when tags were created• it records who created the tags• it allows tags to be tagged• it allows all the users resources and contacts to be
tagged
• We are developing a folksonomical file system, FFS– Core technology behind the MeAggregator™, a JISC
sponsored project.
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
MeAggregator™
• Designed to:– Interact with user-owned technologies– Build folksonomies– Provide a trust network - both permission and
reliability– Allow peer-peer communication and publication– Run as a server or desktop solution
http://meaggregator.googlecode.com/
• Chosen as a backbone because it provides – Ontology– Trust– Peer – Peer– Search
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Thank you
Any Questions?
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Learner model
• Building models of learning partner and self– Open learner modelling
• User control• Reflective
– Both learners, in partnership• User can maintain a model of agent• Helps agent learn about itself, its partner, and the
relationship
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
CeLAN
• MC agents can support multiple roles.– Given a priori domain knowledge, can be intructivist– Can work as a mentor– Can be motivational– In a network, is connectivist
• My preference?– Research assistant – assessing sources for me– Conversational – seeming interested in what I am
doing– Learns the subject area with me
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Joined-up learning – connectivism – The Eighth Annual Durham Blackboard Users Conference
Use case• Pat is researching Facebook and Blackboard, and
searches for “VLE”– CeLAN observes him choose the last link on the results page – CeLAN “Why that link?”
• I trust JISC– CeLAN adds resources and relationships to its model – resA: http://www.jiscinfonet.ac.uk/InfoKits/effective-use-of-
VLEs• relA: Pat searchedFor VLE• relB: Pat choseLink resA• relC: JISC trustedWRT relA• relD: JISC relatedTo resA (etc.)
– CeLAN interprets, and does a background search for “VLE JISC”
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