Transcript AWESOME-Dissertation Environment

INTELLIGENT
AUGMENTATION (IA)
Research Direction
Semantic social
scaffolding (AWESOME)
Augment knowledge
capture
(L. Lau, S. Bajanki, K. Kaufold, R.
O’Rourke, A. Walker)
(R. Denaux, A.G. Cohn, G. Hart)
Social semantic web and
DL (British Library)
Knowledge-enriched
technologies
(right content
at the right time
to the right person)
(working in communities
crowd wisdom)
(S. Kleanthous)
(I. Corda, B. Bennett)
Personalisation
Socialisation
Deriving models of
communities, Communitytailored support
Use of ontology to augment
browsing in DL
Ubiquitous
technologies
Capturing user
experiences - Fire Risk
Assessment
(W. Eamsitavanna, D. Allen)
Intelligent Augmentation
Augmentation – the act of augmenting, i.e.
to understand, support, enhance, improve,
increase, facilitate;
discovering and responding to needs.
What to augment – broad range:
people (improve knowledge/skills/awareness)
tasks (complex tasks, common tasks)
practices (better working together, individual vs
community, organisational practice)
processes (individual & organisational processes)
Flipping the AI
Artificial Intelligence – making intelligent machines
which can perform tasks humans perform
Intelligent Augmentation – use intelligent
techniques to understand and support people,
tasks, processes, and practices
Change of Focus –
not replace humans but augment their work;
what can we augment, how can we be sure that
the augmentation has happened
Related Terms
Intelligence Augmentation – Lydia’s presentation
Augmented Reality – [NOT RELATED]
research in Virtual Reality, create immersive
environments which enable real life experiences in
a virtual world
Augmented Intelligence or Computer-Augmented
Intelligence – [TOO NARROW]
similarity with computer-aided instruction; we aim
for more than just learning
Initial Feedback:
Points for Discussion
What is the step change brought by IA?
How can we justify and proof this?
Why now?
What can we do now which we could not do before?
What impact can it make?
Why is IA important, why the existing approaches do
not offer the expected impact (what is missing in
them which we are offering here)?