INTELLIGENT AUGMENTATION (IA)
Semantic social Augment knowledge
scaffolding (AWESOME) capture
(L. Lau, S. Bajanki, K. Kaufold, R. (R. Denaux, A.G. Cohn, G. Hart)
O’Rourke, A. Walker) Knowledge-enriched Use of ontology to augment
Social semantic web and browsing in DL
DL (British Library) technologies
(I. Corda, B. Bennett)
(working in communities
at the right time
to the right person)
Deriving models of Capturing user
technologies experiences - Fire Risk
tailored support Assessment
(S. Kleanthous) (W. Eamsitavanna, D. Allen)
Augmentation – the act of augmenting, i.e.
to understand, support, enhance, improve,
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
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
Points for Discussion
What is the step change brought by IA?
How can we justify and proof this?
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)?