Large
language
models
(LLMs)
can
help
writers
build
story
worlds
by
generating
world
elements,
such
as
factions,
characters,
and
locations.
However,
making
sense
of
many
generated
elements
be
overwhelming.
Moreover,
if
the
user
wants
to
precisely
control
aspects
that
are
difficult
specify
verbally,
prompting
alone
may
insufficient.
We
introduce
Patchview,
a
customizable
LLM-powered
system
visually
aids
worldbuilding
allowing
users
interact
with
concepts
through
physical
metaphor
magnets
dust.
Elements
in
Patchview
dragged
closer
high
relevance,
facilitating
sensemaking.
The
also
steer
generation
verbally
elusive
indicating
desired
position
element
between
concepts.
When
disagrees
LLM's
visualization
generation,
they
correct
those
repositioning
element.
These
corrections
used
align
future
behaviors
user's
perception.
With
study,
we
show
supports
sensemaking
steering
exploration
during
process.
provides
insights
on
how
visual
representation
sensemake,
steer,
generative
AI
model
intentions.
addresses
the
intricate
dynamics
of
Human-AI
Symbiosis
in
higher
education.This
edition
focuses
on
ethical,
skill-based,
and
philosophical
implications
Generative
Artificial
Intelligence
as
it
integrates
with
human
capabilities
within
educational
frameworks.The
issue
draws
Dov
Seidman's
philosophy
that
"how
we
do
things
matters
more
than
what
do,"
therefore,
manner
which
accomplish
activities
is
greater
significance
themselves.The
articles
this
not
merely
speculate
potential
AI
education;
they
provide
a
deep
dive
into
necessary
ethical
frameworks,
underscore
irreplaceable
value
skills,
consider
challenges
posed
by
technological
integration.Articles
explore
various
themes,
emphasizing
critical
nature
skills
such
empathy,
judgment,
nuanced
understanding,
are
deemed
indispensable
even
an
AI-driven
landscape.Furthermore,
examines
concept
'Fearing
Other',
analyzing
how
might
either
perpetuate
or
alleviate
deeply
ingrained
biases
fears
environments.Insights
uses
to
develop
power
like
creativity,
leadership,
teamwork
also
discussed,
highlighting
their
importance
rapidly
evolving
sector.This
presents
range
interdisciplinary
perspectives,
shedding
light
AI's
diverse
impacts
across
different
academic
disciplines.It
existing
paradigms
encourages
reevaluation
boundaries
between
creativity
algorithmic
precision.Readers
invited
critically
engage
content,
reflecting
broader
for
future
education
AI-enhanced
world.The
community
encouraged
navigate
new
terrain
knowledge,
guided
considerations,
inspired
boundless
possibilities
collaboration
artificial
intelligence.In
synthesizing
these
aims
contribute
discourse
impact
practical
implementations
settings
globally.As
move
forward,
insights
from
should
inform
ongoing
dialogues
initiatives,
ensuring
enhances
outcomes
while
preserving
essential
interactions
underpin
effective
learning
environments.The
commitment
continuous
inquiry
consideration
pivotal
collectively
AI-augmented
reality.This
journey
promises
transform
landscapes
adhering
values
define
our
humanity.The
first
paper
Col.
Mayer
special
need
institutions
maintain
balance
cultivating
enhancing
literacy.Amidst
landscape
increasingly
influenced
intelligence,
emphasis
remains
continuing
thinking,
1
et
al.
Creativity Research Journal,
Год журнала:
2024,
Номер
unknown, С. 1 - 22
Опубликована: Июнь 17, 2024
Both
large
language
models
(LLMs)
and
the
human
brain
develop
internal
of
reality
to
make
accurate
predictions.
typically
prefer
choices
with
strongest
track
records.
However,
when
faced
a
creative
challenge,
LLMs
remain
committed
high-probability
options
while
humans
can
opt
for
unproven
ones.
This
paper
delves
into
one
way
making
unlikely
events
plausible—"amplifying
anomaly."
The
concept
involves
extrapolating
viable
consequences
from
an
proposition.
Rather
than
being
treated
as
oddball
or
"one-offs,"
anomaly
permeates
work.
Notably,
novelty
appropriateness
be
in
tension
each
other,
high
utility
coming
at
cost
low
novelty.
Amplifying
aligns
these
competing
demands.
It
enhances
originality:
rarer
proposition
more
thoroughly
it
is
worked
out,
unique
surprising
result.
At
same
time,
effectiveness
value
option
also
rises:
thorough
elaboration
product
establishes
its
fitness.
Musical
examples
by
Beethoven,
Schubert,
contemporary
composer
Sky
Macklay,
along
products
other
domains,
illustrate
this
principle.
Classic
have
several
limitations
that
difficult
amplify
anomaly:
they
are
steered
toward
norm-driven
outcomes,
short-term
decisions,
not
designed
self-evaluate.
As
result,
difficulty
developing
unusual
propositions
non-obvious
without
guidance.
Alternatives
approaches,
including
adversarial
networks
team
AI,
briefly
examined.
Implications
future
computational
creativity
discussed.
Large
language
models
(LLMs)
can
help
writers
build
story
worlds
by
generating
world
elements,
such
as
factions,
characters,
and
locations.
However,
making
sense
of
many
generated
elements
be
overwhelming.
Moreover,
if
the
user
wants
to
precisely
control
aspects
that
are
difficult
specify
verbally,
prompting
alone
may
insufficient.
We
introduce
Patchview,
a
customizable
LLM-powered
system
visually
aids
worldbuilding
allowing
users
interact
with
concepts
through
physical
metaphor
magnets
dust.
Elements
in
Patchview
dragged
closer
high
relevance,
facilitating
sensemaking.
The
also
steer
generation
verbally
elusive
indicating
desired
position
element
between
concepts.
When
disagrees
LLM's
visualization
generation,
they
correct
those
repositioning
element.
These
corrections
used
align
future
behaviors
user's
perception.
With
study,
we
show
supports
sensemaking
steering
exploration
during
process.
provides
insights
on
how
visual
representation
sensemake,
steer,
generative
AI
model
intentions.
