INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT,
Год журнала:
2024,
Номер
08(01), С. 1 - 13
Опубликована: Янв. 8, 2024
This
research
paper
delves
into
the
critical
dimension
of
Human-AI
Collaboration,
with
a
specific
focus
on
unraveling
intricacies
user
trust
in
ChatGPT
conversations.
In
an
era
marked
by
increasing
AI
integration
various
aspects
human
life,
understanding
and
fostering
conversational
systems
like
is
essential
for
effective
collaboration.
The
study
employs
comprehensive
approach,
investigating
metrics
measurement,
analyzing
experiences,
exploring
factors
that
influence
trust.
By
examining
evolving
impact
collaboration
conducting
comparative
analyses
other
models,
aims
to
provide
valuable
insights.
Ultimately,
not
only
contributes
nuanced
conversations
but
also
offers
practical
recommendations
developers
stakeholders
enhance
collaborative
potential
real-world
applications.
Keywords:
Conversations,
Conversational
AI,
Trust
Metrics,
User
Trust.
International Journal of Interactive Multimedia and Artificial Intelligence,
Год журнала:
2024,
Номер
8(5), С. 5 - 5
Опубликована: Янв. 1, 2024
Generative
Artificial
Intelligence
(GenAI)
has
emerged
as
a
promising
technology
that
can
create
original
content,
such
text,
images,
and
sound.The
use
of
GenAI
in
educational
settings
is
becoming
increasingly
popular
offers
range
opportunities
challenges.This
special
issue
explores
the
management
integration
settings,
including
ethical
considerations,
best
practices,
opportunities.The
potential
education
vast.By
using
algorithms
data,
content
be
used
to
augment
traditional
teaching
methods,
creating
more
interactive
personalized
learning
experience.In
addition,
utilized
an
assessment
tool
for
providing
feedback
students
generated
content.For
instance,
it
custom
quizzes,
generate
essay
prompts,
or
even
grade
essays.The
reduce
workload
teachers
help
receive
prompt
on
their
work.Incorporating
also
poses
challenges
related
academic
integrity.With
availability
models,
them
study
complete
homework
assignments,
which
raise
concerns
about
authenticity
authorship
delivered
work.Therefore,
important
ensure
standards
are
maintained,
originality
student's
work
preserved.This
highlights
need
implementing
practices
models
ensuring
support
not
replace
experience.
International Journal of Surgery,
Год журнала:
2024,
Номер
unknown
Опубликована: Март 19, 2024
It
has
been
a
year
since
the
launch
of
Chat
Generator
Pre-Trained
Transformer
(ChatGPT),
generative
artificial
intelligence
(AI)
program.
The
introduction
this
cross-generational
product
initially
brought
huge
shock
to
people
with
its
incredible
potential,
and
then
aroused
increasing
concerns
among
people.
In
field
medicine,
researchers
have
extensively
explored
possible
applications
ChatGPT
achieved
numerous
satisfactory
results.
However,
opportunities
issues
always
come
together.
Problems
also
exposed
during
ChatGPT,
requiring
cautious
handling,
thorough
consideration
further
guidelines
for
safe
use.
Here,
we
summarized
potential
in
medical
field,
including
revolutionizing
healthcare
consultation,
assisting
patient
management
treatment,
transforming
education
facilitating
clinical
research.
Meanwhile,
enumerated
researchers’
arising
along
broad
applications.
As
it
is
irreversible
that
AI
will
gradually
permeate
every
aspect
modern
life,
hope
review
can
not
only
promote
people’s
understanding
future,
but
remind
them
be
more
about
“Pandora’s
Box”
field.
necessary
establish
normative
use
as
soon
possible.
Journal of Medical Internet Research,
Год журнала:
2024,
Номер
26, С. e56764 - e56764
Опубликована: Март 20, 2024
As
the
health
care
industry
increasingly
embraces
large
language
models
(LLMs),
understanding
consequence
of
this
integration
becomes
crucial
for
maximizing
benefits
while
mitigating
potential
pitfalls.
This
paper
explores
evolving
relationship
among
clinician
trust
in
LLMs,
transition
data
sources
from
predominantly
human-generated
to
artificial
intelligence
(AI)–generated
content,
and
subsequent
impact
on
performance
LLMs
competence.
One
primary
concerns
identified
is
LLMs’
self-referential
learning
loops,
where
AI-generated
content
feeds
into
algorithms,
threatening
diversity
pool,
potentially
entrenching
biases,
reducing
efficacy
LLMs.
While
theoretical
at
stage,
feedback
loop
poses
a
significant
challenge
as
deepens,
emphasizing
need
proactive
dialogue
strategic
measures
ensure
safe
effective
use
LLM
technology.
Another
key
takeaway
our
investigation
role
user
expertise
necessity
discerning
approach
trusting
validating
outputs.
The
highlights
how
expert
users,
particularly
clinicians,
can
leverage
enhance
productivity
by
off-loading
routine
tasks
maintaining
critical
oversight
identify
correct
inaccuracies
content.
balance
skepticism
vital
ensuring
that
augment
rather
than
undermine
quality
patient
care.
We
also
discuss
risks
associated
with
deskilling
professionals.
Frequent
reliance
could
result
decline
providers’
diagnostic
thinking
skills,
affecting
training
development
future
legal
ethical
considerations
surrounding
deployment
are
examined.
medicolegal
challenges,
including
liability
cases
erroneous
diagnoses
or
treatment
advice
generated
references
recent
legislative
efforts,
such
Algorithmic
Accountability
Act
2023,
steps
toward
establishing
framework
responsible
AI-based
technologies
In
conclusion,
advocates
integrating
By
importance
expertise,
fostering
engagement
outputs,
navigating
landscape,
we
serve
valuable
tools
enhancing
supporting
addresses
immediate
challenges
posed
sets
foundation
their
maintainable
future.
Journal of Computer Science and Technology Studies,
Год журнала:
2024,
Номер
6(1), С. 225 - 232
Опубликована: Март 13, 2024
This
comprehensive
review
delves
into
the
landscape
and
recent
advancements
of
Generative
Artificial
Intelligence
(AI)
Large
Language
Models
(LLMs),
shedding
light
on
their
transformative
potential
applications
across
various
sectors.
AI,
exemplified
by
models
like
ChatGPT,
DALL-E,
Midjourney,
has
rapidly
evolved
is
driven
breakthroughs
in
deep
learning
architectures
availability
vast
datasets.
Concurrently,
LLMs
have
revolutionized
natural
language
processing
tasks,
utilizing
text
corpora
to
generate
human-like
text.
The
study
explores
developments,
including
introduction
advanced
GPT-4
PaLM2
emergence
specialized
small
(sLLMs),
aimed
at
overcoming
hardware
limitations
cost
constraints.
Additionally,
expanding
generative
from
healthcare
finance,
underscore
its
addressing
real-world
challenges.
Through
a
analysis,
this
research
contributes
ongoing
discourse
AI
ethics,
governance,
regulation,
emphasizing
importance
responsible
innovation
for
benefit
humanity.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Фев. 27, 2024
Abstract
This
study
embarks
on
an
exploration
of
the
performance
disparities
observed
between
English
and
Chinese
in
large
language
models
(LLMs),
motivated
by
growing
need
for
multilingual
capabilities
artificial
intelligence
systems.
Utilizing
a
comprehensive
methodology
that
includes
quantitative
analysis
model
outputs
qualitative
assessment
nuances,
research
investigates
underlying
reasons
these
discrepancies.
The
findings
reveal
significant
variations
LLMs
across
two
languages,
with
pronounced
challenge
accurately
processing
generating
text
Chinese.
gap
underscores
limitations
current
handling
complexities
inherent
languages
distinct
grammatical
structures
cultural
contexts.
implications
this
are
far-reaching,
suggesting
critical
development
more
robust
inclusive
can
better
accommodate
linguistic
diversity.
entails
not
only
enrichment
training
datasets
wider
array
but
also
refinement
architectures
to
grasp
subtleties
different
Ultimately,
contributes
ongoing
discourse
enhancing
LLMs,
aiming
pave
way
equitable
effective
tools
cater
global
user
base.
2022 ACM Conference on Fairness, Accountability, and Transparency,
Год журнала:
2024,
Номер
67, С. 2454 - 2469
Опубликована: Июнь 3, 2024
Large
language
models
(LLMs)
are
increasingly
capable
of
providing
users
with
advice
in
a
wide
range
professional
domains,
including
legal
advice.
However,
relying
on
LLMs
for
queries
raises
concerns
due
to
the
significant
expertise
required
and
potential
real-world
consequences
To
explore
when
why
should
or
not
provide
users,
we
conducted
workshops
20
experts
using
methods
inspired
by
case-based
reasoning.
The
provided
realistic
("cases")
allowed
examine
granular,
situation-specific
overarching
technical
constraints,
producing
concrete
set
contextual
considerations
LLM
developers.
By
synthesizing
factors
that
impacted
response
appropriateness,
present
4-dimension
framework:
(1)
User
attributes
behaviors,
(2)
Nature
queries,
(3)
AI
capabilities,
(4)
Social
impacts.
We
share
experts'
recommendations
strategies,
which
center
around
helping
identify
'right
questions
ask'
relevant
information
rather
than
definitive
judgments.
Our
findings
reveal
novel
considerations,
such
as
unauthorized
practice
law,
confidentiality,
liability
inaccurate
advice,
have
been
overlooked
literature.
deliberation
method
enabled
us
elicit
fine-grained,
practice-informed
insights
surpass
those
from
de-contextualized
surveys
speculative
principles.
These
underscore
applicability
our
translating
domain-specific
knowledge
practices
into
policies
can
guide
behavior
more
responsible
direction.
Journal of Medical Imaging and Radiation Oncology,
Год журнала:
2024,
Номер
68(3), С. 257 - 264
Опубликована: Янв. 19, 2024
Summary
This
study
aimed
to
comprehensively
evaluate
the
current
utilization
and
future
potential
of
ChatGPT,
an
AI‐based
chat
model,
in
field
radiology.
The
primary
focus
is
on
its
role
enhancing
decision‐making
processes,
optimizing
workflow
efficiency,
fostering
interdisciplinary
collaboration
teaching
within
healthcare.
A
systematic
search
was
conducted
PubMed,
EMBASE
Web
Science
databases.
Key
aspects,
such
as
impact
complex
decision‐making,
enhancement
collaboration,
were
assessed.
Limitations
challenges
associated
with
ChatGPT
implementation
also
examined.
Overall,
six
studies
met
inclusion
criteria
included
our
analysis.
All
prospective
nature.
total
551
chatGPT
(version
3.0
4.0)
assessment
events
Considering
generation
academic
papers,
found
output
data
inaccuracies
80%
time.
When
asked
questions
regarding
common
interventional
radiology
procedures,
it
contained
entirely
incorrect
information
45%
seen
better
answer
US
board‐style
when
lower
order
thinking
required
(
P
=
0.002).
Improvements
between
3.5
4.0
regard
imaging
accuracy
rates
61
versus
85%(
0.009).
observed
have
average
translational
ability
score
4.27/5
Likert
scale
CT
MRI
findings.
demonstrates
substantial
augment
workflow.
While
ChatGPT's
promise
evident,
thorough
evaluation
validation
are
imperative
before
widespread
adoption
Frontiers in Artificial Intelligence,
Год журнала:
2024,
Номер
7
Опубликована: Июнь 18, 2024
The
release
of
GPT-4
has
garnered
widespread
attention
across
various
fields,
signaling
the
impending
adoption
and
application
Large
Language
Models
(LLMs).
However,
previous
research
predominantly
focused
on
technical
principles
ChatGPT
its
social
impact,
overlooking
effects
human–computer
interaction
user
psychology.
This
paper
explores
multifaceted
impacts
interaction,
psychology,
society
through
a
literature
review.
author
investigates
ChatGPT’s
foundation,
including
Transformer
architecture
RLHF
(Reinforcement
Learning
from
Human
Feedback)
process,
enabling
it
to
generate
human-like
responses.
In
terms
studies
significant
improvements
GPT
models
bring
conversational
interfaces.
analysis
extends
psychological
impacts,
weighing
potential
mimic
human
empathy
support
learning
against
risks
reduced
interpersonal
connections.
commercial
domains,
discusses
applications
in
customer
service
services,
highlighting
efficiency
challenges
such
as
privacy
issues.
Finally,
offers
predictions
recommendations
for
future
development
directions
impact
relationships.
