International Journal of Human-Computer Interaction,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 23
Published: March 8, 2024
The
study
aims
to
explore
the
factors
that
influence
university
students'
behavioral
intention
(BI)
and
use
behavior
(UB)
of
generative
AI
products
from
an
ethical
perspective.
Referring
decision-making
theory,
research
model
extends
UTAUT2
with
three
influencing
factors:
awareness
(EA),
perceived
risks
(PER),
anxiety
(AIEA).
A
sample
226
students
was
analysed
using
Partial
Least
Squares
Structural
Equation
Modelling
technique
(PLS-SEM).
results
further
validate
effectiveness
UTAUT2.
Furthermore,
performance
expectancy,
hedonistic
motivation,
price
value,
social
all
positively
BI
products,
except
for
effort
expectancy.
Facilitating
conditions
habit
show
no
significant
impact
on
BI,
but
they
can
determine
UB.
extended
perspective
play
roles
as
well.
AIEA
PER
are
not
key
determinants
BI.
However,
directly
inhibit
From
mediation
analysis,
although
do
have
a
direct
UB,
it
inhibits
UB
indirectly
through
AIEA.
Ethical
Nevertheless,
also
increase
PER.
These
findings
help
better
accept
ethically
products.
Behavioral Sciences,
Journal Year:
2025,
Volume and Issue:
15(1), P. 88 - 88
Published: Jan. 18, 2025
This
study
examines
how
the
use
of
artificial
intelligence
(AI)
by
healthcare
professionals
affects
their
work
well-being
through
satisfaction
basic
psychological
needs,
framed
within
Self-Determination
Theory.
Data
from
280
across
various
departments
in
Chinese
hospitals
were
collected,
and
hierarchical
regression
analyzed
to
assess
relationship
between
AI,
needs
(autonomy,
competence,
relatedness),
well-being.
The
results
reveal
that
AI
enhances
indirectly
increasing
these
needs.
Additionally,
job
complexity
serves
as
a
boundary
condition
moderates
Specifically,
weakens
autonomy
while
having
no
significant
effect
on
relatedness.
These
findings
suggest
impact
professionals’
is
contingent
complexity.
highlights
promoting
at
context
adoption
requires
not
only
technological
implementation
but
also
ongoing
adaptation
meet
evolving
insights
provide
theoretical
foundation
practical
guidance
for
integrating
into
support
professionals.
Clinics and Practice,
Journal Year:
2023,
Volume and Issue:
13(6), P. 1460 - 1487
Published: Nov. 20, 2023
The
rapid
progress
in
artificial
intelligence,
machine
learning,
and
natural
language
processing
has
led
to
increasingly
sophisticated
large
models
(LLMs)
for
use
healthcare.
This
study
assesses
the
performance
of
two
LLMs,
GPT-3.5
GPT-4
models,
passing
MIR
medical
examination
access
specialist
training
Spain.
Our
objectives
included
gauging
model's
overall
performance,
analyzing
discrepancies
across
different
specialties,
discerning
between
theoretical
practical
questions,
estimating
error
proportions,
assessing
hypothetical
severity
errors
committed
by
a
physician.We
studied
2022
Spanish
results
after
excluding
those
questions
requiring
image
evaluations
or
having
acknowledged
errors.
remaining
182
were
presented
LLM
English.
Logistic
regression
analyzed
relationships
question
length,
sequence,
performance.
We
also
23
with
images,
using
GPT-4's
new
analysis
capability.GPT-4
outperformed
GPT-3.5,
scoring
86.81%
(p
<
0.001).
English
translations
had
slightly
enhanced
scored
26.1%
images
worse
when
Spanish,
13.0%,
although
differences
not
statistically
significant
=
0.250).
Among
achieved
100%
correct
response
rate
several
areas,
Pharmacology,
Critical
Care,
Infectious
Diseases
specialties
showed
lower
revealed
that
while
13.2%
existed,
gravest
categories,
such
as
"error
intervention
sustain
life"
resulting
death",
0%
rate.GPT-4
performs
robustly
on
examination,
varying
capabilities
discriminate
knowledge
specialties.
While
high
success
is
commendable,
understanding
critical,
especially
considering
AI's
potential
role
real-world
practice
its
implications
patient
safety.
International Journal of Medical Informatics,
Journal Year:
2024,
Volume and Issue:
184, P. 105377 - 105377
Published: Feb. 15, 2024
Despite
substantial
progress
in
AI
research
for
healthcare,
translating
achievements
to
systems
clinical
settings
is
challenging
and,
many
cases,
unsatisfactory.
As
a
result,
investments
have
stalled
at
the
prototype
level,
never
reaching
settings.
American Journal of Economics and Sociology,
Journal Year:
2024,
Volume and Issue:
83(3), P. 567 - 607
Published: Feb. 24, 2024
Abstract
AI
advancements
are
poised
to
substantially
modify
human
abilities
in
the
foreseeable
future.
They
include
integration
of
Brain–Computer
Interfaces
(BCIs)
augment
cognitive
functions,
application
gene
editing,
and
utilization
AI‐powered
robotic
exoskeletons
enhance
physical
strength.
This
study
employs
a
comprehensive
analytical
framework
combining
factor
analysis,
clustering,
ANOVA,
logistic
regression
investigate
public
attitudes
toward
these
transformative
technologies.
Our
findings
reveal
three
distinct
clusters
opinion
reflecting
varying
optimism
concern
Cluster
1
(1574
participants)
held
positive
view
with
high
excitement
while
2
(1334
showed
balanced
stance.
3
(2199
expressed
heightened
despite
some
excitement.
Notably,
regional
disparities,
particularly
between
urban
rural
participants,
emerge
as
prominent
influencing
(ANOVA,
F
=
15.2,
p
<
0.001).
Furthermore,
identifies
key
influencers
perception,
highlighting
significant
roles
played
by
religion
factors.
The
implications
extend
beyond
understanding
sentiment.
underscore
need
for
informed
policies
that
promote
education
awareness
about
technologies,
address
ethical
concerns,
engage
decision‐making
processes.
As
society
navigates
this
technological
landscape,
nuanced
becomes
paramount,
guiding
regulation,
innovation,
engagement
strategies.
provides
valuable
insights
into
intricate
dynamics
surrounding
acceptance
highlights
importance
adapting
measures
evolving
perceptions
among
general
public.
Acta Psychologica,
Journal Year:
2024,
Volume and Issue:
249, P. 104442 - 104442
Published: Aug. 6, 2024
Prior
research
highlights
the
critical
role
of
AI
in
enhancing
second
language
(L2)
learning.
However,
factors
that
practically
affect
L2
learners
to
engage
with
resources
are
still
underexplored.
Given
widespread
availability
digital
devices
among
college
students,
they
particularly
poised
benefit
from
AI-assisted
As
such,
this
study,
grounded
an
extended
Technology
Acceptance
Model
(TAM),
investigates
predictors
learners'
actual
use
tools,
focusing
on
self-efficacy,
AI-related
anxiety,
and
their
overall
attitude
toward
AI.
Data
was
gathered
429
at
Chinese
universities
via
online
questionnaire,
utilizing
four
established
scales.
Through
structural
equation
modeling
(SEM)
AMOS
24,
results
indicate
self-efficacy
could
negatively
positively
influence
both
tools.
Besides,
anxiety
predicted
Moreover,
a
positive
predictor
through
reducing
AI,
or
combination
both.
This
study
also
discusses
theoretical
pedagogical
implications
suggests
directions
for
future
research.
Journal of Service Theory and Practice,
Journal Year:
2023,
Volume and Issue:
34(1), P. 127 - 154
Published: Oct. 9, 2023
Purpose
Retailers
increasingly
endeavour
to
implement
artificial
intelligence
(AI)
innovations,
such
as
humanoid
social
robots
(HSRs),
enhance
customer
experience.
This
paper
investigates
the
interactive
effect
of
HSR
and
consumers'
speciesism
on
their
perceptions
retail
sales
assistants.
Design/methodology/approach
Three
online
experiments
testing
effects
HSRs'
intellectual
individuals'
perceived
competence
and,
consequently,
decision
shop
at
a
store
that
uses
HSRs
assistants
are
reported.
Furthermore,
authors
examine
whether
attenuates
these
mediation
is
likely
be
observed
for
individuals
low
in
but
not
those
with
high
levels
speciesism.
Data
all
studies
were
collected
Prolific
analysed
SPSS
perform
logistic
regression
PROCESS
4.0
(Hayes,
2022)
moderated-mediation
analysis.
Findings
The
findings
show
level
moderates
relationship
between
an
found
intelligence.
When
low,
higher
(vs
low)
rate
less
competent
display
lower
acceptance
(i.e.
customers'
using
assistants).
Originality/value
research
responds
calls
adopt
human-like
perspective
understand
compatibility
humans
determine
how
personality
traits,
person's
speciesism,
may
affect
AI
technologies
replicating
human
characteristics
(Schmitt,
2019).
To
best
authors'
knowledge,
present
first
moderating
role
non-human
intelligent
service
robots).
study
showcase
normally
considered
negative
behaviour,
can
positively
influence
decisions
engage
HSRs.
Journal of Medical Internet Research,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Feb. 15, 2024
Artificial
intelligence-enabled
clinical
decision
support
systems
(AI-CDSSs)
offer
potential
for
improving
health
care
outcomes,
but
their
adoption
among
practitioners
remains
limited.
Journal of Evaluation in Clinical Practice,
Journal Year:
2025,
Volume and Issue:
31(1)
Published: Jan. 15, 2025
This
study
aims
of
determine
the
mediating
role
individual
innovativeness
in
effect
nursing
students'
artificial
intelligence
anxiety
on
their
robotic
surgery
knowledge
level.
was
cross-sectional
type.
It
conducted
with
391
students.
Artificial
Intelligence
Anxiety
Scale,
Robotic
Surgery
and
Nursing
Knowledge
Level
Survey
Individual
Innovativeness
Scale
were
used
to
collect
data.
PROCESS
Macro
methods
used.
There
a
negative,
very
weak
significant
relationship
among
level
knowledge.
positive,
mediated
contributes
reducing
increase
levels
