Big Data and Cognitive Computing,
Год журнала:
2024,
Номер
8(4), С. 36 - 36
Опубликована: Март 27, 2024
Recommender
systems
are
a
key
technology
for
many
applications,
such
as
e-commerce,
streaming
media,
and
social
media.
Traditional
recommender
rely
on
collaborative
filtering
or
content-based
to
make
recommendations.
However,
these
approaches
have
limitations,
the
cold
start
data
sparsity
problem.
This
survey
paper
presents
an
in-depth
analysis
of
paradigm
shift
from
conventional
generative
pre-trained-transformers-(GPT)-based
chatbots.
We
highlight
recent
developments
that
leverage
power
GPT
create
interactive
personalized
conversational
agents.
By
exploring
natural
language
processing
(NLP)
deep
learning
techniques,
we
investigate
how
models
can
better
understand
user
preferences
provide
context-aware
The
further
evaluates
advantages
limitations
GPT-based
systems,
comparing
their
performance
with
traditional
methods.
Additionally,
discuss
potential
future
directions,
including
role
reinforcement
in
refining
personalization
aspect
systems.
Technological Forecasting and Social Change,
Год журнала:
2023,
Номер
199, С. 123076 - 123076
Опубликована: Дек. 14, 2023
With
the
continuous
intervention
of
AI
tools
in
education
sector,
new
research
is
required
to
evaluate
viability
and
feasibility
extant
platforms
inform
various
pedagogical
methods
instruction.
The
current
manuscript
explores
cumulative
published
literature
date
order
key
challenges
that
influence
implications
adopting
models
Education
Sector.
researchers'
present
works
both
favour
against
AI-based
applications
within
Academic
milieu.
A
total
69
articles
from
a
618-article
population
was
selected
diverse
academic
journals
between
2018
2023.
After
careful
review
articles,
presents
classification
structure
based
on
five
distinct
dimensions:
user,
operational,
environmental,
technological,
ethical
challenges.
recommends
use
ChatGPT
as
complementary
teaching-learning
aid
including
need
afford
customized
optimized
versions
tool
for
teaching
fraternity.
study
addresses
an
important
knowledge
gap
how
enhance
educational
settings.
For
instance,
discusses
interalia
range
AI-related
effects
learning
creative
prompts,
training
datasets
genres,
incorporation
human
input
data
confidentiality
elimination
bias.
concludes
by
recommending
strategic
solutions
emerging
identified
while
summarizing
ways
encourage
wider
adoption
other
sector.
insights
presented
this
can
act
reference
policymakers,
teachers,
technology
experts
stakeholders,
facilitate
means
sector
more
generally.
Moreover,
provides
foundation
future
research.
The
emergence
of
generative
artificial
intelligence
(AI),
exemplified
by
ChatGPT,
has
fundamentally
transformed
numerous
sectors
amplifying
operational
efficiency,
output,
and
customer
satisfaction.
However,
effectively
integrating
such
sophisticated
AI
systems,
especially
in
manufacturing,
finance,
retail,
transportation,
construction,
demands
concerted
efforts
from
cross-functional
teams.
This
investigation
delves
into
the
indispensable
role
played
these
teams
ensuring
seamless
integration
ChatGPT
akin
technologies
across
diverse
fields.
In
research
underscores
vital
significance
collaboration
between
specialists,
industrial
engineers,
production
managers
to
optimize
manufacturing
processes,
preemptive
maintenance,
quality
assurance.
finance
sector,
study
highlights
essential
synergy
data
scientists,
regulatory
experts,
financial
analysts
harness
ChatGPT's
complete
potential
automating
tasks,
detecting
fraud,
providing
personalized
interactions.
For
retail
industry,
this
accentuates
necessity
collaborative
marketing
strategists,
user
experience
designers,
developers
utilizing
for
targeted
campaigns,
virtual
shopping
assistants,
instantaneous
support.
It
explores
how
can
facilitate
assimilation
boost
engagement,
inventory
management,
predict
consumer
trends,
thereby
propelling
business
growth
competitive
advantage.
transportation
imperative
planners,
software
developers,
experts
leveraging
efficient
route
planning,
predictive
vehicle
real-time
logistics
oversight.
construction
importance
cohesive
among
architects,
civil
programmers
project
design
enhancement,
risk
mitigation.
By
promoting
collaboration,
effective
communication,
cross-domain
expertise,
are
instrumental
harnessing
transformative
AI,
industries
toward
a
more
efficient,
sustainable,
technologically
advanced
future.
International Journal of Human-Computer Interaction,
Год журнала:
2024,
Номер
unknown, С. 1 - 15
Опубликована: Фев. 22, 2024
In
the
rapidly
evolving
landscape
of
technology,
emergence
Chat
Generative
Pre-trained
Transformer
(ChatGPT)
marks
a
pivotal
milestone
in
realm
Artificial
Intelligence
(AI).
However,
little
research
has
reported
predictors
people's
intentions
to
use
ChatGPT.
This
pioneering
study
empirically
examines
user
adoption
through
lens
Technology
Acceptance
Model
(TAM)
using
convenience
sampling
method.
The
surveyed
784
ChatGPT
users
China,
whom
58.93%
were
males.
results
have
revealed
several
key
findings:
(1)
perceived
usefulness,
ease
use,
behavioral
intention,
and
behavior
positively
correlated
with
each
other;
(2)
intention
acted
as
mediating
factor
relationship
between
usefulness
behavior,
well
behavior;
(3)
played
chain-mediated
role
(4)
exhibited
greater
strength
among
females
compared
males;
(5)
association
was
found
be
stronger
urban
comparison
their
rural
counterparts;
(6)
connections
observed
individuals
higher
educational
backgrounds
relative
those
lower
backgrounds.
These
findings
provide
crucial
nuanced
insights
advance
practical
application
ChatGPT,
emphasizing
need
for
enhanced
usability
use.
this
exclusively
captured
usage
behaviors
within
Chinese
base.
Future
investigations
could
encompass
diverse
demographics
across
multiple
countries,
enabling
cross-cultural
comparisons.
Journal of Business Research,
Год журнала:
2024,
Номер
180, С. 114737 - 114737
Опубликована: Май 24, 2024
Generative
Artificial
Intelligence
(GAI)
is
witnessing
a
lot
of
adoption
across
industries,
but
literature
yet
to
fully
document
the
nuances
these
applications.
We
develop
comprehensive
framework
for
understanding
factors
that
affect
trust
in
online
grocery
shopping
(OGS)
using
GAI
chatbots.
Our
exploratory
study
was
conducted
via
interviews,
which
helped
build
our
model.
integrate
Elaboration
Likelihood
Model
(ELM)
and
Status
Quo
Bias
(SQB)
theory
Unified
Framework
Trust
on
Technology
Platforms.
In
confirmatory
study,
by
analyzing
372
responses
from
users,
structural
equation
modelling
(SEM),
we
initially
validate
path
Subsequently,
used
fuzzy
set
qualitative
comparative
analysis
(fsQCA)
check
causal
combinations
explain
different
levels.
Apart
perceived
regret
avoidance,
all
other
had
significant
effect
attitude
trust.
Perceived
anthropomorphism
moderated
associations
between
interaction
quality,
credibility,
threat,
attitude.
AI and Ethics,
Год журнала:
2024,
Номер
4(3), С. 791 - 804
Опубликована: Фев. 23, 2024
Abstract
This
paper
examines
the
ethical
obligations
companies
have
when
implementing
generative
Artificial
Intelligence
(AI).
We
point
to
potential
cyber
security
risks
are
exposed
rushing
adopt
AI
solutions
or
buying
into
“AI
hype”.
While
benefits
of
for
business
been
widely
touted,
inherent
associated
less
well
publicised.
There
growing
concerns
that
race
integrate
is
not
being
accompanied
by
adequate
safety
measures.
The
rush
buy
hype
and
fall
behind
competition
potentially
exposing
broad
possibly
catastrophic
cyber-attacks
breaches.
In
this
paper,
we
outline
significant
threats
models
pose,
including
‘backdoors’
in
could
compromise
user
data
risk
‘poisoned’
producing
false
results.
light
these
concerns,
discuss
moral
considering
principles
beneficence,
non-maleficence,
autonomy,
justice,
explicability.
identify
two
examples
concern,
overreliance
over-trust
AI,
both
which
can
negatively
influence
decisions,
leaving
vulnerable
threats.
concludes
recommending
a
set
checklists
implementation
environment
minimise
based
on
discussed
responsibilities
concern.
Psychology and Marketing,
Год журнала:
2024,
Номер
41(6), С. 1254 - 1270
Опубликована: Фев. 10, 2024
Abstract
Should
consumer
researchers
employ
silicon
samples
and
artificially
generated
data
based
on
large
language
models,
such
as
GPT,
to
mimic
human
respondents'
behavior?
In
this
paper,
we
review
recent
research
that
has
compared
result
patterns
from
samples,
finding
results
vary
considerably
across
different
domains.
Based
these
results,
present
specific
recommendations
for
sample
use
in
marketing
research.
We
argue
hold
particular
promise
upstream
parts
of
the
process
qualitative
pretesting
pilot
studies,
where
collect
external
information
safeguard
follow‐up
design
choices.
also
provide
a
critical
assessment
using
main
studies.
Finally,
discuss
ethical
issues
future
avenues.
Technovation,
Год журнала:
2024,
Номер
135, С. 103064 - 103064
Опубликована: Июль 1, 2024
Numerous
enterprises
employ
Generative
AI
(GenAI)
for
a
plethora
of
business
operations,
which
can
enhance
organizational
effectiveness.
The
adoption
might
be
driven
by
multiple
factors
influencing
the
landscape.
Additionally,
numerous
ethical
considerations
could
impact
deployment
GenAI.
This
unique
study
investigated
how
organizations
adopt
GenAI
and
its
effects
on
their
performance.
Further,
this
research
utilized
institutional
theory
guidelines
design
to
develop
framework
examining
A
survey
384
managers
from
information
technology
(IT)
technology-enabled
services
(ITeS)
companies
was
conducted.
Data
analysis
done
using
PLS-SEM
examine
validate
proposed
model.
outcome
reveals
that
pressures,
i.e.,
coercive,
normative
mimetic
forces,
influence
use
in
organizations.
It
also
found
fairness,
accountability,
transparency,
accuracy
autonomy
Also,
results
divulge
influences
performance
is
moderated
innovativeness.
provides
insights
developers
GenAI,
senior
management
companies,
government
IT
policymakers
highlighting
pressures
principles
Humanities and Social Sciences Communications,
Год журнала:
2024,
Номер
11(1)
Опубликована: Янв. 15, 2024
Abstract
While
the
rise
of
artificial
intelligence
(AI)
tools
holds
promise
for
delivering
benefits,
it
is
important
to
acknowledge
associated
risks
their
deployment.
In
this
article,
we
conduct
a
focused
literature
review
address
two
central
research
inquiries
concerning
ChatGPT
and
similar
AI
tools.
Firstly,
examine
potential
pitfalls
linked
with
development
implementation
across
individual,
organizational,
societal
levels.
Secondly,
explore
role
multi-stakeholder
responsible
innovation
framework
in
guiding
chatbots’
sustainable
utilization.
Drawing
inspiration
from
stakeholder
theory
principles,
underscore
necessity
comprehensive
ethical
guidelines
navigate
design,
inception,
utilization
emerging
innovations.
The
findings
shed
light
on
perils
various
levels,
including
issues
such
as
devaluation
relationships,
unemployment,
privacy
concerns,
bias,
misinformation,
digital
inequities.
Furthermore,
proposed
Responsible
Research
Innovation
can
empower
stakeholders
proactively
anticipate
deliberate
upon
AI’s
ethical,
social,
environmental
implications,
thus
substantially
contributing
pursuit
implementation.
Journal of Medical Internet Research,
Год журнала:
2024,
Номер
26, С. e57896 - e57896
Опубликована: Июнь 29, 2024
ChatGPT,
a
generative
pretrained
transformer,
has
garnered
global
attention
and
sparked
discussions
since
its
introduction
on
November
30,
2022.
However,
it
generated
controversy
within
the
realms
of
medical
education
scientific
research.
This
paper
examines
potential
applications,
limitations,
strategies
for
using
ChatGPT.
ChatGPT
offers
personalized
learning
support
to
students
through
robust
natural
language
generation
capabilities,
enabling
furnish
answers.
Moreover,
demonstrated
significant
use
in
simulating
clinical
scenarios,
facilitating
teaching
processes,
revitalizing
education.
Nonetheless,
numerous
challenges
accompany
these
advancements.
In
context
education,
is
paramount
importance
prevent
excessive
reliance
combat
academic
plagiarism.
Likewise,
field
medicine,
vital
guarantee
timeliness,
accuracy,
reliability
content
by
Concurrently,
ethical
concerns
regarding
information
security
arise.
light
challenges,
this
proposes
targeted
addressing
them.
First,
risk
overreliance
plagiarism
must
be
mitigated
ideological
fostering
comprehensive
competencies,
implementing
diverse
evaluation
criteria.
The
integration
contemporary
pedagogical
methodologies
conjunction
with
serves
enhance
overall
quality
To
professionalism
content,
recommended
implement
measures
optimize
ChatGPT’s
training
data
professionally
transparency
process.
ensures
that
aligned
most
recent
standards
practice.
enhancement
value
alignment
establishment
pertinent
legislation
or
codes
practice
address
concerns,
including
those
pertaining
algorithmic
discrimination,
allocation
responsibility,
privacy,
security.
conclusion,
while
presents
also
encounters
various
challenges.
Through
research
implementation
suitable
strategies,
anticipated
positive
impact
will
harnessed,
laying
groundwork
advancing
discipline
development
high-caliber
professionals.
