Entrepreneurial Business and Economics Review,
Год журнала:
2023,
Номер
11(2), С. 7 - 30
Опубликована: Янв. 1, 2023
Objective:
The
objective
of
the
article
is
to
provide
a
comprehensive
identification
and
understanding
challenges
opportunities
associated
with
use
generative
artificial
intelligence
(GAI)
in
business.This
study
sought
develop
conceptual
framework
that
gathers
negative
aspects
GAI
development
management
economics,
focus
on
ChatGPT.
Research
Design
&
Methods:The
employed
narrative
critical
literature
review
developed
based
prior
literature.We
used
line
deductive
reasoning
formulating
our
theoretical
make
study's
overall
structure
rational
productive.Therefore,
this
should
be
viewed
as
highlights
controversies
threats
ChatGPT
case
study.Findings:
Based
conducted
deep
extensive
query
academic
subject
well
professional
press
Internet
portals,
we
identified
various
controversies,
threats,
defects,
disadvantages
GAI,
particular
ChatGPT.Next,
grouped
into
clusters
summarize
seven
main
see.In
opinion
they
are
follows:
(i)
no
regulation
AI
market
urgent
need
for
regulation,
(ii)
poor
quality,
lack
quality
control,
disinformation,
deepfake
content,
algorithmic
bias,
(iii)
automationspurred
job
losses,
(iv)
personal
data
violation,
social
surveillance,
privacy
(v)
manipulation,
weakening
ethics
goodwill,
(vi)
widening
socio-economic
inequalities,
(vii)
technostress.Implications
Recommendations:
It
important
regulate
AI/GAI
market.Advocating
crucial
ensure
level
playing
field,
promote
fair
competition,
protect
intellectual
property
rights
privacy,
prevent
potential
geopolitical
risks.The
changing
requires
workers
continuously
acquire
new
(digital)
skills
through
education
retraining.As
training
systems
becomes
prominent
category,
it
adapt
take
advantage
opportunities.To
mitigate
risks
related
developers
must
prioritize
ethical
considerations
work
user
security.To
avoid
manipulation
weaken
implement
responsible
practices
guidelines:
transparency
usage,
bias
mitigation
techniques,
monitoring
generated
content
harmful
or
misleading
information.Contribution
Value
Added:
This
may
aid
bringing
attention
significance
resolving
legal
arise
from
by
drawing
hazards
these
technologies.
Technology in Society,
Год журнала:
2023,
Номер
74, С. 102301 - 102301
Опубликована: Июнь 19, 2023
Although
Intelligent
Automation
(IA)
represents
the
future
of
business
automation,
organizational
implementation
and
sustainability
performance
this
emerging
technological
innovation
is
vastly
understudied.
Understanding
implications
IA
for
critical
since
leveraging
these
technologies
shapes
operations
policies
that
can
promote
sustainable
digitalization
automation
practices.
We
study
how
firms'
technological,
organizational,
environmental,
human
resource
contexts
impact
implementation.
The
further
explains
may
associate
with
firm's
triple
bottom
line
while
accounting
moderating
role
corporate
social
responsibility
strategy.
surveyed
207
multinational
firms
in
2022
used
partial
least
square-structural
equation
modeling
to
test
hypothesized
relationships.
Results
showed
mainly
determined
by
characteristics
internal
environment,
such
as
absorptive
capacity,
employee
socio-behavioral
concerns,
capital
competency.
offer
valuable
opportunities
boosting
economic
environmental
performance.
Nonetheless,
a
double-edged
sword
sustainability,
harming
values
implementing
informal
strategies.
Conversely,
formal
strategy
have
significantly
higher
opportunity
transform
value
into
Findings
are
expected
assist
managers
decision-makers
streamlining
an
impartial
transition
organizations
toward
automation.
Journal of Applied Learning & Teaching,
Год журнала:
2023,
Номер
6(2)
Опубликована: Сен. 26, 2023
As
the
application
of
Artificial
Intelligence
(AI)
continues
to
permeate
various
sectors,
educational
landscape
is
no
exception.
Several
AI
in
education
(AIEd)
applications,
like
chatbots,
present
an
intriguing
array
opportunities
and
challenges.
This
paper
provides
in-depth
exploration
use
role
research,
focusing
on
benefits
(the
good)
potential
pitfalls
bad
ugly)
associated
with
deployment
chatbots
other
AIEDs.
The
explored
include
personalised
learning,
facilitation
administrative
tasks,
enriched
research
capabilities,
provision
a
platform
for
collaboration.
These
advantages
are
balanced
against
downsides,
such
as
job
displacement,
misinformation,
plagiarism,
erosion
human
connection.
Ethical
considerations,
particularly
concerning
data
privacy,
bias
reinforcement,
digital
divide,
also
examined.
Conclusions
drawn
from
this
analysis
stress
importance
striking
balance
between
capabilities
elements
education,
well
developing
comprehensive
ethical
frameworks
contexts.
Asian Journal of Economics Business and Accounting,
Год журнала:
2024,
Номер
24(4), С. 126 - 146
Опубликована: Фев. 26, 2024
The
study
investigates
the
profound
impact
of
Artificial
Intelligence
(AI)
on
various
facets
global
economic
landscape.
Against
a
backdrop
rapid
technological
advancements,
draws
context
pivotal
IMF
report
highlighting
transformative
potential
AI.
suggests
that
AI
could
modify,
replace,
or
transform
about
60%
jobs
in
advanced
economies
and
significant
proportion
emerging
low-income
countries,
reflecting
paradigm
shift
employment
structures.
core
objective
this
is
to
thoroughly
examine
role
AI-driven
innovation
organizational
competitiveness,
its
community
development
socioeconomic
dynamics,
implications
national
policies
trends.
A
quantitative
research
methodology
was
employed,
involving
structured
survey
targeting
diverse
group
professionals
industries.
meticulously
designed
capture
insights
into
participants'
experiences
perceptions
regarding
implementation
impacts.
total
642
valid
responses
from
consultants,
technology
enthusiasts,
industry
experts,
policymakers
provided
robust
dataset
for
analyzing
study's
four
hypotheses.
findings
reveal
integration
significantly
bolsters
echoing
contemporary
literature.
Higher
levels
adoption
communities
are
linked
improved
outcomes,
albeit
with
risk
intensifying
existing
inequalities.
On
scale,
strategies
focusing
correlate
enhanced
competitiveness.
Furthermore,
business
processes
markedly
influences
workforce
necessitating
shifts
skill
requirements
job
roles.
In
light
these
findings,
paper
recommends
strategic
within
businesses,
equitable
policy
frameworks
deployment,
focus
strategies,
substantial
investment
training,
international
collaboration
ethics
imperative
maximizingAI's
benefits
while
mitigating
risks.
Business Horizons,
Год журнала:
2024,
Номер
67(5), С. 549 - 559
Опубликована: Апрель 21, 2024
Generative
artificial
intelligence
(Gen
AI)
presents
a
disruptive
innovation
for
brands
and
society,
the
power
of
which
is
still
yet
to
be
realized.
In
context
customer
service,
Gen
AI
affords
companies
new
possibilities
communicate,
connect,
engage
customers.
This
article
draws
on
scholarly
research
consultation
with
service
leaders
present
discuss
in
specifically
chatbots.
Importantly,
this
potential
paradoxes
enabled
adding
debate
about
role
impact
brands.
Specifically,
we
six
namely:
connected
isolated,
lower
cost
higher
price,
quality
less
empathy,
satisfied
frustrated,
personalized
intrusive,
powerful
vulnerable.
For
each
paradox,
suggest
brand
response
strategies
mitigate
downside
manage
upside.
Technology in Society,
Год журнала:
2024,
Номер
78, С. 102662 - 102662
Опубликована: Июль 17, 2024
This
paper
explores
the
effects
of
integrating
Generative
Artificial
Intelligence
(GAI)
into
decision-making
processes
within
organizations,
employing
a
quasi-experimental
pretest-posttest
design.
The
study
examines
synergistic
interaction
between
Human
(HI)
and
GAI
across
four
group
scenarios
three
global
organizations
renowned
for
their
cutting-edge
operational
techniques.
research
progresses
through
several
phases:
identifying
problems,
collecting
baseline
data
on
decision-making,
implementing
AI
interventions,
evaluating
outcomes
post-intervention
to
identify
shifts
in
performance.
results
demonstrate
that
effectively
reduces
human
cognitive
burdens
mitigates
heuristic
biases
by
offering
data-driven
support
predictive
analytics,
grounded
System
2
reasoning.
is
particularly
valuable
complex
situations
characterized
unfamiliarity
information
overload,
where
intuitive,
1
thinking
less
effective.
However,
also
uncovers
challenges
related
integration,
such
as
potential
over-reliance
technology,
intrinsic
'out-of-the-box'
without
contextual
creativity.
To
address
these
issues,
this
proposes
an
innovative
strategic
framework
HI-GAI
collaboration
emphasizes
transparency,
accountability,
inclusiveness.
Neural Computing and Applications,
Год журнала:
2024,
Номер
36(21), С. 12655 - 12699
Опубликована: Май 13, 2024
Abstract
Artificial
neural
networks
(ANN),
machine
learning
(ML),
deep
(DL),
and
ensemble
(EL)
are
four
outstanding
approaches
that
enable
algorithms
to
extract
information
from
data
make
predictions
or
decisions
autonomously
without
the
need
for
direct
instructions.
ANN,
ML,
DL,
EL
models
have
found
extensive
application
in
predicting
geotechnical
geoenvironmental
parameters.
This
research
aims
provide
a
comprehensive
assessment
of
applications
addressing
forecasting
within
field
related
engineering,
including
soil
mechanics,
foundation
rock
environmental
geotechnics,
transportation
geotechnics.
Previous
studies
not
collectively
examined
all
algorithms—ANN,
EL—and
explored
their
advantages
disadvantages
engineering.
categorize
address
this
gap
existing
literature
systematically.
An
dataset
relevant
was
gathered
Web
Science
subjected
an
analysis
based
on
approach,
primary
focus
objectives,
year
publication,
geographical
distribution,
results.
Additionally,
study
included
co-occurrence
keyword
covered
techniques,
systematic
reviews,
review
articles
data,
sourced
Scopus
database
through
Elsevier
Journal,
were
then
visualized
using
VOS
Viewer
further
examination.
The
results
demonstrated
ANN
is
widely
utilized
despite
proven
potential
methods
engineering
due
real-world
laboratory
civil
engineers
often
encounter.
However,
when
it
comes
behavior
scenarios,
techniques
outperform
three
other
methods.
discussed
here
assist
understanding
benefits
geo
area.
enables
practitioners
select
most
suitable
creating
certainty
resilient
ecosystem.
Frontiers in Artificial Intelligence,
Год журнала:
2024,
Номер
6
Опубликована: Янв. 15, 2024
The
functions
of
human
resource
management
(HRM)
have
changed
radically
in
the
past
20
years
due
to
market
and
technological
forces,
becoming
more
cross-functional
data-driven.
In
age
AI,
role
HRM
professionals
organizations
continues
evolve.
Artificial
intelligence
(AI)
is
transforming
many
practices
throughout
creating
system
process
efficiencies,
performing
advanced
data
analysis,
contributing
value
creation
organization.
A
growing
body
evidence
highlights
benefits
AI
brings
field
HRM.
Despite
increased
interest
AI-HRM
scholarship,
focus
on
human-AI
interaction
at
work
AI-based
technologies
for
limited
fragmented.
Moreover,
lack
considerations
tech
design
deployment
can
hamper
digital
transformation
efforts.
This
paper
provides
a
contemporary
forward-looking
perspective
strategic
human-centric
plays
within
as
becomes
integrated
workplace.
Spanning
three
distinct
phases
integration
(technocratic,
integrated,
fully-embedded),
it
examines
technical,
human,
ethical
challenges
each
phase
suggestions
how
overcome
them
using
approach.
Our
importance
evolving
AI-driven
organization
roadmap
bring
humans
machines
closer
together
