Overviewing Biases in Generative AI-Powered Models in the Arabic Language
Advances in computational intelligence and robotics book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 361 - 390
Published: Feb. 28, 2025
Natural
Language
Processing
(NLP)
is
an
emerging
field
often
integrated
into
Artificial
Intelligence
(AI)
technologies.
NLP
has
significantly
advanced,
leading
to
the
widespread
use
of
generative
AI-powered
(Gen-AI)
models
across
various
domains.
However,
while
Gen-AI
systems
have
been
successfully
implemented
in
several
languages,
AI-based
language
still
face
considerable
challenges
and
shortcomings,
including
generating
biases
sensitive
languages
like
Arabic.
Therefore,
primary
objective
this
chapter
provide
overview
Gen-AI-powered
context
Arabic
language,
exploring
sources
these
biases,
their
implications,
potential
strategies
for
mitigation.
The
underscore
need
ongoing
research
development
create
more
equitable
accurate
AI
systems.
By
understanding
origins
implications
implementing
effective
mitigation
strategies,
we
can
work
towards
that
better
serve
diverse
linguistic
communities.
Language: Английский
College Students’ Use and Perceptions of AI Tools in the UAE: Motivations, Ethical Concerns and Institutional Guidelines
Education Sciences,
Journal Year:
2025,
Volume and Issue:
15(4), P. 461 - 461
Published: April 8, 2025
This
survey
study
aims
to
understand
how
college
students
use
and
perceive
artificial
intelligence
(AI)
tools
in
the
United
Arab
Emirates
(UAE).
It
reports
students’
use,
perceived
motivations,
ethical
concerns
these
variables
are
interrelated.
Responses
(n
=
822)
were
collected
from
seven
universities
five
UAE
emirates.
The
findings
show
widespread
of
AI
(79.6%),
with
various
factors
affecting
perceptions
about
tools.
Students
also
raised
lack
guidance
on
using
Furthermore,
mediation
analyses
revealed
underlining
psychological
mechanisms
pertaining
tool
adoption:
benefits
fully
mediated
relationship
between
knowledge
usefulness
perceptions,
peer
pressure
academic
stress
adoption
intent,
support
for
institutional
regulations.
this
provide
implications
opportunities
challenges
posed
by
higher
education.
is
one
first
empirical
insights
into
tools,
examining
models
explore
complexity
their
concerns,
guidance.
Ultimately,
offers
data
education
institutions
policymakers
student
perspectives
UAE.
Language: Английский
Artificial Intelligence Creates Plagiarism or Academic Research?
Deleted Journal,
Journal Year:
2024,
Volume and Issue:
1(6), P. 169 - 179
Published: Nov. 1, 2024
Integrating
artificial
intelligence
(AI)
into
academic
research
has
sparked
a
significant
discourse
surrounding
its
ethical
implications
and
potential
benefits.
This
paper
explores
the
complex
relationship
between
AI-generated
content
integrity,
highlighting
challenges
of
blurring
lines
assistance
dishonesty.
As
educational
institutions
increasingly
adopt
AI
tools,
necessity
for
scholars
students
to
reevaluate
boundaries
originality
becomes
paramount.
The
considerations
in
writing
encompass
property,
accuracy,
integrity
issues,
necessitating
commitment
citation
practices
uphold
scholarly
standards.
Moreover,
while
can
enhance
quality
streamline
processes,
it
also
raises
concerns
about
unintentional
plagiarism
authenticity
original
thought.
reliance
on
tools
may
lead
derivative
outputs,
complicating
distinction
genuine
creativity
plagiarism.
To
address
these
challenges,
must
implement
robust
training
programs
that
promote
use
AI,
ensuring
responsibly
integrate
contributions
their
work.
Case
studies
demonstrate
when
used
effectively,
augment
performance
foster
deeper
engagement
with
learning
materials,
illustrating
as
valuable
resource.
Ultimately,
this
advocates
balanced
approach
embraces
benefits
maintaining
strong
scholarship,
thereby
shaping
future
where
technology
enhances
rather
than
undermines
integrity.
Language: Английский