IEEE Technology and Society Magazine - September 2023 - 101

image classification [19], data-centric approaches
to improve GAN training with less data [20], and a
data-centric super-resolution (dcSR) approach for
video quality enhancement [21]. A brief summary of
recent DCAI works is presented in Table 1.
Applications of DCAI for the well-being
of society
DCAI has the potential to revolutionize many
industries and fields by enabling more efficient
and effective decision-making based on insights
extracted from data. There are countless potential
new applications for DCAI, as the field continues
to evolve rapidly [22]. A few potential applications
for the well-being of society as shown in Figure 3 are
briefly discussed below.
Personalized healthcare
Healthcare providers can leverage DCAI to
analyze patient data in real time and make more
informed treatment decisions. This could involve tailoring
drug dosages to specific patients, administering
targeted therapies, and predicting diseases with
more accuracy. AI algorithms could also examine
medical images, recognizing slight variations in tissue
or organ structures that might indicate a greater
risk of illness. By analyzing genetic data and detecting
mutations or genetic markers that may be associated
with certain diseases, AI can contribute to
identifying effective treatment options. Through the
integration of data sets with other sources of information
such as medical history and lifestyle factors,
AI algorithms can help healthcare providers determine
the most appropriate course of action for each
patient. This could lead to faster treatment times,
more accurate diagnoses, and improved patient outcomes
overall [23], [24].
Climate change prediction and mitigation
AI algorithms can be instrumental in analyzing
vast quantities of data on weather patterns, greenhouse
gas emissions, and other factors to predict
future climate change impacts [3]. This can be instrumental
in shaping policy decisions and mitigation
efforts. With mounting concern over climate change
and environmental deterioration, there is a pressing
need for precise and timely data on the state of ecosystems
and the consequences of human activities.
DCAI can scrutinize data from various sources, such
as satellite imagery, weather sensors, and wildlife
September 2023
Figure 3. Social applications of DCAI.
monitoring systems, to detect patterns and trends
that might signify changes in the environment. This
information can be utilized to devise more effective
conservation strategies and steer policy decisions.
Intelligent transportation systems
DCAI applied to intelligent transportation systems
(ITS) can improve transportation safety, efficiency, and
sustainability. By analyzing data from traffic sensors,
cameras, global positioning system (GPS) devices, and
other sources, AI algorithms can optimize traffic flow,
predict and prevent accidents, and manage incidents
in real-time [3], [25]. In addition, DCAI can be used
to optimize public transportation routes and schedules
based on passenger demand and behavior, leading
to increased ridership and satisfaction. By combining
advanced technologies with DCAI, ITS can become
more intelligent and effective, improving the overall
transportation experience for users while reducing
congestion and environmental impact.
Smart agriculture
DCAI could help farmers optimize crop yields
by analyzing data from sensors, weather forecasts,
and other sources. This could include real-time
decision-making about watering, fertilizing, and harvesting
[2]. With the world's population projected to
reach 9.7 billion by 2050, food production will need
to increase by 70% to meet the growing demand.
DCAI can help farmers increase crop yields, reduce
waste, and improve sustainability by providing
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