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THE ROLE OF ARTIFICIAL NEURAL NETWORKS IN SOCIETY.
Mirzaev Mirjalol Rustam ugli,
Karshi State Technical University,
Student of the Department of Telecommunication Technologies
Annotation. The article discusses the technologies that model the human brain,
which are widely used in data analysis, data mining, and decision-making. In society,
artificial neural networks are bringing revolutionary changes in the economy,
healthcare, education, transportation, everyday life, and other areas. With the help of
these technologies, production efficiency increases, medical diagnostics becomes more
accurate, education is individualized, and automated transportation systems work
efficiently. However, they also raise ethical, social, and economic issues. The article
examines the positive and negative impacts of artificial neural networks on society and
discusses the necessary measures for their future development..
Key words: Artificial neural networks, human brain activity, modeling
technologies, economics, healthcare, education, transportation, revolutionary change,
medical diagnostics, educational individualization, automated transportation systems,
ethical, social, economic.
Аннотация.
Аннотация. В статье рассматриваются технологии
моделирования человеческого мозга, которые широко используются в анализе
данных, добыче данных и принятии решений. В обществе искусственные
нейронные сети приносят революционные изменения в экономику,
здравоохранение, образование, транспорт, повседневную жизнь и другие сферы.
С помощью этих технологий повышается эффективность производства,
медицинская
диагностика
становится
более
точной,
образование
индивидуализируется, а автоматизированные транспортные системы
работают эффективно. Однако они также поднимают этические, социальные
и экономические вопросы. В статье рассматриваются положительные и
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отрицательные воздействия искусственных нейронных сетей на общество и
обсуждаются необходимые меры для их будущего развития.
Ключевые слова: искусственные нейронные сети, активность человечес-
кого мозга, технологии моделирования, экономика, здравоохранение, обра-
зование, транспорт, революционные изменения, медицинская диагностика,
индивидуализация образования, автоматизированные транспортные системы,
этический, социальный, экономический.
With the development of artificial intelligence (AI) and machine learning,
artificial neural networks (ANNs) are gaining a significant role in society. A neural
network is a technology based on modeling the activity of a neural network in
accordance with its own behavior, capable of learning from various databases and
performing complex tasks. This technology is widely used in practice, primarily, in the
fields of medicine, healthcare, education, transportation and many other areas. The
article analyzes the role of artificial neural networks in society and the changes,
advantages and socio-economic impacts they have brought about.
The principle of operation of artificial neural networks. Artificial neural networks,
as their name suggests, imitate the structure of the human brain. While the brain is
made up of neurons, an artificial neural network is made up of a collection of
interconnected "neurons". Each neuron receives input, processes it, and transmits the
resulting output. The learning process is carried out either between neurons or within
the network itself. The network "learns" based on the information and gains experience,
which helps it to perform new and complex tasks.
The main parts of a neural network are as follows: Input layers - Incoming data is
fed into the network in this layer.
Hidden layers - Data is processed through hidden layers, and the learning process
of the network continues.
Output layers - The final result of the network, a classification or prediction, is
produced in this layer.
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The network changes its parameters (such as weights and intercepts) as it
processes data, which allows it to work more accurately and efficiently.
Role in society. Economic development. Artificial neural networks are bringing
about major changes in the economic sphere. They help automate production
processes, increase efficiency, and optimize resources. For example, automated
systems or thick production lines, quality control, and inventory processes become
more efficient, reducing costs and speeding up production.
Neural networks are also used in the financial sector, for example, in making
decisions on credit applications, detecting fraud, and analyzing investments. Banks and
financial institutions use AI to make quick and accurate decisions, which allows them
to improve their customer service.
Healthcare. In healthcare, artificial neural networks are making revolutionary
strides. They are used to analyze medical images, such as X-rays, MRIs, or ultrasounds.
Neural networks can detect and diagnose various diseases at an early stage. For
example, neural networks have been very effective in detecting oncological diseases,
such as cancer, in medical images.
In addition, AI is also used in genome analysis and genetic diseases. The role of
artificial intelligence in developing personalized medical treatment approaches is
increasing, but this mindless learning helps to improve health.
Education. In the field of education, artificial neural networks help to create
learning systems that are adapted to students. But first of all, they organize services
and develop customized learning programs, determining their speed. Such systems
allow students to manage their own learning processes, and also help teachers
implement an individual approach to each student.
In addition, SNTs are used in online learning platforms, for example, in video
lessons or in data classification. But they increase the efficiency of learning and allow
students to be provided with the necessary information in a timely manner.
Transport and logistics. Artificial neural networks are also widely used in the
transport and logistics sectors. For example, autonomous transport systems, i.e. self-
driving cars, work with the help of neural networks. Autonomous vehicles use neural
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networks to analyze their surroundings, detect obstacles, and obey traffic laws to
operate safely and efficiently. This, in turn, helps to ensure human safety and makes
transportation systems more efficient.
In logistics, neural networks are used to optimize inventory and supply chains.
They help predict customer demand, distribute cargo, and reduce transportation costs.
Daily life and information technology. In everyday life, artificial neural networks
are used in personal assistants, such as Siri, Google Assistant, and Alexa. These
systems help users perform various tasks: making phone calls, writing text messages,
listening to music, and many other tasks.
Neutral networks are also used in social networks, for example, to display ads
tailored to users, describe content, and detect malicious content. With the help of
artificial intelligence, data from social networks is analyzed and the opportunity to
offer relevant content to users has been created.
Ethical and social issues. Artificial neural networks are raising new ethical and
social issues in society. For example, deepfake technologies can create fake videos,
which can harm people's privacy. Also under discussion are issues such as what
algorithms are used in the decision-making processes of SNTs, how data is collected
and how it is used.
In addition, the widespread use of automation and artificial intelligence may
deprive some workers of their jobs. These issues are widespread in society, and
solutions must be developed by governments and corporations to ensure social
equality.
Artificial neural networks are bringing about major changes in society. In areas
such as increasing economic efficiency, creating innovations in healthcare,
individualizing education, developing transportation, and making everyday life more
convenient, ANNs are playing an important role. However, along with their
development, ethical, social, and economic issues need to be addressed. In order to
fully utilize the impact of artificial intelligence on society and ensure the overall
development of humanity, a careful and responsible approach to managing these
technologies is needed.
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