Artificial intelligence

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Artificial Intelligence is new field of science. The possibility of defining the concept very much depends on the state of research and development carried out in parallel in research centers around the world. Attempts to define AI are difficult. As difficult as defining intelligence of man - a rational being. Consequently, over several years, some sample definitions appeared:

  • Machines designed in such a way that their actions result reflects the result of the activities of human thinking [1]
  • Process of automation of certain tasks, such as making decisions and learning, that is a reflection of human intelligence [2] (R. Bellman, 1978, p. 12)
  • Field of research seeking to explain and implement intelligent behavior through the use of computational processes [3] (R. Schalkoff, 1990, p. 35)
  • Systems that think and behave like men, that is, think and behave in a rational way [4] (S. Russell, 2003, p. 16)
  • Science covering issues of algorithms, fuzzy logic, evolutionary computation, artificial neural network, artificial life and robotics. Artificial intelligence is a branch of computer science, whose subject is the study of the rules governing intelligent human behavior, the creation of formal models of these behaviors, and - as a result - computer software simulating the behavior " [5] (P. Thagard, 1993, p. 11)

Examples of application

The most common artificial intelligence algorithms:

  • herd algorithm,
  • finite states automata,
  • decision trees,
  • fuzzy logic, fuzzy systems,
  • artificial neural networks,
  • evolutionary algorithms,
  • hybrid algorithms.

Advantages of Artificial intelligence

AI has many advantages:

  • It can reduce human workloads and help in the automation of tedious and repetitive tasks. This can save time and money for businesses, allowing them to focus on more important matters.
  • AI can also help in decision making, by analyzing data and providing insights that can help businesses make better decisions.
  • AI can also be used to detect and prevent fraud, as well as to detect cyber-attacks and other malicious activities.
  • AI can also be used to optimize digital marketing campaigns and other online activities, allowing businesses to reach more potential customers.
  • AI can be used to improve customer service, by providing automated customer service agents that can respond quickly and accurately to customer inquiries.
  • AI can also be used to improve medical diagnosis and treatments, by providing more accurate diagnosis and treatments to patients.

Limitations of Artificial intelligence

Artificial Intelligence (AI) is an ever-evolving field of research, however, there are certain limitations to the technology. The main limitations of AI are:

  • Limited ability to use context: AI programs lack the ability to understand context and the nuances of language, which can lead to unexpected outcomes.
  • Limited scalability: AI programs cannot accommodate large amounts of data, which can lead to inaccurate or incomplete results.
  • Difficulty in making ethical decisions: AI programs can make decisions based on limited data and criteria, which can lead to ethical concerns and dilemmas.
  • Difficulty in understanding creativity: AI programs lack the ability to recognize creative solutions or generate creative ideas, which can limit their usefulness in certain applications.
  • Difficulty in replicating human-like feelings: AI programs lack the ability to recognize or respond to emotions, which can limit its effectiveness in certain fields such as healthcare or counseling.
  • Difficulty in understanding complexity: AI programs can have difficulty understanding complex relationships between data points or within data sets, which can limit its ability to make accurate predictions.

Other approaches related to Artificial intelligence

In addition to AI itself, there are many other related fields of research and development that have an impact on the development of Artificial Intelligence. These can be broadly categorized as follows:

  • Machine Learning - where the computer is given a problem and the computer has to figure out how to solve it without any explicit instructions. This involves using algorithms to analyze large sets of data and identify patterns.
  • Natural Language Processing (NLP) - where the computer is given a problem and it has to understand the problem in a human language. This involves using algorithms to interpret spoken or written words and then translate them into a set of instructions that the computer can understand.
  • Computer Vision - where the computer is given an image or video and it has to interpret what it is seeing. This involves using algorithms to recognize objects and patterns in images, videos, and other sources of data.
  • Robotics - where the computer is given a robot and it has to control the robot’s movements and behavior. This involves using algorithms to control a robot’s movements and allow it to interact with its environment.
  • Automation - where the computer is given a task and it has to figure out how to do it without any explicit instructions. This involves using algorithms to automate tasks that might otherwise be done manually.

In summary, Artificial Intelligence is a complex field of research and development that involves many different fields and sub-fields, all of which are interconnected and have an impact on the development of AI. These include Machine Learning, Natural Language Processing, Computer Vision, Robotics, and Automation.

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  1. [1] J. McCarthy, author of the term "Artificial Intelligence", formulated in 1955 at a conference in Dartmouth, 1955
  2. [2] R. Bellman, An Introduction to Artificial Intelligence 1978
  3. [3] Robert J. Schalkoff, Artificial intelligence: an engineering approach, 1990
  4. [4] S. Russell, P. Norvig, Artificial Intelligence: A Modern Approach, 2nd edition, Prentice Hall, 2003
  5. [5] P. Thagard, Computational Philosophy of Science, 1993