Artificial intelligence (AI) is a term used in various ways by experts from different disciplines, such as mathematicians, computer programmers, and information and communication experts. AI has no single, widely recognized definition.

According to Hilker (1986, p. 15), AI is a branch of computer science that focuses on the ability of computers to perform intelligent tasks, including recognition, reasoning, and learning.

Mogali (2015, p. 2) states that AI mainly focuses on understanding and performing intelligent tasks such as reasoning, learning new skills, and adapting to new situations and problems.

The United Nations’ Information Economy Report (UNCTAD 2021, p. 17) defines AI as the ability of machines and systems to acquire and apply knowledge and to carry out intelligent behavior. This may involve tasks such as sensing, processing oral language, reasoning, learning, making decisions, and manipulating objects.

In summary, AI is a subfield of computer science that involves the ability of machines to simulate human intelligence. It is used in decision-making, processing big data through machine learning, image and text processing, robotics technology, and chatbots.

Computer science’s artificial intelligence (AI) field seeks to build machines that can carry out tasks that normally require human intelligence. Some key concepts and components of AI include machine learning (ML), natural language processing (NLP), computer vision, robotics, expert systems, deep learning, and reinforcement learning. AI has various applications, from self-driving cars to medical diagnosis and financial analysis.

What are the uses of artificial intelligence in our real lives?

Artificial intelligence is integrated into our daily lives to help us manage tasks and provide information:

Maps and Navigation: AI is used by maps and navigation systems to analyze massive amounts of data from multiple sources, including GPS, traffic cameras, and user inputs, in order to provide real-time traffic updates, optimize route planning, and forecast travel times. By spotting trends and abnormalities, machine learning algorithms increase the precision of traffic forecasts and route recommendations. To improve the user experience with hands-free navigation, AI-powered voice assistants also provide turn-by-turn directions.
Facial Detection and Recognition: Artificial intelligence is used by facial detection and recognition systems to recognize and authenticate people by examining facial features in pictures or videos. These devices are frequently used in surveillance and security to monitor public areas and identify unauthorized entry, thus increasing safety. Consumer electronics also use facial recognition for functions like smartphone unlocking and user experience personalization.
Text Editors or Autocorrect or Translator: Artificial intelligence (AI) is used by text editors and autocorrect systems to improve writing by making correction suggestions and predicting words based on context, increasing efficiency and accuracy. Machine learning is used by AI-powered translators, such as Google Translate, to continuously improve the quality of translation as they analyze and translate text between languages. These tools help people communicate and are more productive by offering accurate translations and real-time support to users all over the world.
Search and Recommendation Algorithms: Search and recommendation algorithms use artificial intelligence (AI) to evaluate user behavior and preferences and offer tailored content and product recommendations on websites like Google, Netflix, and Amazon. These algorithms use machine learning to improve the relevance and user experience of their recommendations iteratively. Artificial intelligence (AI)-powered search and recommendation systems enhance user engagement and experience by predicting users’ needs and interests.
Chatbots: Chatbots are AI-powered conversations that mimic human interaction and offer instant information and customer service on a variety of platforms, including messaging apps and websites. They use natural language processing, which gets better over time through machine learning, to comprehend and accurately respond to user inquiries. Chabot improves availability and efficiency by automating routine interactions, enabling businesses to provide customer support around the clock.
Virtual Assistant: Artificial intelligence (AI) is used by virtual assistants, like Siri and Google Assistant, to carry out tasks and deliver information through voice commands, simplifying daily tasks like making notes, sending messages, and doing web searches. Natural language processing and machine learning are used by these assistants to comprehend user intent and gradually enhance their responses. Virtual assistants improve daily convenience and productivity by providing personalized, hands-free help.

What are the Types of Artificial Intelligence?

Siau and Yang (2017) classify AI into two categories: strong (or artificial general intelligence) and weak (or artificial narrow intelligence). On the other hand, Harrison and Luna-Reyes (2022) use three categories:

a. Artificial Narrow Intelligence (ANI)

b. Artificial General Intelligence (AGI)

c. Artificial Super Intelligence (ASI)

1. Artificial Narrow Intelligence (ANI)

Artificial narrow intelligence, also known as narrow AI, is the capacity of a computer to carry out a single task extraordinarily well. It is the most common and simplest form of AI, also known as weak AI. ANI is used for specific, narrow tasks and depends on computer-based programs usually used for decision making (Harrison & Luna-Reyes, 2022).

Examples include virtual assistants like Siri by Apple, Alexa by Amazon, and Cortana by Microsoft, as well as facial/image recognition and interpretation software.

2. Artificial General Intelligence (AGI)

Artificial general intelligence is the capacity to carry out complex tasks with limited computational resources in complex environments. AGI, also known as strong AI, can perform complex and multitasking assignments, such as thinking like the human brain. The ability to transfer knowledge from one domain to another, autonomy, self-awareness, understanding problems rather than just solving those that programmers explicitly pose, the ability to solve problems that programmers are not aware of, smart devices and apps, and the ability to comprehend problems are among the key features of artificial general intelligence (AGI).

Examples include self-driving cars, expert systems, and language models like GPT.

3. Artificial Super Intelligence (ASI)

Artificial super intelligence is where machines become self-aware and surpass the capability of human intelligence and ability. In every way, artificial intelligence (ASI) is far smarter than humans. In specific domains, computers have already outperformed individuals, such as in multiplication.

Examples include Google DeepMind, an AI system capable of playing complex games such as Go and Chess, and AlphaGo, an AI system capable of playing the game of Go.

Types of Artificial Intelligence based on functionality:

Limited Memory AI: Limited Memory AI is a type of AI that can store knowledge and use it to learn and train for future tasks. An example of this is self-driving cars. These vehicles use AI systems that continuously collect and analyze data from their surroundings through sensors and cameras to make real-time driving decisions. The AI remembers recent actions and environmental conditions, such as the speed of nearby vehicles or the location of pedestrians, to navigate safely and efficiently.

Reactive Machine AI: AI that can react instantly to outside stimuli but is not able to learn or retain knowledge for later use. IBM’s Deep Blue, a chess-playing computer that beat world champion Garry Kasparov in 1997, is an illustration of reactive machine intelligence. Deep Blue had no memory of previous games, no ability to predict moves beyond its immediate calculations, and the ability to analyze millions of chess positions per second and make decisions based only on the position of the board. It was limited to reacting to the current state of affairs and was unable to draw lessons from past mistakes.

Theory of Mind AI: Theory of Mind AI refers to AI that can understand and interpret human emotions, beliefs, and intentions, enabling them to interact more naturally and empathetically with humans. While some advanced AI systems can recognize and respond to human emotions to a certain extent, fully realized examples of theory-of-mind AI remain a theoretical concept and area of ongoing research.

Self-Aware AI: AI that can recognize others’ emotions has a sense of self and human-level intelligence, the final stage of AI. Self-aware AI is still a theoretical idea that has not been put into practice yet. This kind of AI could comprehend its own existence and condition since it would have consciousness and a sense of self. Present AI technologies, including sophisticated models, function based on algorithms and data rather than having true self-awareness or consciousness. As of right now, no AI system is self-aware.

Artificial intelligence (AI) comes in many forms and applications. From limited memory systems and reactive machines to theoretical ideas like Theory of Mind and self-aware AI, AI advances automation, personalization, and effectiveness in a wide range of applications.