Artificial Intelligence (AI) is one of the most rapidly advancing technologies that has received increased attention. There has been an increase in adoption of AI systems by most businesses and organizations because of their capability to perform a wide range of tasks with great accuracy and efficiency.

AI is an intelligent entity that can perform various tasks intelligently without being explicitly instructed by a human being. AI applications are hitherto visible in communication, public safety, transportation, healthcare, entertainment, and education.

Artificial Intelligence works by merging a significant amount of data with swift, iterative processing and intelligent algorithms that enable machines to learn automatically from features or patterns in the data. The creation of an AI system involves the careful process of understanding human capabilities and transforming them into a machine. The significant components of AI include natural language processing, machine learning, deep learning, and cognitive computing. Machine learning teaches how to make inferences based on past experiences by analyzing data and identifying patterns. Deep learning equips a machine to process inputs through layers to infer, classify, and predict the outcome. Natural language processing is a science of understanding, reading, and interpreting human language by a machine for communication. Cognitive computing involves designing algorithms that help the machine mimic the human brain by analyzing objects, images, speech, and texts in a manner that a human does to provide the most desired outcome.

Akin to any other technology, the use of AI machines has both positive and negative impacts. The prime advantage of AI machines is their capability to perform a wide range of complicated tasks with great accuracy and precision. With incredible accuracy and speed, AI machines can facilitate humans in tedious, repetitive, and laborious tasks.

There have been concerns regarding the use of AI including the issues of data quality and potential bias, a lack of interpretability and transparency in decision making, its potentially disruptive impacts on economic and social structures, and consideration regarding accountability.

Four Types of Artificial Intelligence

Reactive machines are the type I of AI systems that cannot form memories or apply past experiences to inform present decisions. This type of AI machine perceives the world directly and acts according on what they see. They analyze all possible alternatives and select the most efficient one. Deep Blue, the IBM chess program, is a famous example of reactive machines.

Limited memory is a type II of AI systems. These AI systems can use their past experiences to inform current and future decisions. Self-driving cars are an excellent example of type II AI systems. Self-driving cars have decision-making systems that enable them to consider actions, such as changing lanes, avoid being hit by an approximate car or cutting off another driver, based on the observations. However, these observations are only transient because type II AI systems have no permanent storage.

The theory of mind is type III of AI systems. At the moment, these types of AI systems do not exist. However, it is anticipated that there will be AI machines with the capability to form representations about the world and other entities in the world in the future. Basically, to understand that other entities in the world have their desires, intentions, beliefs, and opinions.

Self-awareness is type IV and the last category of AI systems. This is the most sophisticated and highest level of AI with a sense of self, emotions, consciousness, and awareness. It is still a work of science fiction and not something that exists – and in fact, may never exist.

There has been an increase in the adoption of AI systems by most businesses and organizations over the past several decades, and the trend is anticipated to continue.  AI has aroused both fear and excitement in us. Without a doubt, AI is the future of the world and will soon become part and parcel of human life. While we are far from creating AI that is self-aware, it is important to focus on moving forward in understanding memory, learning and the ability to base decisions on past experiences. This is an important step in understanding human intelligence on its own. We are living in an exciting time for AI development and the changes will make most people better off over the next decade.