**5. Perspectives on artificial intelligence**

Scholars like Wilson [5] observed that the rapid development of Artificial Intelligence (AI) heralds an era, one of machines or devices that are capable of learning by themselves (machine learning), and of imitating the human thoughts. The processes and concepts that relate to AI have been around since the 1950s. The term was coined by John McCarthy in 1955 and was popularised in 1956 at a research congregation in Dartmouth College in the United States. Furthermore, the United States Department of Defence focused on the development of Ai in the 1960s and produced computers to imitate basic human reasoning. Casey [6] remarks that although, AI is not new, it has become a technology of immense significance that anyone can hardly predict precisely where it is heading.

Within this context, AI is about systems that can learn and evolve through experience, which would most times carry our specialised tasks in gaming, decisions making and to transform large, complex, ambiguous information into real insights, to solve some of the world's most enduring problems. Sraders [7] sees AI as the science and engineering of making intelligent computerised machines that are programmed to closely imitate human thoughts and actions for the purpose of analysing data to address a variety of problems or execute tasks. It is a computer science filed that ensures the creation of intelligent computerised machines which are enabled to perform tasks, which normally requires human intelligence. These tasks include speech recognition, translation between languages, visual perception, etc.

Although AI is generally a broad term, there are different types or kids of AI, designed to perform different tasks. For example, there is specialised and general AI. Sraders [7] states that specialised AI is AI that is programmed to perform a specific task. Its programming is meant to be able to learn to perform a certain task – not multiple. On the other hand, general AI is not limited to one specific tasks- it is able to learn and complete numerous different tasks and functions. In general, much of the cutting-edge, boundary-pushing AI developments of recent years have been general AI.

AI is made up of a large variety of sub categories and areas in which they are applied some of these sub categories and the advanced abilities they offer include:


Therefore, in recent times, AI has risen to the forefront of public discourse because of its significant influence in the areas of cloud computing, big data, the Internet of Things (IOT), virtual reality and its potential to bring new possibilities for global development [8]. AI is already transforming web search, advertising, e-commerce, finance, logistics, media, and several other areas. The target of AI technology is to provide systems that would enable human-like interactions with software and provide decision-support for specific tasks [9].

Although AI technology is very effective for certain specific tasks, it is still limited and far from matching the highly diverse cognitive abilities of humans. There are still deficiencies in the AI technology. For example, virtual assistants such as Orange's Djingo, Amazon's Alexa, etc. cannot yet respond to questions using natural language, but this is surmountable in not too distant future. Re-echoed some of the limitations of AI to include data labeling, which has to be done by human, explainability problem, generalizability of learning and bias in data and algorithms, all of which would require human assistance for now.
