Artificial intelligence (AI) is an aspect of computer science that is concerned with machine intelligence. Machine intelligence can be described as the theory and development of computer systems to have the capacity to carry out tasks that would ordinarily require human input or intelligence. Some of these tasks include speech recognition, visual perception, language translation and decision making.
AI makes it possible for machines to learn over time from previous experiences and subsequently learn new inputs and carry out tasks that would typically require human intelligence. Most AI systems ranging from self-driving cars to speech recognition and chess-playing computers depend primarily on natural language processing and deep learning.
AI operates primarily by combining several volumes of data with iterative, quick processing and smart algorithm, that enables the software to learn unaided overtime from its self-study of data features and patterns. AI is a very vast field that is made up of several branches of theories, methods and parts. Some of which include;
Machine learning relies on several concepts from statistics, neural research, physics and operation research to uncover extraordinary details about a data or pattern without clear instructions of what needs to be done or what needs to be found. Machine learning by default learns and improves from experiences without an explicit directive to do so. Thus, a computer program that basically develops itself by continuously studying various types of data and pattern.
Deep Learning combines vast neural networks and a plethora of processing units, depending heavily on strides made in improved training and computing processes to learn sophisticated pattern and data in large forms. Speech recognition is a typical application that requires deep learning.
Natural language processing (NLP) is a branch of AI that describes the ability of a computer to understand, interpret and process human speech. NLP involves the application of several computational techniques that enable a computer program to understand and interpret spoken language.
With several advances and strides in AI, there is the impending fear that engineering jobs would soon be swooped by automated systems. The possibility that machines could oust engineers have been one that has come up very often, yet the pointers indicate that it is improbable. A one-hundred-year study on AI that was carried out by Stanford University in September 2016, further went on to clarify that engineering jobs are under no imminent threat by AI.
It is also believed that as the concepts around AI improves, those with a strong background in STEM (Science, Technology, Engineering and Mathematics) will be highly sorted after. Similarly, It is also widely believed that as AI continues to develop, most engineering jobs will still require a close working partnership between computer and humans.
History has shown that technological advances have always created more jobs than it has taken away and with the rapid development of technology, engineers would still be needed to test the application of these systems in a variety of industries and context.
The Times also predict that there are less than 10,000 people that have the background and are capable of filling positions in AI software engineering. Clearly, the demand for AI software engineers by far surpasses the supply. This has even led to the recruitment of other experts with strong STEM skills from other closely related fields like astronomers and physicists to fill this vacuum.
Furthermore, as other less developed aspects of AI come into play, new kinds of engineering experts would also be needed to manage and maintain new applications of AI.
All the signs point to the fact that engineers will always remain relevant as long as the evolution of AI is concerned. What is in doubt is whether the role engineers will play in AI development will evolve as Artificial intelligence develops. However, it is certain that not only would engineers apply AI to solve problems, but they would also be a crucial part of its development and future moving forward.