From the Greek myth of Pygmalion to the Victorian tale of Frankenstein, humans have long been fascinated by the idea of creating a man-made creation that can think and act like a person. Today, with processing power that far exceeds our own and the ability to grasp human behavior at a fundamental level, artificial intelligence (AI) can seem to present a dystopian, sci-fi future in which human beings become increasingly obsolete. But AI systems are not self-contained, independent entities that replace people – rather, they are agile, responsive technologies designed to improve and augment business processes, while also making them more adaptive and adaptable in the face of change.
AI applications are built on a foundation of machine learning – a process that begins with collecting large amounts of data and then reviewing it for patterns and correlations. The data is then used to develop a set of rules that provide computing devices with step-by-step instructions for how to complete a task. For example, an image recognition tool can learn to recognize certain objects by reviewing millions of examples. Once an algorithm has been developed, it can then be applied to new, unseen data sets to see how well it performs.
As data sets have grown in size and complexity, businesses have relied on AI to help them analyze and extract useful insights from it. This allows companies to identify trends, improve operations and processes, and quickly respond to market changes and customer needs.
One of the biggest hurdles to implementing AI has been the availability of adequate computing capability. However, the 2010s saw a steady stream of developments in this area – including the launch of Apple’s Siri and Amazon’s Alexa voice assistants; IBM Watson’s victory on Jeopardy; and self-driving cars.
In addition, specialized hardware is being developed to speed up some types of AI processing. This can reduce the time needed to train an AI model, as well as eliminate the need to send data from a client device to a server – which saves bandwidth charges and electricity costs. For example, a company called D-Matrix is developing chips that move standard arithmetic functions closer to the data stored in RAM cells. This speeds up the process and can reduce energy consumption by up to a third.
In the near future, AI will enable computers to perform a wide variety of tasks – from interpreting the results of medical tests and diagnosing diseases to writing music, filming movies and editing photographs. The potential for AI to revolutionize the world of work is enormous. However, the benefits of AI will be realized only if it is implemented in an ethical and responsible manner. To achieve that, there are several key factors to consider: