Artificial intelligence (AI) is a term used to describe “intelligence” demonstrated by machines. AI programs may mimic or simulate cognitive behaviours or traits associated with human intelligence such as reasoning, problem solving and learning.
Depending on how and if we use it, the future of businesses and the human workforce can be potentially transformed and disrupted by AI as it rapidly evolves, enabling robots and machines to perform the tasks that humans do. From the automation of mundane repetitive tasks to making complex decisions, the opportunities offered by AI can lead us in a variety of directions. As we continue to unlock the potential of AI, we will be changing the way the world works fundamentally and forever.
This emerging technological advancement raises the question: what is (or will be) left for humans to do? If robots and machines can do our jobs in the future, the same way we do them or even better, where do humans fit in the equation?
Understanding the present state of AI capability (or limitations of) and speed of development, computing power and associated resources, it is critical to consider the possible implications and opportunities of AI, as well as actively shape the development and application of these technologies in a way that better serves humanity rather than negatively impacting it.
AI technologies are constructed by mathematical processes that leverage increasing computing power to deliver faster and more accurate models and forecasts of operational systems, or enhanced representations and combinations of large data sets.
However, while these advanced technologies can perform some tasks with higher efficiency and accuracy, human expertise still plays a critical role in designing and utilising AI technology. Human intelligence is what shapes the emergence and adoption of artificial intelligence and innovative solutions associated with it. It is human intelligence that seeks to ask ‘why’ and considers ‘what if’ through critical thinking.
As engineering design continues to be challenged by complex problems and quality of data, the need for human oversight, expertise and quality assurance is essential in using AI generated outputs.
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