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AI is a hot topic, and there is a good reason for that- its impact will be widespread and profound. So profound that we are only just beginning to realize the extent of its current and potential applications and its benefits and issues.
Deep Learning is driving AI as a phenomenon, and it’s uptake by both public and private and public sector organizations. Deep Learning is the part of AI that mimics the way the human brain learns and reacts. Deep learning enables AI to monitor its environment, to learn from it, and to react spontaneously and independently of human oversight or intervention. AI offers improved efficiency with savings in reaction time and associated costs, including staff costs, improvement in job quality, and resource allocation, but of course, there are downsides.
The societal consequences of AI are the focus of concern. It is clear that there will be an impact on existing jobs as AI changes the nature of occupations, though not necessarily on employment overall, because AI is opening new employment opportunities. There is also an impact on individual rights when decisions are made without human involvement, especially because AI can have in-built biases and flaws. Other commentators are concerned about the use of AI in autonomous weapons, the lack of humanity that involves and that AI could lead to a new arms race. Others note that AI is shaping geopolitics as nations vie for AI superiority in industry and commerce.
AI is already directly affecting a wide range of products and services provided by both the public and private sectors, and this is expected to expand significantly over the next years. AI can, and will, control all types of vehicles, including self-driving cars, machines ranging from those used in manufacturing to medical diagnosis and treatment, to utilities like power and water, and other essential services including street lighting, traffic lights, and security systems, to name a few. The extent and nature of AI’s use can be surprising. For example, AI is guiding resume selection for job vacancies. If you have been surprised not to be selected for an interview recently, it may be that your resume did not contain the required keywords needed to trigger an interview automatically. AI is also being used to evaluate performance, and this is true for occupations ranging from refuse collectors to lawyers to teachers.
There are also specific AI applications for every occupation in every sector. In schools and Universities, for example, AI can be used to automate class scheduling, for monitoring submission of assignments, marking and grade calculation, to detect plagiarism, analyzing student abilities and academic performance, and for designing personalized teaching and learning strategies tailored to individuals. But AI is the catalyst for a much more profound change in education as we now know it.
"AI can, and will, control all types of vehicles including self-driving cars, machines ranging from those used in manufacturing to medical diagnosis and treatment, to utilities like power and water; and other essential services including street lighting, traffic lights, and security systems"
It is clear from just this brief overview that AI will impact virtually every occupation and every product and service. For some, the level of automation will be extensive, for others less so; but AI will touch all endeavors and individuals. Consciously acknowledging that fact is a major change in thinking and approach, but inevitably must lead to a fundamental change in the way we educate the workforce of the future, particularly at University level.
Universities in the U.S. and beyond, follow a model developed centuries ago where disciplines are siloed, with little or no cross-departmental integration. The result is that Universities produce physicians, architects, lawyers, economists, and educators with only rudimentary and coincidental awareness of cyber. Similarly, Computer Science Departments produce IT professionals who have inadequate awareness and understanding of the legal implications of what they do, and little or no understanding of how product design and programming does, and can, address the needs of the occupations that use that technology.
Imagine a world where these silos collapse. Where cyber, including AI, is a core part of everyone’s university education. A cyber education for all because of cyber impacts us all, but not just a cyber course for each discipline. Instead, a trans-discipline program of integration and real-world application where IT students work with law students and they both work with students in specialties like health care, architecture and design, and business and economics, and with behavioral science students, to design and refine IT products and services that are truly functional. This level of collaboration can maximize utility, address issues and challenges in the application, and add overall value to the respective occupations and their work.
The objective of this type of approach is deeper understanding by students (and educators) of the profound impact of cyber technology like AI, on all endeavors and all levels of society; and how sectors and specialties can, and should, work together collaboratively to understand and address some of the most important issues facing us all. This type of initiative develops and fosters cross-discipline understanding and multi-discipline collaboration that is crucial to producing a workforce that can understand and collaboratively address the cyber opportunities and challenges of the next decade, including AI. The fact that AI has made it so clear that cyber affects everything and everyone, maybe AI’s greatest contribution to education.