Masters of All We Survey

Using tools to achieve better results is at the heart of what it means to be human. Fire. The wheel. A fork. A Dyson. Like the tools before it, emerging technologies are transforming and disrupting the landscape. And as before, it will be how we use it that differentiates great from mediocre. 

For HE – indeed for every sector – securing the right skills will be key.  To a certain extent, universities here have an advantage – those with a mastery of AI and other emerging technologies are likely already found within their academic population. But securing other, more practical skillsets, will require universities to compete for a scarce market resource along with everyone else.  

But it is not just about mastery: whilst securing in very high level of proficiency within the organisation is critical, some level of competence will be needed by everyone.  

Technical literacy is a must-have not a nice-to-have. 

Mastering GenAI

GenAI might not replace you, but someone who has mastered GenAI might.  AI is to work what fire was to cavemen. It will change everything. This is partly because it is a threat to the kind of jobs that weren’t threatened by other technological advances. The jobs of the white collared worker, middle of the economy, skilled, educated, but not specialist.  It targets not just the administrative and the routine, but the creative and strategic as well, and so what we will need is to not compete with it, but to master it, to use it to expand our capabilities and accelerate our own pace. For example, in the US, universities lecturers are using AI tools to act as virtual tutors when they are not available – so students always have access to some level of support.  

Mastering also means understanding the full implications – and limitations - of its use. For example, Chat GPT can sometimes incorporate inaccurate or just plain made up information - “Ghosts” - in the content it generates. This means understanding of the importance and limitations of data, and digital ethics, becomes really important. 

Critically, GenAI is only as good as the data and the instructions it is given – and those who remain lazy or uninformed about its use will lose out to those able to leverage it effectively.

Driving data literacy

Critical or complex thinking doesn’t feel like something in short supply in academia, so this one feels like low hanging fruit. However, the trick will be using these inherent capabilities in partnership with the emerging technology to think bigger and better than before. And that demands data literacy. 

The ability to crunch unfathomable quantities of data in seconds is at the fingertips of us all: the Big Data promise of the last decade finally coming to fruition. But to analyse any data sets meaningfully demands proficiency in data analytics tools, and familiarity with technical language and code.  And then there is the need to interpret and present large data sets clearly and simply, to visualise data in a way that can be understood easily by others. Tools such as PowerBi offer an entry point but - with the processing power of quantum computing on the horizon – data literacy must become the norm. 

We opened this article with the assertion that we need new skills for a new economy – perhaps the last and potentially most valuable could be summarised as human curiosity.  Technology will do things we cannot currently imagine, but at its heart must be the innovative and curious nature of the mind, that sets the exam, asks the question so to speak, that the technology must answer.