Ai skills gap

See it

With the many AI tools and systems available, AI skills development, and upskilling programs are increasingly being perceived as essential within universities, organisations, and other contexts. This can be problematic in settings such as higher education, as while there is a rush to address the AI skills gaps, this can result in overlooking the digital skills gap, which is yet to be addressed.

Concepts such as digital literacy and fluency are increasingly significant when considering the digital skills gap, as they are prerequisites for the development of AI skills and literacy. The former (digital literacy) refers to the foundational skills and competencies needed to comprehend and use digital tools and systems. The later (digital fluency) implies innovative, strategic and critical engagement with said tools and systems toward applying and transferring digital skills to other contexts, such as when using a new AI tool.

Failure to invest in and strengthen digital literacy and fluency programs in universities can potentially result in many adverse consequences, including an inability to access and consume materials within AI literacy programs; constant feelings of inadequacy when it comes to AI use and adoption; pressure associated with the need to constantly be up to date with developments in AI; lack of innovative, critical, strategic and ethical thinking; and AI training fatigue, among other implications. The outcome of these scenarios is emotional and cognitive exhaustion, which can have detrimental pedagogical and research-related consequences for educators, researchers and other University stakeholders.

Say it

Being aware of the need for foundational digital literacy and fluency skills is a helpful starting point. However, beyond awareness, it important for the information systems community to point out the current lack of attention to these concepts, and to the digital skills gap more broadly.  This can be achieved by clearly stating, in suitable forums, why an over emphasis on AI literacy, without sufficient consideration of digital literacy and fluency, is concerning. Appropriate settings to make such claims may include teaching and learning forums, research project meetings, Faculty / formal committee meetings, strategy sessions and other University gatherings.

This calls for confidence on the part of the information systems community to declare and exhibit their socio-technical expertise, when needed. To go against the grain and challenge the AI hype, misguided optimism and simplistic assumptions relating to the AI skills gap and AI literacy.

When we ‘say it’, we are issuing an invitation to reexamine the digital skills gap or momentarily pause an AI literacy or skills discussion. We are fundamentally challenging the unrealistic expectation that the AI skills gap can be adequately addressed without first developing the core socio-technical skills needed to attend to the digital skills gap.

Saying it does not mean we are halting all AI skills development and literacy initiatives. Rather, it suggests that we first satisfy our digital literacy and fluency needs, which will differ from context to context, prior to establishing AI literacy programs.

Sort it

To sort the issue, ensure that sufficient information is disseminated to relevant university stakeholders regarding the importance of digital literacy, the difference between digital literacy and fluency, and the relationship between digital and AI literacy. This form of information sharing will support the next step, which is to assess the current digital and socio-technical skills levels within a specific work context, such as a discipline, team, school, department or institution.

Assessing the current landscape will allow for appropriate socio-technical expertise to be solicited from disciplines such as the Information Systems discipline for the purpose of providing guidance about how the digital skills gap can be addressed in a particular context. This will form a solid foundation for addressing the AI skills gap, avoiding a one-size-fits-all approach to AI literacy.

  • See the importance of addressing the digital skills gap prior to considering the AI skills gap.
  • Say it confidently in the necessary forums to ensure that unrealistic expectations regarding AI training and skills development are challenged.
  • Sort it by integrating context-specific, socio-technical skills in digital literacy programs before considering AI literacy and skills development.

By Roba Abbas