In today’s world, I would imagine having the right to choose means everything to you. But is this being factored in when it comes to developing our AI capabilities?
On this morning’s jog around the park, I was turning this over in my head, reflecting on a recent hyrox fitness session that I did with a friend – my first (and probably last!).
Whilst she really enjoyed the structured, demanding workout in the gym, my body was craving open fields, solitude (and a rest!). Fast-forward an hour, and I got my own back on her in a swimming race!
Aside from proving my fitness levels are not what I thought they were, it highlighted that we achieve more in doing things that we enjoy and have an interest in. It also showed how much we can be put off doing something for a second time, if we’re pushed outside of our comfort zones too much and too fast.
And I believe this same rule applies when we try to support colleagues to improve their AI capabilities.
Staying with the exercise-theme, imagine if you were tasked to organise an exercise event for a co-department away day and you ran the same class for all 400 staff. What do you reckon your potential for successful engagement would be?
But imagine if you’d allowed people to select their class from a range of varying activities dependant on their capability, interest and experience.
My point:
When it comes to trying to improve our own or colleagues AI capabilities, we have to listen to our hearts and each other’s as to how best to go about doing this; recognising that not everyone has the same interests, capabilities and experience – and in fact we can do more damage than good by not listening.
How to help?
- Start off by listening to your staff and students – what are their thoughts/ concerns/ experiences when it comes to using AI? As MIT’s report ‘Bringing worker voice into Generative AI’ concluded “Our primary recommendation…is to recognize the need to incorporate the perspectives of workers into the ongoing discourse about generative AI….The broader the set of stakeholders involved in defining the problems and opportunities that generative AI technologies can address, the more likely it is that these tools will be used to augment how workers do their jobs rather than displace them.”
- Ensure that a range of voices are heard – and it’s not just the AI enthusiasts that always turn up to training! Often, it’s hearing the voice of the people that don’t come to the training that can be the most powerful in helping you understand the real challenges.
- Create training that is task-based and role-specific – recognising that the AI usage of an academic will probably be very different to a PS staff member. In order to make the training valuable and its impact sustainable, it needs to be relatable and immediately useful.
- Develop or promote the work of your AI champions – recognising the value of peer-to-peer learning and colleague testimonials. The passion and enthusiasm that AI champions often have, can be a huge enabler in encouraging a positive environment and mindset to develop.
- Listen again – as people’s experiences and capabilities in using AI change, so do their L&D support needs. Identifying what the barriers are when it comes to engagement with training, or equally the need for more advanced support to be delivered as people’s capabilities develop, will be essential in maintaining and sustaining momentum.
About the author: Katie Steen is the co-founder of WorkSmart-AI, which specialises in supporting universities to adopt AI, through senior leader consultancy and task-based workforce training.
Katie and her co-founder Dave Weller have both worked within educational L&D and communications for over twenty years, most recently as Digital Skills Leads at the University of Exeter.
If you would like to chat through ideas on building your staff or students AI capabilities, please get in touch, or visit our website – www.worksmart-ai.co.uk.