Feature
The very ubiquity of AI tools means that there is no differentiation or competitive advantage in using the same tools as everyone else.
or resource intensive jobs they do now which they would (perhaps happily) have some assistance in making quicker and/ or more efficient. Identifying where automation delivers joint benefit – freeing up staff to do more interesting and rewarding work as well as enabling more output with similar inputs – seems like a good place to start.
3. Prepare people to work alongside Generative AI. Some of this will be about mitigating the negative effects of AI. There have been well-evidenced examples of Generative AI providing answers that sound correct, but which are based on inference. As OpenAI’s Chief Technical Officer has confirmed, ChatGPT and other AI tools generate answers that appear reasonable but may be factually inaccurate. What’s more, depending on the data set the AI has been trained on, there is the potential for inaccuracies to be amplified. There will be a requirement for checking and quality control of AI-Generated outputs. This may reduce over time. After all, machine learning is continuous and one would hope it will, therefore, get more accurate the more it is put to work. When Generative AI really gets to work
will be when it has been trained on in- company data sets in order to automate specific activities which currently require human interaction. How good is your organisation’s data? Maybe not the most exciting starting point, but a vital one will be to ensure you are training AI tools on data that is complete and accurate. We should prepare people to use
Generative AI alongside the judgment and experience of real people. Generative AI is more than a sophisticated search engine. Its capability to enter into a discussion, to answer follow-up questions (such as ‘Are you sure that’s right?’) is one of its breakthrough features. People need skills to question, check, and manage the outputs it provides.
4. Above all, in the aftermath of automation there will be work activities that Generative AI cannot do – or at least tasks it will not be trusted to perform by employees, customers and service users. These will be the skills most urgently required during and beyond any transformative introduction of automation. Organisations will still require communication skills at a level beyond AI; we will need to invest in the skills to perform where the human touch is still valued – and may well become more so.
Handled well, Generative AI has the potential to free creativity and make collaboration and idea-sharing boundaryless and more democratic. If we are to deliver on the promise of being freed from routine, mundane and repetitive work, we will need teams who can come up with creative sparks of genius that go beyond a repetition of what has gone before. In the past, we have been seduced by the promise of automation to deliver increased efficiency, greater productivity and more leisure time. Instead, we have experienced increased inequality and – for those who retain their jobs – a need to work longer, harder and for less reward. We have another chance to get this stuff right. Let’s not blow it in a machine-inspired race for productivity which happens to us, not with us. n
Robin Hoyle is World of Learning Conference Chair and author of two books. He is Head of Learning Innovation for Huthwaite International and will be delivering the Closing Keynote session at the World of Learning Conference on 31 January – “Ensuring you get value! Practical steps to take tomorrow”.
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