I came to artificial intelligence not primarily as a technologist, but as someone who has spent a lifetime working with ideas, people, places, words and images.
My background crosses geography, history, education, communications, writing, visualisation, coaching and public life. That breadth has probably shaped the way I use AI. I am less interested in asking what the technology can do in isolation than in exploring what happens when it is placed alongside human memory, judgement, creativity and experience.
Over time I have become an intensive and increasingly methodical user of generative AI. I use it for research, writing, historical reconstruction, visualisation, teaching, coaching, civic work and, particularly, for a long-running autobiographical archive based on diaries, letters, photographs and memories extending back more than fifty years.
That work has taught me something important about AI. It is extraordinarily powerful, but it works best when the human remains firmly in charge of the purpose, evidence and judgement.
For example, I do not simply give AI an old diary entry and ask it to improve it. I have developed a staged process. First we preserve the original language. Then AI asks questions that help recover memories. Those recollections are incorporated carefully, without inventing what cannot genuinely be remembered. Only later do we shape the material into something suitable for publication. The machine assists with organisation, questioning, comparison and expression, but the memories remain mine.
That distinction matters.
AI can be astonishingly good at detecting connections, organising complexity, offering alternative formulations and helping us see material afresh. It can also be confidently wrong, excessively smooth, historically careless or too eager to complete a pattern. Learning to use it therefore means learning both when to trust it and when to challenge it.
I have found that productive use of AI is much closer to a conversation than to operating a conventional computer program. You explain what you are trying to achieve, examine the response, correct misunderstandings, refine the instructions and gradually develop a shared working method. Context accumulates. Vocabulary develops. The relationship between intention and result becomes more precise.
The better I have become at using AI, the less inclined I am simply to accept its first answer.
That may be one of the most useful lessons I can pass on to others.
Good AI use is not about discovering a collection of clever prompts. It is about learning how to think with the technology while retaining intellectual independence. It requires curiosity, scepticism, patience and clarity about what belongs to the machine and what must remain human.
I am particularly interested in helping people move beyond the two common extremes: treating AI either as a miraculous oracle or as something inherently threatening. It is neither. It is a new intellectual tool of remarkable breadth, and we are still discovering the forms of collaboration it makes possible.
For writers, it can become an editor and interrogator without becoming the author. For teachers, it can create explanations while leaving educational judgement with the teacher. For researchers, it can accelerate exploration while making source criticism more important, not less. For organisations and public bodies, it can help untangle information and explore alternatives while leaving responsibility firmly with people.
And for individuals, perhaps its most interesting potential is personalisation. An AI that gradually understands how somebody works—their vocabulary, interests, projects, standards and preferred methods—can become much more useful than a generic chatbot.
My own experience has therefore left me both enthusiastic and cautious. I see enormous possibilities, but I also think the most interesting question is not simply what artificial intelligence will become.
It is what we will learn to do with it.
That is the territory I would like to help others explore.
Leave a Reply