Someone hands you a phone.
You can see the problem almost immediately.
You could probably fix it in thirty seconds, hand the phone back and say, “There you go.”
Problem solved.
But perhaps not much has actually been learned.
That small moment captures something I have been thinking about increasingly in my digital inclusion work: what does good digital help actually look like?
It is easy to measure whether a problem has been fixed.
It is harder to measure whether the person leaves with greater confidence, understanding and ability to deal with something similar next time.
And I am beginning to think that distinction matters enormously.
The temptation to be the expert
If you know your way around technology, it is very easy to take over.
You recognise the setting. You know which menu to open. You can navigate the device faster than the person sitting beside you.
Sometimes that is exactly what is needed.
There may be a security issue. Something genuinely technical may be wrong. The person may simply want a quick answer.
But at other times, taking over can unintentionally remove the most valuable part of the interaction: the opportunity for the person to work something out for themselves.
Instead of immediately saying, “Press this”, there may be value in asking:
What do you think we need to find?
Or:
Where might you expect that setting to be?
Or simply:
What have you already tried?
Those questions are not a test.
They are a way of finding out what the person already knows and giving them some ownership of what happens next.
An old educational idea
There is nothing particularly new about this.
The Socratic tradition of teaching places value on carefully chosen questions that help a learner explore what they know, examine assumptions and move towards understanding.
I would not suggest applying that rigidly to digital support.
Nobody wants to ask where the Wi-Fi settings are and receive a philosophical interrogation in return.
Sometimes the answer should simply be given.
But the underlying principle has real value: good help does not always mean supplying the answer as quickly as possible.
Sometimes it means creating just enough space for the other person to discover part of the answer themselves.
The person in front of you matters more than the curriculum
Structured digital programmes have an important role.
Curricula provide direction. Funders need accountability. Organisations need to know what is being delivered. Learners often benefit from a clear pathway.
But real-life digital problems rarely arrive neatly labelled.
Someone may say they need help with email when the real issue is remembering a password.
Someone may say they cannot use a map when the difficulty is understanding what they are seeing on the screen.
Someone else may know perfectly well what to do but be frightened of pressing the wrong button.
That is why the skill of the person providing the help matters.
The practitioner has to listen, observe and adapt.
Sometimes the most important question is not:
“What technology problem do I need to solve?”
It is:
“What does this person actually need from me?”
Success is more than a completed task
One of the challenges in digital inclusion is that the easiest things to count are not always the most meaningful.
We can record that someone learned to send an email.
We can count how many people attended.
We can list the subjects covered.
Those things matter.
But there are other questions worth asking too.
Did the person understand what happened?
Did they do some of it themselves?
Do they know what they might try if the problem happens again?
Did they leave more confident than when they arrived?
Did the interaction protect their dignity rather than reinforce the idea that they are “no good with technology”?
These outcomes are harder to put into a spreadsheet, but they may be some of the most important.
AI makes the human role more important
AI adds another layer to all of this.
Used carefully, it can be extremely useful.
It can help diagnose unfamiliar problems, explain technical language, suggest different ways of teaching something and provide another way of exploring a question.
But AI does not remove the need for human judgement.
Someone still has to decide:
Is this answer trustworthy?
Is it safe?
Is it appropriate for this person?
Should this information be entered at all?
Does the person actually understand what is happening?
In that sense, AI can support good digital help without becoming the person in charge of it.
The human relationship remains central.
Perhaps the goal is to become slightly less necessary
I have come to think that one measure of good digital help might be surprisingly simple.
Not how quickly I can fix someone’s problem.
Not how much technical knowledge I can demonstrate.
But whether, when the person leaves, they understand a little more, feel a little more confident and are a little better equipped to face the next unfamiliar digital problem themselves.
Perhaps the helper has succeeded when the person needs them slightly less than when they arrived.
That seems to me a worthwhile goal.
Put the idea into practice
I’ve also developed a short companion resource, Socratic-Informed Digital Help: A Practitioner Primer for One-to-One Digital Support.
It takes the ideas in this article a step further, with practical approaches for listening, questioning, demonstrating, practising and knowing when simply to step in and help. It also looks at dignity, uncertainty, adapting to the person, and how AI can support — rather than replace — human judgement.
The aim is simple: to help us think more carefully about how we help, not just whether the immediate digital problem gets solved.
Download the Socratic-Informed Digital Help practitioner primer (PDF)
AI-assisted creation
This article and its accompanying visual story were developed collaboratively by Alistair Fraser and ChatGPT. The experiences, perspectives, strategic direction and final editorial judgement are Alistair’s; AI was used as a thinking, drafting and visual-development partner.