I’ve been thinking this week about an odd contrast. On one side: a sensible, direct way of facing what’s happening in Artificial Intelligence as a seismic environmental shift.
Matt Shumer’s viral blog, “Something Big Is Happening” is written in that register: a note to non-tech friends saying, “This is moving fast; you should get familiar with it so you can tell what’s real.”
Alongside that is Noah Smith’s post, “You are no longer the smartest type of thing on Earth”, which argues more philosophically that whether or not AI “really thinks” won’t change the fact that systems can now outperform humans across widening cognitive territory, and society will reorganise around that capability.
On the other side: the huge negativity I’ve been hearing from many Applied Improvisers during my webinar series about AI + AI.
This ranges from thoughtful caution to a reflex opposition, including a kind of proud refusal to engage with it at all. Participants say:
- “This is all soulless / inhuman / not real creativity”
- “We’ll be fine because humans are distinctively human”
- “I’m not touching it on (artistic, moral or historical) principle”
Now I’m used to improvisers saying daft things, usually because they were once impressed by a slogan or an activity during a workshop.
Mistakes and failure are the classic example areas in which half-truths turn into fragile principles, and are then used to avoid the harder work of scrutiny, competence and responsibility.
And I think the relative rarity of rigorous thought (along with a reluctance to reinvent beyond theatrical frameworks) has held back our practice in organisations beyond the theatre for years.
But it’s worrying that as pioneers in uncertainty we’d instinctively oppose a new and increasingly pervasive force in that field.
A better stance: AI literacy for AI practitioners
The suggestion is to remain sufficiently AI-literate to see what is happening and respond competently.
In practice, that includes:
- knowing what the tools are currently good at (and where they are brittle)
- deploying a few personal tests, so you can spot nonsense quickly
- understanding organisational risks (confidentiality, provenance, bias, dependency)
- using AI mainly for the before-and-after of our work:
- agenda options and framing
- stakeholder maps and risk lists
- synthesis drafts and follow-up wording
- keeping live judgement where it belongs:
- reading the room
- negotiating meaning
- holding uncertainty without rushing to closure
The oppositional stance has obvious appeal, offering identity, purity and a ready-made heroic story. But it also risks repeating a pattern: protecting the theatrical version of our craft while the applied version drifts into insignificance.
If we face a simple professional choice between learning enough to use these tools responsibly or sitting virtuously outside the change, it’s the former which looks more like Applied Improvisation.
So perhaps the task is simply not to look away.
We don’t need to celebrate AI, but we do need to understand it well enough to work alongside it with judgement. This is no longer hypothetical -it’s part of the conditions we’re operating in.
For a field built on responding to reality as it unfolds, staying literate here is an important part of our work.
