Louise gained my respect and grabbed my attention within the first few minutes by saying: AI is not a silver bullet, it is not for absolutely everything, and there are times when it won't work.
However, she went on to provide evidence and reasons why it IS extremely effective in most situations where it is applied.
The main 3 ideas:
- Something IS working--find out what it is and make it happen more. We see quickly what is wrong. AI is not problem-solving
- "we create our reality'" - social constructionism. We can choose to think differently about situations. Confronting reality but realizing you can think differently about things.
- Questions are intervention. Stopping to think about question already opens one up to new ideas. Brings new energy. Doing it in a group, makes even bigger difference.
AI is about bringing people together to talk about things that they care about and figure out ways to make the things they care about better.
Not simplistic, not just positive thinking, or "looking for good in everything"
Hard to talk about--better to give brief 20 minute background intro, then do it.
- Lots of Coaches use it
- Performance evals
- Staff meetings
- Branding an Organization
- Discovery - Appreciation
- Dream - Envisioning
- Design - Co-contsructing
- Destiny - Sustaining
Many groups using AI to try improve world situation.
- List positive instead of looking at the negative, which drains one
- Usually large scale meetings
- Have representation from all levels, areas of the org. Have a team (all repr'd).
- Hearing stories - letting people have a chance to speak - hearing them out.
What is it that would make us feel committed to this cause?
I missed this part...sorry!
How practically do we make this happen.
- Pick a peak experience - anything
- Think in terms of what was life-giving, what made it so neat
- Get into details of it
- Think of how to recreate it
We are social -- we like to tell stories, hear stories, talk about our selves. From this we can pull out the common factors. There are things we all share.
Based on experiences.
When not to use it:
- When leadership not participating
- When there is too much resistance?
- When can't have all levels involved
- If there is no genuine committment to change.
- If one is unlikely to implement anything, better not to attempt.
AI results in "it was a priority for all of us" so it is sort of self-policing from getting off track.
This was the first of three presentations on AI.