If you don't try, you'll never know...

If you’ve tried applying AI to your day-to-day work you’ve probably noticed it isn’t perfect. 

It makes things up, it gets maths wrong, it misinterprets you, it’s inconsistent. 

This means it is currently almost impossible to use AI at scale without considerable human oversight. Even the work we’ve already done at Rootcause has involved plenty of trial and error. 

If you or your organisation is pushed for time and strapped for cash there is a high chance that experimenting with AI won’t make it to the top of your to-do list for long.

This means there’s a risk of missing out.

Which is why we are going to do some experimentation on your behalf. 

Over the next couple of months we are going to conduct five AI experiments to see if there’s potential for progressive professionals and organisations to benefit. 

The challenges are:

1. Information Overload - we don’t have time to take in relevant information

2. Filter Bubbles - we inhabit online silos that make it harder to build bridges

3. Knowing our Audience - it’s expensive to find out what people think and why

4. Channel Churn - it’s hard to reach people all at once across lots of channels  

5. Algorithmic Distortion - we don’t want to add to the extreme and polarising content that often performs best online 

Working with co-collaborator Nick Scott we are going to examine five ideas about how we might tackle these problems. They include using AI to create personalised media digests, building personas that explain other political perspectives, AI classification of social media data, AI alternatives to surveys and exploring AI’s potential as a planning partner. 

We’re not doing this because we think AI is the solution to every problem. It really isn’t. 

We’re doing it because we believe AI will eventually reshape the information environment and we want to make sure progressive organisations are well equipped to navigate the AI age - for better and for worse. 

You’ll be able to follow along with our experiments via this newsletter. Please do get in touch if you want to learn more or perhaps collaborate on one of our experiments. 

Jonathan 

(The eagle-eyed amongst you may notice this newsletter is now coming from a different platform. We’ll be using Beehiiv to deliver more regular newsletters in the weeks ahead…)