Update

It is now nearly three weeks since we started the project and there has been quite a bit of activity which is worth putting an update out about.

Core Code

We’ve taken apart the proof of concept app we built for the hackathon and started restructuring it to build a scalable, maintainable service architecture. There is a new database schema, encapsulated in a set of Javascript classes that allow us to manage records of classifications and appeals.

This has allowed us to build a generic message classification and response engine, the personality-server as a standalone micro service that records all of it’s transactions and passes responses back to much thinner service specific bot implementations. This should allow us to quickly build integrations for popular chat services (more on this below).
Part of this also includes a new language and personality module which will allow us to trivially add languages and personalities to the implementation. This is important as this is a global project – we need to bake in the ability to deal with heterogenous languages and cultures.

Integrations

We did a basic Matrix integration at TADHack. Now we’ve taken care of the basic core, I’m re-building this as part of a matrix app-server. We will be hosting an alpha implementation of this this on our newly federated polite.ai matrix home server and hope to make it available to the Matrix community to start testing in early Nov.

In the meantime Joe has started work on a Slack integration which looks promising, and I’m is committed to start a HipChat integration as soon as the new Matrix code is released.

Being Open

When I kicked off the project, I had a pretty good idea of the problem I was looking to solve (and the ones I wasn’t) and put something out there that was pretty good for a hackathon project description. It was more than a single sentence anyway. Since then I’ve been head down making code work to provide proof points and MVPs

If the project is going to make an actual contribution to improving the way the world communicates then we have to solve some really very small technical problems, but some very large ethical problems.  Sound policy decisions we make at the intersection of data & algorithm ownership, machine learning and modifying human communication behaviour will be crucial. This will affect what we build and the conversation about this is now probably more urgent than writing code. I’m going spend a bit of time between now and the end of the year starting the conversation with articles here.

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