Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Develop Roadmap for AI Transparency & Ethics Plans #5

Closed
Nolski opened this issue Jul 28, 2019 · 2 comments
Closed

Develop Roadmap for AI Transparency & Ethics Plans #5

Nolski opened this issue Jul 28, 2019 · 2 comments
Assignees
Labels
new change Adds new capabilities or functionality research Researching documentation for feature enhancement type - AI transparency/ethics Resources specifically for AI transparency & ethics

Comments

@Nolski
Copy link
Collaborator

Nolski commented Jul 28, 2019

Summary

As per my arrangements with UNICEF I am to develop a set of resources, tools, and guidance documents to assist machine learning focused cohorts can develop their technology in a way that is open, responsible, and ethical.

Outcome

A document with my plans in priority order of which tasks I would like to complete.

@Nolski Nolski self-assigned this Jul 28, 2019
@Nolski
Copy link
Collaborator Author

Nolski commented Jul 28, 2019

Some items discussed earlier copied in below...

Here's a couple of ideas I've had in no particular order:

Data Schema document

A lot of AI focused products are hesitant about releasing their data. Personally, I think we should encourage this in a way that's responsible.

The OCHA Humanitarian Data Exchange has some guidelines on identifying privacy risk to data sets but it's fairly vague. I reached out via email to see if they have additional guidance on how to determine whether a dataset should be public or private. They also have a little overview on using metadata to describe datasets

There was a paper written on this as well: https://arxiv.org/abs/1803.09010

Machine Learning Model Card Template

This stems from my talks with MacroEyes and Har Zindagi. They both are wary about releasing their machine learning models as they might be used improperly or not understood correctly. I think we could really provide a useful resource that hasn't been used beyond more than one project yet.

I was reading a white paper a while back which researched this quite a bit. Perhaps we could also adapt the publiccode.yml document created by the public code network?

The Perfect README Template

A lot of companies have asked for guidance on how to write good documentation. I think this is a quick and easy way to start delivering that guidance. We can expand from here.

This would be just a broad outline for a good README with all of the proper bits prefilled in. Some existing resources for this from a quick google search below:

@Nolski Nolski added the type - AI transparency/ethics Resources specifically for AI transparency & ethics label Jul 29, 2019
@Nolski Nolski moved this from To do to In review in LibreCorps 2019-2020 operations Sep 9, 2019
@jwflory jwflory moved this from In review to In progress in LibreCorps 2019-2020 operations Nov 6, 2019
@jwflory jwflory added new change Adds new capabilities or functionality research Researching documentation for feature enhancement labels Nov 6, 2019
@jwflory
Copy link
Member

jwflory commented Mar 24, 2020

Included in 2020-03-24 issue triage and cleanup.


The roadmap exists as a template on our resources site: https://librecorps.github.io/resources/ai/milestone-roadmap/

Closing as complete. 🌊

@jwflory jwflory closed this as completed Mar 24, 2020
LibreCorps 2019-2020 operations automation moved this from In progress to Done Mar 24, 2020
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
new change Adds new capabilities or functionality research Researching documentation for feature enhancement type - AI transparency/ethics Resources specifically for AI transparency & ethics
Development

No branches or pull requests

2 participants