Mozilla AI White Paper Feedback Form
Over the last 18 months, Mozilla has been honing its thinking on Trustworthy AI. As a part of this process, we’re launching a request for comment (RFC) on v0.9 of our trustworthy AI white paper: https://mzl.la/MozillaWhitePaper. The RFC will be open until September, 2020.

The paper talks about how industry, regulators and citizens of the internet can work together to build more agency and accountability into our digital world. It also talks briefly about some of the areas where Mozilla will focus, knowing that Mozilla is only one small actor in the bigger picture of shifting the AI tide.

For additional context, see this post on the Mozilla blog: https://foundation.mozilla.org/en/blog/request-comment-how-collaboratively-make-trustworthy-ai-reality/ 
And for additional background on Mozilla’s AI efforts, go here: https://wiki.mozilla.org/Foundation/AI

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The task at hand is to collaboratively and openly figure out how to get to a world where AI and big data work quite differently than they do today.

As outlined in the blog post above, the Mozilla trustworthy AI RFC process will include three steps:

Step 1: partners, friends and critics comment on the white paper
Step 2: collaboratively map what’s happening -- and what should happen
Step 3: do more things together, and update the paper

Our goal is to engage and build a bigger community around this thinking -- and to support more people and orgs who are driving towards trustworthy AI.

Your involvement in, and feedback on, this process is invaluable. We want to hear from you how we can work together.
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Before we start, do we have permission to quote from your responses below? *
What was your overall impression of the white paper?
Lacks relevance to the debate. Doesn't address key issues in this space.
Perfectly describes the field and what needs to be addressed.
Clear selection
What was your overall impression of the theory of change we laid out?
I don't feel confident it will have impact in the AI space.
I feel confident it could have impact in the AI space.
Clear selection
Can you share the reason for your rankings above?
Which issues raised felt the most relevant to your work?
What strategies or interventions from the paper do you think will be the most effective at pushing for change? Why?
Which strategies do you think will be less effective at pushing for change? Why?
Are there interventions that we missed that should be part of this paper? (e.g. regulatory, consumer, industry etc.) If so, what are they?
Who do you think is the appropriate audience for this work?
What assumptions or blind spots does this paper have that we might have missed?
Have we struck the right balance between tracking what work is already happening and what work still needs to be done?
Clear selection
Do you know of existing measures or metrics that are tracking the impact of the work reflected in the paper?
What topics from the paper would you be excited to engage with?
Are there similar projects or publications you know of that should be on our radar?
Clear selection
If you answered yes to the question above, please describe (or link).
Are there projects you're working on that align with this work/share this language?
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If so, can you tell us more about the project?
Would you mind if we contacted you for follow-up discussions about what you're working on?
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Email address  / Contact Information
Any other comments/suggestions?
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