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Incorporate feedback from the Ethical ML workshops #20
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- Update Operationalization: Putting the Principles into Practice - Add Register of Risks and Mitigations
Gentle ping, PTAL @dontcallmedom :-) Some areas to focus on, mostly presentational:
Comments:
We should use:
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So for example, if we consider the principle of “Fairness and non-dicrimination”, a risk might be that biases in training data lead to model predictions that are less accurate for particular groups, resulting in real-world harms (e.g. denial of services). A mitigation might be to test the training data and model properly for bias, or indeed it might be to not make access to essential services dependent on ML systems. | ||
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To provide a more structured approach to this, we have developed a workshop format which you can adapt and use. |
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To provide a more structured approach to this, we have developed a workshop format which you can adapt and use. | |
To provide a more structured approach to this, we have developed a workshop format that can be adapted and used to help identify such risks & mitigations. |
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I wonder if the details about the workshop (until "it's worth noting" below) should be moved to an appendix - while very useful, it feels a bit out of place in the flow of the document.
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Moved to appendix. Text changes integrated into 13d34dc
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To provide a more structured approach to this, we have developed a workshop format which you can adapt and use. | ||
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The workshop is in two parts (please make a copies for your own use): |
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The workshop is in two parts (please make a copies for your own use): | |
The workshop is articulated around two documents that are expected to be completed interactively by participants: |
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Integrated into 13d34dc
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Part One - [Ethical thinking workshop](https://docs.google.com/document/d/1f_PcByjW8-zXbYWeEyOl-RpZ3SKapm_MWSaNZ9ZOi4c/edit?usp=sharing) - is about using the principles to generate and prioritize potential risks | ||
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Part Two - [Ethical Risk Canvas](https://docs.google.com/document/d/1hTQnpWC5KC4qIJB9-Kkd46yMVgDuTCQlA3MffqtUbCI/edit?usp=sharing) - is about digging deeper into specific risks and thinking about who they might impact and how best to mitigate them. | ||
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we should probably post a PDF copy of these documents somewhere if only for archival sake.
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Opened #21
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# Register of Risks and Mitigations | ||
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Note: The risk register is work in progress and welcomes further review and tidying up. |
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I'm happy to leave this for a future pull request, but I think there is indeed substantive work to harmonize the phrasing of the risks, with possibly merging / sorting some of them as well.
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### Possible Mitigations | ||
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1. Browser-assisted mechanisms to find out about the limitations and performance characteristics of ML models used in a Web app. This could build on an approach published in Model Cards for Model Reporting where making this report machine-discoverable would allow for the web browser to offer a more integrated user experience. Another transparency tool is the [Open Ethics Transparency Protocol](https://github.com/webmachinelearning/ethical-webmachinelearning/issues/6). |
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In terms of mapping mitigations to risks, I would use a naming scheme for risks (e.g. FND-R1 for risk 1 under Fairness and Non-Discrimination), and then references these names from the mitigations that address them.
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Done in b00171e
Incorporate review feedback from Dom
- Creates dfns for all risks and mitigations - Also adds Bikeshed bikeshed includes for repeated notes/issue blocks
Thanks @dontcallmedom for your comments, PR updated. |
Gentle ping, PTAL @dontcallmedom. Your feedback has been addressed. I'd like to merge this after your approval so the WG can advance with its W3C Note publication plan. |
TY @dontcallmedom! |
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