Top Tweets for #AboutML
ABOUT ML Reference Document https://t.co/1JxvfPm4XN #AI #Ethics #AIBillofRights #ABOUTML via @PartnershipAI
Transparency and documentation should be an explicit part of the discussion at each step of the machine learning lifecycle. Learn why in PAI’s #ABOUTML Reference Doc which was recently cited in the @WHOSTP #AIBillofRights: https://t.co/4x5K0tjdNj
Today, @WHOSTP released the #AIBillofRights, five core protections and call to action to protect the American public’s rights in an automated world: https://t.co/8plZLqHha7
Transparency and documentation need to be an explicit part of the discussion at each step of the ML lifecycle. Check out PAI’s #ABOUTML Process Guide for ML documentation questions and considerations: https://t.co/6DU2jgt7OV
So @jennwvaughan , @timnitGebru , @hannawallach and I walk into a bar...
...and decide to initiate a Partnership on AI project on AI transparency.
Now @PartnershipAI put out some more details about the Origin Story around the #ABOUTML project. <3
Our #ABOUTML work was made possible by the contributions of @mmitchell_ai. Please see our Origin Story to learn more about her work. https://t.co/fYOSae2xya
Our #ABOUTML work was made possible by the contributions of @mmitchell_ai. Please see our Origin Story to learn more about her work. https://t.co/fYOSae2xya
Interested in learning more about documentation and transparency? Explore PAI's #ABOUTML Resources Library. https://t.co/YCOpqdcdFp
Are you an ML system developer or deployer hoping to improve transparency throughout the ML lifecycle? Use PAI's #ABOUTML Reference Document to explore documentation recs and identify gaps in the current understanding of documentation. https://t.co/NbA2cJWxn3
📣 We are launching an interview study to understand the challenges of implementing documentation for machine learning systems. #ABOUTML
Learn more about the study here ➡️ https://t.co/qnseZURKmf
If you’re interested in being interviewed, sign up here ➡️ https://t.co/vsYjM3e8qG
@gadonniex @chad_oda @mmitchell_ai @PartnershipAI @jingyingyang Thanks 4 the mention @gadonniex! @jingying is focusing on getting an MS in CS @GeorgiaTech 🎉👩🎓🎓while @teeepain, @BrownJefe and I are continuing the work of helping technology companies implement equity thru programs like #aboutml. Let's connect to chat more @chad_oda!
The #ABOUTML Research Fellow (Qualitative Research) will investigate the challenges of implementing documentation for machine learning within organizations that build and deploy ML systems: https://t.co/9qnda9s2dw (3/4)
The #ABOUTML Research Fellow (UX/HCI) will conduct research focused on understanding and designing for the needs of different audiences for documentation: https://t.co/5CpzLZ1CLX (2/4)
Join the #ABOUTML team to help us realize #ResponsibleAI through increased transparency and accountability with machine learning documentation.
We are hiring two key roles (a week left to apply!) to advance this multistakeholder work: a Program Lead and Research Fellow. (1/3)
To contribute to #ABOUTML, get involved in the work on our webpage. https://t.co/cMEDtteV8G
ABOUT ML is an ongoing multistakeholder initiative to enable responsible #AI by increasing transparency and accountability with #MachineLearning system documentation.
According to @AiCommission's First Quarter Recommendations, our #ABOUTML initiative is an example of an effective strategy for documentation in pursuit of trustworthy AI systems. Learn more in the report: https://t.co/tYv78HWmLI
#NSCAI has submitted its First Quarter Recommendations to Congress! Check them out at https://t.co/Ae5LYh0XxA
For #FAT2020 attendees, we invite you to join us for this interactive happy hour tonight at 7 pm in the Plenary Room. Learn about our work in FTA led by @alicexiang, and discover how you can contribute to #ABOUTML: https://t.co/xsPxFPDwFx
On Wednesday, PAI will host an evening satellite event to bring together members of the FAT* community to learn about PAI's research and contribute to the #ABOUTML project: https://t.co/xsPxFPDwFx @jingyingyang
Proud of this upcoming tutorial presented by @bobirakova & @jingyingyang at @fatconference. We look forward to the insights generated during this session to advance our ongoing #ABOUTML initiative. #FAT2020
So glad to be part of an upcoming @fatconference tutorial on the implications of organizational structure on the work in AI, presenting work we've been doing with @jingyingyang, @ruchowdh, & @hsmcramer! Here's a short post about it: https://t.co/R85ptNxyWU
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