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# WebML WG Teleconference – 16 June 2022 - 14:00-15:00 UTC

<table>
<tr><td> San Francisco (U.S.A. - California) <td> Thu, 16 June 2022 <td> 07:00 <td> UTC-7 hours
<tr><td> Boston (U.S.A. - Massachusetts) <td> Thu, 16 June 2022 <td> 10:00 <td> UTC-4 hours
<tr><td> London (United Kingdom - England) <td> Thu, 16 June 2022 <td> 15:00 <td> UTC+1 hours
<tr><td> Berlin (Germany) <td> Thu, 16 June 2022 <td> 16:00 <td> UTC+2 hours
<tr><td> Helsinki (Finland) <td> Thu, 16 June 2022 <td> 17:00 <td> UTC+3 hours
<tr><td> Shanghai (China) <td> Thu, 16 June 2022 <td> 22:00 <td> UTC+8 hours
<tr><td> Tokyo (Japan) <td> Thu, 16 June 2022 <td> 23:00 <td> UTC+9 hours
<tr><td> Corresponding UTC (GMT) <td> Thu, 16 June 2022 <td colspan=2> 14:00 UTC
</table>

Other locations: https://www.timeanddate.com/worldclock/fixedtime.html?iso=20220616T14

</details>

## Logistics

* Chair: Anssi
* Scribe: ? (see [howto](https://github.com/webmachinelearning/meetings/blob/main/scribe-howto.md), volunteers welcome!)
* IRC: irc://irc.w3.org:6667/#webmachinelearning
* IRC web client: https://irc.w3.org/?channels=#webmachinelearning
* Call-in details: https://lists.w3.org/Archives/Member/internal-webmachinelearning/2020Apr/0000.html
* Minutes: https://www.w3.org/2022/06/16-webmachinelearning-minutes.html

#### ℹ️ Privacy review refresh

>Review the proposed PR to address privacy-impacting changes since last privacy review. For the detailed timeline, see our [previous meeting agenda](https://github.com/webmachinelearning/meetings/blob/main/telcons/2022-06-02-wg-agenda.md#%E2%84%B9%EF%B8%8F-privacy-review-refresh).
- [ ] issue: Fingerprinting via machine-specific artifacts https://github.com/webmachinelearning/webnn/issues/85
- [ ] issue: Related WebGPU/GL Security and Privacy Considerations https://github.com/webmachinelearning/webnn/issues/175
- [ ] issue: Device selection (privacy implications) https://github.com/webmachinelearning/webnn/issues/169

- [ ] PR: Privacy Considerations refresh https://github.com/webmachinelearning/webnn/pull/271

#### ℹ️ Ethical considerations

>Discuss and seek WG approval for the plan to publish the first [W3C Note](https://www.w3.org/2021/Process-20211102/#WGNote) of [Ethical Principles for Web Machine Learning](https://webmachinelearning.github.io/ethical-webmachinelearning/) document once workshop feedback has been incorporated.
- [ ] PR: Incorporate feedback from the Ethical ML workshops https://github.com/webmachinelearning/ethical-webmachinelearning/pull/20

#### ℹ️ Revisit WebNN API Candidate Recommendation scope

>Review and discuss current CR issues. Identify any issues that may be appropriate to be addressed after the first CR release.
- Current CR issues https://github.com/webmachinelearning/webnn/issues?q=is%3Aissue+is%3Aopen+label%3Acr

- Review proposed approach to open use cases:
- Post-CR or close: https://github.com/webmachinelearning/webnn/pull/207
- Redirect to Web Extensions CG: https://github.com/webmachinelearning/webnn/pull/253

#### ℹ️ CommandBuffer usage clarification

>Discuss on how to address the WebGPU resource usage and sharing issues in preparation for the WebGPU WG review.
- [ ] issue: CommandBuffer usage clarification: internal, external, both? https://github.com/webmachinelearning/webnn/issues/264
- [ ] WebGPU issue: Investigation: WebNN / WebGPU interop https://github.com/gpuweb/gpuweb/issues/2500

#### ℹ️ Proposed new features

- [ ] issue: Support asynchronous context creation https://github.com/webmachinelearning/webnn/issues/272

- [ ] issue: Support coordinate transformation modes for Resample2d https://github.com/webmachinelearning/webnn/issues/270

- [ ] issue: Define the data type of the padding, strides and dilations https://github.com/webmachinelearning/webnn/issues/269

#### ℹ️ TPAC 2022

>Discuss [TPAC 2022](https://www.w3.org/2022/09/TPAC/Overview.html) plans for the WG.

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