Proposal for better guideline of commitment and merge
zhimin-z opened this issue · 5 comments
Continuing #392, we should make up a more concrete guideline to solve the following issues:
- What is the goal of this list?
- What categories of tools can be included in this list?
- What are the categorization criteria when a tool is designed with multi-purposes?
- What is the retirement mechanism to remove obsolete tools?
- ...
It is useless to simply avoid superficial phenomena like 3 line PRs resulting in a discussion 10x longer issue. We need to work together to solve the core contradiction for better collaboration.
Closing as discussed in #392 - reached out to align but further discussion won't proceed otherwise as clarified
Closing as discussed in #392 - reached out to align but further discussion won't proceed otherwise as clarified
The current contribute.md did not solve any of the issues mentioned above. @axsaucedo Why are you avoiding the core issues?
I have checked your website: https://ethical.institute/ and this gives a detailed explanation regarding the guideline of Ethical AI & Machine Learning. When it comes to this list, why do you prevent me to talk about the guideline accordingly? Is that ethical in terms of OSS spirit? @axsaucedo
It's been explained over and over Zhimin, unfortunately I don't have the time or energy to entretain this as it seems it's repeating the same point over and over and it's not productive or healthy for the interactions. I reached out to discuss further to align but we can't continue going in circles as the reasonings have been discussed repeatedly.
@axsaucedo I 've read every word of your reply.
I had never said "there should be an exact definition that everyone should agree." I say that we should at least to have a template definition to refer to which helps us to reach a concensus. I am 100% sure now what's on your mind of "production machine learning" is different from that on my mind. But sadly, I have no idea what the difference is. I have to guess and you always close my pr due to my wrong guess.
For example, as a researcher, when you are talking about something in the publication, you usually at first give some background info and define the old concepts before you are going to introduce the new ones, or else the reviewers won't have the same start point as your mind, resulting a lot of misunderstanding and rebuttal. @axsaucedo You understand what I mean?