I’m just going to drop this here:
From the article:
How can we be good stewards of collaborative trust?
TL;DR: This essay makes a lot of suggestions, but the most useful/non-obvious/actionable are likely: (1) Be generous. (2) Use author contribution statements. (3) Put “author order not finalized” if it hasn’t been.
A lot of the best research in machine learning comes from collaborations. In fact, many of the most significant papers in the last few years (TensorFlow, AlphaGo, etc) come from collaborations of 20+ people. These collaborations are made possible by goodwill and trust between researchers.
This goodwill and trust is a precious shared resource, and it can be a fragile thing. When people work together, it’s easy to have conflict, especially around attribution and credit. If dealt with poorly, attribution issues can fester. I’m aware of several cases of collaborations dieing, or people leaving teams and organizations, where and the underlying issue was hurt feelings and lost trust around collaboration. This strikes me as rather sad.
We often talk about credit issues in kind of binary terms. But if the thing we care about is this shared trust, I think it’s not enough to just avoid doing anything wrong. We must also avoid any feeling or appearance of unfairness. In fact, we’d ideally actively cultivate the opposite, to behave in ways that add back to the pool of goodwill.
We should also be mindful that credit issues can easily be perceived as, and likely often are, linked to privilege or power gradients. This might be gender or race, but it can also be things like being a remote collaborator (ie. geographically removed from others), being an engineer or designer instead of a researcher, or being at a lower level professionally. A perception that junior collaborators or those from under-represented minorities are taken advantage not only harms the research community, but the larger cause of making sure all humans are treated fairly.
Core Principles
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Always check in with any person who could plausibly be an author or feel like they should be, even if you disagree . Never have authorship or authorship order be decided behind closed doors or without giving people an opportunity to advocate for themselves.
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Err on the side of sharing credit. Credit isn’t zero sum. It is often in everyone’s benefit to be generous with credit, because it creates an incentive for others to help in the future. It also makes sense to be risk-averse to the possibility of not crediting someone who deserves it, because the harm of not crediting someone who deserves it is often greater than the harm of crediting someone who doesn’t deserve it.
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Acknowledge anyone you can remember talking to about your research significantly. It costs nothing and builds good will. You can still use stronger language to highlight people who helped you more.
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Avoid diffusion of responsibility . For example, have someone clearly responsible for checking in with everyone on authorship.
- Don’t reveal someone else’s unpublished work or merge it into your own without their consent.
- Remember that you are likely overestimating your own contributions.
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Act in ways that will make people want to work with you. Enthusiastic collaborators are one of the most precious thing you can have as a researcher.
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There’s no substitute for emotional labor. Humans have feelings. No magic bullet will remove the need for us to invest energy understanding them and talking them through together.
The article goes on to explore common problems and common solutions around trust and collaboration. The author is one of the leading researchers in the machine learning space. It’s a 5min read and I highly recommend giving it a shot.
