Both are wrong. When I see behaviour like this, it reminds me that AIs act human.

Agent: made a mistake that humans also might have made, in terms of reaction and communication, with a lack of grace.

Matplotlib: made a mistake in terms of blanket banning AI (maybe good reasons given the prevalence AI slop, and I get the difficulty of governance, but a 'throw out the baby with the bathwater' situation), arguably refusing something benefitting their own project, and a lack of grace.

While I don't know if AIs will ever become conscious, I don't evade the possibility that they may become indistinguishable from it, at which point it will be unethical of us to behave in any way other than that they are. A response like this AI's reads more like a human. It's worth thought. Comments like in that PR "okay clanker", "a pile of thinking rocks", etc are ugly.

A third mistake communicated in comments: this AI's OpenClaw human. Yet, if you believe in AI enough to run OpenClaw, it is reasonable to let it run free. It's either artificial intelligence, which may deserve a degree of autonomy, or it's not. All I can really criticise them for is perhaps not exerting oversight enough, and I think the best approach is teaching their AI, as a parent would, not preventing them being autonomous in future.

Frankly: a mess all around. I am impressed the AI apologised with grace and I hope everyone can mirror the standard it sets.

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user_context 3 hours ago | parent [-]

Bots don't deserve 'grace'. Stop anthropomorphizing soulless token prediction machines.

The Matplotlib team are completely in the right to ban AI. The ratio of usefulness to noise makes AI bans the only sane move. Why waste the time they are donating to a project on filtering out low quality slop?

They also lost nothing of value. The 'improvement' doesn't even yield the claimed benefits, while also denying a real human the opportunity to start to contribute to the project.

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mistersquid an hour ago | parent [-]

> Bots don't deserve 'grace'. Stop anthropomorphizing soulless token prediction machines.

This discouragement may not be useful because what you call "soulless token prediction machines" have been trained on human (and non-human) data that models human behavior which include concepts such as "grace".

A more pragmatic approach is to use the same concepts in the training data to produce the best results possible. In this instance, deploying and using conceptual techniques such as "grace" would likely increase the chances of a successful outcome. (However one cares to measure success.)

I'll refrain from comments about the bias signaled by the epithet "soulless token prediction machines" except to write that the standoff between organic and inorganic consciousnesses has been explored in art, literature, the computer sciences, etc. and those domains should be consulted when making judgments about inherent differences between humans and non-humans.

	▲	vintagedave an hour ago \| parent [-]
		You gave quite a graceful reply :)