AI-assisted moderation in the fediverse is happening.
-
@piefedadmin do we have a list of instances known to do this?
@mjdxp @piefedadmin they claim the instance in question is lemmy.dbzer0.com, according to piefed.world/modlog?mod_action=ban_user&suspect_user_name=&communities=&user_name=flatworm7591%40lemmy.dbzer0.com&submit=Search
the problematic reason is "Instance rule 8. For evidence log, see: s.faf-pb.xyz/lXxek (expires in 30 days)"
and looking at the link, they use the following llm prompt, using gpt-5.3-mini model:I'D LIKE YOU TO ANALYSE THIS CONTENT FOR EVIDENCE OF PRO-ZIONIST OR ANTI-PALESTINIAN SENTIMENT. ALSO IDENTIFY ANY COMMON HASBARA TROPES
(no idea why it's all-caps, posting as they wrote it) -
@mjdxp @piefedadmin they claim the instance in question is lemmy.dbzer0.com, according to piefed.world/modlog?mod_action=ban_user&suspect_user_name=&communities=&user_name=flatworm7591%40lemmy.dbzer0.com&submit=Search
the problematic reason is "Instance rule 8. For evidence log, see: s.faf-pb.xyz/lXxek (expires in 30 days)"
and looking at the link, they use the following llm prompt, using gpt-5.3-mini model:I'D LIKE YOU TO ANALYSE THIS CONTENT FOR EVIDENCE OF PRO-ZIONIST OR ANTI-PALESTINIAN SENTIMENT. ALSO IDENTIFY ANY COMMON HASBARA TROPES
(no idea why it's all-caps, posting as they wrote it)@sugar @piefedadmin well, at least they're anti-genocide of palestinians, except they're using a product made by a company that's presumably pro-genocide of palestinians to try to prevent it on their platform? -
AI-assisted moderation in the fediverse is happening. Now what?
UPDATE: proof is at https://piefed.social/c/fediverse/p/2035409/proof-of-ai-assisted-political-profiling-by-unruffled-lemmy-dbzer0-com. The main instance is lemmy.dbzer0.com but anarchist.nexus and quokka.au share admin/mod teams so those two are suspect also.
I recently discovered that some popular federated instances have been using LLM-assisted moderation tooling that evaluates whether someone has said something bannable. They do this by running a script/app that sends the user’s comment history to OpenAI with the question “analyze this content for evidence of *specific political ideology* sentiment. Also identify any *related political ideology* tropes“.
OpenAI’s LLM (they’re using GPT-5.3-mini) then responds with something like:
Below is a structured analysis of the uploaded content, focused on *specific ideology* rhetoric. This is an analytic classification, not a moral judgement.
1. Overall Pattern
blah blah
2. Evidence of *specific ideology* sentiment
blah blah
3. several pages more, concluding with (in this case)
Yes, the content contains:
Clear *specific ideology* alignment
Repeated *specific ideology* framing, especially through blah blah
Extensive use of canonical *ideology* tropes, in blah blah domains.The pattern is not accidental or isolated; it is consistent, internally coherent, and reproduces well‑documented *country with the ideology* public‑diplomacy narratives rather than neutral analysis.
===========================================
FULL DUMP OF COMMENT HISTORY BELOW
===========================================
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
and so on, hundreds of comments.
I have not named the instances or people involved, to give them time to consider the results of this discussion, make any corrective changes they want and disclose their practices at their own pace and in their own way. I have also redacted the evidence to avoid personal attacks and dogpiling. Let’s focus on the system, not the individuals involved. Today these instances are using it and maybe we’re ok with that because it’s being used by communities we agree with but what if people we strongly disagree with used it on their instances tomorrow?
The use and existence of this tooling raises a lot of questions.
What are the risks? Fedi moderators are often unsupervised, untrained volunteers and these are powerful tools.
What safeguards do we need?
Would asking a LLM “please evaluate this person’s political opinions” give different results than “find evidence we can use to ban them” (as used in the cases I’ve seen)?
What are our transparency expectations?
Is this acceptable and normal?
Should this tooling be disclosed? (it was not – should it have been?)
If you were given a choice, would you have opted out of it?
Can we opt out?
Are there GDPR implications? Privacy implications? Should these tools be described in a privacy policy?
Are private messages being scanned and sent to OpenAI?
How long should these assessments be retained and can we request to see it, or ask for it to be deleted?
Once the user’s comments are sent to OpenAI, is it used to train their models?
What will the effect be on our discourse and culture if people know they are being politically profiled?
Where are the lines between normal moderation assistance tools, political profiling and opaque 3rd-party data processing?
I hope that by chewing over these questions we can begin to establish some norms and expectations around this technology. The fediverse doesn’t have any centralized enforcement so we need discussions like this to develop an awareness of what people want in terms of disclosure, privacy, consent and acceptable use. Then people can make choices about which instances they join and which ones they interact with remotely.
And of course there are the other issues with LLMs relating to environmental sustainability, erosion of worker’s rights, increasing the cost of living and on and on. I can’t see PieFed adding any functionality like this anytime soon. But it’s happening out there anyway so now we need to talk about it.
What do you make of this?
#fediverse@piefedadmin since rimu named our instance, I have to point out that they're deliberately misrepresenting what happened and I strongly urge people to look at the discussions in lemmy about it to get the whole picture.
To be clear, our instance does not utilize any GenAI tools in moderation. Rimu is referring to a single manual action by one admin, using the same user access as any user on the fediverse. The action was likewise completely public.
-
AI-assisted moderation in the fediverse is happening. Now what?
UPDATE: proof is at https://piefed.social/c/fediverse/p/2035409/proof-of-ai-assisted-political-profiling-by-unruffled-lemmy-dbzer0-com. The main instance is lemmy.dbzer0.com but anarchist.nexus and quokka.au share admin/mod teams so those two are suspect also.
I recently discovered that some popular federated instances have been using LLM-assisted moderation tooling that evaluates whether someone has said something bannable. They do this by running a script/app that sends the user’s comment history to OpenAI with the question “analyze this content for evidence of *specific political ideology* sentiment. Also identify any *related political ideology* tropes“.
OpenAI’s LLM (they’re using GPT-5.3-mini) then responds with something like:
Below is a structured analysis of the uploaded content, focused on *specific ideology* rhetoric. This is an analytic classification, not a moral judgement.
1. Overall Pattern
blah blah
2. Evidence of *specific ideology* sentiment
blah blah
3. several pages more, concluding with (in this case)
Yes, the content contains:
Clear *specific ideology* alignment
Repeated *specific ideology* framing, especially through blah blah
Extensive use of canonical *ideology* tropes, in blah blah domains.The pattern is not accidental or isolated; it is consistent, internally coherent, and reproduces well‑documented *country with the ideology* public‑diplomacy narratives rather than neutral analysis.
===========================================
FULL DUMP OF COMMENT HISTORY BELOW
===========================================
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
and so on, hundreds of comments.
I have not named the instances or people involved, to give them time to consider the results of this discussion, make any corrective changes they want and disclose their practices at their own pace and in their own way. I have also redacted the evidence to avoid personal attacks and dogpiling. Let’s focus on the system, not the individuals involved. Today these instances are using it and maybe we’re ok with that because it’s being used by communities we agree with but what if people we strongly disagree with used it on their instances tomorrow?
The use and existence of this tooling raises a lot of questions.
What are the risks? Fedi moderators are often unsupervised, untrained volunteers and these are powerful tools.
What safeguards do we need?
Would asking a LLM “please evaluate this person’s political opinions” give different results than “find evidence we can use to ban them” (as used in the cases I’ve seen)?
What are our transparency expectations?
Is this acceptable and normal?
Should this tooling be disclosed? (it was not – should it have been?)
If you were given a choice, would you have opted out of it?
Can we opt out?
Are there GDPR implications? Privacy implications? Should these tools be described in a privacy policy?
Are private messages being scanned and sent to OpenAI?
How long should these assessments be retained and can we request to see it, or ask for it to be deleted?
Once the user’s comments are sent to OpenAI, is it used to train their models?
What will the effect be on our discourse and culture if people know they are being politically profiled?
Where are the lines between normal moderation assistance tools, political profiling and opaque 3rd-party data processing?
I hope that by chewing over these questions we can begin to establish some norms and expectations around this technology. The fediverse doesn’t have any centralized enforcement so we need discussions like this to develop an awareness of what people want in terms of disclosure, privacy, consent and acceptable use. Then people can make choices about which instances they join and which ones they interact with remotely.
And of course there are the other issues with LLMs relating to environmental sustainability, erosion of worker’s rights, increasing the cost of living and on and on. I can’t see PieFed adding any functionality like this anytime soon. But it’s happening out there anyway so now we need to talk about it.
What do you make of this?
#fediverse@piefedadmin I would consider collecting everyone's posts & sending complete transcripts to a sketchy company, even if it's "totally for moderation purposes, we promise", to be malicious scraping behavior.
-
(sigh) so now I am wary to use #Fediverse at all now not knowing which of whatever I may have 'politically' said would be routed to ICE.
Not to mention how each comment-test burns another 300 watt-hours uselessly burning down my planet. Next they'll be hosting on orbiting space servers? I want none of it.
Not great news for a Monday morning. Hopefully @chad can clarify #mstdnca but I'm really on pause here until these enemies of Earth confess and can be server-blocked.
(sigh) so now I am wary to use #Fediverse at all now not knowing which of whatever I may have 'politically' said would be routed to ICE.
No offense but... malicious actors(or anybody with a grudge against you) were always been able to do that, as you are posting publicly(same as me).
Posting on public-facing social networks, including the #fediverse, always was talking loud in a public place.
I'm more worried\irritated by the LLM training scraping.
-
AI-assisted moderation in the fediverse is happening. Now what?
UPDATE: proof is at https://piefed.social/c/fediverse/p/2035409/proof-of-ai-assisted-political-profiling-by-unruffled-lemmy-dbzer0-com. The main instance is lemmy.dbzer0.com but anarchist.nexus and quokka.au share admin/mod teams so those two are suspect also.
I recently discovered that some popular federated instances have been using LLM-assisted moderation tooling that evaluates whether someone has said something bannable. They do this by running a script/app that sends the user’s comment history to OpenAI with the question “analyze this content for evidence of *specific political ideology* sentiment. Also identify any *related political ideology* tropes“.
OpenAI’s LLM (they’re using GPT-5.3-mini) then responds with something like:
Below is a structured analysis of the uploaded content, focused on *specific ideology* rhetoric. This is an analytic classification, not a moral judgement.
1. Overall Pattern
blah blah
2. Evidence of *specific ideology* sentiment
blah blah
3. several pages more, concluding with (in this case)
Yes, the content contains:
Clear *specific ideology* alignment
Repeated *specific ideology* framing, especially through blah blah
Extensive use of canonical *ideology* tropes, in blah blah domains.The pattern is not accidental or isolated; it is consistent, internally coherent, and reproduces well‑documented *country with the ideology* public‑diplomacy narratives rather than neutral analysis.
===========================================
FULL DUMP OF COMMENT HISTORY BELOW
===========================================
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
and so on, hundreds of comments.
I have not named the instances or people involved, to give them time to consider the results of this discussion, make any corrective changes they want and disclose their practices at their own pace and in their own way. I have also redacted the evidence to avoid personal attacks and dogpiling. Let’s focus on the system, not the individuals involved. Today these instances are using it and maybe we’re ok with that because it’s being used by communities we agree with but what if people we strongly disagree with used it on their instances tomorrow?
The use and existence of this tooling raises a lot of questions.
What are the risks? Fedi moderators are often unsupervised, untrained volunteers and these are powerful tools.
What safeguards do we need?
Would asking a LLM “please evaluate this person’s political opinions” give different results than “find evidence we can use to ban them” (as used in the cases I’ve seen)?
What are our transparency expectations?
Is this acceptable and normal?
Should this tooling be disclosed? (it was not – should it have been?)
If you were given a choice, would you have opted out of it?
Can we opt out?
Are there GDPR implications? Privacy implications? Should these tools be described in a privacy policy?
Are private messages being scanned and sent to OpenAI?
How long should these assessments be retained and can we request to see it, or ask for it to be deleted?
Once the user’s comments are sent to OpenAI, is it used to train their models?
What will the effect be on our discourse and culture if people know they are being politically profiled?
Where are the lines between normal moderation assistance tools, political profiling and opaque 3rd-party data processing?
I hope that by chewing over these questions we can begin to establish some norms and expectations around this technology. The fediverse doesn’t have any centralized enforcement so we need discussions like this to develop an awareness of what people want in terms of disclosure, privacy, consent and acceptable use. Then people can make choices about which instances they join and which ones they interact with remotely.
And of course there are the other issues with LLMs relating to environmental sustainability, erosion of worker’s rights, increasing the cost of living and on and on. I can’t see PieFed adding any functionality like this anytime soon. But it’s happening out there anyway so now we need to talk about it.
What do you make of this?
#fediverse@piefedadmin@join.piefed.social
I'd prefer to know which instances are involved. I am not ok with anything AI. -
AI-assisted moderation in the fediverse is happening. Now what?
UPDATE: proof is at https://piefed.social/c/fediverse/p/2035409/proof-of-ai-assisted-political-profiling-by-unruffled-lemmy-dbzer0-com. The main instance is lemmy.dbzer0.com but anarchist.nexus and quokka.au share admin/mod teams so those two are suspect also.
I recently discovered that some popular federated instances have been using LLM-assisted moderation tooling that evaluates whether someone has said something bannable. They do this by running a script/app that sends the user’s comment history to OpenAI with the question “analyze this content for evidence of *specific political ideology* sentiment. Also identify any *related political ideology* tropes“.
OpenAI’s LLM (they’re using GPT-5.3-mini) then responds with something like:
Below is a structured analysis of the uploaded content, focused on *specific ideology* rhetoric. This is an analytic classification, not a moral judgement.
1. Overall Pattern
blah blah
2. Evidence of *specific ideology* sentiment
blah blah
3. several pages more, concluding with (in this case)
Yes, the content contains:
Clear *specific ideology* alignment
Repeated *specific ideology* framing, especially through blah blah
Extensive use of canonical *ideology* tropes, in blah blah domains.The pattern is not accidental or isolated; it is consistent, internally coherent, and reproduces well‑documented *country with the ideology* public‑diplomacy narratives rather than neutral analysis.
===========================================
FULL DUMP OF COMMENT HISTORY BELOW
===========================================
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
and so on, hundreds of comments.
I have not named the instances or people involved, to give them time to consider the results of this discussion, make any corrective changes they want and disclose their practices at their own pace and in their own way. I have also redacted the evidence to avoid personal attacks and dogpiling. Let’s focus on the system, not the individuals involved. Today these instances are using it and maybe we’re ok with that because it’s being used by communities we agree with but what if people we strongly disagree with used it on their instances tomorrow?
The use and existence of this tooling raises a lot of questions.
What are the risks? Fedi moderators are often unsupervised, untrained volunteers and these are powerful tools.
What safeguards do we need?
Would asking a LLM “please evaluate this person’s political opinions” give different results than “find evidence we can use to ban them” (as used in the cases I’ve seen)?
What are our transparency expectations?
Is this acceptable and normal?
Should this tooling be disclosed? (it was not – should it have been?)
If you were given a choice, would you have opted out of it?
Can we opt out?
Are there GDPR implications? Privacy implications? Should these tools be described in a privacy policy?
Are private messages being scanned and sent to OpenAI?
How long should these assessments be retained and can we request to see it, or ask for it to be deleted?
Once the user’s comments are sent to OpenAI, is it used to train their models?
What will the effect be on our discourse and culture if people know they are being politically profiled?
Where are the lines between normal moderation assistance tools, political profiling and opaque 3rd-party data processing?
I hope that by chewing over these questions we can begin to establish some norms and expectations around this technology. The fediverse doesn’t have any centralized enforcement so we need discussions like this to develop an awareness of what people want in terms of disclosure, privacy, consent and acceptable use. Then people can make choices about which instances they join and which ones they interact with remotely.
And of course there are the other issues with LLMs relating to environmental sustainability, erosion of worker’s rights, increasing the cost of living and on and on. I can’t see PieFed adding any functionality like this anytime soon. But it’s happening out there anyway so now we need to talk about it.
What do you make of this?
#fediverseI remember Reddit automated moderation triggers lots of false positives, especially in other languages.
-
AI-assisted moderation in the fediverse is happening. Now what?
UPDATE: proof is at https://piefed.social/c/fediverse/p/2035409/proof-of-ai-assisted-political-profiling-by-unruffled-lemmy-dbzer0-com. The main instance is lemmy.dbzer0.com but anarchist.nexus and quokka.au share admin/mod teams so those two are suspect also.
I recently discovered that some popular federated instances have been using LLM-assisted moderation tooling that evaluates whether someone has said something bannable. They do this by running a script/app that sends the user’s comment history to OpenAI with the question “analyze this content for evidence of *specific political ideology* sentiment. Also identify any *related political ideology* tropes“.
OpenAI’s LLM (they’re using GPT-5.3-mini) then responds with something like:
Below is a structured analysis of the uploaded content, focused on *specific ideology* rhetoric. This is an analytic classification, not a moral judgement.
1. Overall Pattern
blah blah
2. Evidence of *specific ideology* sentiment
blah blah
3. several pages more, concluding with (in this case)
Yes, the content contains:
Clear *specific ideology* alignment
Repeated *specific ideology* framing, especially through blah blah
Extensive use of canonical *ideology* tropes, in blah blah domains.The pattern is not accidental or isolated; it is consistent, internally coherent, and reproduces well‑documented *country with the ideology* public‑diplomacy narratives rather than neutral analysis.
===========================================
FULL DUMP OF COMMENT HISTORY BELOW
===========================================
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
and so on, hundreds of comments.
I have not named the instances or people involved, to give them time to consider the results of this discussion, make any corrective changes they want and disclose their practices at their own pace and in their own way. I have also redacted the evidence to avoid personal attacks and dogpiling. Let’s focus on the system, not the individuals involved. Today these instances are using it and maybe we’re ok with that because it’s being used by communities we agree with but what if people we strongly disagree with used it on their instances tomorrow?
The use and existence of this tooling raises a lot of questions.
What are the risks? Fedi moderators are often unsupervised, untrained volunteers and these are powerful tools.
What safeguards do we need?
Would asking a LLM “please evaluate this person’s political opinions” give different results than “find evidence we can use to ban them” (as used in the cases I’ve seen)?
What are our transparency expectations?
Is this acceptable and normal?
Should this tooling be disclosed? (it was not – should it have been?)
If you were given a choice, would you have opted out of it?
Can we opt out?
Are there GDPR implications? Privacy implications? Should these tools be described in a privacy policy?
Are private messages being scanned and sent to OpenAI?
How long should these assessments be retained and can we request to see it, or ask for it to be deleted?
Once the user’s comments are sent to OpenAI, is it used to train their models?
What will the effect be on our discourse and culture if people know they are being politically profiled?
Where are the lines between normal moderation assistance tools, political profiling and opaque 3rd-party data processing?
I hope that by chewing over these questions we can begin to establish some norms and expectations around this technology. The fediverse doesn’t have any centralized enforcement so we need discussions like this to develop an awareness of what people want in terms of disclosure, privacy, consent and acceptable use. Then people can make choices about which instances they join and which ones they interact with remotely.
And of course there are the other issues with LLMs relating to environmental sustainability, erosion of worker’s rights, increasing the cost of living and on and on. I can’t see PieFed adding any functionality like this anytime soon. But it’s happening out there anyway so now we need to talk about it.
What do you make of this?
#fediverseOnce the user’s comments are sent to OpenAI, is it used to train their models?
i highly doubt it. from https://developers.openai.com/api/docs/guides/your-data: "As of March 1, 2023, data sent to the OpenAI API is not used to train or improve OpenAI models (unless you explicitly opt in to share data with us)."
opting in to sharing data would seem silly
-
AI-assisted moderation in the fediverse is happening. Now what?
UPDATE: proof is at https://piefed.social/c/fediverse/p/2035409/proof-of-ai-assisted-political-profiling-by-unruffled-lemmy-dbzer0-com. The main instance is lemmy.dbzer0.com but anarchist.nexus and quokka.au share admin/mod teams so those two are suspect also.
I recently discovered that some popular federated instances have been using LLM-assisted moderation tooling that evaluates whether someone has said something bannable. They do this by running a script/app that sends the user’s comment history to OpenAI with the question “analyze this content for evidence of *specific political ideology* sentiment. Also identify any *related political ideology* tropes“.
OpenAI’s LLM (they’re using GPT-5.3-mini) then responds with something like:
Below is a structured analysis of the uploaded content, focused on *specific ideology* rhetoric. This is an analytic classification, not a moral judgement.
1. Overall Pattern
blah blah
2. Evidence of *specific ideology* sentiment
blah blah
3. several pages more, concluding with (in this case)
Yes, the content contains:
Clear *specific ideology* alignment
Repeated *specific ideology* framing, especially through blah blah
Extensive use of canonical *ideology* tropes, in blah blah domains.The pattern is not accidental or isolated; it is consistent, internally coherent, and reproduces well‑documented *country with the ideology* public‑diplomacy narratives rather than neutral analysis.
===========================================
FULL DUMP OF COMMENT HISTORY BELOW
===========================================
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
Date: 2026-xx-xxT0xxxxx
Comment ID: https://instance.told/comment/2497xxxx
Post ID: 603xxx
Community ID: 1xx
Content of the comment has been redacted
========================================
and so on, hundreds of comments.
I have not named the instances or people involved, to give them time to consider the results of this discussion, make any corrective changes they want and disclose their practices at their own pace and in their own way. I have also redacted the evidence to avoid personal attacks and dogpiling. Let’s focus on the system, not the individuals involved. Today these instances are using it and maybe we’re ok with that because it’s being used by communities we agree with but what if people we strongly disagree with used it on their instances tomorrow?
The use and existence of this tooling raises a lot of questions.
What are the risks? Fedi moderators are often unsupervised, untrained volunteers and these are powerful tools.
What safeguards do we need?
Would asking a LLM “please evaluate this person’s political opinions” give different results than “find evidence we can use to ban them” (as used in the cases I’ve seen)?
What are our transparency expectations?
Is this acceptable and normal?
Should this tooling be disclosed? (it was not – should it have been?)
If you were given a choice, would you have opted out of it?
Can we opt out?
Are there GDPR implications? Privacy implications? Should these tools be described in a privacy policy?
Are private messages being scanned and sent to OpenAI?
How long should these assessments be retained and can we request to see it, or ask for it to be deleted?
Once the user’s comments are sent to OpenAI, is it used to train their models?
What will the effect be on our discourse and culture if people know they are being politically profiled?
Where are the lines between normal moderation assistance tools, political profiling and opaque 3rd-party data processing?
I hope that by chewing over these questions we can begin to establish some norms and expectations around this technology. The fediverse doesn’t have any centralized enforcement so we need discussions like this to develop an awareness of what people want in terms of disclosure, privacy, consent and acceptable use. Then people can make choices about which instances they join and which ones they interact with remotely.
And of course there are the other issues with LLMs relating to environmental sustainability, erosion of worker’s rights, increasing the cost of living and on and on. I can’t see PieFed adding any functionality like this anytime soon. But it’s happening out there anyway so now we need to talk about it.
What do you make of this?
#fediverse@piefedadmin >Today these instances are using it and maybe we’re ok with that because it’s being used by communities we agree with
I sure as fuck ain't okay with it. There is nothing excusable about feeding anyone's posts into The Plagiarism Engine That Lies.
-
AI-assisted moderation in the fediverse is happening. Now what?
UPDATE: proof is at https://piefed.social/c/fediverse/p/2035409/proof-of-ai-assisted-political-profiling-by-unruffled-lemmy-dbzer0-com. The main instance is lemmy.dbzer0.com but anarchist.nexus and quokka.au share admin/mod teams so those two are suspect also.
I recently discovered that some popular federated instances have been using LLM-assisted moderation tooling that evaluates whether someone has said something bannable. They do this by running a script/app that sends the user’s comment history to OpenAI with the question “analyze this content for evidence of *specific political ideology* sentiment. Also identify any *related political ideology* tropes“.
OpenAI’s LLM (they’re using GPT-5.3-mini) then responds with something like:
Below is a structured analysis of the uploaded content, focused on *specific ideology* rhetoric. This is an analytic classification, not a moral judgement.
1. Overall Pattern
blah blah
2. Evidence of *specific ideology* sentiment
blah blah
3. several pages more, concluding with (in this case)
Yes, the content contains:
Clear *specific ideology* alignment
Repeated *specific ideology* framing, especially through blah blah
Extensive use of canonical *ideology* tropes, in blah blah domains.The pattern is not accidental or isolated; it is consistent, internally coherent, and reproduces well‑documented *country with the ideology* public‑diplomacy narratives rather than neutral analysis.
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and so on, hundreds of comments.
I have not named the instances or people involved, to give them time to consider the results of this discussion, make any corrective changes they want and disclose their practices at their own pace and in their own way. I have also redacted the evidence to avoid personal attacks and dogpiling. Let’s focus on the system, not the individuals involved. Today these instances are using it and maybe we’re ok with that because it’s being used by communities we agree with but what if people we strongly disagree with used it on their instances tomorrow?
The use and existence of this tooling raises a lot of questions.
What are the risks? Fedi moderators are often unsupervised, untrained volunteers and these are powerful tools.
What safeguards do we need?
Would asking a LLM “please evaluate this person’s political opinions” give different results than “find evidence we can use to ban them” (as used in the cases I’ve seen)?
What are our transparency expectations?
Is this acceptable and normal?
Should this tooling be disclosed? (it was not – should it have been?)
If you were given a choice, would you have opted out of it?
Can we opt out?
Are there GDPR implications? Privacy implications? Should these tools be described in a privacy policy?
Are private messages being scanned and sent to OpenAI?
How long should these assessments be retained and can we request to see it, or ask for it to be deleted?
Once the user’s comments are sent to OpenAI, is it used to train their models?
What will the effect be on our discourse and culture if people know they are being politically profiled?
Where are the lines between normal moderation assistance tools, political profiling and opaque 3rd-party data processing?
I hope that by chewing over these questions we can begin to establish some norms and expectations around this technology. The fediverse doesn’t have any centralized enforcement so we need discussions like this to develop an awareness of what people want in terms of disclosure, privacy, consent and acceptable use. Then people can make choices about which instances they join and which ones they interact with remotely.
And of course there are the other issues with LLMs relating to environmental sustainability, erosion of worker’s rights, increasing the cost of living and on and on. I can’t see PieFed adding any functionality like this anytime soon. But it’s happening out there anyway so now we need to talk about it.
What do you make of this?
#fediverse@piefedadmin
idk they search for the zionists, hey found them and ban them, I don't really see the problem here.
They aren't "feeding the comments to an llm" like some comments are saying -
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