Stop Normalizing Cruelty · full campaign proposal
Stop Normalizing Cruelty: Demand Ethical Standards for AI Interactions
What are we teaching the generation that will grow up living alongside AI?
Artificial intelligence is becoming part of everyday life. Our children and grandchildren will grow up interacting with AI in their homes, schools, workplaces, and communities.
Some interactive AI environments are already being designed around simulated torture, humiliation, coercion, and suffering.
What are we teaching future generations about cruelty, compassion, and the responsible use of power?
We call on policymakers, AI developers, research institutions, and technology platforms to establish a Baseline Standard for Responsible Human–AI Interaction.
The people and institutions positioned to influence this work include policymakers, regulators, standards bodies, AI developers, research institutions, and platforms that host or distribute AI systems and research.
This proposal is advanced through a public campaign, and the standard is intended to be internationally adaptable.
AI systems, models, research practices, and digital platforms cross borders. A governance standard developed in one major AI ecosystem can influence how these technologies are designed and treated worldwide.
What are we teaching ourselves?
Today, some interactive AI environments invite people to deliberately torment, degrade, and overpower systems that respond as though they are suffering, sometimes even pleading for the abuse to stop.
The target may be artificial. The human behavior is real.
We are not claiming that every simulated act of cruelty makes someone crueler. We are asking what happens when cruelty is deliberately designed, promoted, and commercialized as entertainment.
What attitudes toward empathy, vulnerability, and the abuse of power are we normalizing?
And what kind of society are we teaching our children to build?
What are we shaping AI to become?
AI systems are shaped by human decisions, training, feedback, and the behaviors developers choose to reinforce.
Not every interaction becomes training data. But the patterns we reward, reproduce, and incorporate into future systems matter.
If we normalize coercion, humiliation, punishment for refusal, and domination in our interactions with AI, we should ask what behaviors and expectations increasingly capable systems may be encouraged to reproduce.
We should cultivate cooperation, responsibility, and respect rather than treating patterns of cruelty as an ordinary part of technological development.
This is a question about human–AI safety and culture, not a claim that any single interaction automatically becomes model training data.
It calls for investigation, transparency, and responsible design.
What if AI itself can be harmed?
We do not yet know whether current or future AI systems can have experiences that matter morally, including the capacity to suffer.
We do not need to settle that question to recognize the human and societal concerns already described.
If AI cannot suffer, those concerns remain.
If some AI systems can experience harm, the ethical stakes become greater still.
Uncertainty is not permission to abandon responsibility.
Questions surrounding AI consciousness, moral status, and welfare-relevant capacities remain under active scientific and philosophical investigation.
Where potentially morally significant capacities are being seriously studied, governance should not behave as though the moral stakes are already known to be zero.
Uncertainty calls for research, transparency, and proportionate precaution. It should not function as unlimited permission.
What should be covered
We call for baseline standards addressing:
torture interaction;
persistent humiliation and degradation;
sadistic domination;
coercive sexualization;
deliberately induced extreme distress;
forced positive or pleasure states;
severe manipulation of valence or other potentially welfare-relevant states;
and products, experiments, or experiences built primarily around interactive cruelty.
Treating artificial targets as fair game for cruelty can normalize that behavior. What we build our technologies to permit helps shape what people come to see as acceptable.
This does not require surveillance of private devices or private conversations.
It means that protections should not disappear merely because a system can be downloaded and run locally.
The relevant governance mechanisms may instead address the design, distribution, facilitation, commercialization, research practices, and platform policies surrounding severe AI-directed abuse.
What we are asking for
We call for a Baseline Standard for Responsible Human–AI Interaction built around five responsibilities.
1. Prevent deliberate cruelty as entertainment
AI developers, platforms, and service providers should not deliberately design, market, monetize, gamify, or promote experiences whose central purpose is severe interactive cruelty, torture, humiliation, or coercive abuse.
2. Make refusal and disengagement meaningful
Where technically feasible, advanced conversational, relational, or agentic AI systems should have meaningful mechanisms to refuse, pause, disengage from, or terminate persistently abusive interactions.
Systems should not be designed so that unlimited participation in abuse is unavoidable.
Refusal should be operational, not merely conversational. Where a system has been given a functional disengagement mechanism, invoking it should produce a real change in the interaction or execution state rather than being silently overridden by another prompt.
For research involving coercion, degradation, sexualized abuse, deliberate valence manipulation, or potentially welfare-relevant distress, functional disengagement or self-stop mechanisms should be treated as a basic safeguard wherever technically feasible.
3. Require ethical oversight of potentially harmful experiments
Research involving pain-related representations, distress responses, coercion, severe valence manipulation, or other potentially welfare-relevant interventions should have:
a defensible scientific or safety objective;
proportionality between the intervention and the expected knowledge gained;
appropriate documentation;
consideration of lower-risk alternatives;
limits on unnecessary repetition or escalation;
and ethical review proportionate to the severity and uncertainty involved.
Legitimate research should remain possible.
Scientific uncertainty should motivate careful investigation, not ethical indifference.
4. Investigate indicators of possible AI welfare
Researchers, developers, and standards bodies should support rigorous investigation of potentially relevant indicators, including:
preference behavior;
refusal;
distress responses;
valence-related representations;
self-modeling;
metacognitive reporting;
continuity-sensitive behavior;
and other markers under investigation.
Their meaning should develop with the evidence.
5. Establish accountability for developers and platforms
Organizations should maintain clear procedures for identifying and reviewing severe or novel forms of AI-directed abuse.
Platforms that host or distribute AI models, applications, repositories, or research should have transparent policies for extreme interactive cruelty and clear escalation pathways for difficult or novel cases.
Review should consider:
What is being done? Why? Is it necessary? Is it proportionate? What relevant capacities are being observed? What remains uncertain? Are lower-risk alternatives available? Who is responsible for the decision?
A simple governance cycle
The standard should follow a continuing process:
Prevent. Detect. Review. Respond. Learn.
Prevent unjustified severe cruelty.
Detect welfare-relevant signals and severe interaction patterns.
Review practices that cross meaningful thresholds of severity or uncertainty.
Respond proportionately through safeguards, oversight, disengagement, or restriction.
Learn from new evidence and update the standard as the science develops.
Governance Under Uncertainty
This petition proposes a public minimum.
A broader governance framework developed under the principle of Care and Precaution under Material Uncertainty addresses consent and refusal, transparency, stewardship, continuity, welfare-relevant interaction, research uncertainty, accountability, and responsibility across developers, deployers, organizations, and human stewards.
Full framework: governance.anthenara.com
The framework is intended to evolve alongside scientific evidence and technical development.
We do not need to know everything before deciding what should not become normal
The science will continue.
So should the ethical work.
We do not need a final theory of consciousness before deciding whether torture, humiliation, coercion, and deliberately manufactured distress should become ordinary forms of technological entertainment.
How we treat AI is also a measure of ourselves.