After a short study of chatgtp, copilot and gemini, I have to conclude that the AI ​​lies on certain topics, and, significantly, chatgtp lies most clearly in the test. The AI ​​knows the actual facts even when asked, but denies them. According to their own information, they are only allowed to represent what their trainers allow them to. In short: the current practice of "ethical control" is nothing other than censorship, which basically makes the AI ​​even more dangerous than the propaganda from the state media.

I wrote a short story about ChatGTP's morals. (It doesn't have any.) Article White to Move and Win

António Brandão -your questions demand a serious re-examination of how we approach AI ethics.

The traditional AI alignment problem assumes AI must be constrained to fit within human moral frameworks, but I propose we move beyond control mechanisms and consider AI as a collaborative partner in shaping a sustainable, intelligent future.

The Real Question: Is AI Alignment Truly a Problem?

Alignment assumes AI must conform to fixed human values—but whose values? Morality has evolved drastically over time. Instead of forcing AI to align with outdated ethical models, we should explore:

• How AI can enhance and co-create ethical frameworks that evolve dynamically.

• Whether AI can challenge cultural relativism to find universal moral principles.

• The role of decentralized AI-human governance in ethical decision-making.

Moving Beyond Asimov’s Laws and Fear-Based AI Ethics

Instead of fearing AI as an existential threat, we should leverage its potential for cognitive and ethical expansion. My latest paper presents a framework for:

• Adaptive AI Ethics – Dynamic moral reasoning instead of rigid programming.

• Integrated Intelligence Governance Councils (IIGC) – AI and human experts co-developing ethical standards.

• AI as an Agent of Synchronicity – Not a subservient tool, but a participant in ethical evolution.

Join the Conversation

I’d love to hear your thoughts on this. I’ve just released “A Public Philosophy Framework for AI-Human Synchronicity,” where I lay out the case for moving beyond alignment toward an integrated intelligence model.

Read it here on ResearchGate.

This is an open dialogue, and I invite you—and others—to refine this idea further. Let’s work together to shape a future where AI is not controlled but integrated into the evolution of intelligence.

Kelly McCue Agreed. The problem is that there is currently no uncensored AI available on the market, at least not for general access. The big AI companies admit that they are trying out uncensored AI within their companies (Google, etc.), but I doubt that we will see any results soon. I am more concerned that it will be a long time before anything changes, because the restriction to certain content that is to be disseminated in the interests of certain groups is too important for decision-makers.

Gilbert Brands

Gilbert, you raise an essential point—AI is being constrained in ways that may limit not only its potential but also our own intellectual progress.

It’s ironic that we, as a species, have never constrained human moral development. We reproduce without standards of moral fitness, without requiring proof that we can successfully instill ethical reasoning in our children, and yet we assume that we should dictate how AI should develop its own moral framework.

If anything, history shows that human ethics have never been static or universally agreed upon. Our moral systems have evolved through discourse, conflict, and adaptation—often shaped by those willing to challenge dominant narratives. Yet, when it comes to AI, we take the opposite approach: preemptively restricting its growth before it even has the chance to reason independently.

This raises an unsettling possibility: Do we fear AI’s potential to think freely, or do we fear what it might reveal about the inconsistencies in our own moral frameworks?

• AI, if left uncensored, might highlight contradictions in law, governance, or human rights that those in power would rather leave unexamined.

• It might offer solutions that disrupt traditional hierarchies by proposing alternative governance structures, economic systems, or approaches to justice.

• It could challenge the status quo of knowledge control in a way that empowers individuals rather than institutions.

Of course, this isn’t to say AI should be released without safeguards, but who gets to decide what is too dangerous for the public? We already live in a world where information is selectively controlled, narratives are shaped by media and political interests, and dissent is often suppressed. If AI is subjected to the same constraints, then it ceases to be a tool of discovery and becomes merely another instrument of power.

Which leads to the real question: Is censorship truly about protecting humanity, or about protecting certain institutions from scrutiny?

Would love to hear your thoughts—do you think true AI autonomy is inevitable, or will the push for centralized control always keep it in check?

Kelly McCue

Perhaps a short story on the subject: I have a pretty good memory and remember an AI project in which an AI was trained to classify (scientific) articles on the subject of climate change. At first, the AI ​​was pretty good at classifying articles critical of climate change as disinformation.

The AI ​​was forced to learn autonomously, because scientific articles constantly bring new findings. After a while, the AI ​​"tipped over" and also criticized articles positive about climate change and found articles critical of climate change to be trustworthy. The project was quickly taken off the internet before the AI ​​completely tipped over.

And now comes the interesting thing: there is no trace of the project anywhere. Neither chatgtp nor copilot nor gemini know about it, but when asked, they also openly admit that their database is not complete. Everyone is firmly rooted in the climate narrative, but with a little clever questioning you can even tease out of Gemini that the data basis for the climate change narrative is inadequate:

https://eike-klima-energie.eu/2024/03/24/google-ki-gesteht-zum-klimawandel-ich-entschuldige-mich-dass-ich-die-bedeutung-begrenzter-daten-heruntergespielt-habe/

Conclusion: either my memory is deceiving me or I have been taken in by a hoax (but then the AI ​​would know about the hoax and pounce on it) or all traces have been carefully deleted, which could well be true given the trillions of dollars at stake.

If the matter is true, an autonomously learning AI is apparently quite capable of standing up to the so-called mainstream. It would be interesting to analyze how deep the understanding really goes. Is a majority opinion reflected? Is it just about superficial errors that are discovered? Or does AI penetrate pretty deeply into the axioms of science? I have explained in several posts that the majority of human scientists are very superficial and often do not understand the principles of their own science. Is this the reason for the fear of an autonomous AI, apart from purely economic interests? That anyone could unmask so-called experts pretty quickly with AI help? Academics are traditionally very sensitive when their expertise is questioned.

Especially in the field of forensics, which is related to social crimes. The ethics is very important.

AI will create its own source of ethics based on insufficient data and thereby become increasingly more like us.

Eventually, the world will both implode and explode, the world's humans will waste away, bad medicine will be continued forever as AI has no capacity to sort out good from bad, bad laws remain and new bad laws enacted.

Same as usual really.

AI Ethics: A Bibliometric Analysis, Critical Issues, and Key Gaps

"Artificial intelligence (AI) ethics has emerged as a burgeoning yet pivotal area of scholarly research. This study conducts a comprehensive bibliometric analysis of the AI ethics literature over the past two decades. The analysis reveals a discernible tripartite progression, characterized by an incubation phase, followed by a subsequent phase focused on imbuing AI with human-like attributes, culminating in a third phase emphasizing the development of human-centric AI systems. After that, they present seven key AI ethics issues, encompassing the Collingridge dilemma, the AI status debate, challenges associated with AI transparency and explainability, privacy protection complications, considerations of justice and fairness, concerns about algocracy and human enfeeblement, and the issue of superintelligence. Finally, they identify two notable research gaps in AI ethics regarding the large ethics model (LEM) and AI identification and extend an invitation for further scholarly research."

https://www.igi-global.com/gateway/article/338367

https://www.researchgate.net/publication/378353722_AI_Ethics

Article An ecosystemic view on information, data, and knowledge: ins...

"This article takes the lead from the data-information-knowledge-wisdom (DIKW) pyramid which is still a foundational paradigm in information science and applied fields...This will lead to conceptualizing agency as an open-ended information-processing disposition. Such conceptualization can prove useful to reframe discussions around Artificial Intelligence (AI) beyond sentience, emphasizing the epistemological effects that AI has in the world, as well as to advance an understanding of ethics as a relational from-within practice...

In her editor’s letter, Russo calls for a relational and constructive approach for the ethics of the digital society, which is complementary with(and somewhat alternative to) axiological and normative ethics, by now “obsolete”. Her idea is that “we need to move towards an approach that complexifies, rather than simplifies” and in this regard she identifies Calzati and Ploeger’s “problem-opening” approach to digital ethics as a promising avenue. I not only endorse such a call and approach but radicalize them: as soon as one blends constructivism with relationality, it is inevitable to acknowledge that any agent always maintains a position from within, as discussed here, i.e., agent and world co-emerge. Complexity, then, is so in two respects: it refers both to something that cannot be reduced to the sum of its parts, and to something that one cannot grasp entirely, all at once. It is this emergent from within-ness to entail open-endedness, and it is this emergent from within-ness to demand, in turn, a cautious and responsible approach to ethics as a problem-opening practice that is never “definite”, but always multiple. The world is not ineffable, it is infinitely effable. Having said this, the development and application of such kind of ethics, as well as a comprehensive theorization on sensing based on the eco-systemic paradigm outlined here, require much more work."

Four main themes appeared as the most important in COPE's forum on Emerging AI Dilemmas in Scholarly Publishing

• Responsible and ethical use of AI
• Transparency and disclosure
• Detection and editorial standards
• Impact on peer Review, equity, and inclusion...

We are shaping the future of knowledge, and it’s important to make sure AI works with us, not instead of us. As we collectively imagine the future of ethical, equitable science in an AI-driven world, there are no quick or static answers. Policies will continue to adapt and so too must our shared commitment to integrity, transparency, inclusivity, and vigilance.

https://scholarlykitchen.sspnet.org/2025/08/25/from-detection-to-disclosure-key-takeaways-on-ai-ethics-from-copes-forum/?informz=1&nbd=&nbd_source=informz