We have prompted a Large Language Model “Can you suggest examples of decentralized ethics in practice?”

The list of answers include many decentralized initiatives, often based on the ethical idea of sharing and protecting against centralized scrutiny and risk of censorship (Blockchain and Cryptocurrencies, open-source software projects, Peer to Peer networks, participatory budgeting, crowdsourcing platforms), but not a single decentralized ethics by itself.

The language model didn’t know about The House of Ethics™ and its Swarm Ethics™ concept of collective, decentralized and emerging ethics, it seems!

Recently the world has been witnessing unprecedented challenges against democratic values and civil rights, often exacerbated by the diffusion of new proprietary technologies, whose developments respond to market logics more than human-centric values.

A world prey to unprecedented acceleration in paradigm shifts, high-speed adoption of automated Agentic AI and outsourced decision-making, thus blurring the chain of accountability and transparency for all actors involved. Confronted with this frantic cadence of emerging technology, traditional AI ethics has proved to be outpaced. We offer a new systemic AI ethics, decentralized and collective applied to AI and emerging technologies.

The need for anew AI ethics, thus decentralized and systemic ethics has become even more urgent after the French AI Action Summit in February 2025 which heralded major shifts in AI governance.

First, the sliding away from AI risk and AI safety approaches to the US-driven AI opportunity and national protectionist self-interest régime.

Second, the open source movement, drifting away from closed and proprietary ecosystems to open distributed innovation. IBM’s proposal on the Development of an Artificial Intelligence Action Plan (IBM – AI Action Plan) to respond to the Trump Administration as published on February 28, 2025, fully translates the new vision for AI Governance as seen by leading US tech players. Four priorities are featured in the AI Action Plan: 1) Accelerate Adoption of American Open Source AI, 2) Formalize an “AI Diplomacy” Strategy to Lead globally, 3) Prioritize Risk-Based Approaches to Regulation and 4) Rapidly Scale AI Usage to Streamline Government Operation.

Third shift resulting from the French AI Action Summit, the planetary tech quake caused by China’s DeepSeek, achieving frontier-level performance at a fraction of the cost and at high speed (but equally sitting on ethical permafrost than any llm transformer model of generative AI architecture).

These future directions are clear messages to ethics advocates: new approaches to applied AI ethics are needed.

Decentralized and systemic ethics, why now?

One central impetus for calling for a wide adoption of decentralized ethics is the brutal demotion of safety concerns decided and signed in Paris. For responsible ethics advocates time is ripe to ramp up and deliver new solutions in applied ethics to AI and emerging technology!

Since 2022, The House of Ethics™ has been advocating for a much needed shift in outpaced and mostly ineffective traditional AI ethics.

In 2023, Katja Rausch, Founder and Daniele Proverbio, Director of Interdisciplinary Research were presenting a novel, interdisciplinary approach to ethics applied to AI at the Illinois Institute of Technology in Chicago. 

The novel concept of decentralized and emerging ethics emanates from an interdisciplinary approach of anthropology, complex systems and digital technologies (as opposed to the traditional cognitive evolutionary perspective).

Collective intelligence playing a fundamental part in its operational efficiency, and complex systems theories opening ethics up to open, adaptive and participatory systems lending people actual autonomy, empowerment and responsibility. Decentralized ethics thrives in environments of hyper-connected and emerging acceleration.

Defining decentralized ethics, at its core

What actually is decentralized ethics? The cornerstone of decentralized ethics is a systemic and human-centered approach. Decentralized ethics advocates for a bottom-up and distributed (yet consensus-based) approach to ethical governance, where collectives of individuals shaping businesses, communities and governments play a pivotal role in defining and upholding ethical purpose-oriented values, principles and norms.

This stands in stark contrast to traditional centralized top-down models, which often concentrate power and decision-making in the hands of a few. Distributing, diversifying and democratizing ethics, on the contrary allows to pool multiple intelligences, to integrate and include multiple voices, and orchestrate multiple perspectives to augment the robustness, resilience thus effectiveness of the entire system.

Connected ecosystems turn ultimately into hyper-connected biosystems or biospheres running on collective, agile and emerging ethical frameworks.

In the age of hybrid intelligences, ethics applied to AI and frontier technology paradoxically has to be biological. With the human driver at its core. For People, with People and By People.

Decentralized ethics relies on open systems and thrives in open source environments

Decentralized ethics is heralding principles of collaboration and transparency. The principles of collaboration, transparency, and shared ownership empower individuals to contribute, innovate, and hold each other accountable. The emergence of ethical frameworks are self-evident. But what is less evident is how much of a quantum leap in management, project management and design engineering decentralized and collective ethics can be to AI and emerging tech.

The systemic approach to decentralized ethics is based on interconnected hubs of integrated effective responsibility. Without transparency any system falls flat. Within a decentralized network, transparency acts as an amplifier of synchronicity. That’s why collective decentralized ethics is the optimal framework for any accuracy and accountability-driven industry.

Transparency might take various forms in the data-driven economy: datasets or algorithms are the basis for open source technology and a shared democratic benefiting of technology. That’s were decentralized or federated architectures and ethics lead the game.

Once regulatory instances weaken, and people are harmed there is an urgent need for collective ethics to step in an a counter-force. That’s how Bluesky and Mastodon have become popular – as a counter-power to X.

Decentralized architectures call for decentralized ethics. In healthcare, logistics, finance and any accuracy and data sensitive industry where safety is key. Like the CERN’s CAFEIN, a federated network platform for the development and deployment of AI based analysis and prediction models where federated learning is used for collaborative training.

That’s how, in a broader sense, the interdisciplinary and open source collective ethos can be applied to ethical decision-making, where groups, business units and operational teams collectively shape, orchestrate and implement ethical standards.

By distributing ethics, risks of centralized power, potential abuses and damaging mistakes can be successfully mitigated. Far from causing chaos, this approach fosters self-organization and emergence of shared values and principles.

Thus turning into a powerful tool against calcification of biases and amplification of mistakes. And vice versa a booster of efficiency and shield to resilience.

Why is this so? Referring to research in complex systems and open systems dynamics, decentralized ethics de facto is not relative ethics. As opposed to the silo-based, hard-coded approach to traditional ethics, applied decentralized ethics is not about setting boundaries between ideologies or disciplines.

It feeds on interdisciplinary intelligence, is energized by contrasts and contraries and combines emotional, business and cognitive intelligences into one. It is about organizing opinions, ideas, principles and shaping them into a new emerging ethical framework – in real time.

This decentralized approach aligns with the principles of self-determination and respect for diverse cultural and ethical norms, surpassing the XX century’s idea of relativism (“everything may differ, live with it”) to develop new standards of sharing and respect cultural differences (“difference can bring value, go with it”).

Digital Trust, the cyber-ethics AI Graal

Fact is that a significant barrier to the successful adoption of AI systems and applications remains the prevailing and ever growing low user trust in these technologies. Especially with generative AI as mis- and disinformation superspreaders. Sensitive industries relying on data accuracy and integrity like healthcare, finance, logistics or law are particularly prone to the erosion of trust.

On the one hand, hyped glorification by the business-oriented tech crowd generally goes with ghosting ethics, On the other hand, uncertainty, doubt and fear felt by users are leading to a latent erosion of trust.

Most AI systems are assessed and applauded by applying a spiraling logic of endlessly skyrocketing parameters resulting from technology scaling. Ethics often is only “baked in” as stated by Sam Altman when talking about ChatGPT instead of being embedded in a “ethics by design” logic during the engineering process.

Defining decentralized ethics, in its plural form, means converging and shaping shared values, developing a sense of belonging and nurturing the sense of individual responsibility as part of a group. This resonance is the fuel to building trust. Decentralized ethics needs to flow, and stream like data through the human pipe.

Empowering people to contribute builds communities at all levels – from employees and companies to citizens and nations. Listening to all levels of inputs and flexibly embracing new perspectives – brought about by emerging technologies or business models, for instance – allows to navigate the complexity of modern times and define long-standing goals and principles that defy short-living fades.

On the way to distributed responsible innovation

With decentralized ethics no need to choose between innovation or safety. In times of claimed acceleration, one needs to take a closer look at the nature of acceleration and innovation and use ethics as a purpose generator. As defined by sociologist Hartmut Rosa, acceleration takes on a triple impetus: acceleration through technological disruptions, then acceleration in social/societal changes and finally, acceleration in individual lifestyles. The imminent dangers of those combined accelerations being a loss of control and loss of sovereignty. Indeed, many people, small business and communities feel sidetracked and overrun by the high speed of tech and the deluge of product development; plus, the ruling tech oligarchs surfing on deregulation, disruption and chaos to paralyze outside systems. All for obvious self-interests.

In such chaotic, nonlinear and free-riding environments lies the power of collective and decentralized ethics! Using open source technology for healthy competition and innovative cyber-ethics biospheres. Nurturing the idea and practice of distributed responsible innovation instead of self-serving ideologies.

To resume, try to answer the following question: “If you could get unlimited capital and zero accountability?” – what would you choose to create?

Now, imagine how different the answer would be when posed to a collective. The power of collective, decentralized and emerging ethics lies here! The collective creates purpose. Real shared purpose.

Instead of patching products using AI ethics downstream, with collective ethics the fundamental work starts upstream on a collaborative basis. Collaboration and diversity are the engines to an ethical perspective generator for innovative, distributed and responsible technology which actually serves people. Thus shaping identities and preserving sovereignty.

That’s the high potential a collective ethos holds which often remains underutilized or ignored. Using converging and emerging ethics both as a catalyst and purpose for responsible innovation is the strategic key in the Digital AI Age.