Historical commentary. First published in German on 24 September 2025. This English translation incorporates the corrections made to the German text on 4 October 2026 and retains the original time perspective. English translation published on 16 October 2026.

Artificial intelligence is advancing rapidly, and it can often seem as though only the major players in the United States and China have a say in where it goes next. Yet this is precisely where a particular opportunity opens up for Germany and Europe. Three observations show where our potential for efficient AI lies.

Why language models hallucinate

In its research on “Why Language Models Hallucinate”, OpenAI examines why language models produce plausible but incorrect answers. The paper on arXiv shows, among other things, how training and evaluation can reward guessing when a model is uncertain. It does not prove that hallucinations are fundamentally impossible to resolve in every AI system. A 2024 study in Nature investigates statistical methods for detecting a particular subset of these errors.

In practice, this means that even the best models available at the time will continue to generate incorrect facts that can be difficult to spot. Bigger models, faster processing and more data alone will not solve this structural problem. This is precisely where research into fundamentally new approaches is needed.

What are hallucinations in AI models?

“Hallucinations” are responses from AI systems that sound linguistically plausible but are factually incorrect or entirely invented. One example would be an AI answering a question about a historical figure with a quotation that person never said. This is a structural problem of today's language models rather than simply a software bug. They work by predicting text on the basis of probabilities, rather than possessing a genuine understanding of truth. However, this way of working does not establish a general proof that the problem is unsolvable. For example, a system can refrain from giving a specific answer when it is uncertain.

The business model of the major technology companies

Companies such as NVIDIA, Microsoft and Google are currently pursuing ever larger models. The NVIDIA CES 2025 keynote and the GTC 2025 event clearly show how their commercial success rests on selling computing power. More models mean more GPUs and more revenue.

As analyses of the CES 2025 announcements show, the focus is on ever more powerful data centres and larger AI infrastructure. Efficient, lean AI is not their current priority, and I do not expect that emphasis to change fundamentally over the next few years. For the major providers, encouraging resource consumption is economically attractive; reducing it is less so.

Europe's opportunity in fundamental research

This is where Europe can make its mark. The future of AI will not be decided solely by the race to build ever larger models. New models, technologies and approaches are needed. German and European researchers can excel at precisely this intersection.

The EU adopted €7.3 billion in funding for research and innovation across several fields under the Horizon Europe work programme for 2025. The DIGITAL work programme for 2025–2027 includes a further €1.3 billion for deploying strategic digital technologies, including AI, cloud and data, cybersecurity and digital skills.

Fundamental research into efficiency, new algorithms and approaches that use fewer resources presents a major opportunity. Far from having lost our chance, we have an opportunity to gain a foothold and deliberately pursue new research directions. The prize is still up for grabs, and Europe has the means to compete for it.

A different approach in practice: Apple's on-device AI

With its Apple Intelligence features, Apple is pursuing a strategy that differs fundamentally from its competitors'. It brings many AI features directly to users' devices through on-device AI, complemented by larger server models for Private Cloud Compute.

As technical analyses show, this substantially reduces the resources required in data centres, strengthens privacy and opens up new possibilities for using AI in everyday life. The approach illustrates that innovation need not always mean “bigger”. Sometimes progress lies in efficiency.

At the same time, the market for small language models, or SLMs, is developing rapidly, alongside edge AI hardware setting new benchmarks in 2025.

Conclusion

The AI revolution is well under way, and Europe has every opportunity to keep pace and lead in crucial areas. While the major corporations pursue scale, Europe can take a leading role in fundamental research, efficiency and innovation. The time to act is now. We have not lost our chance to win.

Related reading added on 16 October 2026: For a later perspective on Europe's role in AI and the responsibility of technology providers, see my analysis of Zuckerberg's vision and European AI governance.

Related reading added on 18 October 2026: AI After 60 explains how critical checking can go together with an encouraging start: through everyday experiments, the dog-training analogy and the question “Does that make sense?”.

Editorial status: 6 October 2026. An analysis of Mark Zuckerberg's essay "The Future is for Everyone" of 10 August 2026 – read through the framework of the 4 Robotic Revolutions, the encyclical Magnifica Humanitas, and a European approach to Robotic & AI Governance.

On 10 August 2026 Mark Zuckerberg published a manifesto at meta.com/thefutureisforeveryone. The text, close to 6,500 words, is one of the most direct statements a Big Tech CEO has offered on superintelligence in years. Zuckerberg writes that Meta is building "personal superintelligence" - an AI available to every individual on a persistent basis as tutor, advisor, business tool, and conversational partner. He argues against a single benevolent superintelligence, against doom rhetoric, against concentration of compute in few hands. He argues for distribution, open source, community compacts, and a US-led model in competition with China. The essay closes with the line "Superintelligence holds the promise of giving everyone that power, and building a positive future for everyone" - signed "- Mark" and dated August 10, 2026.

The text deserves careful reading. It also deserves careful pushback. My thesis for this post: Zuckerberg's essay asks the right question ("Who owns the future?") but delivers a structurally truncated answer. Reading the text as a blueprint for the coming decade of AI and robotics hands governance responsibility to a single company, a burden Meta neither can carry nor should carry. What the text is missing is the institutional substructure that Europe - and specifically Germany - could offer if we stopped making ourselves intellectually small.

What Zuckerberg actually says

Any critique deserves a fair rendering. Zuckerberg opens with an observation that is correct: the debate about superintelligence has so far been either eschatological (doom, existential risk, alignment failure) or utopian (curing cancer, solving physics). Both frames ignore, in his view, how the technology will actually settle into the everyday life of billions of people. His answer is an empowerment narrative. Every human being gets their own AI, one that supports them in work, education, social life, dealing with bureaucracy, and personal organisation. Meta is pursuing this work through its "Meta Superintelligence Labs", investing heavily in data centres, for example in Louisiana, pledging water-positive operations by 2030 (200 percent in water-stressed regions), and signing "Community Compacts" with the municipalities that host the compute. The example named in the text: Richland Parish, Louisiana, with teacher bonuses of USD 50,000 in 2026 from increased tax revenue, according to Zuckerberg.

Zuckerberg makes three philosophical moves. First: empowerment over automation. AI should not replace work; it should extend the capabilities of the individual (he calls this "invention" instead of "automation"). Second: distribution over concentration. He argues explicitly against a "single benevolent superintelligence" held in one place, even if its values were genuinely benevolent. Third: open source as a safety principle. When many actors have access to powerful models, so the reasoning, a "balance of power" emerges between AI systems and between humans and AI.

LeCun announced in November 2025 that he would leave Meta at the end of that year. He also envisaged a partnership between Meta and his new AMI company. His departure alone therefore does not establish a break with Zuckerberg’s position. LeCun’s own announcement.

Zuckerberg identifies recursive self-improvement (RSI) as a risk: systems could improve themselves and become harder to control. He proposes providing more compute for people than for such systems, involving Meta’s independent corporate directors in model-release decisions, and sharing intermediate training checkpoints with the US government. For me, the question remains how these internal measures would work alongside independent public oversight. Aligning AI more closely with individual users does not resolve the wider question of responsibility.

The philosophical question: individual or common good?

Zuckerberg's text is one of the sharpest articulations of a strictly individualistic understanding of AI I have read in years. The empowerment framework sits so deep in the essay that on a first reading it feels obvious. It is not.

The European philosophical tradition asks a different question. It does not begin with "what does AI do to me?" but with "what does AI do to us?". Immanuel Kant formulated this in the Categorical Imperative as the test of whether a maxim of action could be conceived as a general law. Applied here: can the maxim that every human being possesses a private superintelligence be a general law? And if so, what follows for the design of institutions, education, division of labour, and public space? In my view, the essay does not develop these collective preconditions sufficiently. He takes the individualistic model as given and derives institutions from it, rather than the other way around.

AI ethics in my lectures at the Hochschule der Bayerischen Wirtschaft (HDBW) raised questions also addressed by Pope Leo XIV's encyclical Magnifica Humanitas. I analysed it in an earlier post. The core idea: the human person has a value that is not exhausted by utility functions. Technology is not a neutral instrument. It is institutional action that defines chains of accountability and either builds them or breaks them. When an AI sits in every person's toolbox, the shift is not only in individual productivity. It is in the position of the person in the polity. She becomes potentially more autonomous – and simultaneously more dependent on the provider that controls the technical foundation of that autonomy. In my view, the essay gives this ambivalence too little attention.

My philosophical critique concerns the power relations behind the promise of empowerment. AI can give people new capabilities while making them more dependent on their tools’ providers. For me, a central lesson from the development of social platforms is that personal empowerment does not itself guarantee democratic control over infrastructure, data or access. Anyone promising superintelligence should therefore explain how individual freedom and public responsibility fit together.

The ethical dimension: who is liable for the consequences?

In a series of academic papers - including "Roboethics and Robotic Governance" (Bösl & Bode, 2017, in the Springer volume "ROBOT 2017: Third Iberian Robotics Conference", DOI 10.1007/978-3-319-70833-1_12) - I have developed the concept of Robotic & AI Governance. The core: from a governance perspective, autonomous systems (robots as much as AI models) cannot be understood solely as conventional tools. This does not mean they are exempt from product liability. Nor are they legal persons in the sense of civil law. They are institutional intermediary entities whose actions emerge from a chain of design, training, deployment, and use decisions. Governance is the ordering framework that makes this chain reconstructable and legally addressable.

Zuckerberg wants Meta’s independent corporate directors to oversee model releases. This is distinct from the Oversight Board for content moderation. My critique concerns a different question: how are internal decisions complemented by public rules, independent scrutiny and traceable responsibility? Zuckerberg also acknowledges the need for government policy, but leaves the European arrangements open. Users can configure their AI, yet do so within a technical framework shaped by the provider. Personal choices therefore do not replace public accountability.

What is missing is the recognition that governance cannot be self-governance. For any serious regulation of high-risk products - pharma, aviation, nuclear energy, chemistry - the separation between provider, independent testing body, and state supervision is constitutive. The EU AI Act, in force since 1 August 2024, with phased application dates, provides for conformity assessment and public supervision; an independent testing body is not required in every case. Zuckerberg does not mention the EU AI Act in his essay. He does not mention Europe at all. I read this as a deliberate omission and as a strategic self-disclosure: in the world order Zuckerberg imagines, Europe is not an actor. It is a market.

A second ethical question concerns alignment: what should guide an AI? Zuckerberg emphasises individuals and their goals, a plausible promise of personal support. But if individual preferences become the sole criterion, problematic or shortsighted wishes may also be amplified. In my view, this does not settle the question of shared rules and the common good. Reconciling personal empowerment with other people’s rights requires political and public debate.

The socio-political dimension: distribution as a power strategy

Zuckerberg’s argument for open models and distribution is also geopolitical. The essay contrasts the US and China and addresses export controls and American leadership. For me, this raises an institutional question: how do states and multilateral institutions retain the ability to shape developments when powerful AI becomes widely available? Distribution can empower people. It also requires rules whose enforcement does not depend solely on providers’ goodwill.

Distributing applications does not automatically distribute control over their foundations. Those who train models, operate infrastructure and set access conditions retain considerable influence. For me, this is the tension in Zuckerberg’s balance-of-power argument: Meta can make applications available to many people while controlling central decisions about them. Whether that produces a workable balance depends on the specific rules governing access, scrutiny and responsibility.

The first responses show different emphases. The Register and 404 Media commented sharply on the essay on 10 August 2026. The ETC Journal recognised the importance of the question while challenging the answers. These three voices are examples of the early reception, not a systematic survey of the field.

For European policy, the task is clear: formulate its own institutional answers. The EU AI Act is a comprehensive European legal framework. Its implementation will show where it needs clarification and how effectively supervision works. An internal company body can complement that public task, but cannot take it over.

The socio-economic dimension: community compacts and labour displacement

Zuckerberg's essay describes "Community Compacts" - agreements between Meta and the municipalities that host the data centres. The example: Richland Parish, Louisiana. Zuckerberg reports teacher bonuses of USD 50,000 in 2026 from increased tax revenue, supports school infrastructure, and commits to water-positive operations by 2030 (200 percent in water-stressed regions). This sounds generous. It is also a striking shift of the social contract. According to the essay, the bonus is enabled by additional local tax revenue. My institutional question remains: how much room does a municipality have to shape its future when its development depends so heavily on one company? Additional local revenue does not settle how benefits and burdens are distributed within a region and beyond it.

Such a site agreement cannot simply be transferred to Europe unchanged. Additional local revenue and corporate commitments need to work alongside existing public responsibilities, education systems and welfare arrangements. If Germany wants to attract data centres, the question of regional benefit should therefore go beyond a single bonus: vocational education, basic research, social partnership and regional value creation should, in my view, be part of the negotiations.

In my view, the essay does not sufficiently develop the question of work. According to the International Federation of Robotics, around 4.66 million industrial robots were operating worldwide in 2024, nine percent more than in the previous year. World Robotics 2025, Executive Summary. That shows the growing importance of industrial automation. The figure alone does not tell us how many jobs are created, transformed or lost. We need to investigate those effects rather than resolve them rhetorically through a contrast between invention and automation.

In an earlier essay on the 4 Robotic Revolutions I described how robotic industrialisation unfolds in four phases: protected industrial robots, sensitive and collaborative robotics, mobile systems, and cognitive robotics with increasing autonomy. The framework helps distinguish different changes in work and organisation. Anyone assessing generative AI should therefore also consider the experience of industrial automation.

The legal dimension: EU AI Act and provider responsibility

The EU AI Act has been in force since 1 August 2024, with phased application. Provider obligations for general-purpose AI models are set out primarily in Article 53; Article 55 adds requirements for models with systemic risk. Subject to statutory exceptions, these include technical documentation, information for downstream system providers, a copyright compliance policy and a public summary of training content, with additional safety evaluations for models with systemic risk. For Meta’s models, GPAI obligations need to be assessed for the specific version and its placement on the EU market. Transition periods matter: models placed on the market before 2 August 2025 generally have until 2 August 2027 to comply. MSL had already presented Muse Spark in April 2026. The essay does not replace an assessment of European provider obligations.

The legal question is not theoretical. If Meta offers "personal superintelligence" in Europe, these systems fall under the EU AI Act. Additional GPAI provider obligations depend on the actor's role in placing the model on the market, not simply on open weights. Article 53 provides limited exceptions for certain models released under free and open-source licences; those exceptions do not cover models with systemic risk. Whether the high-risk regime applies depends on the specific intended purpose under Article 6 and Annex III, not simply on the sector. Under the amended timetable, the main obligations for Annex III systems apply from 2 December 2027. This timetable was amended by the Digital Omnibus on AI in July 2026. For me, the crucial point is that personal empowerment in a European rollout must be connected with verifiable provider and deployer responsibility.

Copyright cannot be reduced to a blanket admission by Meta. In Kadrey v. Meta, the US court found the training use at issue to be fair use against the 13 plaintiff authors on the specific evidentiary record on 25 June 2025. That was not a general authorisation of all AI training. US court decision. In France, SNE, SGDL and SNAC made allegations against Meta and announced a claim in March 2025; those allegations should be distinguished from judicial findings. The organisations’ announcement. For European governance, the origin of training material and traceable rights clearance remain central questions.

The 4 Robotic Revolutions as an analytical frame

Together with Bernd Liepert, I proposed the "4 Robotic Revolutions" model at IEEE/RSJ IROS in Daejeon in 2016. The first revolution describes the protected industrial robot. The second concerns sensitive and collaborative robotics and cooperation with people. The third is mobility: robots leave their fixed workplace. The fourth concerns cognitive robotics and increasing autonomy. The phases overlap; they are not a rigid chronology. Humanoid systems and generative AI are developments that can be analysed through this framework, rather than additional phases of their own.

Zuckerberg’s essay considers AI primarily through digital models and personal assistants. In my view, the connection with physical robotics receives too little attention. Over the coming decade, I expect generative AI, humanoid systems, autonomous mobility and industrial automation to become more closely connected. That calls for a careful examination of companies’ technical capabilities and investments. Unitree was preparing an IPO on Shanghai’s STAR Market in 2026. Its March application prospectus envisaged around RMB 4.2 billion for investment projects. This was a financing plan, not evidence of a capital inflow already completed at that time.

China’s weight in industrial robotics is already clear: according to the IFR, China accounted for around 54 percent of new industrial robot installations worldwide in 2024. IFR data for 2024. That makes it the largest installation market in this category. The figure alone does not establish leadership across all areas of physical AI or humanoid robotics. An analysis of US-China competition should therefore distinguish digital models, industrial deployment and new robot forms.

The fourth robotic revolution will demand a European response that does not copy Meta. It will need the coupling of generative AI, cobot deployment in the Mittelstand, humanoid robotics in structured environments (care, skilled trades, logistics), and a Robotic & AI Governance infrastructure that builds trust. Germany has the preconditions: social partnership, dual vocational education, the Fraunhofer system, academic research, TÜV, DIN, statutory accident insurance institutions (Berufsgenossenschaften). What is missing is the self-authorisation to position these institutions as robotic governance infrastructure.

Magnifica Humanitas and the European counter-narrative

In my earlier blog post on Magnifica Humanitas, I analysed Pope Leo XIV's encyclical. I also read it as a touchstone for the values that could carry a European AI policy. The core claim of my assessment: the human person is more than her preferences. She is a person, embedded in social relationships, historically grown institutions, culturally shaped educational trajectories, and legal orders. AI governance cannot retreat to the optimisation of individual preferences without damaging this personal dimension.

Zuckerberg's essay is, in this reading, the counter-position. He takes preferences as given, AI as an instrument for preference optimisation, and institutions as external obstacles or flexible negotiation partners (see: Community Compacts). The Magnifica Humanitas position argues the reverse: preferences are shaped, education is the institutional site of that shaping, and AI governance must protect the institutions of education before delivering the tools.

Concretely, for European education policy this means: schools do not need a "personal superintelligence" per pupil. They need a critical engagement with generative AI, teachers competent to shape its use, and examination formats that make the difference between tool use and independent thinking transparent. This connection between technology ethics, application and responsibility has been part of my teaching for many years. The point is not to ban AI. The point is to preserve the institutional setting in which learning takes place as a social practice.

For health care the position means: AI support in diagnostics and treatment planning, yes. But under the condition that the doctor-patient relationship remains protected as a personal relationship. The sick person does not need a "personal superintelligence" that gives her PhD-level advice. She needs a doctor who integrates AI support competently. The difference is not semantic. It is institutional.

For public administration, my position is that AI can support caseworkers, but responsibility and the competent authority must remain traceable. The law does not require a human decision-maker for every decision: section 35a of Germany’s Administrative Procedure Act permits fully automated administrative acts under specified conditions. For me, the decisive question is how citizens can understand decisions, challenge them and obtain effective review. Enthusiasm for efficiency must not obscure that question.

Where Zuckerberg is right

I share several underlying ideas in the essay. First, debate about existential risks should not displace attention to AI’s everyday effects. Second, the concentration of great technical power deserves scrutiny even when justified by good intentions. Third, open models can facilitate independent scrutiny and research. What matters is what is actually accessible: code, weights, documentation or training data. Open weights alone neither enable full reproduction of training nor automatically guarantee safety. Fourth, the municipalities hosting data centres should help shape their development and share in the benefits. Community Compacts offer one approach, whose design should be assessed against the relevant public framework.

One strength of the essay is that Zuckerberg puts his position forward under his own name. He identifies risks, investment plans and commitments, giving us specific statements against which the strategy can be assessed. A public promise is not evidence of delivery. That is why we should read the essay as an invitation to scrutiny and measure later decisions against it.

My agreement ends where the text brackets out the institutional preconditions of a superintelligence distribution. It ends where internal company oversight appears to be a sufficient answer to questions of public responsibility. It ends where Europe is not mentioned. It ends where automation is renamed empowerment without settling accounts with the past fifteen years of Facebook history.

What Europe and Germany should concretely do

First: take the EU AI Act seriously and sharpen its implementation. The provider obligations for general-purpose AI have to be operationalised. The European Commission's AI Office needs resources, technical expertise, and the political backing to act against Meta, OpenAI, Google, and Anthropic when they refuse compliance.

Second: treat German dual vocational education and academic training in robotics and AI as strategic infrastructure. Not as a cost item. In my view, deployment skills deserve as much attention as technological development. The HDBW, the TUM, the Fraunhofer institutes, the vocational academies, and dual vocational training are the institutions that can build robotic deployment competence. They need resources and political recognition.

Third: develop Community Compacts adapted to Europe. In my view, site negotiations should include structural investment in regional value chains, cobot pilots for the Mittelstand, and links between data centre development and vocational education. Bavaria could take a lead. What matters is that states, municipalities, companies and education institutions agree shared goals and make delivery verifiable.

Fourth: position Robotic & AI Governance as a German export good. We have the institutions (TÜV, DIN, VDE, Berufsgenossenschaften). We have the scientific base (Fraunhofer, DFKI, TUM, KIT, RWTH). We have the legal tradition (administrative law, product liability, data protection). We have the European legal bracket (EU AI Act). What is missing is the natural sense that this governance competence is a strategic resource, not an inheritance to be administered. The world market will demand governance standards for autonomous systems in the coming years. Those standards can be German-shaped, if Germany offers them in time.

Fifth: free the debate from its individualistic framing. Superintelligence is not a question of individual empowerment. It is a question of the institutions that decide how empowerment is distributed, controlled, held to account, and shaped. The European answer to Zuckerberg is not a better empowerment promise. It is an institutional self-authorisation with the courage to formulate AI governance as an original civilisational contribution.

What this means for my teaching and practice

Technology ethics has been part of my teaching for many years. At HDBW, I have addressed these questions over numerous semesters. At TUM, I cover them in several of my courses across all MBA programmes and in a focus area. From October 2026, I will also teach a course at MUDT that brings together technology ethics, governance, sustainability and responsible innovation.

I have also addressed current developments and this debate in my keynotes at ABB, DEVELOP and People and Robots in Sicily, with a different emphasis in each talk.

AI is global politics – and Germany needs to take a clearer position

AI is now an issue of global politics. The discussions at the United Nations, including the Global Dialogue on AI Governance, make that clear. They address questions that go far beyond technical performance: Who gets access? Who sets the rules? Who bears responsibility? And how can people influence developments that change their everyday lives? UN account of the Global Dialogue.

These questions will stay with us for years to come. I have yet to see a clear, publicly visible German position. Germany should contribute its experience in technology ethics, industrial applications and public participation far more decisively to this international debate.

For me, AI governance therefore needs a scientific foundation and participatory technology dialogue. I will explore what the UN report can contribute and what this means for Germany in a forthcoming article on that report.

My recommendation to everyone taking a position in this debate: read Zuckerberg's essay. Literally, not in summary. Note the omissions. Note the rhetoric. Then formulate the European position - not as a reaction, but as a stand-alone civilisational statement. We have the institutions. We have the intellectual tradition. We have the legal bracket. What we lack is the natural sense that this equipment is a strategic resource and not an inheritance we merely manage.

The future is not "for everyone". It belongs to those who refuse to let anyone else answer the question about the institutions of their future for them.

FAQ on Zuckerberg's "The Future is for Everyone"

FAQ on Robotic & AI Governance and the EU AI Act

FAQ on the 4 Robotic Revolutions and Magnifica Humanitas

FAQ on European AI policy and German institutions

Sources

• Zuckerberg, Mark (2026): “The Future is for Everyone.” Meta, 10 August 2026. Original essay.
• Claburn, Thomas (2026): “The future is for billionaires – the rest of us will get open weight AI models, maybe.” The Register, 10 August 2026. Original commentary.
• Koebler, Jason (2026): Commentary on the Zuckerberg essay. 404 Media, 10 August 2026. Original article (headline and date publicly accessible).
• ETC Journal (2026): “Zuckerberg Got the Question Right, but Answers Are Up for Grabs.” 10 August 2026. Original article.
• Bösl, Dominik B. O. & Bode, Martina (2017): "Roboethics and Robotic Governance - A Literature Review and Research Agenda." In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N. & Cardeira, C. (eds.): ROBOT 2017: Third Iberian Robotics Conference. Advances in Intelligent Systems and Computing 693, Springer, Cham. DOI: 10.1007/978-3-319-70833-1_12
• Bösl, Dominik B. O. & Liepert, Bernd (2016): "4 Robotic Revolutions - Proposing a Holistic Phase Model Describing Future Disruptions in the Evolution of Robotics and Automation and the Rise of a New Generation 'R' of Robotic Natives." In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, pp. 1262-1267. DOI: 10.1109/IROS.2016.7759209
• European Union (2024): Regulation (EU) 2024/1689 of the European Parliament and of the Council - "EU AI Act". In force since 1 August 2024, with phased application dates.
• Verordnung / Regulation (EU) 2026/1744: Digital Omnibus on AI, 8 July 2026; Official Journal 24 July 2026.
• International Federation of Robotics (2025): World Robotics 2025. Executive Summary.
• United Nations (2026): From AI to killer robots: UN chief issues urgent governance call, 7 July 2026.
• LeCun, Yann (2025): Own announcement of departure from Meta, November 2025.
• Meta (2025/2026): Llama 4 (5 April 2025); Muse Spark / Meta Superintelligence Labs (8 April 2026).
• European Commission: Guidelines on obligations for General-Purpose AI providers.
• US District Court, Northern District of California: Kadrey v. Meta, order of 25 June 2025.
• SNE / SGDL / SNAC (2025): Announcement of claim against Meta, March 2025.
• Unitree (2026): STAR Market application prospectus, March 2026.
• Oversight Board: Our work (content moderation).
• § 35a VwVfG: Fully automated administrative acts.
• Bösl, Dominik (2026): "Magnifica Humanitas: The Encyclical and AI Governance - An Assessment." boesl.org, 16 June 2026. boesl.org
• Bösl, Dominik (2026): "Four Robotic Revolutions: 10 Years On." boesl.org, 25 July 2026. boesl.org
• Bösl, Dominik (2026): "EU AI Act August 2026: What Really Takes Effect." boesl.org, 23 June 2026. boesl.org

About the Author

Since 1 October 2026, Prof. Dominik Boesl has been Professor and Chair of Applied Robotics and Intelligent Automation (ARIA) and Founding Director of the Center for Robotics at the Munich University of Digital Technologies & Applied Sciences (MUDT). Until September 2026, he was a professor at the Hochschule der Bayerischen Wirtschaft (HDBW). He is also an Adjunct Professor at the Technical University of Munich (TUM) and CEO of Innomancer GmbH. His work connects applied robotics with Robotic & AI Governance and the responsible deployment of intelligent machines.

Selected publications:

• "4 Robotic Revolutions – Proposing a Holistic Phase Model …" (IEEE/RSJ IROS, 2016; DOI 10.1109/IROS.2016.7759209)
• "Roboethics and Robotic Governance – A Literature Review and Research Agenda" (Springer, 2017; DOI 10.1007/978-3-319-70833-1_12)
• Bösl, D. B. O. (2019): Predicting the Future of Robotics and Making It Matter for Industry [Industry Activities]. IEEE Robotics & Automation Magazine, 26(4), 128–130.
• Mai, V. et al., including Bösl, D. B. O. (2022): The Role of Robotics in Achieving the United Nations Sustainable Development Goals – The Experts’ Meeting at the 2021 IEEE/RSJ IROS Workshop [Industry Activities]. IEEE Robotics & Automation Magazine, 29(1). DOI: 10.1109/MRA.2022.3143409.
• Boesl, D. B. O.; Bode, M.; Liepert, B.; Greisel, S. (2017): Structured Megatrends Research as Foundation for Future-Oriented Research-Planning and R&D Roadmapping in Robotics. CTCEEC, Mysore. DOI: 10.1109/CTCEEC.2017.8455126.
• Further publications at boesl.org/publications

Contact: dominik@boesl.org
LinkedIn: linkedin.com/in/boesl
Website: boesl.org

On the sense and nonsense of building humanoid, bipedal robots.

You might be asking yourself: Why do we even need humanoid, two-legged robots? Aren’t they just toys for science fiction fans or dangerous fantasies of power-hungry militaries? What’s the point of creating machines that look and act like us? Are they an asset to society – or a threat?

In my opinion, humanoid robots are more than curiosities or potential dangers. They could support us in many areas of life, especially where humans reach their limits. For example, they can assist in disaster zones by searching for survivors, clearing debris, or delivering supplies. They could also be used in care work or healthcare, supporting elderly or ill people, keeping them company, or motivating them. They might even play a role in education or culture – teaching us new things, entertaining or inspiring us. They can open up new perspectives, help us develop new skills, or present us with new challenges.

Humanoid robots have the advantage of navigating human environments more effectively than other robot forms. They can climb stairs, open doors, use tools, or manipulate objects designed for humans. They’re also better at interacting with people – using facial expressions, gestures, or language we understand and respond to. They can meet us as partners, colleagues, or friends – not just as servants or slaves. They can show us respect, build trust, or even express empathy – not just obedience or fear.

Of course, there are challenges and risks associated with developing and deploying humanoid robots. We need to ask how we can design and use them in ethically, legally, and socially responsible ways. We also need to recognize that they will never truly replace or surpass humans – they can only complement or extend what we do. We must be clear about what defines us as humans and what we expect and demand from robots. And we need to consider how to protect our identity, values, and rights as we learn to coexist with them.

I believe we have the opportunity to turn humanoid robots into a valuable, sustainable support technology for humanity. But to do that, we need to take responsibility now and actively shape this innovation. We need to stay informed, engage in the conversation, and take part in deciding how we want to live alongside our artificial counterparts. We also need to prepare ourselves to adapt to the changes they will bring. And we must remain open to the possibilities they offer – to better understand and improve ourselves and the world we live in. I explain how I interpret this change in my retrospective on the four robotic revolutions.

Want to dive deeper into the question of whether humanoid robots make sense – or not? Then feel free to check out my article in Schaeffler’s corporate magazine tomorrow:

Quo vadis, Robotics? – tomorrow (schaeffler-tomorrow.de)
[Click the image to read the full article – in German]