Language machines, robotics and setting the course for a human future:

A critical examination with Simanowski and Schulte-Huermann

The world is increasingly permeated by algorithms and autonomous systems. Robots populate our factories and voice machines shape our communication. But while many celebrate efficiency and progress, an uncomfortable question arises: What does this development mean for us as humans, for our understanding of knowledge, creativity and identity? The media philosopher Roberto Simanowski has adopted a critical perspective in his works, particularly in "Language Machines", which forces us to take a closer look.

These philosophical warnings were taken up early on by practitioners such as Markus Schulte-Huermann. As early as 2023, when the general public could barely imagine the full force of generative AI, he asked the crucial question: "The future with AI: do we need to set the course now?" [[DOCREF:The_future_with_AI_must_we_set_the_course_now.pdf]]. His analysis underscores the urgency of Simanowski's concerns from a business and societal perspective. It is a warning against uncritical acceptance, which we must not ignore in the context of the rapid development of robotics and artificial intelligence.

The market for humanoid robots may grow to over $38 billion by 2035, with giants such as Tesla, Agility Robotics and Figure AI in the US, as well as NEURA Robotics in Germany and PAL Robotics in Spain, driving development [[DOCREF:humanoid_report_2026_v19-jwxa0v.pdf], [DOCREF:Lister der Robotoic-Hersteller.pdf], [DOCREF:portal-memory-humanoide roboter Hersteller europa-2026-01-13.pdf]].

Current developments in robotics (June 2026) underpin this urgency: Humanoid robots are rapidly advancing into everyday life. China is massively promoting their use in factories and has issued national guidelines to turn the sector into a new growth engine by 2027. NVIDIA has presented Isaac GR00T, an open reference design that is intended to accelerate commercialization. The cost of humanoid robots is falling dramatically (Chinese models are sometimes under USD 10,000) and they are increasingly being used in factories, warehouses and hospitals. There are reports of robots that can work autonomous 8-hour shifts or even run a half marathon. While Europe plays an important role as a supplier of sensors, drives and chips, large investments in companies such as Standard Bots and NEURA Robotics show the enormous growth potential. In parallel, research in AI and machine learning is progressing, with new open-source datasets to reduce the need for training data, concepts such as "Physical AI" and a focus on "Uncertainty Representation" in neural networks [[DOCREF:_user_Aktuelle_Entwicklungen_Robotik_Juni_2026.md]].

However, these figures and advances mask the real challenge: the increasing presence of machine-generated content and actions. When robots operate in complex environments, they encounter epistemic uncertainty - gaps in knowledge that they are unaware of [[DOCREF:A_Review_of_Uncertainty_Representation_a.pdf]]. But the deeper philosophical question that Simanowski raises, confirming Schulte-Huermann's early warnings, is: what happens to our epistemic certainty when we rely on systems that themselves do not know what they do not know, and whose "knowledge" is often only a statistical probability?

Philosophical and practical areas of tension: A dialectical consideration according to Simanowski and Schulte-Huermann

The discussion about AI and robotics is a battlefield of ideas. Simanowski forces us to critically question the supposed opportunities and to recognize the risks in their full philosophical scope. Schulte-Huermann's article from 2023 provides concrete, early warnings from the field.

Knodge.eu: A European anchor in the epistemic crisis?

Amidst these philosophical challenges and practical warnings, Knodge.eu offers an approach that attempts to directly address some of the issues raised by Simanowski and echo Schulte-Huermann's calls. It is not a universal solution to all philosophical dilemmas, but it is a pragmatic step towards a more responsible use of AI:

• Precision versus hallucination: Knodge.eu relies on the Retrieval Augmented Generation (RAG) principle to provide precise and valid answers based on the user's own, verified data [[DOCREF:2026-01-27_09-41.md]]. This is a direct counter to the "greed is cool" mentality of knowledge by prioritizing quality and traceability over mere generativity. It reduces the epistemic uncertainty created by unreliable AI outputs and supports the integrity of knowledge that both Simanowski and Schulte-Huermann call for.
  Controlled action instead of blind automation: The Science Context Protocol (SCP) enables Knodge.eu to not only interpret data, but also trigger actions - for example, controlling machines or robots [[DOCREF:2026-01-27_09-41.md]]. When epistemic uncertainty is high, SCP can retrieve relevant protocols or expert knowledge to enable the robot to make an informed decision. This promotes a controlled, knowledge-based interaction and prevents an unreflective delegation of judgments to the machine [[DOCREF:2512.24189v1.pdf]].
  Data protection as the foundation of trust and protection of individuality: With an isolated, EU-based infrastructure, zero logging and zero training, Knodge.eu ensures the highest data protection standards [[DOCREF:2026-01-27_09-41.md]]. This is a decisive step against the opacity of many language engines and creates a trustworthy environment that protects the integrity of the data and thus the knowledge. By leaving data sovereignty with the user, it also indirectly supports the development of "individually trained, personality-tailored AI systems", as called for by Schulte-Huermann, without compromising privacy. The Secure Copy Protocol (SCP) also ensures secure and encrypted data transmission and software deployments for robotics applications [[DOCREF:portal-memory-scp und robotic-2026-01-13.pdf], [DOCREF:wie-kann-meta-ros-und-scp-sich_2026-02-01.md]].

The future of robotics and AI will not only be determined by technological progress, but also by our ability to understand the philosophical implications and set ethical guardrails. Knodge.eu offers an approach that seeks to harness the benefits of AI without compromising the integrity of knowledge and the autonomy of humans. It is an attempt to shape the "language machines" not as masters, but as responsible tools, and to set the course for a human future with AI.

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