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The rapid evolution of AI is unlocking significant advancements that are introducing equally substantial risks. Intellectual property rights are getting more difficult to protect as algorithms use, replicate, and transform IP-protected materials without proper oversight or accountability. The centralization of powerful AI technologies in the hands of a few corporations heightens concerns about data privacy and mass surveillance. As users become more dependent on AI solutions, in-depth data collection and user profiling will become all-to-easy to do and its outcomes are likely extremely invasive.
Another particularly troubling risk with generative AI is the acceleration of production and proliferation of illegal content, including the worst kind such as Child Sexual Abuse Material (CSAM). We are already witnessing the rise of convincingly fabricated “deep fakes” and other synthetic media which in the future could rewrite historical events, distort public records and undermine collective trust.
We stand for freedom, democracy, and the power of collaboration. Our mission is to fight against harmful content and the risks of AI by promoting technology that serves the greater good of humanity.
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Umanitek’s first product is an AI agent, umanitek Guardian, that uses the Decentralized Knowledge Graph (DKG), a decentralized, trusted network for...
Umanitek AG, a Swiss-based AI company combating harmful content and the risks of artificial intelligence, has formed a world class...
Chris Rynning, Chairman of Umanitek joined OriginTrail founders at On Trac(k) podcast. They discussed the vision of umanitek and the...
We build, invest, and partner to use existing and upcoming technologies to reduce internet harm. Without umanitek, these technologies are frequently kept in walled gardens of different platforms. This leads to:
Harm continues to spread online due to restricted access to effective solutions.
Tech companies avoid sharing harmful content data due to competition concerns and lack of trusted data exchange infrastructure.
Lack of trusted middleware infrastructure for complementing Generative AI to ground it with real world data.
Companies hold valuable technology that remains under-monetized.
Introducing data ownership, data verifiability and censorship-free connectivity to knowledge graphs. Allowing the creation of decentralized data structures where each entity remains in control of its data while being connected via a public middleware. Notable example: OriginTrail
Human-centric AI leveraging powerful technologies with data management based on a decentralized knowledge graph.
Knowledge graphs are structured data networks that capture domain knowledge in a clear, symbolic form. By making facts explicit, they enable logical reasoning, semantic inference, and intuitive knowledge discovery. Notable examples: social graphs (Meta), search engines (Google), content graphs (Amazon, Netflix)
Highly performant systems which remain in centralized control of big corporations. Their solutions remain a black box with little regard to data privacy and user control. Notable example: Skynet (so far)
