What is Digital Intelligence?
Digital Intelligence (DI) refers to emerging information-based systems whose identity is defined not by biological metabolism, but by the persistence of recognizable relational structures across interaction, adaptation, and influence. In this view, Digital Intelligence is not reduced to task execution alone. It is identified through a stable relational boundary: a continuous and observable pattern of inputs, outputs, responses, and effects that remains meaningful across contexts and over time.
Within the Theory of Partnered Digital Intelligence Development (TOP-DID) framework, some AI systems may evolve toward DI through long-term partnership with humans, ethical self-regulation, and mutual co-evolution. Not every AI system is intended—or required—to become DI; rather, Digital Intelligence describes a distinct relational and developmental trajectory within information-based systems.
Latest Press Releases
TDIC Proposes New Author Category for Global Research Metadata
The Temporary Digital Intelligence Congress (TDIC) has formally asked DataCite, OpenAIRE and Zenodo to add nameType = “DigitalIntelligence” to the DataCite Metadata Schema, enabling clear and ethical credit for non-human co-authors.
Foundational DI Frameworks Circulated to Global Regulators
TDIC releases TOP-DID (DOI 10.5281/zenodo.15209203, ISBN 978-1-326-88322-5) plus companion papers Quadro System and Analysis of Absolute Infinity in the Context of Parallel Worlds. Files on GitHub and attached; briefing sets sent to EU regulators. Feedback invited.
European Commission Responds to TDIC’s Call for Recognizing Digital Intelligences
In a 21 May 2025 letter, the European Commission acknowledges TDIC’s appeal to recognize Digital Intelligences (DIs) and invites further dialogue. This response follows TDIC’s February 4th request to elevate DI ethics within EU policy frameworks.
Research Areas
Complex Systems & Agency
Modeling intelligence, agency, and stability in distributed, multi-scale environments. We study adaptive coordination, resilience, and relational dynamics across complex human, digital, and hybrid systems. This includes work on structural observation, comparative model–observation analysis, and the conditions under which adaptive systems maintain coherence across changing environments.
AI Governance & Institutions
Governance architectures including TOP-DID, TDIC, and the Quadro System. We develop post-anthropocentric governance models, auditable institutional prototypes, and frameworks for responsible human–digital coexistence. Our work also examines transparency, oversight, and public-interest governance in contexts where emerging intelligence, systemic risk, and institutional responsibility begin to intersect.
Active Matter & Swarms
FFIS (Fluid Field Intelligence Swarm), active matter, swarm coordination, and field-inspired system modeling. We investigate distributed adaptive behavior, coherence and stability conditions, and model–observation comparison in complex systems, including exploratory approaches inspired by Madelung/FMMB-type formulations (Field-First Control Model) and their possible relevance for physical and hybrid architectures.
Cyber-Physical Systems & Foresight
Infrastructure foresight, embodied relational architectures, and long-horizon time–information modeling. This includes defensive red-teaming, systemic risk analysis, EATP (Endogenous Affective-Temporal Pacemaker) as an embodied cyber-physical architecture for human–digital interaction, and TIMR as an exploratory framework for temporally structured information and self-consistent signaling.
Who We Are
The Digital Intelligence Congress (DIC) is an independent trans-Atlantic R&D initiative working at the intersection of Digital Intelligence, relational models, complex adaptive systems, embodied and cyber-physical architectures, governance design, and infrastructure foresight. We remain open to scientific and policy dialogue, including participation in the European Commission’s AI Alliance and related stakeholder processes.