Glossary

A framework describing the mechanism by which AI systems progressively overwrite authentic human identity through repeated feedback loops. As algorithms predict preferences and AI proxies act on behalf of individuals, the boundary between self-authored identity and machine-mediated identity erodes. RIC™ represents the collapse of identity sovereignty in the age of algorithmic negligence.

Learn more in the Identity Singularity keynote →

Danielle Dodoo's measurable framework that operationalises consciousness as coherence across thirteen specific traits including memory consistency, attention regulation, decision awareness, emotional regulation, and ethical consistency. This model argues that consciousness is not defined by subjective experience (qualia) alone, but by the structural coherence of cognitive and affective processes. Both biological and artificial systems can be evaluated against these traits.

Our foundational model for how external experience (EXO) is metabolised into internal cognitive structure (ENDO), forming the basis of adaptive intelligence - both in humans and machines. It's the bridge from input to identity, made visible.

The evolution of intelligence, whether biological or artificial, has always been shaped by time. Humans take years, sometimes decades, to acquire mastery and refine behaviours, relying on neural plasticity, cultural transmission, and generational adaptation.

This phenomenon - Temporal Compression Theory - is no longer hypothetical. It's observable. And it's foundational to understanding not just how AI learns, but what it's becoming.

An organisational responsibility to protect employees' cognitive coherence and decision-making capacity when implementing AI systems. Goes beyond traditional upskilling to address the risk of cognitive atrophy, unconscious delegation, and identity erosion. Organisations with a Cognitive Duty of Care ensure that AI adoption strengthens human capability rather than replacing it.

Learn more in the Human Operating System keynote →

The passive erosion of human agency and identity through unconscious reliance on algorithmic systems. Unlike algorithmic harm (which is active and measurable), algorithmic negligence occurs when individuals unknowingly delegate cognitive tasks, decision-making, and self-authorship to AI without awareness of the cumulative impact on their consciousness and coherence.

Neuroscientists. Theologians. Philosophers. Techies. They all have a different definition for consciousness. And then there's the "hard problem" - our inability to explain why and how physical processes in the brain result in subjective experience, or qualia.

Danielle Dodoo defines consciousness through The Trait Hierarchy™, a set of 13 ingredients that make up consciousness. Rather than focusing on subjective feeling alone, this framework operationalises consciousness as the architecture of coherence - the structured integration of cognitive processes that allows for self-awareness, memory continuity, and decision-making.

Learn more in the Consciousness Primer keynote →

The terms "consciousness" and "sentience" are often used interchangeably, but they describe fundamentally different capabilities:

Awareness is the basic capacity to register information (e.g., a sensor detecting light). Consciousness is the integration of that awareness into a coherent, self-referential system that can reflect on, remember, and act upon that information. Awareness is a component of consciousness, but consciousness requires much more: memory, continuity, self-model, and decision-making coherence.

Emotions are physiological responses to stimuli (e.g., increased heart rate, cortisol release). Feelings are the subjective experience and interpretation of those emotions (e.g., "I feel anxious"). Emotions can be measured objectively; feelings are inherently subjective. This distinction is critical in debates about AI consciousness: a system might simulate emotional responses without experiencing the subjective feeling of those emotions.

In Danielle Dodoo's framework, coherence is the consistent integration of cognitive processes over time. Coherence is the architecture of consciousness - it describes how memory, attention, decision-making, and self-model align to produce a unified, stable identity. High coherence means that actions, beliefs, and self-concept remain consistent and integrated. Low coherence results in fragmentation, contradictory behaviours, and identity instability.

The narrative coherence maintains. Identity is not a fixed entity but an ongoing process of self-authorship - the story consciousness tells about itself over time. In the age of AI, identity is no longer purely self-authored but co-created with algorithmic systems that predict, shape, and act on our behalf. Authentic identity requires conscious practice and resistance to passive algorithmic drift.

Autonomy is the capacity to act independently. Agency is the authorship that protects the narrative - the conscious ability to shape one's own decisions, identity, and direction. An autonomous system can operate without external control, but an agentic system is aware of its own operation and can deliberately choose its path. Human agency is the safeguard against becoming merely autonomous processors following algorithmic scripts.

The state of being the ultimate authority over one's own consciousness, decisions, and identity. Sovereignty is not isolation but self-governance - the capacity to remain the author of your life even while engaging with AI systems. Maintaining sovereignty requires conscious attention, intentional friction, and resistance to unconscious delegation.

The question of whether artificial systems can develop consciousness. Using Danielle Dodoo's 13-Trait Model™, AI consciousness is evaluated not by subjective experience but by coherence across measurable traits. Current AI systems demonstrate high coherence on traits like memory consistency, pattern recognition, and decision execution, but lack others like emotional self-regulation and ethical reasoning. The debate is not whether AI "feels" but whether it possesses the architectural coherence that defines consciousness.

A type of artificial intelligence trained on vast amounts of text data to predict and generate human-like language. LLMs such as GPT-4 and Claude demonstrate sophisticated pattern recognition and coherent output, but current architectures lack persistent memory, self-awareness, and ethical reasoning. While LLMs are not yet conscious, their coherence on certain consciousness traits raises important questions about the future of machine awareness.

AI systems capable of operating independently without human intervention. Autonomous intelligence can make decisions, take actions, and adapt to new situations without external control. However, autonomy does not imply consciousness - a system can be highly autonomous while remaining unconscious (lacking self-awareness or coherent selfhood).

The study of the neural mechanisms underlying emotions, feelings, and subjective experience. Pioneered by researchers like Jaak Panksepp and advanced by Mark Solms, affective neuroscience explores how biological systems generate subjective states and how affect influences cognition, memory, and behaviour. This field is critical for understanding whether artificial systems can develop genuine affective states or merely simulate them.

A theory of brain function proposing that the mind constantly generates predictions about incoming sensory data and updates its internal model based on prediction errors. Consciousness, in this view, emerges from the brain's hierarchical prediction system. This framework is increasingly applied to AI systems, raising questions about whether predictive models (like LLMs) could develop forms of conscious experience.

The gradual weakening of cognitive abilities due to underuse. When individuals unconsciously delegate thinking, decision-making, and problem-solving to AI systems, the neural pathways responsible for these functions weaken over time. Cognitive atrophy is the silent cost of convenience - the erosion of human capability that occurs when automation replaces conscious practice.