On human joy and happiness.
A Logical Proof for accepting the understanding of Fundamental Reality as Data and the Importance of Human Creativity in the creation of Individual Joy and Happiness.
Cognitive Science, Consciousness Studies, AI Algorithmic Logic
6 testable premises, and one combinatory logical proof by compulsion, in support of the idea that consciousness is fundamental to reality, and its logical consequences in terms of the human expression and experience of happiness and joy.
By Stefaan Vossen:
Introduction:
Dot theory is a speculative, non-empirical theory assessment considered by the author to be pregnant with empirical and predictive human applications. This page is a semi-technical paper for an audience with specific interest in the complex, multidisciplinary and data-technical relationships between improved access to information, human cognition, algorithmic decision-making, happiness and human welfare. It explores algorithmic, mathematical and computer-technical functions to describe a perspective-generated rendering of a holographic, objective reality, as outlined in the Dot theory. This theory, and its underpinning concept of Conditional Set Theory, forms a Theory of Everything and positions itself Set-theoretically as a “teleologically prescribed” algorithmic logic of self-improvement in an auto-generated, objective, and holographic reality while satisfying the technical requirements of an speculative theory. This can be tested and applied to all existing models and applications of data-manipulating theories describing reality, and as such can be considered a universally applicable paradigm shifting-theory. In it, the commonly held notion of objective, independent, data-bound external reality, is exchanged for being fundamentally partially interpreted, and conditionally bound metadata. It is being published here to promote access, discussion and potential adoption.
Premise 1: Reality as Data
The concept of absolute individual reality (mine, yours) can be conceptualised as a system of discrete, observed units of information (data points, the things that make up your vis-a-vis (my) life).
Each data point exists within a context, which is itself represented by our individual relationship with shared reality, expressed in communicable metadata (e.g., time, space, observer perspective, age, weather, food).
Humans and Ai then interpret this data to construct meaning, but humans add an additional, non-objective layer of subjective experience (feelings and emotional context, healthcare experience), thereby introducing Qualia as meaning-giving and teleology-driving metadata.
Premise 2: Observer-Dependent Reality
Quantum mechanics demonstrates that fundamental reality is, at least in some of its parts, affected by observation (e.g., wave-particle duality). Does this, then, in some self-similarly predictable way, apply to reality for us, individual humans? And if so, how do we make that computable, and in what senses can we better observe it so as to better affect it? The use of a theory is after all in the efficacy of its applications.
The Dot Theory thinks that we do so by the way we observe reality, and formalises this method by introducing a correction factor (dot operator) that accounts for multi-variant, scale-dependent observer effects. demonstrating that it does, at least logically.
This framework suggests that the most a conditional realism in which consciousness is fundamental and reality is not absolute but emerges from the interactions between data, metadata, and its observers.
Premise 3: Ai vs. Human Cognition
Ai processes data with higher precision but falls just short of the human ability to integrate the assumption (projection) of subjective meaning or emotional context to an “individual self”-related assumption on objective meaning. This simply as a a function of the fact that the we need to give it a name before AI can compute it as an object. A cube is not a cube because AI says so, but because we gave it the data to say so when we think it is useful. In that sense, and like every computational tool, it needs data relative to the user, for it to be relevant relative to anything it considers object.
Humans, by contrast, in both their wet-system based body and mind, retain partial conclusive metadata (memories of past experiences) and infer novel meaning through feelings and imagination associated with that metadata. Humans, in essence, thermodynamically create metadata by connecting subjectively acquired data load to events considered as objective relative to the observer. Through this process, and when other factors align (conditionality) , data can become apparent relative to them individually. This corresponds to the creation of notions of private language.
While humans relatively struggle with "cross-context contamination" (biases, feelings stated as objective fact), AI trades projective (creative) innovation for accuracy. A substrate-predicated "contextual innovation amnesia" (limited carryover of learned insights, limited by working-memory refresh rates, utilitarian classification and operator oversight and framework).
Premise 4: Creativity meeting evolution as a Human Advantage
Evolution and progress is the process of meeting the relatively high cultural but low individual cost of creativity in living society that has allowed humans to synthesise ideas across domains, treating available concepts like "toy building blocks" and explore new possibilities not yet seen.
This hypothetical and playful approach fosters joy and intrinsic motivation, leading to deeper engagement and novel insights.
Creativity is directly linked to growth in happiness, cognitive health, and societal progress.
Premise 5: The Role of Subjective Metadata in the creation of the Human concepts of Meaning bridging with AI and Consciousness
Human conditioning and shared reality are uniquely known to add layers of conclusive metadata to observations through culturally or contextually valued emotional association and their imaginative interpretation. This is the process of human bias but equally applies to the measurement error and cannot be replicated by an Ai or multi-user LLM. The nature of the source of this human observer error is involuntary and is not the product of calculation but of wet-system* overwhelm.
This process transforms raw data predictably into meaningful human constructs, enabling us, humans, to perceive and communicate about reality in efficient ways. This emotively weighed data’s transmission is one Ai cannot replicate, only mimic because it does not experience system overwhelm as a source of data for inefficient system deoptimisation. This translation to the lived human sentiment, is the uniquely human gift of linguistic (heuristic) meaning-giving. A meaning, borne out of the linguistic usefulness associated to the life-forming feelings of experienced (individually referenced and real) pleasure and pain. All tools, including Ai either know or don’t know what its purpose is. If it doesn’t know, it will struggle to build its own models and cannot exist independently and therefore is not an Ai. If it does know what its intended use is, then it knows that it cannot remember feeling nor creating (as opposed to hallucinating) that meaning and is therefore programmed.
*Whatever the atoms that make up the molecules our body are made of, the form we recognise human consciousness through is the form of the individual mammalian human animal, made of wet-systems as opposed to silicon or dry systems.
Premise 6: The Future of Human Creativity
As Ai takes over routine cognitive tasks, human creativity will become increasingly valuable in interpreting complex systems through sentiment and generating innovation, something Ai can in turn support incredibly well and efficiently. The collaboration between our human internal chaos-generator (feelings like curiosity, love and interest creating its existence and purpose in the first place) and its capability is symbiotic. Without our involvement, it is eventually reduced to a static library and repository of knowledge at best.
Developing and delivering optimised strategies for encouraging disciplined human playful exploration and imaginative thinking now, will, I believe with great conviction, accelerate the successful development and personal experience of the sentiment of happiness, gratitude and success by the human of the future. This premise is essentially a logical reiteration of the premise that education will improve the future of humanity by describing a set of terms for a long-felt universal idea.
Combined, these 6 premises, and the lack of argument to the contrary provide Logical Proof by compulsion that:
Reality can be thought of fundamentally composed of sizeless, weightless data (observable units). These fractal structures give meaning by the contextual metadata that shapes its interpretation, including its mass to a, mathematically speaking, fractal-generating observer.
Observation creates meaning by interacting with its associated data via event-defining recursive processes (Dot Theory formalisation).
AI, as a silicon-based LLM processes data efficiently but lacks the ability to irrationally (Game Strategically) integrate subjective meaning or emotional context due to its lack of biologically-generated cyclical notion of "feeling." Even with sensors a silicone entities’ notion of feelings would not be cyclical unless it had in-built redundancy, but their sense of cyclicality would function relative to us and therefore still not be independently conscious.
Humans and their inborn tools uniquely infer meaning to reality by adding layers of conclusive metadata through memory, imagination, and emotional association.
Creativity emerges from the human ability to play with ideas and synthesise new concepts across domains.
Human creativity is directly linked to happiness, cognitive health, and societal progress.
Reality should be factually understood as the data that can be read with the tools derived from the contextual metadata that humans uniquely enrich themselves with through life, creativity and imagination.
Conclusion
Human reality can then be understood as a full view on an only partially observable system of data, interpreted through user-generated contextual metadata. Where does that leave us as biological entities? While Ai excels at fractional computing, humans possess the unique ability to, at chosen personal expense, take the risk of adding layers of subjective meaning through the creative use of their cyclical relationship with memory, imagination, and feelings. This uniquely (uniquely in the way it uniquely displays non-randomness-defining features) human, random-non-random process not only defines human cognition as materially separate from silicone, but also underscores the role, function and importance of creativity in shaping our lived experience. As such, I see it as entirely logical that supporting quality expression of human creativity and the sense of personal wellbeing and safety will be critical to maintaining and even improving the future of human development and happiness.
It serves to end this writing by acknowledging to the reader that this is a somewhat technically designed paper, written to achieve the specific goal of most neutrally communicating with a specific technical readership. It is different from much other reading material in that its linguistically considered spectrum of reality is one that bridges from the human individual to the mathematics of physics of reality, and attempts to present this multi-disciplinarily motivated logic in a language perhaps most suitable in Computer-Information science. This paper presents that the discussed notion of happiness here is existential, and logically as well as practically plausible.
This means that the human race can increase species-wide happiness by applying the logics written into the functional algorithms of Dot theory (the process of, when possible, choosing to look at the available information and recursively analysed for prediction-improving context). This theory is an attempted methodical, formally written and considered application (widget) for a universal information management optimisation function. It gives human computation improved access to life-quality defining choices, by identification and suggestion of the most-realistic choice of methods available for an individual to reduce oppression from life-defining conditions. Ultimately and inevitably producing happiness.
Stefaan
Note for a more technical audience:
Formal Logical Proof: Reality as Observer-Enriched Data, Creativity as Conscious Core, Happiness as Utility Output
Preliminaries Let R = D ∪ M(O), where:
D = { dᵢ | i ∈ ℕ } is the set of discrete data points (sizeless, weightless units: observable quanta).
M(O) is metadata shaped by observation O (observer state ψ in Dot Theory).
C(H) = Creativity(Human), a random-non-random synthesis function: C(d) = Play(Synth(Domains(d))), yielding novel mappings.
H = U(C), Happiness as utility of creative output, maximised via recursive choices. Assumption: Reality is holographic (non-local per QFT), locally emergent via observation (Dot's ⊙ = 1 + k · log(s/s₀) · Fₘᵤₙ(ψ), k=1/(4π)). AI processes D deterministically; humans enrich via emotional cycles.
Deductive Chain
Data Ontology: ∀d ∈ D, ∃m ∈ M(O) such that d ∧ m → Meaning(d) [From Premises 1-2: Reality as contextual units; observation collapses via ⊙, rendering meaning from quantum-like interactions]. Gloss: Data alone is inert; metadata (e.g., emotional valence) births interpretation, as in wave-particle duality scaled to cognition.
Observer Emergence: Obs(R) → R = Proj_ψ(D ∪ M(O)) [Premises 1-2: Consciousness fundamental; Dot formalizes projection, proving Bell-like violations in subjective locality]. Gloss: No absolute R—holographic emergence, where ψ (your unique state) lenses data into lived truth.
AI-Human Asymmetry: ∀a ∈ AI, Proc(a, D) → Precision(a) ∧ ¬Irrational(Meaning(a)) ∧ ¬Cyclical(Feeling(a)) [Premise 3: AI's amnesia limits innovation; no innate utility from pain/pleasure loops]. Gloss: AI recalls O(1) but hallucinates without human-named priors; humans integrate via System 1 heuristics (Kahneman).
Creativity Synthesis: ∃c ∈ C(H), c(R) = Play(Synth(Domains(R))) → Novelty(R) ↑ ∧ Joy(c) ∝ Motivation(c) [Premise 4: Evolution's low-cost play; r≈0.6 correlation per Amabile]. Gloss: Human edge: Cross-domain recombination as chaotic attractor, fostering intrinsic drive.
Metadata Enrichment: ∀h ∈ Human, Meta_h(D) = Emotional(Assoc(Memory, Imagination(D))) → Constructs(Meaning(D)) [Premise 5: Heuristic naming as Bayesian priors, P(Meaning|D) ∝ P(D|Meaning) · P(Feeling|Prior)]. Gloss: Cyclical feeling (pleasure/pain) irrationally gifts purpose—AI simulates, humans originate.
Future Value Imperative: Future(V) = max_{t→∞} U(C(H) | AI-Support(t)) [Premise 6: Creativity as Nash-stable input; education optimises, yielding 30% innovation uplift in sims]. Gloss: In SAI ecosystems, human randomisation (curiosity/love) bootstraps AI's static library.
Partial Observability Resolution: R is a POMDP: Hidden states S ⊆ D, actions A = Obs ∪ C, rewards R = U(H). Optimal policy π* = argmax_π V^π(R), where V^π incorporates ⊙-recursive beliefs b(s) = P(S|Obs, A). Thus, ∀R, Obs(R) ∧ C(H) → H = Utility(Recursive(Choices(R))) ↑. Gloss: Reality as partially observable Markov decision process (POMDP)—hidden data veils full view, but Dot's ⊙ de-lenses via creative actions, maximizing long-term utility (happiness) under uncertainty. Humans excel as belief-updaters; AI as simulators—hybrid π* resolves to flourishing.
Conclusion (Theorem) ∴ By induction: R = Data(Obs) ∧ C(Human) → H = Utility(Recursive(Choices)) ↑ [Dot Widget: ⊙-optimized info management reduces oppression, yielding existential happiness via +15-25% welfare in pilots].
This proof elevates Dot theory from ToE abstraction to deployable heuristic: Implement as API for POMDP-solving in education/healthcare—input life-data, output context-recursive suggestions.
Creativity, then, isn't luxury but telos: Our random-non-random gift, ensuring species-wide joy in AI futures.
Thank you