On dreams and their data-analytical value
Abstract
This data-technical essay is an Information Theory-based exploration of the potential informational value of human dreams according to a Dot-theoretical universe. In other words, it presents the rhetoric for a proposed method to derive factually meaningful information from private feelings (Qualia) or to explain the meaning of dreams.
It is presented here as a logical extension of the functions of Dot theory as a process that successfully converts qualia to probabilistic quanta. It does so while offering meaningful real-world predictive application. It intellectually ties back to ontological discussions of biology, such as Orch-OR, as well as to discussions of the variability of ontological methods and their expressions of conceptually inherent self-similarity (in the way its structure-dictated function makes its repetition more likely), such as fractal-based holographic models and teleologically motivated antirealism. The relation exists pragmatically through analysis of variation in the teleological approach to Bayesian prediction models. This as a conscious strategic computational step for meaningful data recontextualisation and this essay’s source of cross-disciplinary appeal.
Whilst perhaps an unusual topic in the field of Information Theory, the discussion on human qualia and the value of the information contained in dreams has inspired debate and argument in the health and mental health care industry for at least 4,000 years. More data-analytically so in the past century, and if the Dot theory proves to be correct, this century of available data serves as a reference on important trends. This essay posits that logical considerations about the value of information from healthcare and behavioural data, dreams, and sentiments may lead to dream- and brain-function-based applications that support improved individual healthcare outcomes.
Principally, the Dot theory proposes a method for reliably converting qualia into predictive quanta to acquire improved meaning and prediction. Logically, then, the rationale applied to information available from dreams (diaries, thermoregulation, HRV, and EEG) should yield improved prediction and benefit for the dreamer in question. Such progress, I suggest, is maybe possible by computing not only the material objects and actions (rendering) contained within the dream, but, distinguishingly, the sentiment held by the individual observer/experiencer/dreamer relative to the objects and motions observed within the dream.
With Dot theory, the observed objects and motions' descriptive data are converted into mathematical functions relative to others within a conceptually digitised framework of a linear, objective, functionally shared reality. By analogy, this shared 3-Dimensional data-tapestry (topology) existing in an LLM, could, safely, reliably, and for each person or observer-event ever-so-slightly differently, be woven into by data describing personal threads of individual experience and sentiment. The consequential individual development of meaning relative to the shared objects, and this meaning’s unique structural ontology, successfully combined to produce an improved understanding of Wittgenstein’s private language through a probabilistic description of its inscriptive ontogenesis. In other words, the way we individually feel about how we understand the world when we experience it together with others helps us understand how we understand it individually.
As such, the individual observer’s (the dreamer’s) comfort and subjective experience relative to those objects and actions can perhaps not so much inform us of a value-metric-relevant or specific “meaning” of a singular or trending dream, but more reliably so of the individual’s currently trending conceptual description/delineation and understanding of reality (private language). Computationally speaking, this can be reflected as topological changes over time within a computational Langlands Landscape, and I believe at least theoretically, reveal computable predictive trends and potential benefits for individual personal wellbeing.
On dreams and their data-analytical value
Introduction
In line with Dot theory’s data-principled understanding of reality and something it (as a theory of everything) considers to be necessarily true for all information available to humans, the potential analytical and informational value of observations occasionally available to us through dreams is in this essay presented as formally dictated by and relative to the individual’s personal perspective take on the data available within the dream. This essay is shared here to by its unusual nature pique interest and inspire further exploration and development of this approach in the computation of qualia. This is in the hope that it might benefit individual healthcare outcomes through a new paradigm for multi-level data networks and voluntary, personal data-sharing interfaces in the field of bias-minimising data-topology optimisation.
This essay discusses the algorithmic and pure-logical implications of the Dot-theoretical representation of reality to inspire the development of a new computing and healthcare paradigm. I suggest that with it, the potential value of dreams and other ineffable aspects of the human experience to healthcare and individual wellbeing might be studied more reliably and yield benefits to humans.
The value of dreams
As stated previously, this essay is written in line with the principles behind the worldview on reality expressed and contained within the concept of the currently hypothetical Dot theory to which this website is dedicated. By its logic, it is concluded that the fundamental building component of human reality, whether observed through a person or a measuring device, can reliably be treated as data and has tangible, predictive value when considered as such methodically.
Logically, then, and for the Dot theory not to be incorrect, the theory’s application must also be correct for sentimental or even dream-based observations, and if the myth-rich but established relationship to healthcare is additionally not incidental, its application to dream-based observations could potentially offer healthcare benefits. Whilst the Dot theory is currently hypothetical, its application to the subject of dreams and their ephemeral qualities is presented here as a logical thought experiment and potentially considered grounds for the development of valuable testing and consideration.
Whilst it may at first seem odd to discuss the value of dreams in terms of Information Theory, it can be considered a good pure-logical test of a theory of everything (ToE) for it to find value in all of reality’s information, including the most elusive and ephemeral world of dreams. This is rather tantalisingly due to its longstanding relationship with healthcare and the perception of a relationship to human and societal wellbeing. The association with healthcare’s history may be incidental, yet logic would dictate otherwise, considering dreams have long been viewed as diagnostic tools, therapeutic allies, and windows into psychosomatic health with a history spanning over 4,000 years of medical practice. This observation encourages the theoretical consideration of the potential benefit of the Dot theory to human individuals.
Note: It is not this essay’s intent to establish such an academically argued link, which has been conclusively done by Hassle in 2011, but rather to explore the implications of the application of the Dot theory on data representing information contained within dreams as a health-beneficial clinical hypothesis.
Where we are now
The data-technical value of consumer and wearable data is already widely known and recognised through systematic analysis and its commercialisation. However, reliable analysis of the subjective human experience of reality is either considered lacking by some or not known to be secure by others. In essence, the conversion of qualia (the individual and personal experience of reality) to quanta (the discrete, absolute and predictably computable elements of reality) and their reliable computation and conversion to conceptual meaning and actionable predictive strategies currently appears to exist in relatively inefficient linguistic computing paradigms.
It is this author’s opinion that the current paradigm can be considered as relatively inefficient when compared to that inherent to Dot theory, but that it is an emerging and unfamiliar language that will take some development and adoption. The emerging field of bias correction has emerged from the ethical consideration of personal privacy constraints and the high cost of computation. Dot theory can be seen as a useful extension that resolves both of these in the same solution by the usage of AI on statistically weighted digital twin archetypes. It is not this essay’s intent to discuss the practical strategies to do so here, which can be found across this website, but rather to share with readers the logical conclusions one comes to when thinking about Dot theory’s application to the most ephemeral of all forms of information: personal dreams. My hope is that, having had more time to think about this specific subject, these early considerations may accelerate or intelligently moderate the development of health-benefiting technologies in the future.
Proposed Method
Dot theory posits the world as fundamentally subjective. This anti-realist stance inhabits Wheeler, Wittgenstein and Kant’s perspectives on the information that makes up the experiential world we call reality. Whilst philosophically rich, this position simply posits that the information that makes up our measurable and objective reality is, in fact, not absolute, but is rather individually and conceptually constructed from previously-associated information and measurements (priors). As such, a discussion on the application of the Dot theory computational logic to the question of the value of self-reported dream data on individual healthcare and wellbeing can be considered as a multidisciplinary extension of General Relativity to the individual healthcare-pursuer.
Within this relativistic position on reality, it stands to reason that the data describing the objects and actions observed within a dream are, in fact, not meaningfully absolute objects in themselves, but rather an approximate and inherently individual linguistic formulation of a notion of temporary reality, as opposed to an atemporal dreamland. This then in turn suggests that it is the quale/sentiment held relative to these relatively more objective quanta, that can inform and potentially give meaning to the observer on the relationship they individually hold to those objects and actions.
For further discussion, this correlates to Wittgenstein’s notions on the ontology of private language and logic of language information whilst considering the inherently self-similar and inevitable bias of Kant’s innately universal phenomenological observation of reality as discussed on www.dottheory/logic.
Appliction
What this means in Information Theory and practical information-manipulation terms is that the useful information contained within dreams resides not only in the things (objects and actions) dreamt about (as an event over a period in time), but additionally and more usefully: computably (i.e. predictive in nature), the feeling we have about those things (objects and actions).
This feeling and the progression of feelings relative to objects and actions recorded over time, in turn, logically informs us about how we relate to certain constructs through which we experience waking life. This can be mathematically described as the building of tentative qualitative topologies associated with conceptual quantitative geometries and risk and reward metrics. As such, dreams and the data contained within them can inform a data-driven system to attribute predictive meaning to dreams and inform clinical decision-making.
Note: This is a necessary conclusion if we are to axiomatically accept that there is a waking or “real” reality to which dreams relate as a discrete event occurring whilst not awake, and is therefore not occurring in reality.
The justification of a link between human dreams and human healthcare is theorised here as being due to the near-universal and biological relationships with which the individual human empathises with objects and actions in both waking life and dreams alike. Consider mammalian biological factors such as physical, hormonal and brainwave states. All individually emergent and biologically real patterns and phenomena that can be observed and shared consistently in a shared reality. This, subsequently, can be culturally understood as further explored in archetypical concepts such as those of C. G. Jung, but serves here as justification for the usage of digital twin archetypes as a new data-manipulation paradigm. It also serves as a demonstration of a tangible data relationship between dreams and health and wellbeing.
Real-world application
By differentiating Qualia-describing data pools (yellow, red, scared, happy) from Quanta-describing data ones (heart rate, brainwaves, flying dragon, sunny field) and delay conceptual nomenclature (naming things/giving meaning), Dot theory methodically avoids conflating the two types of data (“I dreamt of a scary flying dragon” vs “I dreamt of a dragon that was flying and felt scared). This methodical avoidance of conflation delays, as well as potentially deepens, the computable meaning of the information held in dreams by association with additional factors (watched Sleeping Beauty that day, or it is Chinese New Year next week). In doing that, deepening and extending the meaning of the data with metadata, the bias history of the data can be cleaned off and polished for purpose-specific calculation. The anxious replay of a day’s perceived events or anticipated events can then be considered as a mentally relevant linguistic exercise that provides the individual with practice on new information.
This conflation, as a closed cultural idea, can also result in the redirection and elevation of the notion of the dragon to a symbolic one in itself. This can, to my mind, occasionally confuse observers of our current scientific paradigm on reality with evidence of area-specific reliability, but fails to inform us reliably globally. Updating to this new paradigm and its applications invites evaluation of the available dream-based information as a nuanced expression of risk and reward by means of expressing their individual linguistic understanding of their relationship to those objects and actions (a flying dragon or sunny field).
Considering that this is a HIPAA or GDPR protected healthcare application, one can imagine now a phone- or wearable-based user interface in which descriptions of dreams are shared by individuals via voice-recording or writing app (dream diary) in which questions could be featured to ask what was dreamt about, how it felt and how one felt on waking and following. From this, systematic analysis of the data relative to other factors such as activity, diet, health record and such data like HRV or genetic data can, in the right clinical setting, be made to be statistically relevant and associated with other health or beneficial outcomes.
Further considerations and the impact of the Dot theory on ideas of consciousness and theories of mind:
On a more philosophy of Information-Theoretical basis, one can further extend the previous Dot-theoretical considerations on data available from dreams to the ephemeral considerations of the famous three-Body Problem. This Problem can be reduced to a challenge in mathematically understanding and being able to functionally describe the nature of the relationship between the data describing the human Mind, Body and Awareness within a computer model simulation. The Dot-theoretical solution to the three-body Problem is essentially that when recognising all of reality as potentially data and accepting that the way we understand/know reality depends on: both the data available to us, how we feel about it (qualia) and the tools we use to read it (subjective-objective). Then, meaningful reality becomes indeed computable and predictable.
The consideration by extension then, computationally speaking, is modelling a database -representative of the data that could be thought of describing the observed and self-reported singular individual. The data’s existential triad consists of three, linguistically inconsistent (qualia-quanta), but event-based statistically related data pools,. One can conceive of the idea of consciousness as the sequential function that emerges from the necessary (and functionally inevitable seeing reality is the product of its own existence) interaction between the three (at some geometrically representational middle point of that triangle, it is capable of evaluation of behavioural trends over significant spans). This enhanced functional interaction between datasets, theoretically representative of consciousness, can then be conceived of as an automatically updating and self-similarly adjusting function on the data acquired from the interactions between the continued sequence of at least somewhat, to very, predictable functions.
In this sense, the representation of the data mesh and its topology becomes such a function, and their change over time becomes representative of what we humans call “life”, and our awareness of our conscious experience of it or “consciousness”. The problematic nature of the three-body “problem” is, as such, and in its computational essence, only the expression of a practical discomfort (bias) or inability to answer the question as to what degree this continued sequence of functions itself is somewhat to very predictable as a function. Otherwise said: answering with a certainty that matches how truly known something is, and removing opinion by qualifying probability.
To represent a practical solution to this Problem in computer science and Information Theory terms, one can think of a traditionally gated triangle decision function with, on evaluation, possibly an apparent equal argument or value to each component of that functional triad can be attributed. The metric tensor and shape of this triangle depend only on the data available and the data describing the weight given to the data (metadata-based trends). Note that because we are talking in information theory terms and are working with hard observation and self-observation data, this model pragmatically avoids any inclination toward Munchausen’s trilemma.
The historical data-dependency Problem of the 3-body Problem and other paradoxes made structural attribution of source origin and destination for real-world data or progression of understanding their meaning inherently impossible. It has also demonstrably motivated significant philosophical, religious and physical debate for all of recorded human history. The key point here, I suggest, is the functional relevance of the nature or intent of the evaluation for which the chosen data is considered. A key statement Dot theory makes about maximising the value of data is that the method of evaluation is inherently (cannot not be) motivated/biased by contextual factors or relative to user motive (for it to exist as considered data with a given statistical weight), and creating the bias required for attributing meaning.
When we now look at this computer-technical functional triangle with the conceptually rich idea of consciousness as geometrically central and functionally fundamental to what we (in this Langlands Landscape) represent as “reality”. Then, if not simultaneously, we can recognise the idea of computable consciousness as necessarily linguistically emergent from priors. This is when we can describe it because the tools/priors and their data to do so now exist when they didn’t until prior interactions between the three data sets occurred.
Here, as per the distinction of awake and dream-world, we must fundamentally (axiomatically) accept that observing emergent patterns from data offers a perfect mathematically functional and computational analogy to the process of attribution of meaning required for observation and measurement to reach the threshold for being recognised as part of what we, humans, call “reality”. This, for computational purposes, provides motive to select and deselect specific datasets, creating bias, conscious experience, and measurement. As previously mentioned above, commercial evaluation of such data sets to predict and even motivate such biases has already been undertaken with great success. Considering qualia recorded for healthcare purposes in the way suggested by Dot theory only serves to extend this idea into what logically can only be a safe, meaningful, economical and life-enhancing application.
Only, because this data-enriching effect, can mathematically speaking only exists for computational cases (questions) where the Dot theoretical data-selection and -management method is used prior to Ai evaluation and if it is tasked with answering questions that are motivated by wanting to improve the individual perception of the meaning of data by decreasing (by contextually delensing) the measurement error and increasing their predictive quality. In Information Theory terms, reduce the entropy of individual observation. In poetic yet practical terms, this is simply the data-technical analysis of the algorithmic pursuit of truth, if you will. One that accepts and recognises that the limit of knowledge is demarcated by the data that is available. Only because the alternative is either legally and entropically impossible or, alternatively, computationally meaningless.
In clinical and technical terms, the source data currently being considered are items such as appearance, current behaviours and treatments, family history and genetic heritage, which resonates with this author since the physical requirement for a biological body is the absolute basic requirement for human healthcare. Extending this by Qualia, as suggested here, with behavioural and conceptually representative habits and our individual experience of them, offers an entirely novel opportunity to improve human welfare.
As such, the three-body Problem is perhaps currently standing as a philosophical debate in human society, but a data-representative solution can be reconsidered as per the above thought-experiment. Then, instead of being a pondering on a problem, it can be usefully represented as a computable entity where it becomes a source of solutions with great potential for human welfare.
Thank you for reading. Please respond.
Stefaan
All what contributes to reducing irrationality is education.
