2.0 Definition of Real
From the philosophy textbooks we know that the definition of knowledge is neither fixed nor universally agreed upon; it
can vary
widely (Appendix D2.3-Epistemology). Similarly, the concepts of "empirical evidence" and "real" are also open to
interpretation
(Appendix D2.2-Metaphysics). However, this
variability does not imply complete freedom for us to define them however we like. Certain criteria must be
met for these definitions to make sense to us. For example, we expect these definitions to align with our
intuitions and to be useful in our practices.
While referencing intuitions might not be particularly popular today, as long as these intuitions are
guided by practical considerations, the definitions they support can be sufficiently justified.
In this section, we introduce our own definition of a "real entity." We aim for this definition to be sensible yet
general enough to lay the groundwork for creating new artificial worlds.
Features of the real (ie observable) things
Studies on twins separated at early childhood suggest that even personal traits, such as a disposition to believe
or not believe in a divine entity, are strongly influenced by our genes. Our preferences are also shaped by
environmental factors like mass media, school, family, country of residence, and culture. Since we do not choose our
genetic makeup or the time and place of our birth, our religious preferences are often subjective. The same applies to
our intuitions about what is real and what is not—they are influenced by historical and contingent factors.
While these contingencies play a significant role and different people may internalize different visions of reality,
there must be some features we expect all real objects to share. For instance, real things must be reliable; we need to
be able to count on them in our practices. The Egyptian pyramids, for example, have existed for thousands of years and
may remain for many more. It makes sense for us to acknowledge their existence when planning a trip to Egypt. In contrast, a
mental image of a flying elephant does not impact our plans. Additionally, we believe that observations of real things
must be reproducible so that others can confirm our findings. Reproducibility implies some persistence in time and space
and a certain accuracy in describing the observational experiment.
In what follows, I will try to identify and consolidate features common to real things and integrate them into a
definition of a "real entity." This definition aims to be broad enough to accommodate a multiverse vision of the world
and specific enough to guide our subsequent developments.
For the impatient readers,
i suggest skipping this section and jumping straight to the definition of the real entity in
Definition of real entity.
General Description
First of all we need to have a general understanding of the real entity to be able
to work with it. This understanding must be based on a more or less coherent description of that entity.
Characteristic features
In the rest of this chapter, we shall call the key, defining properties of an entity as “characteristic features” of
that entity. Other properties, less critical to that entity, we shall call “secondary properties” or just “properties”.
For example, the shape of the clock and the material it is made of are all secondary properties of the clock, while the
capacity to show the right time is a feature characteristic of it.
Observations
For an entity to be real it must be observable. We must have some sort of a special or privileged access to it
to be able to distinguish this real entity from the fake of imaginary counterparts.
Accuracy of observation
Observing an entity implies a certain accuracy of observational data (otherwise, if the uncertainty is too high, the observation
is useless).
Under different circumstances, the same data could be considered either as an outcome of the simulation or
an observation,
depending on the relative accuracy of the data. For example, ocean temperatures derived from satellite measurements
involve interpretation and modeling. However, as long as the uncertainty of this data is smaller than that of the ocean
model (e.g., interpolated temperature), it is used to validate the latter, and the satellite data is considered an
observation. Conversely, when remote-sensing data are tested against more precise ground measurements, they are treated
as a model.
Reliability (persistence)
Accuracy is integral to our understanding of the term “observation of the real entity.” However, if we had a computer
model of the Indian Ocean that was completely detached from the actual ocean, no matter how accurate its predictions, we
wouldn't call it observations. It remains a model because there is no guarantee that its accurate predictions will
persist indefinitely. Models can fail, while observations are meant to provide reliable data whenever measurements are
made. For example, if the behavior of the Indian Ocean goes beyond its typical range due to extreme events, measurements
can still provide accurate records, whereas a detached computer model might not be able to track these changes.
Accuracy and reliability have little value unless specified in the context of their intended use. Data considered
accurate and reliable in one context might be inaccurate and unreliable in another.
Observations and models
Typically, observations involve some level of interpretation and therefore include a modeling component. Conversely,
every model is based on observations.
Privileged Access
When we refer to "access to the object," we're talking about a specific method, protocol, or set of rules that must be
followed to obtain a valid observation. The particulars of this protocol can differ depending on the type of object
being observed. For example, it might involve a procedure that yields undeniable insights into a personal experience (like
a feeling, a spiritual encounter, or a personal memory). In other contexts, such as in physics, this protocol could be
an experimental setup, or in mathematics, it could involve a series of logical inferences.
Regardless of the specific procedures involved, the purpose of these protocols is to provide privileged access to the
object under observation. This access is considered "privileged" because it produces a unique form of knowledge known as
empirical evidence. This type of knowledge is derived from reproducible practices that reveal the characteristic
features of the observed entity.
The process of observation involves not only defining specific rules but also engaging in the act of observation
itself. This act requires interaction between the observing system and the observed object, and these interactions occur
in real time, within the present.
It's commonly understood that observations relate to the present or past states of the
object being studied. However, in certain contexts, it might be appropriate to consider
observations of future events as well. For instance, while the observational process itself is anchored in the present,
the data collected can relate to the present, past, and future states of the system. This notion aligns with
the idea of intelligence as a kind of "eye" that can peer into the future. The
further into the future we try to see, the less clear our vision become, mirroring the decrease in accuracy with
increased spatial distance.
From this perspective, the past and the future are somewhat analogous. One might consider the reliable inference about
events near the present (whether they are in the past or the future) as observations, while the uncertain descriptions
of distant future or past events could be labeled as interpretations. Ultimately, whether we label something as an
observation or an interpretation, and how we allocate these in time, often comes down to our subjective preferences.
Partial Observations
Often, our observations of a real entity are incomplete; we only see parts of it. Despite this, we can still consider
the entity real, especially if the unobserved parts could potentially be observed in future tests. Take, for example,
the temperature of the Indian Ocean interpolated between several sampling sites. While we haven't measured the
temperature at every
point between our sample sites, we understand that we could do so if necessary. Our hypotheses about the temperatures in
these unmeasured areas can be verified by directly observing the temperature at any chosen location within the ocean.
We affirm that the temperature of the Indian Ocean is a real entity because we have made measurements at several points,
and importantly,
we could measure it at any other point if required. Its reality is established not because we have observed every
possible location but because it is possible to observe at any location.
Having said this, it’s important to do not overstate the requirement "can observable directly". There are unique cases,
such as historical events, which we cannot directly observe but still regard as real.
Reproducibility
A critical feature of an observation is its reproducibility—other observers, when properly educated and resourced, must
be able to replicate the results of our observation. The importance of this feature arises from the significance of
regular patterns in our lives, particularly those associated with reproducible cause-and-effect relationships. We live
in an ordered universe with observable laws and regularities, enabling us to communicate with each other.
For a given cause, there is a given effect. In a world
without reproducibility, there would be no stable connection between causes and effects, leading to a lack of order,
law, language, and truth.
For an observation to be reproducible, certain conditions must be met. For example, a sufficiently accurate description
of the observational experiment must be available so that the observer knows how to reproduce and test it. The observer
must have the capacity and resources to conduct the experiment. Additionally, the subject of the observation must be
stable and available for observation at least during the experiment.
For instance, to observe the track of an electron particle on a film, one must have access to the necessary experimental
facilities, follow specific instructions to carry out the experiment, and then analyze the particle tracks on the film.
This experiment and its results are fully reproducible because electron particles are well-defined entities with
consistent properties over time. Anyone can perform the same experiment at any time, and the particle trajectories will
be consistent with the laws of physics. We have a well-defined and relatively stable object to experiment with.
The concept of reproducibility becomes more complex when dealing with poorly defined objects that evolve over time, such
as biological or social systems, or unique objects and phenomena like the Big Bang, the birth and life of a particular
person, or special events. Even in physics, we never achieve complete reproducibility since every observational
experiment has its own irreducible errors. Reproducibility typically refers to an approximation to an ideal state
(except perhaps in mathematics). In the real world, it is often more appropriate to talk about degrees of
reproducibility rather than making a clear-cut distinction between reproducible and non-reproducible experiments.
Consistency
In the realm of scientific inquiry, observations are expected to integrate seamlessly with existing knowledge. For
example, a well-established theory might predict various outcomes, and the purpose of an observation is to narrow these
possibilities down to a single hypothesis that aligns with the broader body of knowledge. However, achieving this
consistency between new observations and existing knowledge isn't always possible.
In fact, the value of observational data in science often lies in its ability to challenge and potentially contradict
established knowledge. Such contradictions can be highly significant, prompting reevaluations and advancements in
understanding. Nevertheless, an observation that starkly contradicts all established knowledge and doesn't fit within
any existing theoretical frameworks is an outcast. It must either prompt an adjustment or refinement of the
current knowledge base or be set aside (swept under the carpet) until further data or a new theory can provide
a suitable explanation.
Once in a life-time event
Reproducibility is a hallmark of reliable observations, yet there are instances where observational data is
considered valid even
if the observation itself cannot be reproduced. Historical events are a prime example. These events, by their very
nature, are unique and cannot be recreated. Nonetheless, we often accept historical records as sufficient evidence of their
reality. Take a wedding ceremony that occurred many years
ago as an example of such a historical event. For the groom, this wedding is not reproducible, but he still believes it
was a real event because of the abundance of indirect empirical evidence supporting it (e.g. his wife, wedding photos,
children, his mother-in-law, and his own memories of the event). He believes the
wedding ceremony was real rather than a product of his imagination because of these numerous empirical
facts consistent with the
past event. These indirect observations are connected to the wedding through a chain of
interpretations, reinforcing the belief in the reality of the event.
Singular Experiences
Now, assume one night, after the wedding, he goes outside on the balcony and observes an alien jumping into a UFO and
flying away. His experience is vivid and lifelike, yet no one else is there to witness it, and no traces of the alien
are left behind. Over time, he is likely to doubt the reality of the alien on the balcony, considering it might have
been a hallucination. The credibility of his experience is low because it is not reproducible and has left no observable
traces.
However, if other people report similar experiences at different times and places, his confidence in the reality of the
alien encounter increases. He may still not believe it 100%, but there will be some grounds to suggest it was real. The
collective reports of similar experiences lend credibility to his observation, even if it remains a singular and
non-reproducible event.
Degrees of Reality and the Role of Interpretation
From these observations, we can infer that the notion of what is real is not black and white but encompasses various
degrees of plausibility. Empirical evidence is always intertwined with interpretations. We almost never observe an
entire object or phenomenon, only parts of it. These observable parts are then integrated into the whole entity through
interpretation.
The whole, comprising empirical data and interpretations, can evolve over time. This means that for a given protocol,
the requirement of strict reproducibility might only be valid over a certain period when the object is relatively
stable. Despite the ephemeral nature of such objects, if there is a logical continuity of events caused by the object
and we can trace its evolution through current observations, we have empirical evidence pointing to the object's
existence in the past.
An Image of the Real Object
An image of a real object that emerges from these considerations is that of a collection of observations connected through a
network of interpretations (see figure below). We believe this object is real because:
(a) We have reproducible access to features characteristic of it (eg. empirical evidence represented by filled circles).
(b) This evidence is integrated with other knowledge (represented as white circles) into a coherent whole.
The object may reside in the distant past or belong to some metaphysical domain, but as long as we can observe present data
and link it through a chain of inferences to the past states of that object, we consider these indirect
observations as justifying our belief in the object's reality.
Fig. 3.1. Real object interpreted as empirical evidence (filled circles) connected via the net of interpretations with
other knowledge (white circles)
Note that, empirical part of the real object can be represented by observations not directly associated
with the object but only pointing to it (e.g. the wedding event is not reproducible by itself but there are indirect
observational support of it – empirical evidence which fits the story). If we flip around the time axis and allocate the
object/event in the future (rather than in the past) than we have an observable real object/event allocated in the future.
For example, having reliable models, we can make predictions (observations) that point to a particular event in the future,
and then call it a real event.
Utility to practice
Reproducibility is an important feature of observational data, but its ultimate value does not lie solely in its
reproducibility. Instead, we value observational data because it underpins empirical knowledge, which is useful for our
practices. Being reproducible makes observations reliable and thus useful. In other words, the key and most important
feature of observations (empirical evidence) is their utility to our practices. If an observation is not entirely
reproducible but is still useful, it can still be considered as delivering knowledge. The same applies to the
requirement for the consistency of empirical knowledge.
Given the high value we place on utility, it might be tempting to define observations in terms of their utility to our
practices. However, the notion of utility is too broad to be useful. Almost anything can have some utility to our lives
and would pass this test, including fiction, myths, and hypotheses. The definition we seek must be more specific to
distinguish between real and fake storied-worlds. Note that every storied-world we've considered so far has some
promises built in (e.g., salvation, a good life, a comfortable life, nirvana). It makes sense to talk about the utility
of these worlds in terms of their delivery of such promises.
Definition of a Real Entity
The purpose of this section is to consolidate the sporadic considerations we've made so far into a definition of a real
object. We will assume the following two requirements must be satisfied to provide necessary and sufficient conditions
for an entity to be considered real:
-
A logically cohesive description of the entity must exist.
-
Reproducible practices delivering features characteristic of that entity must exist.
The term “logically cohesive description” refers to a degree of logical coherence inherent to the description of the
real entity. In other words, the description does not need to be fully self-consistent but must have enough consistency to be
comprehensible. THe dergee of this logical cohesion varis from one area to another (very strict in math, and flexible is
social sciences and philosophy)
The entity under consideration could represent either an entire storied-world or some fraction of it (a
particular item in that world). When the description is restricted to a particular item, it must be consistent not only
within itself but also with the description of the whole.
The description of an entity can be expressed in various
forms, including texts, audio messages, algorithms, theories, images, and equations. It should explain the purpose and
key functions associated with that entity and how to recover its characteristic features.
The term “characteristic features” refers to properties and attributes that define that entity. In the case of artificial
objects, these features are often associated with the discharge of functions inherent to that entity. Most items created
by people are made with a specific purpose in mind. The delivery of goods or services associated with such items
provides an important indicator of their existential status. For example, an airplane which cannot fly is not real.
Reproducibility means that anyone (with proper training and access to resources) can conduct an observational experiment
and recover features characteristic of the observed object. The knowledge gained through such reproducible practices is
called empirical evidence. Reproducibility also implies that:
-
Observers have a general understanding of the observed entity.
-
There are protocols (instructions, procedures, roles) specific enough for the observers to follow.
-
Outcomes of the observational experiment (i.e., empirical evidence) are well-defined.
-
Observers have the capacity and resources to implement these protocols and recover features characteristic of the
observed entity.
### Pragmatic Interpretation of the Definition
This definition of a "real" object can be also interpreted in terms of the "promises" outlined in the
description of the entity, and the "practices" meant to deliver these promises.
#### Promises (Description)
The first part of the definition involves promises embedded within the general description of an entity including
instructions on how to deliver these promises. Promises can vary widely depending on the nature
of the entity in question. For example:
- A numerical model might "promise" to yield forecast data that enhances the prediction capabilities
for a physical system.
- A religious artifact or practice might offer an immediate or mediated experience of the divine.
- A social or political ideology might aim to deliver a good life, a sustainable ecosystem, or a specific cultural
experience, like living as a samurai.
#### Practices (Testing Promises)
The second part of the definition focuses on the practices through which these promises are tested or delivered. This involves
applying specific algorithms or instructions to see if the promised outcomes are achieved. This testing phase is crucial
as it provides the empirical evidence needed to validate the entity's claims. For instance:
- In science, the models effectiveness is tested by simulating it under the prescribed conditions to see if it indeed
improves system predictions.
- In spirituality, the validity of a religious practice might be evaluated based on the spiritual experiences it
facilitates.
- In ecology, the success of a conservation strategy is measured by its actual impact on ecosystem health.
This practical application of the initial promises not only tests their validity but also helps in refining the entity's
definition and improving its integration into broader practices. This dynamic interplay between promise and practice
ensures that the entity's "realness" is continuously vetted and validated, making the definition both robust and
adaptable.
One sticky point with this definition is determining which empirical evidence can be considered proof of the existence
of a particular object. In principle, everything is connected to everything else. For instance, an image of some random
wedding cake might remind you of your own wedding ceremony many years ago. Does this observation count as empirical
evidence of your wedding? What if the image is not just any random cake but actually a photo of the cake from your
wedding? Intuitively, we feel that a random cake does not count as evidence of your wedding, while the actual wedding
cake does. However, upon reflection, we realize that even the cake from your wedding may not count as evidence — you
cannot take this picture to court to prove the event was real.
For something to be considered empirical evidence (or a source of knowledge), it is not sufficient to serve as proof to
oneself; it must be shared and accepted by others.
You remembering your wedding cake, is not a sufficient argument to prove your wedding real
(you might be mistaken, imagining, dreaming, hallucinating etc). To prove it real you need others to concur.
This aspect of shared validation and communal verification is crucial for ensuring the utility of the empirical evidence.
Knowledge is a product of social, rather than individual, practice.
Did we miss this point in our definition?
I think, the requirement of reproducibility addresses this issue. An image of a random cake shown
to random people does not evoke memories of your specific wedding — it serves as empirical evidence of wedding events in general.
Conversely, when you show people a photo of your wedding cake with a sign indicating something specific about your wedding,
then this cake points not only to the notion of weddings in general but to your particular wedding.
In this case, the observational experiment is reproducible — other people can see it and confirm that
the photo was taken at your wedding.
Therefore, it can be used in court as empirical evidence of this particular wedding event.
The key is that the evidence is
verifiable and can be independently observed and confirmed by others, which ensures its validity.
By emphasizing the social validation through reproducibility, we ensure that the knowledge gained from observations is a
shared reality, validated through communal practice.
This makes the empirical evidence robust and suitable for confirming the existence of the real entity in question.
An interesting point that emerges from the idea that knowledge is social is that our beliefs need to align with those of
others to be considered knowledge. This concept, inspired by philosopher Richard Rorty, highlights the importance of
commensurability—our ability to find common ground with others in our beliefs. This common ground is largely built on the
reproducibility of empirical evidence, which allows us to use it as a foundation in discussions with others. When
knowledge is reproducible, it means that it possesses qualities that all reasonable people can recognize and agree upon.
Another potential source of controversy with this definition lies in the loose meaning of the word "cohesive," which we
define as a certain degree of coherence. When it comes to storied-worlds, we say the whole story should make sense, but
we do not require complete consistency—some contradictions are allowed. The problem is that it's unclear how much
consistency is enough to call a story real.
The best I can suggest at the moment is to consider a story sufficiently coherent if you tend to
believe it and not otherwise. The whole notion of the “cohesive story” is subjective and not well defined. On the other
hand, empirical evidence delivered through practice may provide further constraints on this definition helping us to
delineate between real and fake objects.
Examples of real (i.e. observable) things
In this section, we use different types of entities to illustrate our definition and assess their existential status.
**Lawn Mower**
Many people know what a lawn mower is: a machine with wheels that can roll over the lawn and cut the grass.
There are also user manuals that provide assembly and operating
instructions. By following these instructions, we can verify whether a lawn mower performs its key functions, such as
grass cutting. If it does, it is real; if not, it is not real.
Note that instead of broadly questioning the reality of an object, we can pose a more specific and well-defined inquiry: "Does this
object belong to the class of real objects of this specific type?" For instance, rather than asking "Is this lawn mower
real?", we could ask "Does this lawn mower belong to the class of real lawn mowers?" This approach focuses on the
properties and functions characteristic of all real lawn mowers, rather than all real objects, allowing us to determine
whether this particular lawn mower qualifies as a member of that class.
**Indian Ocean**
When assessing whether the Indian Ocean fits within the class of real oceans, we must define what constitutes a "real
ocean." If we consider real oceans as 3D fields of temperature that evolve according to the laws of physics, then the
Indian Ocean qualifies since it fits this description and its properties can be tested through reproducible practices.
However, this definition is overly broad and could apply to almost any three-dimensional object.
To refine our definition, we might specify that real oceans must be large bodies of salty water suitable for activities
like swimming, fishing, and sailing. To test whether the Indian Ocean meets the requirements of this definition,
you could drive to the
shore, dip your finger into the water to taste its saltiness, and engage in fishing, swimming, and sailing. These
reproducible practices help verify the features characteristic of real oceans, confirming the Indian Ocean's reality.
Contrast this with a depiction of the Indian Ocean on a television screen. Attempting to interact with this
representation as you would with real water—by touching it to feel its wetness or taste its saltiness—proves impossible.
You cannot swim, fish, or sail in it. The television depiction fails to fulfill the physical criteria established for
real oceans, demonstrating that this representation of the Indian Ocean is not real. Thus, our practical tests affirm
the Indian Ocean's reality while disproving the reality of its simulated counterpart on TV.
**Electron Particle**
Consider the electron, commonly referred to as an "e-particle." Textbooks on physics provide a general description of
electrons, outlining their properties which can be observed through precise experimental studies producing,
for example, visible tracks
on photographic films. Additionally, there's indirect evidence of electrons through various devices based on
electron theory, like electrical appliances. The reproducibility of these scientific experiments and everyday use of
electrical devices supports the reality of electrons.
**Fake E-Particle**
For a hypothetical example of a fake particle, imagine a scenario where a scratch resembling a spiral appears on
film during a physics experiment, mistakenly believed to be caused by a particle. In reality, this mark was
accidentally made by the technician. A physicist, mistakenly assuming it was caused by a new type of particle, might develop a theory
to explain this observation.
However, since the scratch was accidental, subsequent experiments will not replicate the original
observation. The lack of reproducibility means this hypothetical particle does not meet the criteria for being
considered real.
**Temperature as a Property**
Consider temperature — a property of a physical body. Physics textbooks provide a clear description of temperature, along with
established procedures for measuring it. We define a key characteristic of the temperature as its dynamic nature; it changes
and evolves according to the laws of physics. Armed with this description and measurement instructions, we can
test and observe temperature's behavior via experiments. Therefore, based on its description
validated through reproducible practices, temperature can be confidently classified as a real entity.
**Mathematics: Euclidean Geometry**
Consider the theorems of Euclidean geometry. These theorems are well-documented in geometry textbooks. A key
characteristic of these theorems is their self-consistency; they are proven true through logical inferences. These
proofs are reproducible—anyone with the proper educational background can follow the proofs and arrive at the same
conclusions. Therefore, theorems that are successfully proven within Euclidean geometry are real entities.
Conversely, a theorem that is mistakenly proven — due to errors in logical reasoning or calculation — serves as an example
of a fake (i.e., not real) theorem.
**Feeling of Pain**
When considering whether feelings are real, let's specifically examine the feeling of pain. There are descriptions of
pain available in medical and psychological literature. It is possible to design an experiment that consistently
provides empirical evidence of pain (such as poking your finger with a pen). The result (experiencing pain) is reproducible
across different individuals under similar conditions. Therefore, according to our definition that emphasizes
reproducibility and empirical evidence, pain must be considered a real entity.
### Gods
Consider the notion of God. We have a general understanding of this term, typically encompassing a complex network of
practices, experiences, and statements, some of which refer to the future or the past. Let's assume that a
characteristic feature of this entity (i.e., empirical evidence of God) is the immediate and mediated experiences of
God, delivered via religious practices. The capacity to implement these practices is maintained by corresponding
religious institutions. Experiences induced by these practices are generally reproducible (subject to proper education
and training). The conclusion we reach is that God must be real for those who believe in it.
One might think of God in terms of the delivery of certain special goods associated with this entity and promised in the
future. Consider, for example, the notion of salvation in Christianity. Salvation typically refers to future events that
we never experience for sure while alive (except, perhaps, through experiences in the divine liturgy). Is salvation
real? Let's see what our definition has to say in this case.
There is a general understanding and description of what salvation means. There are instructions that tell practitioners
how to achieve salvation, and they may have the capacity to implement these instructions. But can we check now that the
promised goods (i.e., salvation) will indeed be delivered?
The right answer depends on the case in hand. An entity called “salvation” is not directly observable (at least while we are alive) and belongs to the
interpretive part of the notion of God. You may have indirect empirical evidence available now and a web of logically
coherent inferences leading from that evidence to the future entity (analogous to the situation discussed earlier about
the past wedding ceremony). Depending on how tight these logical links are (and how much you want to believe), you may
consider this entity a theoretical construct or a real object you have empirical evidence for. In other words, it works
and, hence, is real for those who believe, and it does not for those who do not. According to our definition, it is real.
Fake Gods, by contrast, do not deliver the promised goods (e.g., salvation, a good life, nirvana).
### Love
Is love real or it is not?
We have a general understanding of this
complex phenomena available from literature and private experiences. Analogous to the example with gods, there are immediate and mediated
experiences of love (i.e the feeling of love we can experience individually and various ceremonies, traditions,
rituals we can witness or participate.). In the right conditions (age, health, cultural settings), sooner or later,
almost everybody falls in love (i think) - the phenomena must be reproducible (at least in a statistical sense).
The conclusion we are reaching here is that love must be real. And it's reassuring to know that.
As an example of fake love, consider someone only pretending to be in love and not actually experiencing this feeling.
In this case, the practice fails to deliver emotions, thoughts, and actions associated with love.
Character type
Take a person practicing Buddhism as an example. There are practices delivering experiences specific to Buddhism (e.g. meditative
states). These practices are reproducible (i.e. with a proper training others can follow and have similar experiences).
There are also mediated experiences of the Buddhism associated with the religious ceremonies and practices maintained by the Buddhist communities.
There is a general understanding of what it means to be a Buddhist. The Buddhist personality must be a real entity - we
can provide a general description of that personality, including features characteristic of it, and instructions to follow
in order to reveal these features.
Fake object: someone pretending to be what he is not. That sounds as a dubious statement given that not many people can
tell who they are. However, if you say “I am a samurai” but you do not live like samurai, do not think like a samurai and
do not feel like samurai, then you are probably not a real samurai.
Santa Claus
If we take Santa Claus to be a person who lives at the North Pole, rides flying reindeers,
and distributes Christmas presents all over the globe in one instance, then this description contradicts the laws of physics.
Therefore, the description of Santa Claus is not consistent with the established body of knowledge and thus fails to meet the criteria for being a real
entity.
However, if we consider Santa Claus as a cultural symbol or a character representing the spirit of giving and joy during
the Christmas season, then he takes on a different kind of reality. The experiences of joy, generosity, and festive
celebration associated with Santa Claus are real and reproducible within cultural practices. In this symbolic sense,
Santa Claus can be considered real in terms of the cultural and emotional impact he has on people's lives.
### Possible Worlds and Multiverse Theories
What about possible worlds and multiverse theories? Are they real or not? Each of these entities, particularly
multiverse theories, has an elaborate and fairly coherent description. Regarding special practices that deliver
empirical evidence, there is some sparse data supporting certain multiverse theories. However, in general, these
theories have very weak observational support, and it is not clear how to rectify this situation.
Consequently, possible worlds and multiverse theories seem to represent real theoretical constructs entertained within
certain academic circles. On the other hand, they do not represent real physical entities.
Based on our definition, possible worlds and multiverses do not belong to the class of real physical objects.
### Storied Worlds
All storied worlds considered so far (Appendix D1) must be real according to our definition. Each storied world has a more or less
coherent description. There are reproducible practices that deliver empirical evidence supporting these worlds. The
capacity to implement instructions underpinning these practices is typically maintained through culture and social
institutions.
A key point here is that some storied worlds may represent a mixture of true and false beliefs. However, as long as
there are key features characteristic of these worlds, and we can test whether these features are indeed delivered,
these storied worlds must be real — even if a fraction of them incorporates false beliefs. The presence of reproducible
and verifiable elements within these storied worlds ensures their reality despite the potential presence of some false
components.
Storied-world multiverse
Another question that requires further elaboration is the reality of the collection of storied worlds, which we call
a storied multiverse. According to our definition, all storied worlds considered so far are real. Therefore, the
multiverse comprising these and probably other storied worlds must also be real. The question then is whether the
definition of “real” we just introduced applies to this multiverse as well.
To prove this storied multiverse is real, we need both a logically cohesive description of it and practices delivering
empirical evidence of this multiverse. Developing a self-consistent description of the multiverse is not as simple as
just postulating a collection of storied worlds. The worlds comprising the multiverse will have shared content, and we
will have to resolve contradictory claims made by the inhabitants of different worlds regarding that shared
contradictory content.
We will return to this and other questions pertaining to the multiverse theory in the next chapters.