3 ISO Machinery
3.1 Our definition of real
In previous chapters we learnt the definition of knowledge is neither unique nor objective. It can be
defined in many different ways. Analogously, neither the notion of “empirical evidence” nor the
notion of “real” can be specified unequivocally. Yet, the uncertainty associated with a normative nature of these terms
does not translate into a complete freedom of defining them. Certain requirements must be satisfied for these definitions
to make sense to us. For example, we often anticipate them to be consistent with our intuitions
and have some utility to our
practices. I know, the reference to intuitions nowadays is not particularly fashionable, but, as long as these
intuitions are constrained by practices, the definitions they underpin may, at least, appear to us to be sufficiently
justified.
In this section we shall introduce our own definition of the “real entity”. I want it to be reasonable. Besides that, it
must be general enough to underpin a strategy for us to create new artificial worlds. To create such new worlds, we needs
some guiding principles, including a fairly general definition of the real entity
(and hence the definition of the real world).
Features of the real (ie observable) things
Observations of twins separated at early childhood, suggest that even such personal traits as a disposition to believe
or do not believe in a divine entity, is strongly influenced by the arrangement of our genes. Our preferences are also
shaped up by environmental factors, such as mass media, school, family, country of residence, culture etc. Since we
choose neither our genetic pool nor the place or the time of our birth, our religious preferences are often subjective.
Same comment goes for our intuitions about what is real and what is not – it is loaded with historical, contingent
factors.
While the contingency is likely to play a prominent role here, and different people may internalise different visions of
the reality, there must be some features we anticipate all real objects to have in common. For instance, real things
must be reliable, we must be able to count on them in our practices. Egyptian pyramids have been there for thousands of
years and may stay there for many more – it would make sense for us to acknowledge their existence when planning our
trip to Egypt. A mental image of the flying elephant, on the other hand, does not make much difference to our plans.
Further, we believe that observations of real things must be reproducible, so that others were able to confirm our
findings. The requirement of reproducibility implies some persistence in time and in space, a certain accuracy of the
description of the observational experiment etc.
In what follows I shall try to filter out and consolidate features, I believe, are common to real things and integrate
them into a definition of the “real entity”. This definition is meant to be general to accommodate a multiverse
vision of the world, and also specific enough to guide our subsequent developments.
To kick it off, let’s take as an example the Indian Ocean. To make it simple, we will assume the key property of the
Indian Ocean is a 3D field of temperature allocated at a particular location and evolving through time according to
the laws of physics. Observing Indian Ocean, according to this definition, is equivalent to observing the temperature of
the Indian Ocean. We can also simulate this ocean in a computer. Let’s see, what is the difference between these two:
the observed real and the simulated, not real Indian Ocean? This example may help us to clarify the distinction between
theoretical constructs and observations and lead us towards the definition of the real entity.
The Indian Ocean
General Description
First of all, be it a real or simulated Indian ocean, we need to have a general understanding of this entity to be able
to work with it. This understanding must be based on a more or less coherent description of that ocean. To keep it
simple, we have defined it in terms of the temperature field allocated at a particular location and evolving through
time according to the laws physics. We assumed these two (location and temperature changing in a very particular way)
are key features of that ocean. There are other properties of the Indian Ocean considered less important (e.g. being wet
and salty). We assume also all other terms relevant to this description are defined elsewhere.
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. In the case of our idealised Indian Ocean, we assumed
the location and evolving temperature to be features characteristic of that ocean, and salinity and wetness to represent
its secondary properties.
Accuracy of observation
Observing the Indian Ocean in our example is equivalent to estimating the temperature of the Indian Ocean.
We make point measurements at a number of isolated sites and then interpolate this data over the whole ocean.
One of the key differences between the interpolated (the whole of the ocean) temperature
and the temperature at individual sites
(observations) is varying uncertainty. Point measurements have smaller errors and are quite
reliable, while interpolated data have larger uncertainty and may not be so credible. Either of those (point data and
interpolations) involves some theory and interpretations, plus some specific kind of interactions between the observing
system and the ocean. The interpolated data we tend to call a model, while point measurements provide observations to
test that model.
Exactly the same system under different circumstances could be considered either a model (simulation) or an observation
depending on the relative accuracy of this data. For example, ocean temperature derived from satellite measurements
involves interpretation and modelling, but as long as the uncertainty of this data is smaller than the uncertainty of
the ocean model (e.g. interpolated temperature), the former is used to test the later and the remote-sensing data is
considered an observation. On the other hand, whenever remote-sensing products themselves are tested against more
accurate ground measurements they are considered a model.
Reliability (persistence)
An accuracy of the description seems to be integral to our understanding of the term “observation of the real entity”.
However, if we had a model of the Indian Ocean in a computer fully detached from the ocean, however accurate predictions
by this model, we hardly call it observations. We still call it a model because there is no guarantee these accurate
predictions will persist forever. Anytime this model can go wrong, while observations are meant to provide reliable data
whenever we make a measurement. For example, if the behaviour of the Indian Ocean goes
beyond its typical range of operations (due to some extreme events), using the same measurement we may still be able
to obtain temperature records with the same degree of accuracy while the computer model detached from the ocean would
not reproduce these changes.
An accuracy and reliability have little value by themselves unless they are specified through the reference to practices
where this data is meant to be used. Something considered accurate and reliable in one context could be inaccurate and
unreliable in another context.
Observations and models
Typically, observations involve some interpretation and, hence, modelling component. Conversely, every model stems from
observations.
Privileged access
Observations of the Indian Ocean are acquired through the very specific procedure which involves direct interaction
between the observing system and the Indian Ocean. A common assumption is that such an observation provides a privileged
access to that object.
When we say “access to the object” we mean a specific algorithm, rule, protocol one must follow in order to get a valid
observation. The details of that protocol may vary from one class of objects to another. THe protocol could be based
on certain
practices delivering incorrigible knowledge of a private experience (such as a feeling or a sentiment, experience of the
divine or experience of an autobiography). This protocol may represent an experimental setup in physics, or a logical
inference in math. Regardless the implementation details, it is meant to deliver a privileged access to the observed
object. The reason that access is privileged is that it delivers a special kind of knowledge called empirical evidence -
a knowledge based on reproducible practices delivering features characteristic of the observed entity. Reproducibility
here means that other observers (when properly educated and resourced) must be able to replicate the results of the
observation. Reproducibility entails also a certain accuracy of the description of the observational experiment, an
accuracy of the data delivered through that observation, capacity to carry out observational experiment, persistence,
utility to our practices etc.
The process of observation implies not only rules but also an action itself. That action involves interactions between
the observing system and the observed object and unless we talk fiction, these interactions are allocated in present
time. One may speculate further that allocation into the present implies that the knowledge established through the
observation is always about the present or past states of the object. However, this may not necessarily be the case - in
some circumstances it might be appropriate to talk even about observations of the future events. For instance, we may
argue that while the process of the observation is always allocated in the present, the data we collect pertain to the
present, past and future states of the system, and the knowledge we gain is about all these states. Remember intelligence
being compared to a kind of an eye which can see into the future. The longer distance the less we can see (i.e. the
lower accuracy of the prediction). From this perspective, the future and the past are analogous to each other. You may
refer to the reliable inference about the near-present events (located in both the past and the future) as an
observation and may call uncertain description of the distant future or distant past as interpretations. Ultimately, the
choice of what to call an observation and what to call an interpretation and where they are allocated in time seems to
be a matter of our subjective preferences.
Partial observations
Typically, we observe only parts of a real entity. Despite incomplete observation, we may still call that object real,
particularly if the unobserved part could be a subject of the further observational test, at least in principle. For
instance, in our example of the interpolated temperature of the Indian Ocean, while we have not measured that
temperature in between the measurement sites, we know that we can do it if we wish. Our speculations about the
temperature interpolated between these sites can be tested through the direct observation of the temperature at any
selected point. We say that the Indian Ocean is a real entity, because we have measured it at a few sampling locations,
but if needed we can measure it at any other location within the ocean. It is real because we can observe it at every
possible location (not because we have observed it at every possible location). Note also that the requirement “can
observe” should not be overstated. In some cases we have unique events (e.g. historical) which we cannot observe
directly but still consider them 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 significance of that feature stems from the significance
of regular patterns in our lives and in particular patterns associated with the reproducible cause and effect relations.
We live in an ordered universe, we observe laws and regularities, we can communicate with each other because there are
stable cause-effect relations between different phenomena. For a given cause there is a given effect. In the world with
no reproducibility there is no stable connection between cause and effects, and there is no order, no law, no language,
no truth.
For an observation to be reproducible, certain conditions must be satisfied such as, for example, sufficiently accurate
description of the observational experiment must be available to the observer so that s/he knows how to reproduce and
test it. The observer mus have capacities and enough resources to implement and conduct this experiment. Besides that,
the subject of the observation must be stable and available for observation at least during the time of the experiment.
For example, to observe the track of an electron particle on a film, one must have access to the relevant experimental
facilities, s/he will have to carry out experiment according to some specific instructions, and then analyse the track
of particles on the film. An experiment and the results are fully reproducible, because there is only one kind of the
electron particles and their properties do not change with time. The same comment goes for the experimental settings.
Anyone and anytime can perform the same experiment and the trajectory of the particles will be the same (up to the
measurement errors, of course). We have well defined relatively stable object to experiment with.
The notion of reproducibility becomes more involved when dealing with poorly defined objects evolving through time (e.g.
biological or social systems), or unique objects and phenomena such as for example a big-bang, birth and life of a
particular person, special events. Note that, even in physics we never have complete reproducibility of observations
since every observational experiment has its own irreducible errors. The notion of reproducibility typically refers to a
certain approximation to the ideal state (except perhaps math objects). In real world it is often more appropriate to
talk about certain degrees of reproducibility, rather than a black and white clear-cut distinction between reproducible
and not reproducible experiments.
Consistency
Typically, we expect observations to deliver new knowledge consistent with the rest of our knowledge. For instance, a
number of hypotheses may follow from the established theory, and the role of observations is to collapse this spectrum
of possibilities into a specific outcome – a single true hypothesis which is consistent with the main body of our
knowledge. Clearly, such agreement between observations and our current knowledge is not always achievable. In fact, the
value of observational data, at least in science, to large extent is associated with the capacity of observations to
contradict the established knowledge. Yet, an observation which contradicts all established knowledge and cannot be
explained within the established framework is a fairly transient phenomenon. It must be either explained through the
refinement of the established body of knowledge or suspended until new data or theory becomes available.
Once in a life-time event
Reproducibility of an observation is an important feature and yet we may refer to some knowledge as based on
observations even though the observation itself is not reproducible. Historical events, for example, may not be
reproducible and yet we believe that historical records provide sufficient evidence for these events to be considered
real. Take a wedding ceremony which has happened many years ago as an example of such a historical event.
For a bridegroom this wedding is
not reproducible, and yet he may still believe it was real event because there is plenty of empirical
evidence proving it. There is his wife, there are wedding photos, there are
kids, there is his mother in law, and finally, he has some memories of that event. He believes this wedding was a real
event, rather than the product of his imagination, because there are many empirical facts which are consistent with the
past wedding ceremony. He cannot reproduce that particular wedding event, but there are many other reproducible
observations that support the hypothesis that wedding was real. And these indirect observations are linked to the
wedding through the chain of interpretations.
Assume now, first night, after the wedding for some reasons he goes outside on the balcony and observes an alien jumping
into the UFO and flying away. His experience was very vivid and alive, yet no one else was there to witness it, and
there were no marks or other traces of the alien left in the environment. After some time he is likely to doubt that
alien on the balcony was real (it could have been the product of his hallucination). The credibility of his experience
is low because it is not reproducible by itself and it has not left any observable traces of it. However, if there are
other people who had similar experience, perhaps in different time and different places, then his confidence in the
reality of that alien will be much higher. He may still not believe it 100% but there will be some grounds to suggest it
was real.
A point following from this discussion is that the notion of real is not black and white but can be referring to various
degrees of plausibility. Another point is that empirical evidence is always entangled with interpretations. We almost
never observe the whole object or phenomena, but only parts of it. Observable parts are then integrated into the whole
entity through the interpretation. The whole, comprising the empirical data and interpretations could be evolving with
time implying that for a given protocol the requirement of a strict reproducibility could be valid only over a certain
time period when the object is relatively stable. Despite such an ephemeral nature of that object, if there is a logical
continuity of events caused by that object and given current observations we can trace back its evolution, then we have
an empirical evidence pointing to that object in the past.
An image of the real object that emerges from these considerations is that of a collection of observations connected via
the network of interpretations (see figure below). We believe this object is real because (a) we have a reproducible
access to the empirical evidence (filled cycles) (b) this evidence is integrated with other knowledge (white circles)
into the coherent whole. The object may reside in the distant past (or it may belong to some metaphysical domain), but
as long as we can observe current evidence and link it through the chain of inferences to the past states of that
object, we take these indirect observations as justifying our belief in that object.
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 (observable) 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 in the future (rather than in the past) than we have an observable real object allocated in the future. In other
words, if we have reliable models, and make predictions (observations) that point to a particular event in the future,
then we may call it an observation of the future event.
Utility to practice
Reproducibility is an important feature of observational data but the ultimate value of observations does not come from
the fact that they are reproducible per se but from the fact that they underpin empirical knowledge, and we value that
knowledge because of its utility of to our practices. Being reproducible makes observations reliable and useful to our
practices. In other words, the key and the most important feature of observations (empirical evidence) is their utility
to our practices. If an observation is not quite reproducible but is useful, it may still count as delivering knowledge.
The same comment goes for the requirement of consistency of the empirical knowledge.
Given high value we attach to the notion of the utility, it is tempting to define observations in terms of their utility
to our practices. However, the notion of the utility is too general to be useful. Almost anything has some utility to
our lives and would pass the test (fiction story, Santa Claus, hypothesis). The definition we seek must be more specific
so that we can distinguish between real and fake storied-worlds. Note that every storied-world we considered so far has
some promises built in (e.g. salvation, or a good-life, a comfortable life, nirvana etc). I think, it makes sense to
talk about utility of these worlds in terms of the delivery of such promises.
Definition of real entity
The purpose of this section is to consolidate sporadic considerations we made so far into the definition of the real
object. We will assume the following two requirements to provide necessary and sufficient conditions for an entity to be
real:
- A logically cohesive description of an entity must exist.
-
Reproducible practices delivering features characteristic of that entity must exist.
The term “logically cohesive description” in this definition refers to a certain degree of logical coherence inherent to
the description of the real entity. In other words, the description does not have to be fully self-consistent, but a
certain degree of the consistency is required so that we can comprehend it. The entity under consideration could be
representing either the whole storied-world or some fraction of it (a particular item in that world). When the
description is restricted to a particular item of the whole, it must be not only self-consistent but also consistent
with the description the whole. The description of an entity can be expressed in the form of texts, audio messages,
algorithms, theories, images, equations etc. It may tell us the purpose and the key functions associated with that
entity and also explain how to recover features characteristic of it.
The term “characteristic features” refers to properties and attributes defining this entity. In the case of artificial
objects it can be associated specifically with the discharge of functions inherent to that entity. Most items
created by people have been created with some purpose in mind. The delivery of the goods or services associated with
such items provide an important indicator of their existential status. For example, the capacity of the clock to show
the right time is considered a feature characteristic of that clock and defining its existential status.
Reproducibility means that anyone (subject to a 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 an empirical evidence. Reproducibility implies also 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 a capacity and resources to implement these protocols and recover features characteristic of the
observed entity.
We can give a pragmatic interpretation of this definition in terms of promises built in the first part of it
(description), and practices which are meant to test these promises in the second part. The first part (promises)
provides a general description of an entity and also describes instructions to follow and goals to be achieved through these
instructions. It may promise, for example, observational data to improve prediction of a physical system, or an
immediate or mediated experience of God, or a good life, or a healthy ecosystem, or a life of samurai etc. The second
part is about practice - an application of that algorithm where we check if promises made through the description are
indeed delivered through practices.
One sticky point with this definition is that in some cases it is not quite clear which empirical evidence we take as a
proof of the existence for a particular object. In principle, everything is connected to everything, and an image of
some random wedding cake, for example, may remind you about your own wedding ceremony many years ago. Does this
observation count as an empirical evidence of your wedding? What if the image of the cake is not just any random, but it
is actually the photo of the cake taken at your wedding? Intuitively we feel that random cake does not count as an
evidence of your wedding, while the cake from the wedding does. However, after some reflection, we realise that the cake
from your wedding does not count as evidence either – you cannot take this picture to the court to prove this particular
event real. For something to be considered empirical evidence (or source of knowledge) it is not sufficient to have such
proof to yourself but it must be shared with others. The knowledge is a product of a social rather than individual
practice. Did we miss this point in our definition?
I think, the requirement of the reproducibility fills the bill on this account. An image of a random cake shown to
random people does not produce memories of your wedding – it serves as an empirical evidence of wedding events in
general. Conversely, when you show people your wedding cake with the sign on it, saying something about your wedding, it
will point not only to the notion of the wedding in general but to your particular wedding too. In this case
observational experiment is reproducible (other people can also see it was taken at your wedding) and therefore it can
be used in the court as an empirical evidence of this particular wedding event.
Another interesting point that follows from the social nature of knowledge is that (speaking Richard Rorty’s language)
to claim knowledge our beliefs must be commensurable with the beliefs of others. That commensurability builds on top of
reproducibility - it is because of the reproducible nature of the empirical evidence that we can use it as an argument
in communication with others. Reproducibility of knowledge implies qualities shared universally among all reasonable
people.
Further potential source of the controversy with this definition is due to the loose meaning of the word “cohesive”
(which we define as a certain degree of coherence). With regard to storied-worlds, we say the whole story should make
sense, but do not require full consistency of all ingredients of that story – a certain degree of contradictions is
allowed to sneak in. The problem with this account is it is not clear how much consistency exactly is enough to call
this 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, to illustrate our definition, we consider different kinds of entities and evaluate their existential
status.
A lawn mower
We have a general understanding of lawn mowers and can describe properties and key functions of lawn mowers (it is a
device which has wheels, can roll on the lawn, and can cut the grass). We may have also instructions (user manuals)
telling us how to assemble and operate a lawn mower so that by following these instructions we can test and see if the
key functions associated with lawn mowers are indeed delivered for this particular product (e.g. if it cuts the grass
– it must be real, otherwise it must be not).
Note that for particular objects, instead of asking a general question “Is this particular object real?” we can ask a
more specific and, I believe, better defined question “Does this object belong to the class of real objects of this
specific kind?”. For example, instead of asking “Is this lawn mower real?” we may have asked “Does this lawn mower
belong to the class of the real lawn mowers?”. The description would provide properties and functions of all real lawn
mowers (instead of all real objects), and practices would test if this particular instance of the lawn mower is a member of that class.
Indian Ocean
Consider the Indian Ocean. Does it belong to the class of real oceans? If we define real oceans as 3D fields of
temperature evolving according to the laws of physics, then it does - we have a description and we can test it through
reproducible practices. The only problem with this definition is it is too general and accommodates almost any 3D
object. We can fine-tune it to describes real oceans by adding extra features. For example, we can assume all real
oceans to be represented by a big pool of salty water, where you can swim, catch a fish and sail. To test the Indian
Ocean belongs to this class, you jump into the car, drive to the shore, stick a finger into the water and taste it –
it must be salty. You go fishing, swimming, sailing etc. In principle, anybody can repeat these procedures meaning that
the practices are reproducible. To summarise, we have a description of the Indian Ocean including features
characteristic of it and we can recover these features (and thus prove description) through reproducible practices - the
Indian Ocean must be real.
As an example of the fake Indian Ocean consider the video of that ocean streaming on the TV screen. Try to stick a finger
into this water – it will be neither wet nor salty. You cannot can swim, or catch a fish in such water. The Indian Ocean
on the TV screen must be not real meaning that our practices failed to prove the description of the ocean we gave
earlier.
e-particle
Take now an electron particle. We have a general description of this class of objects available from text-books on
physics. The properties of a particular e-particle could be observed through the well-defined experimental studies (e.g.
a track on the film). There is indirect evidence of these particles through various devices designed with the use of
e-particles theory (e.g. electrical devices). Practices recovering these evidence (e.g. science experiments and day to
day usage of the electric devices) are reproducible. E-particles must be real.
As an example of the fake e-particle, imagine an accidental scratch on the film in the form of a spiral produced during
the physical experiment using some sophisticated device. The physicist thinks the scratch was produced by a real
particle, while if fact it was made by the technician. To explain this scratch, the physicist first, invents a
hypothetical new e-particle and builds a new theory around it. This theory meets the first requirement of our definition
of the real object – it provides a logically cohesive description. Next, the physicists writes down the schedule for
another experiment to reproduce earlier experiment and prove this theory. However, since the scratch was made by
an accident, new
experiment will not reproduce this result. Observation of the hypothetical particle is not reproducible and, hence, the
particle is not real.
A property
Let’s consider an abstract entity, temperature, for example. There is a description of this property available from the
text-books in physics. There are established procedures telling us how to measure this property. We will assume a
feature characteristic of temperature is a dynamic nature of this property which evolves according to the
laws of physics. We have a description, instructions to follow, and the behaviour we can test through practice.
The temperature must be real.
Math
Take now theorems of the Euclidean geometry. We have a description of these theorems available from the text-books in
geometry. A feature characteristic to all these theorems is a set of self-consistent logical inferences proving them
true. These inferences are reproducible - anyone (subject to a proper education) can follow proofs and obtain the same
results. Proved theorems of the Euclidean geometry must be real entities.
A mistakenly proved theorem represents an example of the fake (i.e. not real) theorem.
Feeling of pain
Let’s consider feelings - are they real or they are not? To be specific, take the feeling of pain. We have some
description of it available from literature. It is easy to design a practice that would always provide an empirical
evidence of pain (e.g. poking your finger with a pen). The result of this experiment (i.e. the feeling of pain) is
reproducible. Hence, according to our definition, pain must be real.
Love
Take now a bit more complex phenomena such as “love”. Is it real or not? We have a general understanding of this complex
entity available either from literature or private experience.
We will assume further a feature characteristic of love is
a special feeling people have when they fall in love. Can we think of protocols or rules which would make this
special feeling reproducible? In other words, can we make someone to fall in love by following certain procedures?
I believe we can. There are rules and customs available in every culture and offering guiding principles such that
following these principles, people are likely to make someone to fall in love, and vice versa, being subjected to
similar influences they are likely to experience this feeling
themselves (with some reservations of course with regard to the health, age, social status etc).
These customs and practices are maintained by social institutions and culture.
The outcomes of
such practices (the feeling of love) are reproducible (at least statistically), so we can take it as empirical evidence
of the real entity called love. Da-da-m! According to our definition, love must be real. Good to know.
As an example of a fake love, consider someone only pretending to be in love and not having experience of this
feeling. The practice in this case fails to deliver goods promised in the description of the notion of love.
Gods
Take the notion of God. We have a general understanding of this term, typically comprising a complex network of
practices, experiences, and statements, some elements of this network referring to the future or the past. Let’s assume
a feature characteristic of that entity (i.e. empirical evidence of the God) to be the immediate and mediated
experiences of the God. These experiences are delivered via religious practices. The capacity to implement these
practices is maintained by the corresponding religious institutions. Experiences induced by these practices are
generally reproducible (subject to the proper education and training). The conclusion we reach is that God must be real
for those who believe it.
Note that one may think of the 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 the salvation in Christianity. The salvation typically
refers to the future events which we never experience for sure while alive (except, perhaps, experiences through 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 this term (salvation) means. There are instructions that tell practitioners how to
achieve salvation. They may have a capacity to implement these instructions. Can we check now that the goods promised in
the future will be indeed delivered (i.e. salvation)? I think, it depends. 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 an
indirect empirical evidence of it available right now and some web of the logically coherent inferences leading from
that evidence to the future entity (analogous to the situation we discussed earlier about the past wedding event).
Depending on how tight these logical links are (and how much you want to believe), you may consider this entity a
theoretical construct, or real object you have had empirical evidence for.
Fake Gods do not deliver promised goods (e.g salvation, Good life, nirvana etc).
Character type
Take a Buddhist as an example. We have some description of that entity based on our readings and perhaps direct
encounters with Buddhists. There are religious practices delivering experiences specific to Buddhism (e.g. meditative
states). The capacity to implement these practices is maintained by the Buddhist communities. The practice is
reproducible (i.e. with a proper training others can follow and have similar experiences).
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 behave like samurai and
do not feel like samurai, then you are probably not a samurai.
Santa Claus
Consider now Santa Claus (SC). If we take him a person who lives on the North Pole, rides flying reindeers and takes
care for Christmas presents distributing them all over the globe in one day, then such SC contradicts laws of physics.
Hence, the description of SC is not logically cohesive.
Possible worlds and multiverse theories
What about possible worlds and multiverse theories we talked earlier? Are they real or they are not? Each of these
entities and particularly multiverse theories have an elaborated fairly coherent description. With regard to special
practices delivering empirical evidence, there is some sparse data to support some multiverse theories but in general
these theories have a very weak observational support and it is not obvious how to rectify this situation. Subsequently,
possible
worlds and multiverse theories seem to represent purely theoretical constructs entertained within certain academic
circles and having little relevance to our practices. The conclusion we reach is that possible worlds and multiverses,
according to our definition, are unlikely to be real.
Storied worlds
All storied worlds considered so far (according to our definition) must be real. We have a more or less coherent
description of each storied-world. There are reproducible practices delivering empirical evidence which prove these
worlds. The capacity to implement instructions underpinning these practices is typically maintained through culture and
other social institutions.
A point to make 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 promised by these worlds, we can test if these features are
indeed delivered, and if they are, then the storied worlds must be real even if a fraction of it incorporates false
beliefs.
Storied-world multiverse
One more question which requires further elaboration is about the reality of the collection of storied worlds. Let’s
call this collection a storied multiverse. According to our definition, all storied worlds considered so far are real.
Hence, the multiverse comprising these and probably other storied-worlds must be real as well and if so then the
question is whether the definition of “real” we just introduced applies to this multiverse too? To prove this storied
multiverse real, we need to have both a logically cohesive description of it, and practices delivering empirical
evidence of this multiverse. Note that developing a self-consistent description of the multiverse is not as simple as
just postulating a collection of storied-worlds. The worlds comprising multiverse will have a shared content and we will
have to take care to resolve contradictory claims made by the inhabitants of different worlds with regard to that shared
content. We come back to this and other questions pertaining to the multiverse theory in next chapter.