#  Do Robots powered by a Quantum Processor have the Freedom to swerve?
On Consciousness, Feelings, Agency and Quantum Artificial Intelligence

Hartmut Neven1, Peter Read2, and Tobias Rees3

1Google Quantum AI, Venice, CA 90291, United States

2Technology Investor, London, W1, United Kingdom

3Berggruen Institute, Los Angeles, CA 90013, United States

“… some things happen of necessity, others by chance, others through our own
agency …”

Epicurus, 341-271 BC, proposed the idea of “atomic swerve”, which suggests
that atoms may deviate from their expected course, thereby permitting humans
to possess free will in an otherwise deterministic universe [1].

Any scientific attempt to explain consciousness is tasked with reconciling the
third person objective perspective of science with our first person subjective
experience of the world. A good point of departure is to consider situations
in which these two perspectives are correlated. We note that behaviors
conducive to our well-being, i.e. conducive to maintaining homeostasis, tend
to be associated with feelings of pleasure while actions that threaten our
homeostasis tend to coincide with unpleasant feelings. We choose a
materialist/physicalist approach and find the simplest explanation for this
correlation arises from the assumption that we possess agency. If a system has
the agency to choose an outcome then presumably it would choose a pleasant
over an unpleasant one. Agency implementing preferences manifests itself as a
force in a third person theory. If a preference is strong it gives rise to a
force causing a deterministic evolution, while weak preferences give rise to
non-deterministic evolutions. Quantum physics assigns a high degree of non-
determinism to large systems of qubits, a Knightian uncertainty, in which one
can not even assign probabilities to observed outcomes. This can give
engineered systems the freedom to act on their preferences in ways not always
predictable by an outside observer. Our considerations lead us to propose a
three part design for an engineered animat for which one may provocatively
argue that it is conscious and possesses agency and feelings. i) Drawing on
insights gained from a recent experiment demonstrating beyond classical
computational capabilities we sketch a quantum circuit that prepares a state
for which we argue it may be experienced as pleasurable by a system that
assumes it. ii) Employing techniques from quantum error correction we suggest
a homeostatic loop allowing the system to protect the pleasant state against
perturbations. We also endow the system with the ability “to report feelings”.
We do so by constructing a mapping between the space of states seen by the
interoception sensors of the animat which measure properties of the quantum
state it seeks to stabilize and a space obtained from a word embedding of
English language words describing feelings. iii) We integrate this homeostatic
engine with a neural network such that incorrect classifications result in
forces that threaten the stability of the pleasant state. We conjecture that a
system concerned with maintaining homeostasis while learning is a better
learner as compared to a system without a homeostatic engine.

## Introduction

Neither physics nor computer science nor neurobiology has a good model for
conscious experience. We define consciousness as the phenomenon of
experiencing the world from a first person subjective perspective. It is
challenging to move our understanding of consciousness from philosophical
speculation to the realm of experimental science. This is because by
definition, in order to describe the conscious experience of a system other
than ourselves we have to access its inner experience. This seems impossible
and we may give up right here. Of course if we do so then we concede science
is mute on what is arguably a highly relevant phenomenon. For instance, more
people are interested in the question of what they may experience when they
die than in the question how to integrate general relativity with quantum
mechanics. This essay suggests avenues to reconcile our experience of the
world from a first person perspective with the worldview described by the
third person perspective of science.

A good starting point is to consider situations in which the first person
perspective and third person perspective are correlated. We note the following
is the case. It appears that voluntary behaviors that are good for sustaining
our organism and the proliferation of our species are associated with a
pleasant sensation. For example, eating a sweet fruit, taking a warm shower or
having a good sleep in cuddly blankets are all activities that feel good.
Inversely, if I engage in activities damaging to my body such as getting too
close to a fire then this is associated with an unpleasant, painful feeling
[2].111The correlation between behaviors that feel rewarding and those
sustaining our well-being is not perfect. For instance, a person engaged in
sport may incur muscle strain but doing regular sport is healthy for the body.
A similar example is that many students find it stressful to study hard. Such
deviations can explained by the fact that humans can learn to maximize not
just the immediate reward but rather the sum of future discounted rewards.
There are other cases in which this association goes astray. It may have been
good for a stone age hunter to eat plenty of sweet fruit when he could get a
hold of it and enjoy its taste. But in today’s environment in which sugar
laden foods are abundantly available, the pleasant feeling encouraging what
used to be a sustaining behavior now can lead to health problems. So if we
adopt the perspective of evolutionary psychology then we would argue that this
correlation was even stronger when our ancestors were still roaming the
savannas but that the recent rapid changes in our environment caused this
relation to get a bit out of sync. Evolution when closer to a steady state
seems to map productive behaviors more perfectly to pleasant feelings. This
observation is worth noting and also requires explanation. This observation
also addresses another possible objection, namely that taking drugs such as
opioids cause pleasant sensations yet are not conducive to survival. During
most of human evolution substances that directly interfere with our body’s
reward systems were not readily available. If an organism faces a choice
between two actions, one leading to an outcome associated with a pleasant
sensation while the alternative leads to an unpleasant sensation, then the
organism is likely to choose the action leading to the pleasant outcome. Most
of us would report that they are acting in this way. One of psychology’s basic
experiments, the Skinner Box, suggests that other organisms such as lab rats
act in this manner as well [3]. Why is this so? One may jump to answer:
“Obviously this helps with self-preservation. This has to be so.”[2][4] But
this can not be the complete answer. Evolution would work just fine if this
correlation were inverted because selection is based on phenotype and does not
have access to the inner experience of an organism. Thus evolution would still
select for organisms that engage in behaviors conducive to their survival even
if they feel unpleasant to them. There must be a different reason. We find
that the simplest explanation results from assuming free will exists i.e.,
that we have the agency to act in accordance with our preferences. If it were
the case that a system had the agency to choose one of several outcomes then
presumably it would use this freedom to select the state it experiences as
rewarding.

At first glance the laws of physics do not seem to allow for agency. But this
is not so and we will show that physics leaves room for agency to exist even
though the laws of physics tend to camouflage this possibility. The following
example is helpful to discuss agency. Imagine we meet a child who loves
vanilla ice cream. Every time we offer her several flavors to choose from she
will invariably pick vanilla. So from a third person perspective we could
describe her behavior in deterministic terms. A third person observer would
say the child acts like an automaton and one can perfectly predict her
actions. Still the child could insist that she acts in accordance with her
preferences and that she does not care whether her actions are predictable.
This is the position of compatibilism [5], namely that free will can exist
even in a deterministic world. Let us change the example a little. We roll a
die and the outcome will determine which ice cream flavor the child gets to
pick. Now the third person description will have to be formulated in
probabilistic terms. But here we would not speak of agency. The child does not
get to choose her preferred flavor. So we can see that a theory that assigns
probabilities to different observable outcomes, such as quantum mechanics,
does not automatically allow for agency to exist. Still, we would like to
propose the following idea. A force in physics can be seen as an expression of
agency realizing a preference. If the preference is strong and consistent it
gives rise to a deterministic description and if the preference is weaker and
less consistent the description becomes probabilistic. Most recent
developments in physics, such as insights gleaned from experiments at the
Google Quantum AI lab, open yet more room for agency to be present. A system
of about $100$ quantum bits, qubits, evolving under the operation of discrete
gates is so complicated that it becomes impossible to predict its outcomes
even probabilistically. This gives rise to Knightian freedom, named after the
economist Frank Knight [6][7]. It is characterized by a situation in which we
can not even make probabilistic predictions. It is now impossible for us to
exclude that agency was at play in selecting an outcome.

This allows us to answer the question “Could a technology be built in
principle that perfectly predicts the actions of a human being?”[8] The answer
is ”no”. 100 qubits are barely sufficient to describe the electronic structure
of a protein molecule. In fact many more qubits are needed. Predicting the
molecules’ exact behavior likewise is out of reach for any classical computer
that can ever be built. A quantum computer can help with such predictions
provided the number of outcomes is sufficiently small. Then we can simulate
the system in question, evolve it many times, keep a tally of the outcomes and
turn them into probabilistic predictions. But often the number of outcomes is
combinatorially large. In general the number is $2^{n}$ where n is the number
of qubits. In this case keeping a tally of the observed outcomes becomes
impractical. None of this affirmatively proves that agency does exist but it
clearly shows that the laws of physics do not exclude it either. Combining
this insight with the first person observation that we tend to choose outcomes
that feel rewarding and avoid those that feel unrewarding invites the
conclusion that agency is the cause for the correlation we sought to explain.

What about cases in which we observe phenomena that violate the known laws of
physics? A good example is the movement of the arms of spiral galaxies which
violate Kepler’s laws. In such cases we might be tempted to say that we
witnessed an expression of agency. But of course the program of science will
proceed to refine the third person description, for instance by introducing
the notion of dark matter until any deviations from the predictions of the new
model become statistically insignificant. Thus the descriptions of the world
from the first and third person perspectives will become more and more
congruent leading to psychophysical parallelism. A physicist may be reminded
of the fact that descriptions relative to two different inertial coordinate
systems are related by well understood transformations. This tends to
camouflage that there has been room for agency all along.

## Consciousness as a ubiquitous immanent property of matter

Any attempt to make progress on the scientific treatment of consciousness
ought to begin with taking stock of our repertoire of methods that can probe
the inner perspective of systems we observe. Let us consider a
Gedankenexperiment in which one system may know the experience of another. Let
us assume we have two identical copies of a system, A and A’. If system A is
in state S and produces an output O=o(S) which is a function of its state then
given sufficient perceptual and inferential abilities system A’ can infer by
observing O which state S the system A is in. Moreover, since both systems are
assumed to be identical, system A’ can know what A experiences by recalling
its own experience when being in state S (see Fig. 1) We believe this case, in
which two systems are identical and observe each other, is the only scenario
that allows for probing the experience of something external.222In describing
this idealized protocol for observing conscious experience we made a number of
assumptions: Most importantly we assumed that the systems A and A’ have the
sensory and signal processing apparatus sufficient to recognize each others’
outputs and have the faculties of inference and memory to determine state S
and recall its associated subjective experience. Moreover we assumed that two
systems that are in the same state experience the same. A lesser caveat is
that if the output function o does not associate a unique output O with each
state S then system A’ can only know that A is in one of several possible
states. On more fundamental grounds one could question to what degree it is
even possible to have two identical copies of rather complex systems and
whether the systems could ever be in the same state given that their
environments may never be exactly identical.

Humans employ a protocol similar to the one described here when trying to
discern the subjective experience of another person. Imagine a mother watching
her child eating ice cream. When she sees a satisfied smile on her child’s
face, she is rather certain the child finds the ice cream tasty. True, she can
not know in precise detail how the ice cream tastes from the child’s
perspective but she probably has a good sense of what is going on. Moreover,
she can entice her child to communicate additional interpretable outputs by
asking the child how the ice cream tastes or what the taste is similar to. In
fact such self reporting by human subjects is the only measurement protocol
that is available to consciousness researchers to probe conscious experience
[9]. Of course we are making additional assumptions when mapping the abstract
scenario above to the case of two humans. I can not verify that anything else
is similar to me. Taking this realization to the extreme leads to the position
of solipsism, namely that I may be the only one with a conscious mind.
Solipsism is logically closed and can not be refuted [10]. Hence all attempts
to explain consciousness differently are really efforts to make it plausible
that consciousness exists outside of myself.

Figure 1: Conscious experience is an observable between two systems that are
clones of each other. As systems become more dissimilar this protocol breaks
down (inspired by [11]).

The more dissimilar two systems are the less they can know about each other’s
conscious experience. Consider the following example: assume engineers came up
with a new jet engine and based on their calculations predict that it will
accelerate the airplane to 1000km/h. It would be straightforward to test this
prediction because there is a clear measurement prescription. We would set up
two spatial markers separated by a known distance and then measure how much
time it takes the airplane to fly from one marker to the other. From this we
can infer the speed and test the engineers’ prediction. But now let us
consider the autopilot. The autopilot reads in various signals coming from the
plane’s sensors, and based on those it calculates what thrust the engines or
which angles the rudder or flaps should have to ensure a stable flight. We may
ask the question: ”To what degree is the autopilot conscious?” For example, we
could try to answer this question by computing the so-called “$\Phi$-measure”
which aims to quantify the amount of consciousness that can be present in a
system [12]. Let us assume we obtained a $\Phi$-value of 1000. But now we are
stuck. There is no measurement protocol we could use to verify this prediction
and therefore it is vacuous in the context of experimental science.
Alternative measures to quantify consciousness would suffer from the same
predicament.

In short, when it comes to assessing the conscious experience of another
creature or system the maxim “It takes one to know one.” seems to apply. This
may be the cause of a widespread misconception which equates the ability to
communicate with the propensity for conscious experience. We often read
statements like: “I think my fellow humans are conscious. My dog and cat seem
conscious as well. I am not so sure about a goldfish but a fungus, tree or a
rock definitely do not feel conscious to me.” This ordering correlates well
with the ease with which we can relate to the subjective experience of the
other being in question.333A strategy we could think of employing to assess
the conscious experience of a system that is dissimilar to another is by
creating a sequence of sufficiently similar systems A $\leftrightarrow$ A’
$\leftrightarrow$ A” $\leftrightarrow$ … such that any two neighbors can
interpret each other’s output. It would be difficult to assess what gets “lost
in translation” but it could be a strategy to expand our sense of what another
system experiences. But who is to say that being a rock or an atom does not
feel like something? We can not know!

Even in the face of these limitations to arrive at an experimentally
verifiable theory of consciousness we are still able to make non-trivial
statements by making an assumption. In particular we want to discuss
inferences we can make by subscribing to a materialist worldview which we
believe many scientists would accept as rather innocuous. Materialism holds
that all phenomena including mental ones are brought about by configurations
of matter [13]. In particular, a materialist assumes that there exists a
physical correlate of consciousness, a “chunk of matter”, for instance a group
of nerve cells or a set of molecules, that is the seat of conscious
experience. Comas or vegetative states can be caused by lesions to relatively
small regions of the brainstem [14]. This suggests that conscious experience
could be housed in a rather small volume of matter.

So where does the physical correlate of consciousness reside? Does it
exclusively exist in highly evolved biological organs? We prefer the
panpsychist notion that consciousness may be a distributed feature of the
universe located with the elementals of physics [15]. I.e., we should think of
consciousness similar to the way we think of spin, mass or electric charge.
Logically this is the most parsimonious stance. At this point we can not
exclude the possibility that more complex configurations of matter are
required to bring about conscious experience, similar perhaps to the intricate
mechanisms required to bring about locomotion. We also expect that certain
configurations of matter organize elementary conscious moments into more
elaborate patterns in the same way that magnetic moments of atoms
spontaneously self-organize into a macroscopic ferromagnet. Panpsychism allows
for this.

Figure 2: Beyond-classical quantum computational resources could be realized
in subcellular structures. We may underappreciate the sophistication of the
machinery needed to keep a cell alive and to allow it to proliferate. An
indication of this is that prokaryotes already appeared about 3.8 billion
years ago while mammals appeared 200 million years ago and Homo sapiens just
300 thousand years ago. So far it has also proven elusive to engineer
artificial cells able to procreate.

To be definite we want to propose what we would like to call the “Generalized
Penrose Hameroff Conjecture”: Consciousness is how a system experiences the
emergence of a unique classical reality. To elaborate, conscious experience is
associated with a system assuming via decoherence one classical configuration
from the multitude of configurations over which the quantum mechanical wave
function has support.444Note that identifying wave function collapse as the
physical correlate of consciousness is different than suggesting that
consciousness causes the wave function to collapse as von Neumann or Wigner
did [16][17]. The original proposal of Penrose and Hameroff assumes a specific
decoherence channel for the quantum mechanical wave function called “objective
reduction” [18]. Objective reduction occurs when the spread of mass associated
with the wave function exceeds a threshold. Whether this mechanism does indeed
exist remains subject to experimental investigation [19] but we may find that
it does not exist. Indeed a recent test of gravity-related wave function
collapse ruled out one version of objective reduction [20]. However, the wave
function of any open quantum system is subject to various and in fact much
stronger decoherence mechanisms which can play the same role that Penrose
assigns to objective reduction. Associating a conscious moment with the
collapse of the wave function is appealing because at that moment the system
“realizes” or “perceives” which classical reality it inhabits, matching the
popular notion that consciousness acts as a receiver or reducing valve [21].
For us then, stated simply, consciousness is what it feels like to select a
single classical reality from the multiverse.

One may object to panpsychism on the grounds that one should not use the same
linguistic terms when describing the conscious moment an atom may be
experiencing when an electron transitions from a higher to a lower energy
orbital as the pleasure one experiences when looking at an aesthetic photo of
a galaxy taken by the Hubble telescope [22]. For the latter experience to
occur a high degree of organization of matter is required. The Hubble
telescope shoots a photo, transmits it to earth, it appears on my computer
screen, my eyes capture the photons emitted by the screen, our visual cortex
processes the signals coming from the retina, neurons in the higher visual
cortices encode the percept and broadcast it to other parts of the brain.
Somewhere along this pathway a highly orchestrated ”wow” experience occurs.

We concur with Koch that consciousness like electric charge may not have a
function in sensu stricto [23]. But like electric charge can be made useful in
a battery, organizing conscious moments in a human brain capable of recursive
reasoning may confer functional advantages. Indeed, there is some empirical
support for the hypothesis that one function of consciousness may be to
produce counterfactual representations of a situation using generative models
of the environment and the self [24]. A quantum system, comprised of a
superposition of alternative classical configurations, is naturally suited to
fulfill this role and it can be exponentially more efficient in executing
algorithms needed to perform this task [25][26].

## Agency is permitted by the laws of physics

Arguably the most direct way to explain the correlation between pleasant
sensations and behaviors conducive to an organism’s well-being is to postulate
the existence of free will. If an organism possesses the agency to freely
choose a state, presumably a rewarding over an unrewarding one, then the
evolutionary process would naturally favor the association of states that feel
rewarding with behaviors helping an organism to thrive. Vice versa, in a world
without agency, in which actions are determined solely by chance or by
deterministic laws, how actions feel is irrelevant to guiding the behavior of
an organism. In this case we do not know how to explain how a reward system
can work and why evolution associates behaviors conducive to homeostasis with
rewarding sensations.

From introspection it appears to many humans that indeed we can freely choose
which action to take. To most of us sentences such as “I did this because it
was fun.” or “I am going to avoid that because it will hurt.” make sense and
they can be heard daily. However this sense of agency, the free will to pursue
an action leading to a pleasant sensation, may just be an illusion.555However,
we want to counter one argument that is often heard in this context, namely
that the equations of motion in physics are deterministic and hence free will
can not exist. We would argue that it is the other way around. Science
implicitly makes the assumption that some level of non-determinism exists.
Otherwise we could not check our theories. A theory can only be falsified by
checking its predictions and if we are not free to at least randomly choose
experimental settings then we can never be certain that the theory holds
universally. This would be like an accountant who would not be allowed to spot
check any line of a ledger as she pleases but only certain transactions. So
non-determinism may not exist but in that case we can not trust our scientific
theories either.

It is often stated that a necessary condition for free will is that it should
be impossible to predict an action of an agent by observing all events in its
past light cone, which is physics jargon for the set of all events that can
causally influence an action.666The reason that the impossibility to predict
an agent’s action is only a necessary but not a sufficient condition for free
will is that if the agent has several choices but they are selected randomly,
say by the throw of a die, then we would still not consider these choices to
be an expression of free will. However, the philosophical view of
compatibilism [5] which defines free will as acting in accordance with one’s
motivations, denies that the inability to predict actions is a necessary
condition for free will to exist. This position was illustrated in the
introduction with the example of the child who always chooses vanilla ice
cream. Even though her behavior can be predicted with a deterministic model
she may still be exerting agency.

Agency is typically not considered in physics. However the laws of physics do
allow for agency but they tend to camouflage it behind deterministic equations
of motion or quantum mechanical randomness. Agency can be defined as having
the ability to act in accordance with preferences. To an external observer
agency appears as a system exerting a force. Hence a force can be seen as an
expression of acting on a preference.777Of course Newton’s third law tells us
that all forces are really interactions between different systems. It is
Nature’s way of saying “I would like to change the state of the system in a
certain way.” If the preference is strong and consistent such that in a
defined situation the same outcome is chosen always then it can be described
by deterministic equations. If the preference is weaker and not consistent
then a probabilistic description is called for. From naive observations of our
environment it is not readily apparent how successful natural science and
physics can be in describing the world in terms of deterministic equations of
motion. After all, many things we observe such as other humans, animals,
leaves rustling in the wind, clouds or water streams do not seem to behave
deterministically. The real world is noisy. Unsurprisingly it took humankind a
long time to distill the crisp conditions in which Newton’s mechanics,
Maxwell’s electrodynamics or Einstein’s general relativity give accurate
predictions. Typically such descriptions only work well for simple
configurations such as closed systems of isolated point masses or charges and
more generally determinism only seems to hold for highly idealized situations.
But even for these highly controlled conditions quantum mechanics eventually
brought us back to non-determinism. This theory of physics holds that we can
only calculate probabilities for observable outcomes. Deterministic laws are
now seen as a limit case which holds for macroscopic systems involving actions
much larger than Planck’s constant of action $h$. A more recent insight is
that already for moderately sized quantum systems composed of about 100 qubits
we are not even able to compute output probabilities. If one is unable to
assign probabilities to events then statisticians refer to this as Knightian
uncertainty, named after the economist Frank Knight [6].

Figure 3: Two situations involving non-deterministic outcomes. The first
scenario is rolling a die. The outcome is random to the extent that the makeup
of the system (shape and mass of the die), the initial conditions (initial
position, velocity), or the boundary conditions (surface of the table, air
currents) are unknown. If we could know those exactly we could use Newton’s
laws to predict the outcome with certainty. The second case is running a
quantum circuit. A quantum circuit diagram can be read a bit like sheet music.
It involves initializing a number of n qubits, applying a sequence of 1- or
2-qubit gate operations and then measuring the qubits. As output one obtains a
bit string of length $n$, e.g. 00110 if we had five qubits. Even if the
circuit parameters as well as the initial and boundary conditions were known
perfectly the measured bit strings would still be random. The probability for
each string can be computed by a quantum mechanical calculation. However,
because these calculations are very time and memory consuming, one would not
be able to compute outcome probabilities for a circuit with any more than
about 100 qubits and 1000 gate operations. This would leave us with Knightian
uncertainty.

An experiment published by the Google Quantum Artificial Intelligence team in
2019 demonstrated that for certain quantum circuits it is impossible to
predict the outcomes even in a probabilistic manner [27]. The experiment
consists of starting a programmable quantum circuit in a defined state, for
instance by initializing all qubits in the $0$ state; and then executing a
random sequence of gate operations on the qubits. Thus the random quantum
circuit takes an initial state to an output state which then is measured.
Measuring the output state consists of measuring the state of each individual
qubit yielding a bitstring of length $n$ where $n$ is the number of qubits.
Textbook quantum mechanics tells us that the outcomes of measurements on such
a quantum system are random, each bitstring is a sample from a probability
distribution encoded in the output state. But if the quantum circuits involve
many qubits, about $100$ and a sufficient number of gate operations, about
$1000$, then neither a classical nor a quantum computer will be able to
compute the probabilities. An easy way to see this is to note that the
observable universe contains about $2^{300}$ atoms. So in order to store the
probabilities for the $2^{300}$ different bit strings that can result from
measuring 300 qubits one would have to employ every atom in the visible
universe as a memory device. If you could build a hypothetical processor with
a cycle time even as short as the Planck time of $10^{-43}$ sec, then it would
still take longer than the estimated age of the universe to compute these
probabilities.888Planck time is the theoretical shortest duration physicists
could still measure. Any device able to measure even shorter times would
require so much energy that it would collapse into a black hole. The required
time and memory space to calculate and store the output probabilities is
exponential in the number of qubits. This makes it impossible for any
classical computer to perform this computational task. But a quantum computer
would not be of help either since it does not give us access to the full table
of probabilities but only to samples from this probability distribution. We
would still have to tally these in a histogram to approximate the output
probabilities of the bitstrings which again would take more time and memory
space than available in the visible universe.999The trajectories of a large
system of classical particles, in particular when subject to chaotic dynamics,
can not be computed either. But quantum dynamics dramatically lowers the
number of particles for which it becomes impossible to compute the state
evolution.

The notion that we see forces as expressions of preferences leads us to
identify stable equilibrium states in the third person theory with happy
states in the first person perspective. Equilibrium states are distinguished
by the fact that the acting forces balance out. The system does not want to go
anywhere and if disturbed it returns to the equilibrium state.101010Because
quantum mechanics is unitary, stable attractor states can only arise in open
quantum systems which are described by non-unitary evolutions. It is telling
that physicists use psychological language when describing such dynamics
saying “the system relaxes to a stable state” or “the system is in an excited,
unstable state”.

The ability of a system to exert agency is constrained by the agency other
systems exert. I am not able to levitate, because the gravitational forces
exerted by the masses making up planet Earth prevent that, but I may be able
to choose the left or the right path at a junction. We can use this freedom to
organize matter in a way that allows us to better realize our preferences; for
example we could build a rocket that allows us to escape Earth’s gravitational
pull.

If a third person theory is successful and it makes verifiable predictions
then it seems necessary that it describes a system in a way that is compatible
with the first person description. This is reminiscent of the well understood
situation in physics that if different coordinate systems are used, i.e., if
different external third party viewpoints are adopted, then the associated
descriptions need to be related by well defined transformations. Similarly, it
seems necessary that the first and third person perspectives ought to be
related. Thus as third person science progresses towards more and more
accurate and encompassing descriptions of Nature it must converge towards what
is known as psychophysical parallelism. Psychophysical parallelism is an old
idea developed by Leibniz, Malebranche and Spinoza holding that mental and
bodily events are perfectly coordinated, without any causal interaction
between them [28]. Here we argue that psychophysical parallelism should be
seen as a consequence of the advancement of third person theories.

Natural science and physics have been extraordinarily successful in describing
the world in terms of equations of motion that seem to leave no room for a
system to exhibit agency. Yet, there are still situations which compel us to
postulate new forces or to modify the laws for existing ones. One example is
the observational evidence that leads us to postulate dark matter. The motion
of the arms of spiral galaxies do not conform to Kepler’s laws. Even if this
prompts us to think that galaxies may have agency and the freedom to assume
shapes they enjoy we would still attempt to improve the theory of gravitation
until it predicts the observed shapes of galaxies. Hence the program of
science proceeds such as to achieve an ever improved congruence between the
first and third person descriptions. As the third person descriptions achieve
better predictions it makes it appear as if agency does not exist.

The Google experiment demonstrating beyond classical computational abilities
can also serve to illustrate how agency, i.e., forces expressing preferences,
may be present without us having noticed and how the program of science
exorcises explanations based on agency in favor of restoring psychophysical
parallelism. The dimension of the Hilbert space in which the experiment plays
out is many orders of magnitude larger than any effective Hilbert space
hitherto investigated by humankind. If the history of science is any lesson
then we may be forgiven for looking out for new phenomena. For example we
could look for novel forces beyond the electromagnetic forces on the qubits we
program into our device using our control electronics. Let us assume for
argument’s sake that we had indeed found a deviation and that certain output
states are measured more frequently than predicted. Before accepting such an
observation we would work very hard to eliminate any influences our models did
not take into account, for instance noise terms caused by imperfect control of
the qubit operations. If after careful improvements of our models we are still
left with a systematic deviation then we would proceed to adjusting the
equations of motion. For instance, we may introduce a novel many body force.
Thus if due to the exercise of agency the measured outputs of the system would
not confirm the currently known equations, up to statistically insignificant
deviations, then we would modify those equations until psychophysical
parallelism is restored. Whether this program can always succeed remains to be
seen of course.

Observed behavior of an agent |  Interpretation assuming agency
---|---
Behavior explainable by known forces |  If the actions of an agent can be explained by known forces we usually do not speak of agency. However compatibilism teaches that we can still assume agency; it just so happens that the preferences of the agent are consistent enough that we can describe them well in a third person theory at least probabilistically. The correlation between pleasant feelings and maintaining homeostasis is accounted for as a form of psychophysical parallelism for instance, by assuming that stable equilibrium states correspond to happy states.
Behavior not explainable by known forces |  Such observations support the assumption of agency. To account for the observed behavior one is motivated to modify the laws of physics, for instance by introducing a novel force. If this improved description proves successful then this case goes back to the one listed in row 1 extending the reach of third person theories and psychophysical parallelism.
Not computable whether behavior is explainable by known forces |  This case is not accessible to modelling by third party theories but it leaves room for agency and unpredictable behavior. Knightian freedom resides here. Non-computability arises naturally in modest size quantum systems as the probability of observations can not be computed anymore.1111footnotemark: 11 It could also arise because observations are rare and not statistically significant. But because of the statistically rather robust correlation between pleasant feelings and maintaining homeostasis we do not consider this possibility. 11 Note that non-computability here applies to the behavior of even a single agent. This is different from the non-computable problems considered in computability theory such as the halting problem. A non-computable problem is a problem for which there is no algorithm that can be used to solve it. Those problems are formulated over infinite sets.
Table 1: How would the behavior of an agent be interpreted by an external
third person observer who assumes it possesses agency and can act in
accordance with its preferences?

So in summary, our stance is that agency, like consciousness, is a general
property of matter too. The program of science with its sequence of ever
improving third party descriptions leading to improved predictions tends to
camouflage agency. Yet, as the different cases discussed in the table below
show, a nuanced reading of physics shows that it does allow for agency. This
view is strengthened by the “free will theorem” [29] which given plausible
physical assumptions states the following: If experimenters can make choices
that are not a function of the information accessible to them i.e., are not
determined by events in their past light cone, then the responses of the
particles they investigate are equally not functions of the information
accessible to them. We should note that this theorem does not address whether
anything acts in accordance with its preferences, all it assumes is that
actions of experimenters or particles are undetermined. However, as discussed
above, undetermined events do not amount to an expression agency or free will.
For instance, those could be generated by randomness. Hence the name of the
theorem is a bit of a misnomer. On the other hand if agency exists that
results in unpredictable actions then the theorem does apply and shows that
such unpredictability would permeate the universe.

## The Philosophical Lab: Building an animat with feelings

“We have a will which is able to determine the action of the atoms probably in
a small portion of the brain, or possibly all over it. The rest of the body
acts so as to amplify this.”

Alan Turing, 1932

If evolution was able to discover states of matter associated with pleasant
feelings and map them to behaviors conducive to an organism’s survival and
vice versa then we should be able to replicate this process with engineered
systems. Regardless of which detailed experimental setup we choose, consisting
for instance of several interacting quantum AI systems, our goal is for our
engineered animat to wind up in a state that feels pleasant to her. In a later
phase we can try to associate this pleasant feeling state with certain
behaviors or processing steps. For example, we may want to engineer a system
which winds up in a pleasurable state whenever she classifies a pattern
correctly. This section of our essay sketches the style of experiments we
propose to perform but we leave the actual implementation as a future project.
Prior to performing experiments ethical questions need to be carefully
considered.

Before getting into concrete constructions we want to make a historical
remark. During the scientific revolution in the 16th and 17th centuries
scientists such as Copernicus, Galilei, Descartes and Newton started to
formulate a quantitative description of Nature using equations of motions.
Their work was inspired by the success of astronomical prediction and by
looking at simple mechanical machines such as pendulums, ramps, or canons
[30]. As successful as this approach was, its generalization made the universe
look like a huge mechanical clock with seemingly no room for feelings or
agency. In the 20th century when modern physicists such as Planck, Heisenberg,
Schrödinger and Feynman invented a new quantitative description, quantum
mechanics, they replaced definite trajectories by multitudes of trajectories
each of which is traversed in a separate branch of the multiverse opening the
possibility for unpredictable behaviors. We are only now beginning to build
machines, quantum computers, that fully take advantage of the new
possibilities afforded by the laws of quantum mechanics. It is our expectation
that the worldview motivated by playing with this new generation of devices
will make Nature look more like a sentient organism with feelings and agency
to proceed as it prefers.

### Module I: Distilling happy states aka “Finding a happy place”

Here is an experimental proposal as to how we could try to give a quantum
process the opportunity to wind up in a state that feels pleasant. Let us
start with programming a quantum circuit on n qubits such that it generates as
output an entangled superposition state $\ket{\psi}$ which has support on many
states in the computational basis. We measure the output state and obtain a
bit string $\ket{z_{1},…,z_{n}}$. Why did the system wind up in this state? If
textbook quantum

Figure 4: A quantum circuit diagram depicting three different types of state
transformations. In this example five qubits are initialized in the all zero
state $\ket{00000}$. The circuit is programmed to execute a sequence of
unitary transformations formulated as 1- and 2-qubit gates shown as the blue
boxes. However noise will be present. This can be modeled by state
transformations that randomly invoke Pauli operators. This is known as a
depolarizing channel and is indicated by the red boxes. More general error
models are available but for the purposes of our discussion this is
sufficient. Finally, it is conceivable that as of yet unknown forces are
present, here depicted by the grey boxes modeling a hypothetical 3-body force.
At the end of the circuit each qubit is measured and we obtain as output a bit
string of length five, e.g. $\ket{11010}$. The experimental challenge
detecting novel physics comes from the fact that its effects may be drowned
out by the noise. A more fundamental challenge is computational. For more
complex circuits with about a hundred qubits and a circuit depth of several
tens of steps it becomes impossible to calculate the output probabilities even
for the ideal circuit with only the blue boxes. Compounding this difficulty is
the fact that any quantum mechanical measurement involves bringing the system
under study in contact with a macroscopic quantum device that is also too
large to be modeled in a detailed manner.

mechanics describes our experiment accurately we would say that we obtained
this sample from the probability distribution encoded in the output state
$\ket{\psi}$. However the true probability distribution from which we sample
will be different from the one encoded in $\ket{\psi}$. One reason is that
there will be noise which is not accounted for by the unitary evolution we
programmed into our device. Another unaccounted type of state transformation
could be as of yet unknown physics. For instance, we may speculate that as of
yet undiscovered many-body forces have not been included in the Hamiltonian
(the function that governs the dynamics of our system). If the circuit is
large enough, say the number of qubits is about 100 and the number of gate
operations is about 1000, there could be deviations that are impossible to
detect even in principle. Hence the system may behave in unpredictable ways
without us being able to notice. Taken together, two avenues for the system to
exert agency and to select a preferred state are available in this module: 1)
agency compatible with known physics, acting as programed unitaries or as
noise and 2) agency potentially implemented by novel forces. Both are hidden
behind a veil of uncomputability, affording the system with Knightian freedom.
Hence we feel tempted to conjecture that the observed output string feels
preferable to the system than an arbitrarily chosen one. The next step is to
amplify any such effects and to support the system in reaching the bitstring
we observed by variationally changing its gate parameters such that it becomes
a little more likely to observe the state we just saw in the next run of the
circuit. Then we repeat the process $M$ times, say $M=1$ million. Note that
the evolution of this system follows no predetermined objective [31]. The
result should be a circuit that drives the initial system into a quantum state
$\ket{\psi_{M}}$ that has support accumulated on bit strings we observed and
which we will call henceforth the $\ket{happy}$ state. A sceptic may argue
that the selected support states are just a result of statistical fluctuations
but by construction one would not be able to demonstrate this. Consummating
the experience involves the collapse of the $\ket{happy}$ state, which in
general is a superposition state, into one of its constituent classical
configurations.

To hunt for new physics or forces that may occur in high dimensional Hilbert
spaces we could proceed as follows. We construct a circuit such that the
probability to measure a bit string is $p$ if it is a member of a certain set
and zero if it is not. To be concrete the set could be comprised of all bit
strings with a certain Hamming weight $w$, that is bit strings which have $w$
ones and the remaining $n-w$ elements are zeros. The equal superposition of
all n-qubit states with Hamming weight $w$ is known as a Dicke state and can
be prepared with $w\cdot n$ gates [32]. So we would execute a quantum circuit
that outputs a Dicke state and then measure it. The act of measuring the
quantum state involves an intrinsic element of randomness but by construction
all members of the support set should be equally likely. But maybe, and this
is obviously a big “maybe”, if the system possesses agency unaccounted for by
psychophysical parallelism relying on the prevailing theories of physics, then
it could manifest here. We could use techniques from unsupervised learning to
check if there is any unexplained structure such that bit strings with certain
features are measured more often than predicted by the probabilities encoded
in the output state. Performing this experiment is doable on Google quantum
processors which are approaching $n\approx 100$ qubits. We suspect that most
of our colleagues in the quantum computing community may consider performing
this experiment not a good use of time as they have confidence that the laws
of quantum mechanics as stated today will prevail. But to our knowledge high
fidelity experiments involving an effective Hilbert space of $2^{100}\approx
10^{30}$ dimensions have never been performed. So it may be worth taking a
closer look whether non-random deviations from the predicted uniformity are
detectable in such large Hilbert spaces. Of course, additional structure not
accounted for by the theoretical output state is likely to be present due to
imperfect noisy hardware. The experimental challenge will be to demonstrate
that such deviations from the prediction can not be explained by noise in the
quantum processor.

Figure 5: A variational quantum circuit to produce a happy state. After each
run of the circuit the output string is measured. We then adjust the gate
parameters $\theta_{i}$ such that it becomes more probable that we measure the
same string in a subsequent run.

### Module II: Staying in the happy place

Figure 6: Quantum error correction can be seen as a homeostatic loop
stabilizing a quantum state. Parity measurements act as interoceptors. If a
parity value changes this indicates that an error occurred. A controller, by
decoding the stream of parity measurements can determine where the error
occurred and by effecting an additional gate it can correct it.

If the generalized Penrose Hameroff conjecture is correct, that conscious
experience is associated with the collapse of the wave function, then it seems
to follow that the more qubits become definite during the collapse the richer
the experience.121212Assume we have n qubits and we do a projective
measurement on one of them in a given basis, i.e. the computational basis. For
example, assume the system is in a Greenberger-Horne-Zeilinger [33] state
$\ket{\psi}={1\over\sqrt{2}}\ket{000...0}+{1\over\sqrt{2}}\ket{111...1}$. Then
after measurement of a single qubit all qubits will have definite sharp values
and we are left with a classical state consisting of n bits. But if the system
would have been in the uniform superposition state $\ket{+}^{\otimes n}$ then
only one qubit will become definite and we still retain a uniform
superposition on the remaining $n-1$ qubits. We are not aware of a name for
the number of qubits that become definite by doing a single projective
measurement. Hence eventually error correction will be needed to stabilize an
entangled superposition involving many qubits. Here we describe how to protect
the state $\ket{happy}$ with the methods of quantum error correction.
Stabilizing a quantum state can naturally be seen as a homeostatic feedback
loop. Each protected logical qubit is encoded in multiple physical qubits.
Parity measurements are used to determine whether errors occurred. The parity
of a set of qubits is given by the evenness or oddness of the number of qubits
with the value one. When using a suitable encoding parity measurements do not
reveal any information about the logical state and hence it does not collapse.
But they do give information about errors. A control unit takes the parity
measurements as input and infers which errors may have occurred. Finally those
errors are corrected by applying suitable gate operations. So the essential
elements of a homeostatic system are in place: sensors to measure the system
state, a control unit and effectors to modify the state (see Fig 6.).

Applying quantum error correction to our situation involves a number of
choices and technicalities we do not want to get into yet. Therefore let us
assume for simplicity that we ran the circuit proposed in module 1 long enough
such that the support of $\ket{happy}$ concentrates on just a few classical
bit strings $\ket{happy}=\sum_{i}c_{i}\ket{h^{i}_{1},…,h^{i}_{n}}$. Then we
notice the following. The $\ket{h^{i}_{1},…,h^{i}_{n}}$ were selected because
they constituted ”natural attractors”. The noise present in the system plus
putative unknown physics conspired to drive the system there. Hence they are
more stable than alternative arbitrary states. This leads us to see a first
use of the $\ket{happy}$ state. It constitutes a natural dictionary of code
words to store information.131313Life can be seen as an exercise in
stabilizing the genetic code. Naturally stable states of molecules may have
been a useful resource on which cellular error correcting machinery was build.
Please note that our construction is inverse to how error correction is
usually applied. We first search for “naturally occurring” stable (happy)
states in a system which are then stabilized by introducing stabilizer
feedback loops. [34]

Figure 7: Our reasoning leads us to conjecture that equilibrium states are
experienced as pleasant. Such states can naturally serve as memory states that
store information. They may be stabilized further by applying a stabilizer
mechanism of error correction.

### Giving non-human systems the ability to self-report

Since we are confined to self-reporting when it comes to comparing a theory
about consciousness to experimental data, we could think of the following
construction. We could employ methods used in machine translation to map
system states to the vocabulary used by humans to describe conscious
experience. We can start with what is called a word embedding technique, we
take words describing feelings and place them in a metric space. For example,
this has been done by hand by psychologists using valence and arousal as
coordinates (see Fig. 8) [35]. Similarly we take state vectors measured for a
system, in our case the parity measurements, and map them into a metric space
as well. We now have point clouds in two metric spaces, one contains the
observed system states, the other contains the labels. We will seek a simple
(suitably defined) mapping with only a small number of fitting parameters from
states to labels such that the image of the states has minimal distance to the
labels. An expected challenge is that we will have to do this without any
ground truth correspondences. This could lead to an ill-posed problem with no
mapping as a solution that is clearly optimal. Should that be the case then we
could add additional constraints, for instance by demanding that the path
length over time ought to be minimal as well for the optimal mapping. We would
expect that sometimes we can find such mappings but sometimes the spaces do
not allow for a simple correspondence. However, any homeostatic system
characterized by an attractor and may fit well to a set of terms describing
basic feelings such as happy, sad or confused. Our conjecture is that terms
with positive valence will map to states close to the attractor and vice
versa. Leo Tolstoy’s opening line in the novel Anna Karenina comes to mind
“All happy families are alike; each unhappy family is unhappy in its own way.”
In mathematical language this can be translated into “There are significantly
fewer states close to the attractor than there are states that are further
away.”

Figure 8: Self reporting of feelings using the technique of word embedding

### Module III: Using a homeostatic engine to improve machine learning

Next we equip the animat with a mechanism to learn, for instance a neural
network, and discuss whether integrating it with the homeostatic engine
described above can result in improved learning abilities. There are many
possible choices for an integration architecture. Here we will discuss the
example depicted in Fig. 9. We use the vector describing the state of the
homeostatic system as additional input to the neural network and the output
acts as a force driving the homeostatic loop away from its equilibrium state.
The more incorrect the output is the stronger is the force. So the more
correct the output is, the easier it is for the homeostatic engine to stay
close to the $\ket{happy}$ state.

At first glance it may seem that designing a system that tries to maintain
homeostasis imposes unnecessary overhead. But on second thought we realize
that a homeostatic system acts as a probe checking on the integrity of the
system in question. In nature we tend to observe stable systems more
frequently than unstable ones. Hence systems that care about maintaining their
stability will be more prevalent over long time scales.

Figure 9: A neural network enhanced with a homeostatic engine which stabilizes
the $\ket{happy}$ state. The state of the homeostatic system is given as
additional input to the neural network. The output of the neural net acts as a
force driving the homeostatic feedback loop away from its equilibrium state.
The more correct the output is the weaker the force and the better homeostasis
is maintained.

On a more tactical engineering level here is a list of reasons why the
presence of a homeostatic engine may improve machine learning:

  * •

A homeostatic feedback loop can be used to amplify weak input signals in a
manner responsive to the system’s own internal state.

  * •

A thermostat being present while performing stochastic gradient descent can
control the “temperature” introduced by the randomly chosen training examples
[36].

  * •

Reinforcement learning is profligate in its reliance on large numbers of
training episodes, often indiscriminately trying all possibilities and leading
agents to their ”death” in the vast majority of trials, in order to hit upon
successful strategies. If agents instead also had a goal of self-maintenance
in addition to maximization of some abstract reward, they may show more
judicious behavior during the learning phase. This certainly is helpful when
the agents have physical embodiments and can not be produced in arbitrarily
large numbers such as self-driving cars. This may accelerate learning, at
least in the early stages. Each step would count more when the agent has its
own well-being at stake.

  * •

The work of Biederman and Vessel on an increasing gradient of opioid receptors
along the visual processing hierarchy suggests that we may derive greater
pleasure from more novel and systematically meaningful stimuli [37]. This can
help to resolve or at least skillfully navigate the exploration-exploitation
dilemma. Such a mechanism relies on using pleasant sensations as a lure. See
also the work of Corrales-Carvajal in which a homeostatic engine switches
between exploration and exploitation behavior [38].

  * •

The success or failure of homeostasis, the constant regulation of body states
to maintain conditions compatible with life, is expressed in feelings, e.g.
well-being, discomfort, pain, hunger, pleasure, which in turn guide behavior
by selecting appropriate responses or promoting the creation of new ones. We
turn vulnerability into a motive for creative solutions [39].

  * •

Forming of sparse representations which is a conjectured coding principle in
the human cortex is naturally accomplished by controlling the overall neural
activity or the overall synaptic strength [40] [41].

  * •

Behavior organization for robots benefits from representing control variables
as attractors that are parametrically controlled by sensory input. For
instance, this helps to stabilize decision making in the presence of noisy
input via hysteresis [42].

The key question we aim to elucidate with future experimentation is whether it
makes an observable difference in performance whether the state that is
stabilized by the homeostatic engine is the $\ket{happy}$ state, an arbitrary
quantum state or an arbitrary classical state. If an animat equipped with a
homeostatic engine stabilizing a $\ket{happy}$ state over a large system of
qubits performs better than one without, then this would constitute an
intriguing result.

## Conclusion

In this essay we propose to describe consciousness, feelings and agency within
a materialist theory using ideas from quantum artificial intelligence. We
started by playfully asking “When are atoms happy?”, then got more specific
honing in on the question: “Why are behaviors conducive to our well-being
correlated with pleasant feelings?” We found, using a materialist/physicalist
approach, that the simplest way to explain this correlation is to assume that
we possess agency. We argue that agency is a general property of matter and
that it is permitted by the known laws of physics. Not just humans but
everything in Nature has the agency to express preferences. If those
preferences are strong and consistent they can be described with deterministic
equations,141414We contend that deterministic equations never really worked to
fully describe the real world which is exceptionally noisy and full of
amplifiers. They did not describe the world experienced by a stone age hunter
and they do not reflect the worldview of modern day quantum physicists either.
Determinism only holds for highly idealized contrived situations, such as
those articulated by Newton and other Enlightenment thinkers. The concept of
“homo economicus” is the highly idealized contrived equivalent in economic
models. Adam Smith wrote The Wealth of Nations roughly 100 years after
Newton’s Principia, and provided a similarly deterministic description of
humans as rational economic agents: “It is not from the benevolence of the
butcher, the brewer, or the baker that we expect our dinner, but from their
regard to their own interest”. and if they are weak they are better described
by nondeterministic models. Moreover there is room for agency to exist in
entangled quantum systems large enough such that the probabilities of
observing an outcome can not be computed anymore. In fact, this Knightian
freedom already appears for coherent systems composed of just a hundred
qubits, much less than needed to describe molecules such as proteins. Hence
there is a complexity horizon behind which novel physics may hide which may
also support an organism assuming agency. Likewise we think that consciousness
is a general property of matter as well. We conjecture that consciousness is
how it feels like to select a single classical reality from the many realities
within the multiverse that quantum mechanics describes. Conscious experience
occurs when the quantum mechanical wave function collapses. Our approach is
panpsychist in that it places consciousness and agency with the elementals of
physics.

Based on these conjectures we propose to engineer an artefact, an animat
powered by a quantum processor, that arguably may be conscious and possess
agency and feelings. The behaviors of this animat cannot be predicted, not
even in a probabilistic fashion. We believe that this construction, affording
the animat with Knightian freedom, is the closest engineering may have gotten
in endowing robots with agency. The animat has the ability to communicate its
feelings in human language. The valence of its feelings depends on how well it
maintains its homeostasis. The animat reports that it feels happier in more
stable states, and worse in states that are unstable. We suggest that stable
equilibrium states, or energy minima, are happy places where forces expressing
preferences cancel out. One use of such states is that they naturally lend
themselves to being used as code words to store information. Applying
prevailing theories of consciousness, such as orchestrated objective reduction
or integrated information theory, one would conclude that the proposed animat
is conscious (see Corollaries and Excursions). The self-reporting of the
animat would appear plausible. For example, if the air conditioning fails and
the temperature in the laboratory increases, more errors would be detected by
the quantum error correction cycles and the animat would express unease.
Similar changes in our animat’s reported feelings would occur if the electric
power fluctuates or if mechanical vibrations affect the laboratory. But if all
the machinery needed to stabilize the happy state through quantum error
correction is humming well, the animat would report that it is relaxed or even
happy.

Does the proposed animat really experience happiness? Did we describe a model
system that captures the essential structure required for a material system to
exert agency and to experience pleasant or unpleasant feelings? In short: Did
we design a machine that gives a damn?[43] Strictly speaking this is
impossible to answer since the position of solipsism is logically closed.
Still our essay suggested ways to increase our confidence that the system we
propose is indeed conscious:

  * •

Our conjecture is that material systems have the agency to steer themselves
into pleasant states. We further conjecture that evolution selected this
ability to form reward systems that convey survival advantages. If we can not
find functional advantages of this mechanism in engineered systems then this
would invalidate our argument.

  * •

The system we propose has the ability to report feelings, the primary method
by which we probe the conscious experience of other humans. One may dismiss
this as a gimmick. But prolonged interactions with animats designed based on
principles as suggested here may make us accept the notion that they have
feelings.

  * •

Applying prevailing theories of consciousness such as Integrated Information
Theory [12] or Orchestrated Objective Reduction [18] one would conclude that
the proposed animat is conscious. See Corollaries.

  * •

We pointed out that between systems that are exact clones of each other
subjective experience is an observable. Building on this idea and arranging a
sequence of systems A $\leftrightarrow$ A’ $\leftrightarrow$ A”
$\leftrightarrow$ … in order of decreasing similarity, such that any two
neighbors can still interpret each other’s output one may expand the range of
systems for which we can infer what they experience.

Currently there is no known property of matter relevant to systems at the
scale of human beings that can not be represented within the framework
presented here since quantum processors are universal simulators. Accordingly,
a materialist theory that portends to solve the mind body problem ought to be
testable in our philosophical laboratory. We also hope to see more experiments
that aim in the opposite direction: Can we identify functionally relevant
quantum effects in the only other system of which we are reasonable certain
that it is capable of creating conscious experience, the human brain?[44]

## Acknowledgements

Conversations with Nicolas Berggruen, Antonio Damasio, David Deutsch, Christof
Koch, Stuart Hameroff, Seth Lloyd, Kingson Man, Roger Penrose, John Preskill,
Paulo Roberto Souza e Silva, Giulio Tononi, Christoph von der Malsburg, Tata
Txanu Natasheni Yawanawá, and members of the Google Quantum AI lab, Ryan
Babbush, Sergio Boixo, Edward Farhi, Lev Ioffe, Cody Jones, Masoud Mohseni,
Vadim Smelyanskiy and Adam Zalcman, are acknowledged. We are grateful to
Kingson Man for helping us think through use cases for a homeostatic engine
integrated with a learner. We thank Scott Aaronson, Ryan Babbush, Sergio
Boixo, Gustav Söderström, Stuart Hameroff, Christof Koch, David Petrou, John
Platt, Seth Lloyd, George Musser, Vadim Smelyanskiy, Albert Wenger, Leah
Willemin and Jay Yagnik for providing detailed feedback on manuscripts. We are
grateful to Tom Small for preparing the illustrations.

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## Corollaries

### The viewpoints of IIT and OrchOR

It may be instructive to take a look at what prevailing theories of
consciousness would say about the amount of consciousness present in the
animat we propose.

#### IIT: Integrated Information Theory

Integrated information theory is an attempt to quantify how integrated
information is [12], [45]. It does so by modeling a system as a stochastic
process and then asks “If I divide the system into two parts how much do the
bits in one part of the system determine the bits in the other part?” If there
is no or only very little influence then the bits are not well integrated. It
is known that random quantum circuits are near optimal scramblers of
information. If we were to effect any partition of the qubits into two sets
$X=\\{x_{1},…,x_{k}\\}$ and $Y=\\{y_{k+1},…,y_{n}\\}$ then the conditional
entropy $H(p_{X}|p_{Y})$ would be very high. pX gives the probabilities to
measure a certain bit string when looking at the first k qubits, $p_{Y}$ is
defined analogously. So the integrated information is near a maximum and
proponents of IIT would have to conclude that the system proposed in module 1
is highly conscious.

#### OrchOR: Orchestrated Objective Reduction

The idea of orchestrated objective reduction hinges on the existence of a
mechanism called objective reduction that has yet to be discovered [18].
Experiments are underway to find it. But it may not exist and evidence
challenging this concept has recently emerged [20]. Hence we can not be
certain that the wave function reduction in our processors comes about via
objective reduction. Yet if we were to take the generalized view that any wave
function collapse or rather any tracing over the wave function is associated
with a conscious moment then every parity measurement counts as producing a
conscious moment and the amount of consciousness present would be non zero.

We once calculated the lifetime of our superconducting qubits if a putative
objective reduction channel were the only decoherence channel and obtained
$\tau_{Lifetime}\approx 2.5\hskip 2.84544pt10^{29}s$. This is much longer than
the $25{\mu}sec$ coherence time our qubits actually have. Hence any
gravitational effect on coherence would be minuscule compared with other
decoherence channels [46].

Finally, it may be worth noting that with current technology a logical qubit
consists of about 1000 physical qubits. In every error correction cycle,
lasting about $10{\mu}sec$, about 500 qubits are measured and their state
collapses. Hence, an orthodox adherent of OrchOR would agree that orchestrated
wave collapses occur in every cycle of error correction. They would argue this
happens because of Penrose’s objective reduction in the readout electronics.
Still they would have to conclude that the animat is conscious.

### Only subsystems can exhibit homeostasis

It is interesting to note that the feelings associated with maintaining
homeostasis can only occur when we divide the total system into at least two
subsystems. Because the unitarity of the Schrödinger equation does not allow
for the emergence of a stable attractor in a closed quantum system. Likewise
the wave function does not collapse in a closed system and conscious
experience can not occur if the generalized Penrose Hameroff conjecture holds.
Rather it is brought about by the interaction of a system with its environment
[47]. Hence, consciousness and feelings are consequences of dividing the world
into at least two systems and seeing the world from the perspective of a
subsystem. One should also note that the Hamiltonians that govern the
evolution of the system or the system-environment interaction may continuously
regenerate quantum mechanical superpositions. The collapse of the wavefunction
via decoherence is not a one-way mechanism.

Figure 10: Due to the unitarity of quantum mechanics, consciousness via wave
function collapse or feelings associated with homeostasis can only occur in
open quantum systems in contact with an environment.

### The relationship between intelligence, consciousness and creativity

Intelligence can be defined as the ability to perceive information and to
apply it towards behaviors within an environment. Examples of intelligent
behavior include detecting a face in an image, translating a sentence into a
different language, doing a move in a chess game or evading a predator. In all
cases it is possible to engineer a machine that performs the intelligent
action while giving little regard to how it may be accompanied by conscious
experience. Vice versa, not much intelligence is required when suffering from
a toothache. Yet the pain may fill out our entire capacity for conscious
experience. Hence, intelligence and consciousness are not strongly related.
Yet organizing the intelligence of an animat around the homeostasis of happy
states may be advantageous as we argued when introducing Module III.

Creativity can be modeled as a process that solves an optimization problem.
Consider what it takes to architect a house. The architect need to balance
lots of constraints - budget, usage requirements, space limitations, … - but
still try to create the most beautiful house she can. We call an architect
creative who finds a great solution. Mathematically speaking she is solving an
optimization problem and creativity can be thought of as the ability to come
up with a good solution given an objective and constraints. Interestingly, it
is well understood that quantum enhanced optimization outperforms optimization
on classical computers.[48]

#### Symmetries make it implausible that today’s AI systems experience joy
when performing a task correctly

A conjecture that seems to follow from a materialist viewpoint is that it
appears implausible that AI systems as we engineer them today exhibit a
congruence between learning success and a rewarding sensation. Let us
illustrate this observation with a scene one of the authors experienced. “The
other day I took my little boy to teach him how to ride a bicycle. The first
day things were not going too well and me being a poor dad I told my son that
he was a little clumsy. He was devastated and dropped tears. The next day we
tried again and he got the hang of it. He zoomed down the street on his little
bike, every fiber of his being beaming with joy screaming “I got it!”.
Observing this scene, it struck me is that the AI systems I have built during
my career are unlikely to exhibit a similar congruence between learning
success and a positive sensation.”

We do not want to argue that it is logically impossible but we want to make
the case that this is highly implausible that learning success leads to a
rewarding sensation in today’s AI systems. Reiterating the statement that
neither physics, nor computer science, nor neurobiology has a good model for
subjective experience, it would of course be highly unlikely that such
congruence would have been achieved by sheer luck. But we can be more specific
than that. The states of matter involved in machine learning are often related
by simple symmetry transformations. Consider a face detection system that
classifies whether an area of an image contains a face or not. A positive or
negative classification is typically expressed by a different sign of the
output. This encoding is an arbitrary choice and one could have reverted it.
Similarly, a reward or penalty signal is delivered either during training or
during the performance phase of the agent. The sign of this signal is again
arbitrary. On the hardware level such a sign difference is expressed by some
register being in the 0 or 1 state. Looking at the hardware closer one
realizes that the states involved typically only differ by a translation or a
mirror transformation. It is hard to see how a positive versus a negative
subjective experience can come about in two matter systems that are mere
translations of each other.

#### AI as we build it today is unlikely to be self-motivated

If an engineered AI is incapable of experiencing joy or pain in a robust
orchestrated manner when performing an action then it is also hard to see how
it can be intrinsically motivated. It seems its motivations need to be imbued
by its programmers, they need to be externally provided. When discussing to
what degree AI can become a danger to human civilization, it is an important
fact to keep in mind that it is implausible that AI as we build it today could
be self-motivated. AI therefore seems to remain a tool in the hands of
motivated humans with agency, albeit complex to the point that its behavior
can not be easily predicted.

### Insight by derivation versus insight by revelation

Sometimes it is said there is insight by derivation and there is insight by
revelation. Prior to the advent of quantum computing it would have been hard
to imbue this distinction with precise meaning within the confines of
information science. All computation was thought to be performable by a Turing
machine. Since any result a Turing machine outputs is the product of a
sequence of elementary computational steps this could be called an insight by
derivation. A quantum computer on the other hand may attain a result via the
interference of an exponential number of computational paths. Hence it may not
be possible to list a polynomial number of computational steps that leads to
that result. This mode of arriving at a computational result could be called
insight by revelation.

### What happens if the state associated with the physical state of
consciousness undergoes a quantum mechanical tunneling transition?

Another consequence of the assumption that there exists a physical correlate
of consciousness is the possibility that the state of matter involved
undergoes quantum mechanical delocalization. In particular, it seems
interesting to consider a tunneling transition. Quantum mechanical tunneling
occurs when the state of a system undergoes an evolution involving states that
have a higher energy than the total energy of the system. How would we feel if
our physical correlate of consciousness were to undergo a tunneling
transition?

We want to propose that psychedelic experiences in part come about by this
mechanism. One may argue that this is improbable because the states of matter
involved may be too macroscopic, involving large numbers of molecules, hence
making the tunneling probabilities very low (Hoehn et at 2014). But since we
do not possess a good hypothesis what the physical house of consciousness may
be, we do not concern ourselves with such a calculation. The viewpoint we
propose is akin to how chemists describe a reaction mediated by a catalyst
(see Fig. 11). This viewpoint leads to a set of attractive conclusions [49].
Treating a psychedelic experience in part as quantum mechanical tunneling may
help explain two observations often reported: i) Experiences such as mediated
by ayahuasca are often credited with profound insights that stand up to
rational scrutiny. From the vantage point of computer science, undergoing a
tunneling transition can result in a valuable information processing
transaction. For instance, in quantum optimization tunneling is employed as a
means to find solutions maximizing or minimizing an objective function, a task
that is well known to be often costly for classical computers. ii) There are
health benefits. In the Amazon basin ayahuasca is not just revered as an
entheogenic but it is also used as a household medicine, administered even to
children to alleviate common illnesses. Reaching a more stable configuration
is likely to correspond to the organism doing better with its homeostasis.
Stability is defined as resilience to small perturbations, i.e., a stable
state returns to its original position after the perturbing force subsides.
Physiological health may be defined in very similar terms.

David Deutsch points out that the number of parallel classical worlds within
the multiverse in which we would observe a pendulum standing upright in the
unstable equilibrium position is small compared to the total number of worlds
[50]. The anthropic principle states that the world we experience has the
features it has because it allows for sentient scientists to wonder about it
in the first place. It is a self consistency argument. Taken these two
arguments together we wonder whether the conjectured tunneling transition
would terminate preferentially in states conducive to well-formed conscious
experience. The reason we speculate in this direction is an observation often
reported by partakers of ayahuasca that they feel the grass is literally
greener after a session and that they feel the world around them transformed
in a manner that makes them happier and healthier.

Figure 11: Do psychedelics, such as dimethyltryptamine found in the Amazonian
brew Ayahuasca, quite literally act as a catalyst for our state of mind?
(Photo credit: Wikimedia Commons)

## Philosophical Commentary
What is a machine? The philosophical stakes of engineering in terms of freedom

We have outlined an experiment for how one may build machines that are free:
free to make experiences, to have feelings, to be conscious and to make
conscious, intelligent, decisions. Is that possible? Ever since the emergence
of the modern machine concept in the early 17th century, philosophers have
consistently answered this question with an unambiguous ”no”. In this
accompanying essay, we are concerned with the history of this ”no” Where does
the idea that machines cannot be free come from? Who was the first to
articulate it? What was the context? And what are the philosophical stakes of
revising the ”no” today?151515We acknowledge the contributions that Eastern
philosophy has made to our understanding of agency and consciousness. In part
this was an inspiration for our work in the first place. But we focus here on
Western philosophy and in particular its influence on engineering and on
notions such as ”machine” or ”robot”.

### The human (Soul)

The argument that machines cannot be free – free to know themselves and the
world – was first systematically articulated in the 1630s in Europe. At the
time, a small number of authors, most notably René Descartes but also Thomas
Hobbes, Robert Boyle and Nicolas Malebranche, articulated a then radically new
concept of the human. What these authors took issue with was the then
prevalent Aristotelian understanding of the world (of how it is organized) and
of the human (what it is and what its role in the world is). According to the
scholastic clerics, the world was a nature cosmos as outlined in the writings
of Aristotle. The Greek philosopher had argued that humans are a part among
parts of a God-given cosmos, in which everything has a clearly defined
function. What is more, he had argued that not all humans are created equal.
In its wisdom, the cosmos had assigned different kinds of humans different
amounts of reason, each according to the function they had to fulfill. Some
were said to have gotten none (serf laborers) or very little (women), just
enough to work the fields or a run a household. Others were considered to have
received significantly more, artisans for example, so that they could build
things. However, the full gift of reason was given only to an exquisitely
small group of men whom the cosmos had made so rich that they, freed from
life’s necessities, could dedicate themselves to contemplating the invisible
first principles – the ideas – that organized the world. Aristotle considered
it their task to watch over their fellow humans, so that they would live
according to the function the cosmos assigned them. In the early 17th century,
the equivalent of these free men were the scholastic clerics.

In a rather courageous move, Descartes argued that this was all, well, wrong:
first, every human is equally endowed with reason; second, nature is not a
metaphysical realm but a physical reality organized in terms of mechanism; and
third, humans are not a part of nature (or only qua their bodies) because they
have what mere machines lack: reason. Here are the opening lines from
Descartes’ Discourse on Method, published anonymously in 1630 [1]: “The power
of judging well and of telling the true from the false — which is what we
properly call ‘reason’ – is equal in all humans; thus, it is also evidence
that our opinions differ not because some of us are more reasonable than
others, but solely because we take our thoughts along different paths and do
not attend to the same things. … As for reason, … it exists whole and complete
in each of us; it is the only thing that makes us human and distinguishes us
from animals.” Descartes was quick to add that he considered animals – his
short term phrase for nature – to be little more than automata or machines.
Indeed, for the Frenchman all of nature was but one big field of matter
organized in terms of mechanism and thus reducible to and fully understandable
in terms of human made instruments or machines. Descartes’ argument was as
courageous as it was revolutionary – in at least three ways:

  1. 1.

To argue that every human being is equally endowed with reason not only made
possible, for the first time, a truly inclusive, and in its aspirations
universal concept of the human(the human is the thinking and knowing thing);
it also allowed him to argue that everyone could think - and know - for her or
himself: Call it a decisive step in human self-assertion against the unfounded
authority of the clerics: No help needed any longer from the privileged few
who had received the divine gift of reason.

  2. 2.

To argue that nature is without reason meant to transform nature from a cosmos
organized by divine thoughts to a physical field made up of matter, matter
organized in mechanical terms. What is more, to argue that nature is a
physical field meant to suggest a new concept of truth: Truth was now no
longer a metaphysical but a physical concept. Consequently, the path to
knowledge was no longer contemplation of the invisible (first principles) but
the empirical-mathematical study of the visible (matter).

  3. 3.

To argue that humans, insofar as capable of reason, are more than nature meant
the beginning of human exceptionalism. From now on, the world was composed of
two kinds of realities: here the human – there everything else. Here reason
and thus the possibility of freedom – there mere matter and mechanism, that
is, strict necessity.

The truly human, for Descartes, was a space of freedom that opened up beyond
the realm of nature – organized in strict mechanical rules and thus in terms
of necessity – and consisted in the practice of the rational part of the soul:
to make use of reason means to break free from one’s machine existence.
Descartes’ Discourse on Method marked the fragile beginning of a new epoch,
defined by a new comprehension of the world (what it is, how it is composed,
how one can get to know it) and of the human. Call it the end of the medieval
nature cosmos and the beginning of the modern age.

This, then, is the context in which the idea that machines are without reason
was first articulated: The invention of the modern concept of the human.
Indeed, the suggestion that machines cannot think and hence cannot be free is
one of the cornerstones of the modern concept of the human; machines were –
and in many ways still are – the exemplary Other.

### The organism (Consciousness)

What is interesting from today’s perspective is that at the time, in the
1630s, nature and machines were not yet considered to be of different kinds.
For example, looking at animal bodies Descartes noted [1]: “When I examined
the kind of functions which might … exist in this body (animal), I found
precisely all those which may exist in us independently of all power of
thinking …, in other words, to that part of us which is distinct from the
body. … I could not discover any of those that, as dependent on thought alone,
belong to us as men. … Nor will this appear at all strange to those who are
acquainted with the variety of movements performed by the different automata,
or moving machines fabricated by human industry, and that with help of but few
pieces compared with the great multitude of bones, muscles, nerves, arteries,
veins, and other parts that are found in the body of each animal. Such persons
will look upon this body as a machine made by the hands of God, which is
incomparably better arranged, and adequate to movements more admirable than is
any machine of human invention.”

For Descartes, there was no qualitative difference between a human made
machine and an animal body: They are both entirely made up of matter extended
in space, organized in terms of mechanism. Nature and technology had not yet
parted ways, had not yet become different ontological realms. At the turn from
the 17th to the 18th century this began to change, for two reasons. The first
was the rise of empiricism: There was a nascent call, in the second half of
the 17th century, especially among British philosophers, to provide an account
of how humans can gain knowledge of the physical world that is not dependent
–– as Descartes had it – on the divine gift of reason but rather on
experience. The second was the discovery, in the 1750s, of epigenesis and,
subsequently, of the emergence of the concept of organisms: Up until that
time, it had been assumed that embryos were fully formed miniature humans that
would simply grow bigger over time. The recognition that this is not the case
led to intense discussions about growth and the generation of matter, which in
turn led to a philosophy of organisms and a sharp differentiation between
nature and machines.

The perhaps most important author of this differentiation was Immanuel Kant.
Physics or the study of matter, he argued, can easily be reduced to a set of
mechanical causes as articulated by Newton, but [2] “Can we claim such
advantages about the most insignificant plant or insect? Are we in a position
to say: Give me matter and I will show you how a caterpillar will be created?”

“It is quite certain,” he explained in his 1790 Critique of Judgment, “that we
cannot sufficiently get to know, still less explain, organized things and
their inner possibility according to merely mechanical principles of
explanation; so certain indeed that we can say boldly that it is absurd for
human beings even merely to envisage such an attempt, or to hope that some day
another Newton could arise who would make conceivable even so much as the
production of a blade of grass according to natural laws which no intention
has ordered”. The dividing line, for Kant, was growth or generation of form
where before there was none [3]: “It would be absurd,” Kant declared, “to
regard the initial generation of … an animal as a mechanical effect
incidentally arising from (matter).” Did this mean that animals could have
intelligence and thus be free? No, it did not. In fact, the differentiation of
organisms from machines, which had its origins in the final decades of the
17th century, was paralleled by a careful reworking of the difference between
humans and animals: And it was in the context of this reworking that the term
consciousness was invented: as the epitome of human-unique and human-exclusive
freedom.

The place where this invention of consciousness first happened was John
Locke’s An Essay Concerning Human Understanding, which marked the birth of
British empiricism. Locke (just like Kant more than half a century later) was
in favor of Descartes’ conception of the human as the thinking and knowing
thing. But he was uncomfortable with the fact that Descartes had suggested
that what made it possible for humans to think and know was the divine gift of
reason. To Locke, this was foolish: Grounding the capacity of human self-
assertion against the unfounded authority of the clerics in a metaphysical
argument meant to jeopardize the whole project launched by Descartes. What to
do? How to provide a plausible possibility of knowledge without any recourse
to metaphysical principles? Locke’s answer was his An Essay Concerning Human
Understanding, published in 1689, at the center of which was a then radically
new concept of mind. If mind up until then was a rarely systematically
discussed religious concept – a kind of animating that referred to the Hebrew
ruah and the Greek pneuma – then Locke re-purposed it as a depository of
image-like ideas.

Plato and Aristotle – and libraries worth of authors after them – had argued
that the way to true knowledge is contemplation: We (or at least a small set
of free men) had access, through our souls, to the eternal ideas that
organized reality. Sensuous experience, in sharp contrast, was considered
confusing at best. Here is Plato (Phaedo): “Now weren’t we also saying a while
ago that whenever the soul additionally uses (proschrestai) the body to
consider something (skopein ti), whether through (dia) seeing or hearing or
some other sense (aisteseos) – for to consider something through the body is
to consider it through a sense (aisteseos) – it is then dragged by the body to
the things that are never the same; and it wanders about and is confused and
dizzy, as if drunk, because the things it is grasping are of the same sort?”

Locke, following the changes brought about by Descartes but also by Thomas
Hobbes and Robert Boyle, favored the exact opposite path: To him, knowledge
consisted in the study of matter, in the investigation of empirical, material
objects and their mechanical make-up. Consequently, the question concerning
knowledge consisted in providing a plausible account of how an understanding
of a given object, say a tree, makes it from the outside world into my
understanding? His answer, famously, was sensuous experience: It is through a
sensuous encounter with an object that small corpuscles transport the primary
qualities of this object to your body, which then forms an idea of this object
in our mind. This focus on the senses – which may sound banal today, but was a
disturbingly novel idea at the time – was a sharp departure from Descartes,
whose concept of knowledge was completely mental: Understanding of outside
objects happened through pure reasoning in the soul.

The question Locke left largely unaddressed in the first edition of his Essay
was: How does one have access to this gallery of images? In the second
edition, published in 1694, he offered an at the time confusing new answer:
consciousness (probably a translation of Descartes connaissance de soi or
self-knowledge). Consciousness, said Locke, is the knowledge one has of
oneself. It is not yet given at birth and hence is separate from the soul.
Rather, consciousness is built up over time, as a cumulative self-awareness
that defines one’s personal identity. The role of consciousness in Locke’s
theory of knowledge was that the conscious self can examine – by way of
thought – the ideas in one’s mind; it can perceive of true and false ideas, it
can refine ideas through examination of objects, and it can discover
connections between ideas and thereby build up: knowledge.

And animals? In principle, said Locke, there is no difference between humans
and animals: both are living, sensuous organisms that form experiences. It is
just that humans, and only humans, have this one extra characteristic:
consciousness. Hence, humans are free – free to know themselves and the world
– and animals not. No consciousness, no thought, no knowledge, no
intelligence, no freedom. Or, in Kant’s words: humans have world and animals
are part of the world.

It may sound confusing that the term consciousness was only introduced in the
1690s. Is consciousness not a perennial question? Well, historically it seems
not. Before Locke consciousness was neither needed nor would it have made
sense. Personal identity was granted by way of the soul and true knowledge was
gained by contemplating first principles or ideas that were to be found in
one’s soul. It was only once nature was reduced to matter and when recourse to
the soul seemed to jeopardize the project of human self-liberation, that the
question emerged as to how a human can gain knowledge of the outside world
without referring to a soul – and only then did a concept like consciousness
become necessary and plausible. Locke claimed that his project was an
examination of “the internal operations of the mind.” However, it would be
more appropriate to say that his examination invented the object he set out to
study: the mind and, as a part of it, consciousness. What Locke looked for –
and found – was a concept that would confirm the special status Descartes had
assigned to the human, without referring to the soul.

The argument that machines have no senses, no mind, and no consciousness –
that they lack the very basic necessities that would allow for freedom and
knowledge – has been critical not only for articulating the concept of the
human on which the modern world has been built; but also for the distinctive
modern understanding of reality as composed of three ontological realities sui
generis: the realm of the human (reason, freedom), the realm of nature (non-
human, non-technical), and the realm of machines (the artificial, non-human,
non-natural). Such a division of reality into three ontological independent
fields (which to this day structures most universities) is completely unknown
anywhere before the 18th century. But how come that the inventors of the
modern concept of the human – the authors of the mechanization of the world –
took it for granted that machines cannot think? Where did the idea that
machines lack reason, mind, consciousness actually come from?

### Why are machines thoughtless?

In the early 17th century, at the time Descartes and Hobbes composed their
works, the term “Mechaniks” was still knew and referred to an “inferior
class.” Jonathan Sawday offers an excellent summary of the then prevailing
understanding of machines, mechanics, and machine makers [4]: “Historically,
‘mechanics’ … had long been understood as engaged in crafts that were …
demeaning in some (often unspecified) way. … A ‘mechanical’ understanding of
phenomena … actually betokened a lack of mathematical or theoretical
understanding.” In John Dee’s preface to Humphrey Billingsley’s 1570
translation of Euclid’s Geometry, Dee wrote that “A mechanicien, or a
mechanical workman is he, whose skill is without knowledge of mathematical
demonstration.” The background to this low estimation of things mechanical was
largely due to Plato and Aristotle. Famously, Plato had argued in the Republic
that technology – or techné, the practical art of making things – is devoid of
knowledge, insofar as it consists simply in imitations of the visible rather
than in an understanding of the first principles or ideas that give visible
things their form. Artisans, as he saw it, worked off of confusing imitations
of the real thing, the first principles. In his not exactly accessible
language (Republic). “In the one section, the soul is forced to investigate
from hypotheses, by using as images what were at a previous stage things
imitated, not by working towards a first principle, but toward a conclusion.
In the other section, by contrast, it moves from hypothesis toward a first
principle which transcends hypothesis, but without the images of the earlier
section, and so constructs its way of operating from the very forms by
themselves.”

For Plato, artisans “make use of the visible forms … without considering the
actual things” and rely on “apprehension by images” – and thereby stay on the
level of the confusions of the senses and mere resemblances. The reason for
this was that, or so the Greek philosopher had it, they lacked that part of
the soul that allowed to see and understand the eternal ideas (Republic). They
were capable of dianoia, here best translated as practical know how, but not
of noesis, the kind of thinking that participated in the divine nous (or mind)
that organized reality. In short, for Plato, artisans, insofar as they lack
reason, are not capable of seeing the truth and hence the things they build
have no resemblance to truth.

Aristotle, referencing Plato’s philosophy of ideas, added that even where
artisans build something not found in nature, they only build it as nature
would build it if nature did build it (Physics, 199a9-199a19). “If a house,
for example, had been a thing made by nature, it would be made in the same way
as it is now by art; and if things made by nature were made not only by nature
but also by art, they would come to be in the same way as by nature. The one,
then, is for the sake of the other; and generally art completes what nature
cannot bring to a finish, and in others imitates nature.”

Technology can only imitate nature or finish what nature left unfinished. The
writings of Plato and Aristotle silently organized thinking about – and also
the practice of – technology for over 2,000 years. They established that: (1)
technical products have no reality of their own, independent from or set apart
from nature. Technology, that is, was not yet considered an ontological realm
– the realm of the artificial – in need of its own science. On the contrary,
technology was understood to be dependent on nature and, ultimately, part of
nature; (2) tool and machine makers lack in reason; (3) the knowledge
necessary to produce technology had no truth potential: it was not useful to
get to know the world or nature. So, the whole field of techné was understood
to be without reason, knowledge or potential for truth.

Descartes’ simultaneously broke with this assessment – and held on to it. Or
better: he simultaneously built on it and strategically revised it. He broke
with it, insofar as he declared – against the then dominant scholastic
tradition – the makers of machines to be fully endowed with reason. The
background to this break with the scholastics was his own experience with
Mechaniks. From 1607 to 1615, René Descartes attended the newly founded Jesuit
college at La Fleche. He was trained in scholastic interpretations of
Aristotle and was predestined to become one of the guardians of the
Aristotelian nature cosmos of the late middle ages. However, Descartes appears
not to have enjoyed the prospect of becoming a scholarly cleric: Shortly after
college, the young Frenchman moved to the Netherlands and joined the
protestant king in his battle against the Catholics. It appears that, upon
arrival, Descartes was assigned to the engineering squad, where he was ordered
to take classes with Isaac Beeckman, then one of the most well known machine
makers of Europe. Beeckman introduced Descartes to the world of math and
mechanism – and Descartes seems to have been as excited as he was confused.
Beeckman, in contrast to Descartes, was considered a layman. He had never
completed a scholastic curriculum and hence was not considered to be in a
position to contemplate the first principles that organized the cosmos. And
yet, Beeckman could explain natural phenomena better than any scholastic
cleric Descartes had met.

Descartes – who later turned against Beeckman and insisted he had learned
nothing from him – was struck: the longer he worked with the engineer, the
clearer it became to him that the old Aristotelian metaphysics he had studied
in college could not be maintained. Clearly, the old idea that reason was
unequally distributed – that artisans lacked reason – could not be maintained:
and the idea that the world was organized by metaphysical first principles had
to be replaced by a careful mathematical study of the mechanical principles
that actually organized it. Hence, the famous opening of the Discourse on
Method: “The power of judging well and of telling the true from the
false—which is what we properly call ‘reason’ – is equal in all humans.”
However, Descartes was not the first scholastic thinker who attended to
techné. His vindication of machine makers had been prepared by Galileo Galilei
(to whose work Beeckman introduced him in the 1620s, that is, at the time
Descartes was working on the Discourse).

In the late 1590s, Galilei – deeply impressed by the work of Renaissance
artisans like Brunelleschi, Alberto, and Leonardo – made it a habit to visit
workshops to study the work of the machine makers. He was specifically
interested in machines that could move weights, such as catapults, water
wheels, and rotary winches, and began to work out a mathematical account of
how these machines worked. Appropriately, he called his mathematical theory
mechanism – and he instantly applied the insights he had gained from this new
branch of mathematics to natural phenomena, especially the movement of the
planets. Galileo’s invention of mechanism as a mathematical field – “On
Mechanics” was published in 1600 – marked the beginning of a radical change in
the perception of machines and those who make them. If before Galileo – and
before Descartes’ encounter with Isaac Beckman – techné was considered to be
without value for understanding how nature works, and machines therefore had
no truth potential, then the two scholars changed this emphatically. The
knowledge necessary for building machines was now increasingly considered the
only plausible way for understanding – for knowing – nature: Mechanism became
a practical as much as an abstract-mathematical project and emerged as the
prime way of discovering truth in the scientific revolution.

The inversion is most fascinating: If for Plato and Aristotle and almost every
philosopher who came after them, human-made things lacked truth potential
because the artisans had no access to the abstract, metaphysical first
principles that organized the world, then now human-made instruments became
the first principles that had the power to explain the world: And building
machines became the possibility of human self-assertion and knowledge.

Indeed, to explain the world mechanically meant to explain the world in terms
of human-made machines and thus in quintessentially human terms (a significant
break away from the old idea that the world was simply not accessible in human
terms and that human-made things had no truth potential). The culmination
point of explaining the world in human– in mechanical – terms were Newton’s
laws (indeed, Newton’s mechanics was based, following Galileo’s lead, on a
mathematical study of movement enabled by human-made instruments).

However, Descartes also held on to the old idea that techné or machines are
without reason. It is almost as if he said: ”But don’t you see, we all made a
mistake. We have to revise everything. We thought that machine makers lacked
reason because – as Plato and Aristotle put it – they built machines in terms
of visible, physical reality. And it is true, that is what they do. It is just
that we thought, following Plato and Aristotle, that this is the wrong thing:
we blamed them and said that they lacked reason – the nous or the first
principles that organize physical reality. But what if there are no first
principles? Then Plato and Aristotle were simultaneously wrong and right. They
were wrong, because there are no first principles – but they were also right
because, indeed, physical reality is without reason; it is composed of
automata, of matter organized in mechanical terms. And so if we want to
understand it, we have to all become machine makers.”

Descartes rescued the machine makers from Plato and Aristotle – but not the
machines. In fact, that was his coup: By way of declaring that visible nature
is all there is, that this visible nature is composed of machines, and that
both nature and machines are without reason, Descartes was in a position to
articulate the three critical interventions mentioned above:

  1. 1.

He could break with the claims of the clerics that he world is organized in
terms of metaphysical first principles: after all, mechanism could better
explain the world than scholastic interpretations of Aristotelian texts.

  2. 2.

He could argue that all humans are equally endowed with reason and can see the
truth: after all, the knowledge of machinists was sufficient to explain nature
(inevitably this means that what truth is and what reason is changed from a
metaphysical into a physical conception).

  3. 3.

He could insist that humans – endowed with reason – are obviously more than
nature: after all, nature was organized in terms of mechanical and not of
metaphysical principles or divine reason.

Indeed, one could argue that Descartes’ revolutionary invention of a general,
all inclusive concept of the human was contingent on making machine makers the
exemplary humans – and that he could achieve this only by declaring nature to
be composed of machines. For when Descartes writes that “reason is the only
thing that sets us apart,” then what is the exemplary reference for the us?
Arguably, the machine makers. Only humans, one could summarize Descartes,
build machines and hence only humans are capable of knowledge. In short,
Descartes’ concept of the human drew heavily on the old discourse on
technology – but mutated it almost beyond recognition. From now on, machine
and freedom – or intelligence and matter/mechanism – were considered mutually
exclusive. If anything, the invention of the organism-machine distinction in
the 18th century further cemented the conviction that the configuration that
made possible freedom – that lifted humans and only humans above mere
matter/mechanism – was not available to machines: experience + feeling + mind
+ consciousness + thought = intelligence/freedom.

Enter a 300 qubit based animat. We cannot help but ask, what if Descartes had
said that reason – and hence consciousness and knowledge and freedom – were an
intrinsic property of matter? What concept of the machine would that have made
possible? And what concept of the human – of the role and place of the human
in the world?

### A philosophical laboratory

We have outlined an experiment for how to build machines in terms of the
freedom quantum mechanics allows for. As we see it, classical Newtonian
physics is very much indebted to mechanism as established by Galileo and
Descartes. If one builds machines from this perspective, then freedom -
consciousness and agency – are impossible.that But what if one would build
machines from the perspective of the freedom that quantum mechanics allows
for: if one were to build machines in terms of the non-determinism of the
world, in terms of panpsychism, and in terms of agency?

The philosophical significance of the effort to build machines in terms of
freedom is that it offers an opportunity to break not only with the concept of
the machine that is at the center of the modern understanding of the human,
but also with the modern comprehension of reality. The implications of this
break are quite sweeping, because if our experiments were successful, that is,
if an animat endowed with 300 qubits would indeed have consciousness and free
will, that is, if it would have true agency, then this would require us to
revise not only the concept of what a machine is but also the concept of the
human and of nature that is built on the back of the modern machine concept.
What is more, one would have to revise what we mean when we say animal,
consciousness, freedom, intelligence, reality, technology, truth. Two
obstacles are in the way of appreciating the philosophical stakes of our
experiments.

  1. 1.

To argue that machines can be free and have consciousness may at first seem to
suggest that machines can be human too: If only humans are free – then saying
machines are free too means to grant machines a quality that was hitherto
reserved for humans only.

  2. 2.

One may understand our suggestion that machines can be free and have
consciousness as a reduction of humans to mere machines. For if consciousness
were explainable in terms of machines then humans, counter to what we moderns
thought thus far, could be sufficiently explained in terms of machines: Being
human would be, in principle, no different from being a machine. And the
language of engineering would be sufficient to account for the human.

In our observation, both of these obstacles ultimately hold on to the concept
of the machine and the human invented by Descartes and other early modern
philosophers. To assume we are humanizing machines would inevitably mean
making the concept of consciousness and freedom invented to consolidate human
exceptionalism the model for all forms of consciousness and freedom. And to
assume we would reduce humans to machines, would only make sense if we would
hold on to the classical modern conception of the machine as without reason,
without freedom. It would mean holding on to the concept of matter and
machines developed in terms of human-made instruments. Our work, however,
radically calls these concepts of the machine and the human in question: And
also the ontologies – the clear cut distinction between human things, natural
things, and technical or artificial things – that were built on their back. If
both freedom and consciousness – the freedom to consciously act – are
intrinsic to matter then neither the argument that machines are necessarily
devoid of consciousness would hold nor the argument that consciousness is a
unique human quality that lifts us above mere matter, above mere mechanism.
Three transformations, in particular, excite us.

  1. 1.

The human The human would then no longer be the only, the defining instance of
freedom and consciousness but one example among many: Human
consciousness/freedom would be just one entry in a series; a series comprised
of humans as well as of machines and animals and plants and microbes.That is,
it would be an entry in a series that renders useless the modern ontology that
strictly separates human things, natural things, and technical or artificial
things.

  2. 2.

The machine Machines would no longer be the exact opposite of reason,
intelligence, freedom. They would no longer be instances of rogue, mindless,
automated, repetitive behavior fully reducible to the intent of the engineer
who built them. No, machines built in terms of freedom would have an agency of
their own, beyond human intent or control: and it is precisely this aspect
that would make them valuable. Machines could be something in themselves.

  3. 3.

The practice of engineering. Ultimately, mechanism was an explanation of the
world in terms of human-made instruments. It was a practice of simultaneously
reducing the world to human intent and control. With our animat this
inevitably changes: building machines in terms of quantum mechanics means to
build machines in terms of the world (as brought into view by quantum
mechanics) rather than of the human. What is more, it means integrating
machines into a fabric – into a reality – that is bigger than the human and
predates the human by billions of years.

These, then, are the philosophical stakes of building a 300 qubit based
animat: The experiments we propose will inevitably challenge and, likely,
change what we mean – since the early modern period – when we say human,
nature, technology, machine, freedom, consciousness, agency. The power of our
qubit based animat is that it releases the world from the grip of the modern
concept of the human/the machine and invites us to think again. That is, our
work will likely change some of the very key terms that have defined what it
is to be human for almost 400 years. It is no exaggeration to claim that the
entire philosophical – conceptual – basis of modernity is at stake in the
experiments we propose. What new vocabulary for being human will they give
rise to? At present no-one knows. However, what we do know is that the old
vocabularies have lost their validity. Experimentation, thus, is essential.

### Coda: after the boring game

It is a distinctive feature of contemporary technology – whether we talk about
quantum computing or about microbiome research or synthetic biology – that it
enables knowledge, often in the form of new practical possibilities, that
render the classical modern understanding of the human/the world untenable: as
untenable as the emergence of mechanical philosophy once rendered the Platonic
and Aristotelian understanding of the human/the world. Call it a mutation of
the space of possibility in which we have to organize our thoughts. A hugely
fascinating consequence of this perhaps provocative but hard to argue with
observation is that technology has become a philosophical laboratory. But
where are the experimenters who can practice philosophy in terms of
engineering? Who can simultaneously build a qubit based animat and understand
how doing so may change the architecture of how we have been thinking? Who can
build machines in ways that reflect our new understanding of humans, of
nature, of machines, of engineering? At present, they might not exist. That
has much to do with the fact that our universities are, to this day, organized
in terms of the old concept of the human and the machine. They have a faculty
of arts (concerned with the human insofar as it is more than nature or a
machine and hence cannot be explain in terms of the natural sciences or
engineering); a faculty of science (concerned with nature as the non-human and
as the opposite of the artificial); and a faculty of engineering (concerned
with machines understood as the non-natural and the non-human). And to this
day – call it the boring game – any attempt by the natural sciences or
engineering to explain the human results in a defense of the human as more
than nature/machine on the side of the faculty of arts.

Our animat makes this boring game implausible because it renders untenable the
premises on which it is based. Is building machines in terms of freedom a
philosophical or an artistic or a technical task? To understand what comes
after the human/the machine we need experimenters – call it the work force of
the future – who (1) understand that technology itself has become
philosophical and (2) who can practice philosophy in terms of technical
experiments. For our experiment, building on the work of the ’Transformations
of the Human’ program at the Berggruen Institute, we seek to address this need
by composing a team made up of philosophers, artists, and engineers. Our hope
is that our collaboration will give contours to a new, experimental and yet
teachable expertise that unfolds beyond the old and now dysfunct division of
labor between the human sciences and the natural sciences and engineering. An
expertise that brings philosophy + art + technology together in a single
practice, a practice that allows us to build machines that reflect an
understanding of their philosophical stakes. Call it the work of freedom.

#### References for the Philosophical Commentary

[1] René Déscartes. 1630. Discourse on Method. [2] Immanuel Kant. 1755.
Universal Natural History and Theory of the Heavens. [3] Immanuel Kant. 1763.
The Only Possible Basis for a Demonstration of the Existence of God. [4]
Jonathan Sway. 2007. Engines of the Imagination. London: Routledge.