Could Computers Be Kantian Persons?

Kari Colemanof Philosophyof British Columbia, BC, Canada V6T 1Z1:  kgcolema@unixg.ubc.ca

September 2, 1996

Could Computers Be Kantian Persons?

In the realm of science fiction, accounts of androids, robots, cyborgs, and other human-like computational beings are plentiful.  In examining the many philosophical issues raised by these portrayals, we seem to have overlooked one of the more interesting ones: at what point, if any, do these creatures gain moral considerability?  In other words, when -- if at all -- ought we to stop regarding them as tools and start regarding them as persons?  The focus on computational consciousness in the literature, including articles and books by Turing, Lucas, Searle, Penrose, and others, functions as a red herring.  That humans possess consciousness (whatever that is), and that computers can't (or so the literature tends to argue) would entail only that computers cannot be persons in a human sense; it entails nothing about computers being persons in a moral sense unless, as utilitarian theories often do, one's basis for moral considerability holds consciousness as a prerequisite for personhood.  My goal here is to challenge the reader to consider the possibility of computational moral personhood by suggesting that Kant's account of rational beings, in particular as elaborated in his Groundwork, may provide a basis for claiming that some computers might in fact be persons in a moral sense.  
Kant's discussion of rational beings as ends in themselves -- and therefore persons -- includes two parallel but interwoven threads.  On the one hand, rational beings are the objects of moral inquiry -- they are moral agents who are subject to moral law.  Rational beings qua agents must be able to act in accordance with the law (and indeed from or because of the law).  On the other hand, rational beings are also the inquirers of moral inquiry in which they author the moral law.  Rational beings qua authors must be able to use reason (and reason alone) to create and impose moral law.  Although Kant's exploration of rational beings separates the perspectives of authorship and agency, moral personhood derives from their combined presence in the same being.
In discussing issues of agency and authorship, Kant uses the terms autonomy and freedom somewhat interchangeably (i.e., "What else then can freedom of will be but autonomy?" (114 [98]))  Because of the deterministic nature of computers, issues of freedom with respect to agency require separate attention.  In addition, I have chosen to use the term 'freedom' when referring to issues of agency, and the term 'autonomy' when referring to issues of authorship in an effort to keep the issues separate.  
In order to argue that a deterministic computer could even possibly be a rational being, Kant's conception of freedom must be compatible with determinism (or natural necessity, as Kant refers to it).  This problem was not overlooked by Kant, and in fact Allison notes that 
Kant himself explicitly denies that it was his intention to establish either the reality or even the real possibility of such [transcendental] freedom.  On the contrary, ... the transcendental idea of freedom plays a necessary regulative or modeling function with respect to our conception of ourselves as rational agents.  And ... not only is this perfectly compatible with the (epistemic) possibility that we are merely complex mechanisms rather than genuine (spontaneous) rational agents, but this was clearly recognized by Kant.  (Allison 459)

In order to understand how Kant reconciles freedom with determinism in such a way as to preserve the moral significance of our free will, let's consider how he sets out the problem in the Groundwork: 
All men think of themselves as having a free will.  ... On the other hand, it is just as necessary that everything which takes place should be infallibly determined in accordance with the laws of nature; ...  
From this there arises a dialectic of reason, since the freedom attributed to the will seems incompatible with the necessity of nature;  (123 [113-114])

On the grounds that reason can reject neither the necessity of nature nor free will, Kant concedes that 
[r]eason must therefore suppose that no genuine contradiction is to be found between the freedom and the natural necessity ascribed to the very same human actions.  (124 [115])

Kant's first step in reconciling freedom with natural necessity is to move reason -- and therefore freedom -- out of the sensible world which is subject to natural necessity, and into the intelligible world which is subject solely to the laws of reason.  Leaving the realm of physical causation does not entail leaving the realm of causation in general, however.  In order to claim that reason provides us with categorical imperatives that are universally applicable, Kant's laws of reason can be no less deterministic than those of natural necessity.  
The concept of causality carries with it that of laws (Gesetze) in accordance with which, because of something we call a cause, something else -- namely, its effect -- must be posited (gesetzt).  Hence freedom of will, although it is not the property of conforming to laws of nature, is not for this reason lawless:  it must rather be a causality conforming to immutable laws, though of a special kind; for otherwise a free will would be self-contradictory.  (Kant 114 [97-8])

Freedom then requires that the maxims that move the will to action must conform to laws of reason, even though the actions themselves may still be completely physically determined.
Kant's distinction between the deterministic systems of the intelligible realm (reason) and the sensible realm (natural necessity) is very similar to the contemporary distinction between the hardware and software of computers.  The hardware in a computer is the physical instantiation of some Turing Machine.  Turing Machines, in turn, are the mathematical abstractions which specify the rules of a specific procedure; they are the software.  In carrying out these procedures, computers follow the laws of logic while simultaneously following the laws of physics.  Just as Kant separates the intelligible realm from the sensible realm for humans, with the former governed by laws of freedom and the latter by natural necessity, we can separate the software from the hardware in computers, the former governed by laws of logic and the latter by the laws of physics.  The link between the algorithm and computer is simply that elements of the physical world are arranged in such a way that natural law requires that the algorithm be carried out.  If humans can be considered morally free in spite of Kant's insistence on natural necessity, then surely we can not easily dismiss the possibility of moral freedom for computers simply because of their deterministic nature.  
 But of course Kant was not referring to computers when he separated the intelligible and sensible realms, so our understanding of the relationship between hardware and software does not necessarily provide a basis for understanding the relationship between the sensible body and the intelligible will.  Indeed, Kant claims that the intelligible realm is removed not only from the realm of the sensible but is removed also from the realm of the understandable:  "But where determination by laws of nature comes to an end, all explanation comes to an end as well."  (127 [121])  This strategy removes any obligation on Kant's part to explain the metaphysics of the intelligible realm (or of freedom) or how the intelligible and sensible realms interact.  
Since it is utterly beyond comprehension, why not merely do away with the intelligible realm altogether?  For Kant, doing so would entail also doing away with freedom, free will, our ability to determine ourselves to action in accordance with reason, our privileged moral status as rational beings, and morality in general.  In order to maintain the moral relevance of free will, Kant needs only the idea of freedom for use by rational authors in creating moral law, not freedom itself as a property of rational agents.  This idea of freedom is exactly what he appeals to:
Reason must look upon itself as the author of its own principles independently of alien influences.  Therefore as practical reason, or as the will of a rational being, it must be regarded by itself as free; that is, the will of a rational being can be a will of his own only under the Idea of freedom, and such a will must therefore -- from a practical point of view -- be attributed to all rational beings.  (116 [101] emphases added)

With this shift from actual freedom to the mere idea of freedom, the issue of free will for Kant takes on a ethical, not a metaphysical, role: that rational beings are free is no longer an assertion about what is the case, but instead is a premise used by moral authors in creating moral law.  
Understanding freedom, then, is not an issue of how the intelligible quality of moral agents intervenes or coincides with their sensible and appreciable qualities; understanding freedom necessitates an understanding of autonomy and the role that the idea of freedom takes in formulating moral law.  Kant as the author of moral law, must conceive of freedom as a fact, while Kant as the author of a work on moral law has the luxury of recognizing that freedom is an idea, merely a premise in the authoring process.  The computer, as author of moral law, must likewise conceive of freedom as fact, while we have the luxury of recognizing that such freedom need not be real but merely a premise used in authoring moral law.  Consequently, the ability of computers to be rational beings has more to do with their capacity to autonomously author moral law conceiving of themselves as free than it does with their capacity to achieve freedom from their determined natures.
For Kant, autonomy of authorship refers to the requirement that authorship of moral law be based solely on reason.  Because morality is the rational part of the laws of freedom, the incorporation of other factors such as utility or pleasure in the authorship of moral law would contaminate the process.  As May points out, 
Moral value is self-sufficient, independent of considerations such as usefulness, desire, etc.  . . . 
Kant's doctrine of universalizability is a test of self-sufficiency; a test to determine if the moral value of a potential duty is dependent upon external [i.e., non-rational] factors.  (May 136) 

In deriving moral law, a rational author must start with some premises.  In Kant's case, one of those premises seems to be that morality is the rational part of the laws of freedom; another premise that such an author must make is that of freedom of agency as discussed above.  We could not derive a categorical imperative -- how we as sensible beings ought to act -- if we did not presuppose (for the purpose of authoring moral law) that we could act in accord with the resulting moral law.
In order for computers to be considered Kantian rational beings, then, they must be able to author purely rational moral law (autarkeia) with freedom as a premise in the authoring process, impose the moral law on themselves, and then act in accord with -- and indeed from -- the moral law (self-rule).  Considering first the possibility of a computer authoring purely rational moral law, note that this is not a case of merely modeling the law for application in real-world situations, but of modeling the authoring process -- could a computer derive Kant's Categorical Imperatives?    I suggest that two key ingredients to successfully modeling the purely rational authorship of moral law would be concept representation and problem solving capabilities.  There may of course be others, but I will limit my discussion here to these two.
In order to answer to the question 'what ought I do?', the computer must first be able to represent and manipulate certain concepts, for example, those of identity (of self or agent), and capacity and options for action.  Merely modeling and manipulating a language is insufficient for the task at hand.  At issue in conceptualization is not whether the computer can verbalize what we consider to be relevant propositions regarding autonomous action and moral choice; if we were interested in merely the verbalization, intelligently engineered natural language processing programs would be sufficient.  What is needed is some sort of concept representation that not only manipulates the concepts in a manner that mimics understanding but also is able to associate the representation of these concepts with both external and internal information.  One promising avenue to such a goal is Schank's conceptual dependency theory, which Caudill describes as follows:
The idea is that most simple English vocabulary can be described by using only [a few basic] actions.  The meaning behind a sentence or paragraph thus drives from the concepts expressed by various combinations of these actions, along with their relationships to the agents that perform them -- and have them performed upon them. . . . 
Schank's basic actions include behaviors such as 'ingesting," "expelling," "propelling," "speaking," "moving a body part," and "moving an object." . . . His list of about 20 fundamental actions does an amazingly good job of classifying most of the vocabulary that is considered basic English.  (Caudill 159)

Because Schank is interested in modeling cognitive processes, not merely mimicking the output, I'm inclined to believe that his approach, or others like it, may result in computers with the needed concept representation abilities.
Assuming we can succeed in such concept representation (which is perhaps the biggest assumption here), we need to next look at problem solving.  The problem to be solved is not merely what to do in a given situation, but rather what guidelines, or principles, to use in such a determination.  Kant considers morality to be the formal, or rational, part of the laws of freedom, and he arrives at moral law essentially by rational deduction from a few premises.  Using the conceptual representations discussed above, could a computer start with the same premises and similarly derive moral law?  In contrast with the task of conceptualization, such a logical derivation is a task to which computers are well suited.  Numerous search strategies and heuristics including backward- and forward-chaining and means-ends analysis, various reasoning paradigms including probabilistic logic and possibilistic or fuzzy logic, and knowledge-base or expert systems serve to provide a wide range of problem-solving capabilities which, in combination with concept representation, would likely be sufficient for the task. 
Having discussed the types of programming that would be needed for a computer to author moral law we must now consider whether a computer could act in accord with, and indeed from, the moral law.  If we refer to the programming discussed above to as Prational, the simplest approach would be to feed the results of Prational into yet another program, Papply, that applies the moral law to the given situation.  Again, all of this requires concept representation in order to represent both the moral law and the given situation, as well as problem solving capacities to figure out how to apply it.  The success of such a program could be tested by simulating moral dilemmas and observing the computer's responses.  
It could be argued that such an approach will result in a computer that acts in accord with the moral law, but does not act from the moral law.  For Kant, this is a crucial distinction; one must act from duty -- from the moral law -- in order to act morally.  (Kant 65-67 [8-13])  Of course, the computer, using the programming specified so far, could be said to be acting from the moral law; after all, the actions were chosen by Papply because they are in accord with the results of Prational (and indeed, this is precisely why the computer acts as it does).  However, since there are no other (non-rational) moral principles programmed in that the computer can consider and dismiss, the decision to follow the moral law would seem to be the programmer's rather than the computer's. 
One solution to this objection is to incorporate, in addition to Prational, several programs for deriving moral principles, each based on different factors such as utility (Putility) or interest (Pinterest).  Heuristics such as neural nets and fuzzy controllers could be used to decide which factor -- rationality, utility, interest, etc. -- will serve as the maxim and subsequently be applied to the given situation; I shall call such programming Pmaxim.  The entire process now includes Prational, Putility, and Pinterest, (and any other programs for deriving moral principles) run in parallel, their results fed into Pmaxim to determine which of them (or combination of them) will function as the maxim for action to be applied to the given situation via Papply. 
Of course, this process may well destroy the moral autonomy in the authorship of the moral law.  Although the computer is deriving rational moral law using Prational, it does not necessarily apply it in its pure form, allowing it instead to become contaminated by other factors such as utility or interest.  The challenge here is to enable the computer to evaluate and adjust Pmaxim so that it may select Prational consistently, but is not required to do so.  For this, we need to consider learning algorithms. 
Without learning algorithms, a program is only as good as its programmer.  So far, the programming discussed above is of the sort where the desired output typically is reached via only one iteration on the input.  Learning algorithms, on the other hand, make use of feedback loops to evaluate their own performance and adjust it as needed.  There are a number of different types of learning algorithms including supervised, reinforcement, and unsupervised learning, distinguished by Russell & Norvig as follows:
Any situation in which both the inputs and outputs of a component can be perceived is called supervised learning. . . .  
On the other hand, in learning the condition-action component, [if] the agent receives some evaluation of its action . . . but is not told the correct action. . . . this is called reinforcement learning; . . . 
Learning when there is no hint at all about the correct outputs is called unsupervised learning.  (Russell & Norvig 528) 

Each of these types of learning are appropriate for different goals.  Although supervised learning algorithms are frequently the fastest learners, they learn only what they are told to learn.  In order not to rob the computer of the opportunity to merge authorship and agency on its own -- essentially to become an end in itself -- an unsupervised (or at most, a reinforcement) learning algorithm should be implemented as Pevaluate in a feedback loop with Pmaxim.  (Figure 1 depicts how Prational, Putility, Pinterest, Pmaxim, Papply, and Pevaluate all fit together.)
 				Figure 1.  Building a (Kantian) Rational Being 
Of course, this brief description of the proposed programming is rough at best.  I do not mean to imply that construction of a computer with the appropriate programming will be easy; given the challenges posed by natural language processing and concept representation, and the importance of the latter to the construction of a rational being, I do not expect such construction to be forthcoming in the near future.  In addition, as mentioned earlier, a more thorough investigation of Kant's work is needed.  However, from this initial exploration of Kant and the implications for computational personhood, I am inclined to say that computational personhood seems quite possible, with the needed technology currently under development.  Whether we ought to build such rational beings, and how we ought to treat them if we do, is a topic for another paper.

 

REFERENCES
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