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This answer is given by the asker of the original question, four years after the question. It does not substitute for or supersede answers earlier given, for most of the earlier answers are more interesting than this one is. However, this answer might add some additional context.

As far as I can tell, most AI research seems implicitly to grant the premise that thought and reason were solely material phenomena, or at least that results indistinguishable from thought and reason must necessarily be achievable by solely material processes. I do not dispute the premise (nor here promote it, for that matter). I merely observe that it seems to be a premise.

And, after all, in AI research, how should this not be a premise? AI researchers must work through material processes, whether they will or nill.

The schoolmen of realist philosophy, back through Duns Scotus, St. Thomas, Aristotle and Plato, have had much to say regarding the theory of mind. Representationalists like Kant have had rather different things to say. AI research is probably closer to Kant, but this does not make the schoolmen wrong.

Admittedly, there is a God-of-the-gaps objection which tends to pop up at this point in conversations of the present kind, yet a professional philosopher would tell you that the God-of-the-gaps objection attacks a straw man, that this objection tends to be useful only against persons who have studied no philosophy and thus do not know what they are talking about. Per Aristotle, it is formal and final causation which wouldmight be implicated in the question of the self-trained chess AI. InYet in Aristotlean terms, the AI researcher works purely with material and, especially, efficient causation (except perhaps obliquely, insofar as human trainers personally bring formal and final elements into the system). If reason is formal, if thought is final, if Searle's Chinese room proves to be an ontological impossibility (as it might), then it may be that a purely self-trained chess AI cannot even in theory be achieved.

I suspect that a purely self-trained chess AI can be indeed be achieved, and will be—that, in Aristotlean terms, this question will prove to be adequately framable in view of merely efficient causation. I am more skeptical of strong AI generally, but these are to be proved in experience, are they not? No one really yet knows.

The philosophy of causation and mind is subtle, grasped by few (and probably by few, even among AI researchers, who are more practical men). If you wish to learn such philosophy, it is well worth the learning; but be advised that, on the Internet and even often in print, it is extremely easy to find misleading explanations based on untutored misunderstandings. For my money, the best introductory teacher writing today on the subject is Edward Feser, whose books remain in print at reasonable prices. You can learn much more from him.

However, one doubts that even Dr. Feser would venture an authoritative answer on the present question! The answer remains to be proved in the laboratories of AI.

This answer is given by the asker of the original question, four years after the question. It does not substitute for or supersede answers earlier given, for most of the earlier answers are more interesting than this one is. However, this answer might add some additional context.

As far as I can tell, most AI research seems implicitly to grant the premise that thought and reason were solely material phenomena, or at least that results indistinguishable from thought and reason must necessarily be achievable by solely material processes. I do not dispute the premise (nor here promote it, for that matter). I merely observe that it seems to be a premise.

And, after all, in AI research, how should this not be a premise? AI researchers must work through material processes, whether they will or nill.

The schoolmen of realist philosophy, back through Duns Scotus, St. Thomas, Aristotle and Plato, have had much to say regarding the theory of mind. Representationalists like Kant have had rather different things to say. AI research is probably closer to Kant, but this does not make the schoolmen wrong.

Admittedly, there is a God-of-the-gaps objection which tends to pop up at this point in conversations of the present kind, yet a professional philosopher would tell you that the God-of-the-gaps objection attacks a straw man, that this objection tends to be useful only against persons who have studied no philosophy and thus do not know what they are talking about. Per Aristotle, it is formal and final causation which would be implicated in the question of chess AI. In Aristotlean terms, the AI researcher works purely with material and, especially, efficient causation (except perhaps obliquely, insofar as human trainers personally bring formal and final elements into the system). If reason is formal, if thought is final, if Searle's Chinese room proves to be an ontological impossibility (as it might), then it may be that a purely self-trained chess AI cannot even in theory be achieved.

I suspect that a purely self-trained chess AI can be indeed be achieved, and will be. I am more skeptical of strong AI generally, but these are to be proved in experience, are they not? No one really yet knows.

The philosophy of causation and mind is subtle, grasped by few (and probably by few, even among AI researchers, who are more practical men). If you wish to learn such philosophy, it is well worth the learning; but be advised that, on the Internet and even often in print, it is extremely easy to find misleading explanations based on untutored misunderstandings. For my money, the best introductory teacher writing today on the subject is Edward Feser, whose books remain in print at reasonable prices. You can learn much more from him.

However, one doubts that even Dr. Feser would venture an authoritative answer on the present question! The answer remains to be proved in the laboratories of AI.

This answer is given by the asker of the original question, four years after the question. It does not substitute for or supersede answers earlier given, for most of the earlier answers are more interesting than this one is. However, this answer might add some additional context.

As far as I can tell, most AI research seems implicitly to grant the premise that thought and reason were solely material phenomena, or at least that results indistinguishable from thought and reason must necessarily be achievable by solely material processes. I do not dispute the premise (nor here promote it, for that matter). I merely observe that it seems to be a premise.

And, after all, in AI research, how should this not be a premise? AI researchers must work through material processes, whether they will or nill.

The schoolmen of realist philosophy, back through Duns Scotus, St. Thomas, Aristotle and Plato, have had much to say regarding the theory of mind. Representationalists like Kant have had rather different things to say. AI research is probably closer to Kant, but this does not make the schoolmen wrong.

Admittedly, there is a God-of-the-gaps objection which tends to pop up at this point in conversations of the present kind, yet a professional philosopher would tell you that the God-of-the-gaps objection attacks a straw man, that this objection tends to be useful only against persons who have studied no philosophy and thus do not know what they are talking about. Per Aristotle, it is formal and final causation which might be implicated in the question of the self-trained chess AI. Yet in Aristotlean terms, the AI researcher works purely with material and, especially, efficient causation (except perhaps obliquely, insofar as human trainers personally bring formal and final elements into the system). If reason is formal, if thought is final, if Searle's Chinese room proves to be an ontological impossibility (as it might), then it may be that a purely self-trained chess AI cannot even in theory be achieved.

I suspect that a purely self-trained chess AI can be indeed be achieved, and will be—that, in Aristotlean terms, this question will prove to be adequately framable in view of merely efficient causation. I am more skeptical of strong AI generally, but these are to be proved in experience, are they not? No one really yet knows.

The philosophy of causation and mind is subtle, grasped by few (and probably by few, even among AI researchers, who are more practical men). If you wish to learn such philosophy, it is well worth the learning; but be advised that, on the Internet and even often in print, it is extremely easy to find misleading explanations based on untutored misunderstandings. For my money, the best introductory teacher writing today on the subject is Edward Feser, whose books remain in print at reasonable prices. You can learn much more from him.

However, one doubts that even Dr. Feser would venture an authoritative answer on the present question! The answer remains to be proved in the laboratories of AI.

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This answer is given by the asker of the original question, four years after the question. It does not substitute for or supersede answers earlier given, for most of the earlier answers are more interesting than this one is. However, this answer might add some additional context.

As far as I can tell, most AI research seems implicitly to grant the premise that thought and reason were solely material phenomena, or at least that results indistinguishable from thought and reason must necessarily be achievable by solely material processes. I do not dispute the premise (nor here promote it, for that matter). I merely observe that it seems to be a premise.

And, after all, in AI research, how should this not be a premise? AI researchers must work through material processes, whether they will or nill.

The schoolmen of realistrealist philosophy, back through Duns Scotus, St. Thomas, Aristotle and Plato, have had much to say regarding the theory of mind. RepresentationalistsRepresentationalists like Kant have had rather different things to say. AI research is probably closer to Kant, but this does not make the schoolmen wrong.

Admittedly, there is a God-of-the-gapsGod-of-the-gaps objection which tends to pop up at this point in conversations of the present kind, yet a professional philosopher would tell you that the God-of-the-gaps objection attacks a straw man, that this objection tends to be useful only against persons who have studied no philosophy and thus do not know what they are talking about. Per Aristotle, it is formal and final causation which would be implicated in the question of chess AI. In Aristotlean terms, the AI researcher works purely with material and, especially, efficient causation—except (except perhaps obliquely, insofar as human trainers personally bring formal and final elements into the system). If reason is formal, if thought is final, if Searle's Chinese roomSearle's Chinese room proves to be an ontological impossibility (as it might), then it may be that a purely self-trained chess AI cannot even in theory be achieved.

I suspect that a purely self-trained chess AI can be indeed be achieved, and will be. I am more skeptical of strong AI generally, but these are to be proved in experience, are they not? No one really yet knows.

The philosophy of causationcausation and mindmind is subtle, grasped by few (and probably by few, even among AI researchers, who are more practical men). If you wish to learn such philosophy, it is well worth the learning; but be advised that, on the Internet and even often in print, it is extremely easy to find misleading explanations based on untutored misunderstandings. For my money, the best introductory teacher writing today on the subject is Edward Feser, whose books remain in print at reasonable prices. You can learn much more from him.

However, one doubts that even Dr. Feser would venture an authoritative answer on the present question! The answer remains to be proved in the laboratories of AI.

This answer is given by the asker of the original question, four years after the question. It does not substitute for or supersede answers earlier given, for most of the earlier answers are more interesting than this one is. However, this answer might add some additional context.

As far as I can tell, most AI research seems implicitly to grant the premise that thought and reason were solely material phenomena, or at least that results indistinguishable from thought and reason must necessarily be achievable by solely material processes. I do not dispute the premise (nor here promote it, for that matter). I merely observe that it seems to be a premise.

And, after all, in AI research, how should this not be a premise? AI researchers must work through material processes, whether they will or nill.

The schoolmen of realist philosophy, back through Duns Scotus, St. Thomas, Aristotle and Plato, have had much to say regarding the theory of mind. Representationalists like Kant have had rather different things to say. AI research is probably closer to Kant, but this does not make the schoolmen wrong.

Admittedly, there is a God-of-the-gaps objection which tends to pop up at this point in conversations of the present kind, yet a professional philosopher would tell you that the God-of-the-gaps objection attacks a straw man, that this objection tends to be useful only against persons who have studied no philosophy and thus do not know what they are talking about. Per Aristotle, it is formal and final causation which would be implicated in the question of chess AI. In Aristotlean terms, the AI researcher works purely with material and, especially, efficient causation—except obliquely, insofar as human trainers personally bring formal and final elements into the system. If reason is formal, if thought is final, if Searle's Chinese room proves to be an ontological impossibility (as it might), then it may be that a purely self-trained chess AI cannot even in theory be achieved.

I suspect that a purely self-trained chess AI can be indeed be achieved, and will be. I am more skeptical of strong AI generally, but these are to be proved in experience, are they not? No one really yet knows.

The philosophy of causation and mind is subtle, grasped by few (and probably by few, even among AI researchers, who are more practical men). If you wish to learn such philosophy, it is well worth the learning; but be advised that, on the Internet and even often in print, it is extremely easy to find misleading explanations based on untutored misunderstandings. For my money, the best introductory teacher writing today on the subject is Edward Feser, whose books remain in print at reasonable prices. You can learn much more from him.

However, one doubts that even Dr. Feser would venture an authoritative answer on the present question! The answer remains to be proved in the laboratories of AI.

This answer is given by the asker of the original question, four years after the question. It does not substitute for or supersede answers earlier given, for most of the earlier answers are more interesting than this one is. However, this answer might add some additional context.

As far as I can tell, most AI research seems implicitly to grant the premise that thought and reason were solely material phenomena, or at least that results indistinguishable from thought and reason must necessarily be achievable by solely material processes. I do not dispute the premise (nor here promote it, for that matter). I merely observe that it seems to be a premise.

And, after all, in AI research, how should this not be a premise? AI researchers must work through material processes, whether they will or nill.

The schoolmen of realist philosophy, back through Duns Scotus, St. Thomas, Aristotle and Plato, have had much to say regarding the theory of mind. Representationalists like Kant have had rather different things to say. AI research is probably closer to Kant, but this does not make the schoolmen wrong.

Admittedly, there is a God-of-the-gaps objection which tends to pop up at this point in conversations of the present kind, yet a professional philosopher would tell you that the God-of-the-gaps objection attacks a straw man, that this objection tends to be useful only against persons who have studied no philosophy and thus do not know what they are talking about. Per Aristotle, it is formal and final causation which would be implicated in the question of chess AI. In Aristotlean terms, the AI researcher works purely with material and, especially, efficient causation (except perhaps obliquely, insofar as human trainers personally bring formal and final elements into the system). If reason is formal, if thought is final, if Searle's Chinese room proves to be an ontological impossibility (as it might), then it may be that a purely self-trained chess AI cannot even in theory be achieved.

I suspect that a purely self-trained chess AI can be indeed be achieved, and will be. I am more skeptical of strong AI generally, but these are to be proved in experience, are they not? No one really yet knows.

The philosophy of causation and mind is subtle, grasped by few (and probably by few, even among AI researchers, who are more practical men). If you wish to learn such philosophy, it is well worth the learning; but be advised that, on the Internet and even often in print, it is extremely easy to find misleading explanations based on untutored misunderstandings. For my money, the best introductory teacher writing today on the subject is Edward Feser, whose books remain in print at reasonable prices. You can learn much more from him.

However, one doubts that even Dr. Feser would venture an authoritative answer on the present question! The answer remains to be proved in the laboratories of AI.

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source | link

This answer is given by the asker of the original question, four years after the question. It does not substitute for or supersede answers earlier given, for most of the earlier answers are more interesting than this one is. However, this answer might add some additional context.

As far as I can tell, most AI research seems implicitly to grant the premise that thought and reason were solely material phenomena, or at least that results indistinguishable from thought and reason must necessarily be achievable by solely material processes. I do not dispute the premise (nor here promote it, for that matter). I merely observe that it seems to be a premise.

And, after all, in AI research, how should this not be a premise? AI researchers must work through material processes, whether they will or nill.

The schoolmen of realist philosophy, back through Duns Scotus, St. Thomas, Aristotle and Plato, have had much to say regarding the theory of mind. Representationalists like Kant have had rather different things to say. AI research is probably closer to Kant, but this does not make the schoolmen wrong.

Admittedly, there is a God-of-the-gaps objection which tends to pop up at this point in conversations of the present kind, yet a professional philosopher would tell you that the God-of-the-gaps objection attacks a straw man, that this objection tends to be useful only against persons who have studied no philosophy and thus do not know what they are talking about. Per Aristotle, it is formal and final causation which would be implicated in the question of chess AI. In Aristotlean terms, the AI researcher works purely with material and, especially, efficient causation—except obliquely, insofar as human trainers personally bring formal and final elements into the system. If reason is formal, if thought is final, if Searle's Chinese room proves to be an ontological impossibility (as it might), then it may be that a purely self-trained chess AI cannot even in theory be achieved.

I suspect that a purely self-trained chess AI can be indeed be achieved, and will be. I am more skeptical of strong AI generally, but these are to be proved in experience, are they not? No one really yet knows.

The philosophy of causation and mind is subtle, grasped by few (and probably by few, even among AI researchers, who are more practical men). If you wish to learn such philosophy, it is well worth the learning; but be advised that, on the Internet and even often in print, it is extremely easy to find misleading explanations based on untutored misunderstandings. For my money, the best introductory teacher writing today on the subject is Edward Feser, whose books remain in print at reasonable prices. You can learn much more from him.

However, one doubts that even Dr. Feser would venture an authoritative answer on the present question! The answer remains to be proved in the laboratories of AI.