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[https://www.usi.ch/en/education/master/philosophy MAP, USI, Lugano], Spring 2024
[https://www.usi.ch/en/education/master/philosophy MAP, USI, Lugano], Spring 2024


'''Background'''
'''Background'''  


Much of the material for this class is derived from our book ''[https://buffalo.app.box.com/v/AI-Without-Fear Why Machines Will Never Rule the World: Artificial Intelligence without Fear]'' (Routledge 2022). Artificial Intelligence (AI) is the subfield of Computer Science devoted to developing programs that enable computers to display behavior that can (broadly) be characterized as intelligent. On the strong version, the ultimate goal of AI is to create an artificial system that is as intelligent as a human being. Recent successes of ChatGPT and other Large Language Models (LLMs) have led to a new popularization of AI, since these tools are immediately available to the wider population, who for the first time can have real hands-on experience of what AI can do. LLMs belong to the class of stochastic AI.
[[Philosophy and Artificial Intelligence 2025]]
 
Artificial Intelligence (AI) is the subfield of Computer Science devoted to developing programs that enable computers to display behavior that can (broadly) be characterized as intelligent. On the strong version, the ultimate goal of AI is to create what is called ''General Artificial Intelligence'' (AGI), by which is meant an artificial system that is as intelligent as a human being.
 
Since its inception in the middle of the last century AI has enjoyed repeated cycles of enthusiasm and disappointment (AI summers and winters). Recent successes of ChatGPT and other Large Language Models (LLMs) have opened a new era popularization of AI. For the first time, AI tools have been created which are immediately available to the wider population, who for the first time can have real hands-on experience of what AI can do.  


These developments in AI open up a series of questions such as:
These developments in AI open up a series of questions such as:
Line 17: Line 21:
We will describe in detail how stochastic AI work, and consider these and a series of other questions at the borderlines of philosophy and AI. The class will close with presentations of papers on relevant topics given by students.
We will describe in detail how stochastic AI work, and consider these and a series of other questions at the borderlines of philosophy and AI. The class will close with presentations of papers on relevant topics given by students.


[https://buffalo.app.box.com/v/AI-Without-Fear Table of contents, first chapter and references]
Some of the material for this class is derived from our book
 
:''[https://buffalo.app.box.com/v/AI-Without-Fear Why Machines Will Never Rule the World: Artificial Intelligence without Fear]'' (Routledge 2022).
 
and from the companion volume
 
:''[https://cosmosandtaxis.org/submissions/upcoming-issues/Cosmos+Taxis Symposium'' on ''Why Machines Will Never Rule the World''] — Guest editor, Janna Hastings, University of Zurich
 
which will appear as a special issue of the public access journal ''Cosmos + Taxis'' in early 2024.
 


'''Faculty'''
'''Faculty'''


[https://www.cognotekt.com/en/ Jobst Landgrebe] is the founder and CEO of Cognotekt, GmBH, an AI company based in Cologne specialised in the design and implementation of holistic AI solutions. He has 17 years experience in the AI field, 8 years as a management consultant and software architect. He has also worked as a physician and mathematician.
[https://www.cognotekt.com/en/ Jobst Landgrebe] is the founder and CEO of Cognotekt, GmBH, an AI company based in Cologne specialised in the design and implementation of holistic AI solutions. He has 20 years experience in the AI field, 8 years as a management consultant and software architect. He has also worked as a physician and mathematician, and he views AI itself -- to the extent that it is not an elaborate hype -- as a branch of applied mathematics. CUrrently his primary focus is in the biomathematics of cancer.


Barry Smith is one of the world's most [https://scholar.google.com/citations?view_op=search_authors&hl=en&mauthors=label:metaphysics widely cited philosophers]. He has contributed primarily to the field of applied ontology, which means applying philosophical ideas derived from analytical metaphysics to the concrete practical problems which arise where attempts are made to compare or combine heterogeneous bodies of data.  
Barry Smith is one of the world's most [https://scholar.google.com/citations?view_op=search_authors&hl=en&mauthors=label:metaphysics widely cited philosophers]. He has contributed primarily to the field of applied ontology, which means applying philosophical ideas derived from analytical metaphysics to the concrete practical problems which arise where attempts are made to compare or combine heterogeneous bodies of data.  
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After introducing the relevant ideas and tools from both AI and philosophy, all the aforementioned questions will be thoroughly addressed in class discussions. The class will close with presentations of papers on relevant topics given by students.
After introducing the relevant ideas and tools from both AI and philosophy, all the aforementioned questions will be thoroughly addressed in class discussions. The class will close with presentations of papers on relevant topics given by students.


'''Very Early Draft Schedule'''
'''Grading'''
:Essay with presentation: 80%
:Essay with no presentation: 95%
:Presentation: 15%
:Class Participation 5%


==Tuesday, February 20 (14:30-17:15) Why machines will never rule the world ==
'''Draft Schedule'''


:Barry Smith: Overview of the arguments and introduction to the human mind
==Tuesday, February 20 (14:30-17:15) Introduction: Philosophy and Artificial Intelligence ==


:Room:  
:Room: A23


Readings:
We begin with a survey of the development of AI research from 1970 to today, paying attention especially to the background role of ontology (Knowledge Graphs) in  this development.
:John Searle: [https://www.law.upenn.edu/live/files/3413-searle-j-minds-brains-and-programs-1980.pdf  Minds, Brains, and Programs]
 
:Jobst Landgrebe and Barry Smith: [https://arxiv.org/pdf/1906.05833.pdf There is no Artificial General Intelligence]
We then outline the main theses of the recent book, ''[https://buffalo.app.box.com/v/AI-Without-Fear Why Machines Will Never Rule the World]'', by Landgrebe and Smith, before moving on to discuss the relation between a human mind and the intelligence that might be ascribed to a machine.
 
[https://buffalo.box.com/v/Introduction-Philosophy-and-AI Slides]
 
==Wednesday February 21 (14:30-17:15): The Glory and the Misery of ChatGPT==


:Room: A23


==Wednesday February 21 (9:30-12:15 noon): Artificial General Intelligence and Introduction to Stochastic AI ==
''Part 1: What is intelligence?''


:Room:
All students are expected to have some familiarity with [https://www.youtube.com/watch?v=tt-JzB50sJE Searle's Chinese Room Argument].
'''Artificial General Intelligence'''


[https://buffalo.box.com/v/Landgrebe-March-1-2023 Landgrebe Slides]  
Machines cannot have intentionality; they cannot have experiences which are ''about'' something. Searle: [https://www.law.upenn.edu/live/files/3413-searle-j-minds-brains-and-programs-1980.pdf  Minds, Brains, and Programs]  


[https://buffalo.box.com/v/Bibliography-LandS Bibliography of ''Why Machines Will Never Rule the World'']
:[https://buffalo.box.com/s/vw99q3dexcdd4as4a8blvfh33woq2wbg Slides]
 
What are the essential marks of human intelligence? 


The classical psychological definitions of intelligence are:  
The classical psychological definitions of intelligence are:  
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:B. a very general mental capability (possessed only by humans) that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience 
:B. a very general mental capability (possessed only by humans) that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience 


What are the essential marks of human intelligence? 
Can a machine be intelligent in either of these senses?


Readings:
Readings:
:Linda S. Gottfredson. [https://www1.udel.edu/educ/gottfredson/reprints/1994WSJmainstream.pdf Mainstream Science on Intelligence]. In: ''Intelligence'' 24 (1997), pp. 13–23.
:Linda S. Gottfredson. [https://www1.udel.edu/educ/gottfredson/reprints/1994WSJmainstream.pdf Mainstream Science on Intelligence]. In: ''Intelligence'' 24 (1997), pp. 13–23.
Human and machine intelligence
:Jobst Landgrebe and Barry Smith: [https://arxiv.org/pdf/1906.05833.pdf There is no Artificial General Intelligence]


:[https://buffalo.box.com/v/Hutter-Definition Slides from 2022]
''Part 2: An introduction to ChatGPT. How is it built? How does it work? Is it intelligent?''
:[https://www.youtube.com/watch?v=ReoyoinaKUE Video from 2022]


'''The Legg-Hutter Definition of Intelligence'''
Can ChatGPT become intelligent?


What is it that researchers and engineers are trying to do when they talk of achieving ‘Artificial Intelligence’?  
Are Large Language Models a threat to humanity?


To what extent can AI be achieved? 
Capabilities, or: What do IQ tests measure?
:[https://buffalo.box.com/v/What-do-IQ-tests-2022 Slides]


Problems with the Legg-Hutter Definition of Intelligence
Is Psychology Finished?
:[https://buffalo.box.com/v/Is-Psychology-Finished? Slides]


'''Theory of complex systems'''
The human brain and the Theory of complex systems


Readings:
:Shane Legg and Marcus Hutter: [https://arxiv.org/abs/0712.3329 Universal Intelligence: A Definition of Machine Intelligence]
:Jobst Landgrebe and Barry Smith: [https://arxiv.org/pdf/1901.02918.pdf Making AI Meaningful Again]
:Jobst Landgrebe and Barry Smith: [https://arxiv.org/pdf/1901.02918.pdf Making AI Meaningful Again]
:S. Thurner et al. (2018): Introduction to the theory of complex systems (Oxford):
:[https://www.academia.edu/93423257/Introduction_to_the_Theory_of_Complex_Systems S. Thurner et al. (2018): Introduction to the theory of complex systems (Oxford)]


==Thursday, February 22 (14:30 - 17:15): Language and Natural Intelligence ==
==Thursday, February 22 (14:30 - 17:15): Can an Artificial Intelligence Act? ==


[https://buffalo.box.com/v/Landgrebe-March-1-2023 Landgrebe Slides]
:Room: A23


Language Structure and Language Economy (Landgrebe)
:[https://buffalo.box.com/s/n70b84o813hp0jsfnznczeg8sid9mtnv AI Ethics Slides]


Large Language Models (Landgrebe)
''What is agency?''


Natural Intelligence (Landgrebe)
:Featuring Emanuele Martinelli. Emanuele is a PhD student in philosophy at the University of Zurich, co-affiliated with the Chair of Political Philosophy and the Digital Society Initiative. He has a bachelor's in philosophy and a master's in philosophy and economics, both from USI.


==Friday, February 23 (9:30 - 12:15) The Missing Human Will==
:What are the different types of agency?
:Examples of collective agency, government agency, agency of socio-technical systems (armies, corporations, ...)
:Relation between agency and responsibility. (Responsibility as the origin of ethics.)
:Can an AI be responsibe?
:Can there be such a thing as an AI will?


[https://buffalo.box.com/v/Digital-Immortality-2023 Slides]
''Agency and the capacities and limits of AI''
:Case study: AI and economic planning
:Hayek's knowledge problem
:The price system and market competition
:Market economies vs planned economies: the agents at stake
:Proposed ways to use AI to plan the economy
:The role of the entrepreneur
:Can AI be entrepreneurial


Background reading:
:"[https://www.rcandela.com/uploads/2/0/1/6/20163847/boettke_and_candela_on_the_feasibility_of_technosocialism.pdf On the Feasibility of Technosocialism]"
:"[http://philsci-archive.pitt.edu/19406/7/List-GA-AI.pdf Group Agency and Artificial Intelligence]"
:"[https://www.argumenta.org/wp-content/uploads/2023/06/Argumenta-82-Emanuele-Martinelli-Toward-a-General-Model-of-Agency-1.pdf Toward a General Model of Agency]"


Simple and complex systems
==Friday, February 23 (9:30 - 12:15) No Machine Will ==


The human will
:Room: A23


The missing machine will
Computers cannot have a will, because computers ''don't give a damn''. Therefore there can be no machine ethics


Consequences for the limits of AI
:The lack of the giving-a-damn-factor is taken by Yann LeCun as a reason to reject the idea that AI might pose an existential risk to humanity – an AI will have no desire for self-preservation “Almost half of CEOs fear A.I. could destroy humanity five to 10 years from now — but ‘A.I. godfather' says an existential threat is ‘preposterously ridiculous’” ''Fortune'', June 15, 2023. See also [https://www.nature.com/articles/s41562-023-01723-5 here].


Preliminary Remarks on ChatGPT and other Large Language Models
Implications of the absence of a machine will:
<!-- This is a comment
:The problem of the singularity (when machines will take over from humans) will not arise
:The Limits of Mathematical Models and the Limits of AI
:The idea of digital immortality will never be realized [https://buffalo.box.com/v/Digital-Immortality-2023 Slides]
:[https://buffalo.box.com/s/xnmc8zi1btpnku365bysxmowcgk99epd Slides]
:The idea that human beings are simulations can be rejected
:There can be no AI ethics (only: ethics governing human beings when they use AI)
:Fermi's paradox is solved


::'''Models'''
==Monday, May 13 (9:30 - 12:15) The absolute limits of AI ==
:::All science requires mathematical models
:::Types of models 1: descriptive, explanatory, predictive
:::Types of models 2: qualitative, quantitative
::::All predictive models are quantitative
::::Synoptic models
::::Adequate models
:::Computability
:::All AI engineering requires mathematical models
::::Explicit and implicit mathematical models
::'''Systems'''
:::System elements and system interactions
:::Systems are fiat entities: they are a product of delimitation
:::System boundaries
:::Relatively isolated systems
::'''The Limits and Potential of AI'''
:::Intentions and drivenness
:::No emulation of animate drivenness


:'''AI and the Mathematics of Complex Systems'''
:Room: A23
::[https://buffalo.box.com/s/xnmc8zi1btpnku365bysxmowcgk99epd Slides]
::Bayesian networks
::Complex systems
:::Comprehensive and partial models             
:::The scope of extended Newtonian mathematics         
:::Seven Properties of complex systems               
:::Examples of complex systems                   
:::Human beings as complex systems
::::Complex systems of complex systems
:::Animate complex systems are organized and stable    
::'''Mathematical models of complex systems'''
:::Multivariate distributions                      
:::Adequate models for complex systems           
:::Predictive models of complex systems
::::Why we ain’t rich
:::::Example of a social fact
::'''Approaches to complex system modelling'''
:::Naïve approaches
:::Consequences for AI applications
:::Refined approaches
::::Scaling
:::Explicit networks
::::Evolutionary process models
::::Entropy models
:::Complex system emulation requires complex systems
:'''AI and the Ontology of Power, Social Interaction and Ethics'''
:[https://www.youtube.com/watch?v=EiBBS8ueyz4 Preliminary Video] -->


==Monday, May 13 (9:30 - 12:15) Quantum Computation 1 ==
Topics to be dealt with include:


1. Introduction to the theory of computation and of Turing machines: What is a Turing machine?, Turing machine elements and structure, example of a Turing machine, recursive functions, non-recursive functions, Church-Turing computability
: What is AI?
: How does it work?
: What are its limits?
: And what about ChatGPT?


2. Classical logic-gate based computation: binary logic of computers, registers, logic gates and circuits, examples of circuits
Background: '''[https://www.youtube.com/watch?v=1rnam1w8ztM Will AI Destroy Humanity? A Soho Forum Debate]''' (Spoiler: Jobst won)


3. Quantum mechanics: superposition, double slit, uncertainty, Stern-Gerlach, Hamiltonian, Hilbert space
[https://buffalo.box.com/s/wmim09dtsf1dd11rwnlb3wydqbcf3xcl Slides]


Source: Nielsen and Chuang, ''[https://csis.pace.edu/~ctappert/cs837-19spring/QC-textbook.pdf Quantum Computation and Quantum Information]''
==Tuesday, May 14 (9:30 - 12:15) The ontology of physics ==


[https://youtu.be/_mvoS_H_kA8 Video]
:Room: A23


[https://buffalo.box.com/v/Quantum-Computing-1 Slides for Parts 1 and 2]
The ontology of physics
:[https://buffalo.box.com/s/j6hhv85hfyedzcv3ry0d4by30w3u3eqj Slides]


==Tuesday, May 14 (9:30 - 12:15) Quantum Computation 2 ==
==Wednesday May 15 (9:30 - 12:15): Are we living in a simulation? (II), digital twins and and Certifiable AI  ==


Continues Wednesday's lecture:
:Room: A23


4. Quantum computing: quantum bits, registers, quantum gates, simple quantum algorithm, quantum error (correction), future of quantum computing
On David Chalmers' theory of reality and the role of physics [https://buffalo.box.com/s/x0v0e9wug00t680lne2kyrlradvv7pwm Slides]


5. Philosophical interpretation of quantum computing
==Thursday May 16 (14:30 - 18:15) The Replication Problem==


6. Why quantum computers are Turing machines
:Room: A23


Mikhail Dyakonov, ''[https://spectrum.ieee.org/the-case-against-quantum-computing The Case Against Quantum Computing]''
''Complex Systems and Cognitive Science: Why the Replication Problem is here to stay''


[https://youtu.be/BB89YcLeAko Video]
:The 'replication problem' is the the inability of scientific communities to independently confirm the results of scientific work. Much has been written on this problem especially as it arises in (social) psychology, and on potential solutions under the heading of 'open science'. But we will see that the replication problem has plagued medicine as a positive science since its beginnings (Virchov and Pasteur). This problem has become worse over the last 30 years and has massive consequences for healthcare practice and policy.  


==Wednesday May 15 (9:30 - 12:15): The Nature of Intelligence: Humans vs. ChatGPT ==
[https://buffalo.box.com/s/m3nu15lqjw0qhpqycz3wjsai057p9jf6 Slides]


Human and machine intelligence
Background:


Can ChatGPT become intelligent?
:[https://plato.stanford.edu/entries/scientific-reproducibility Reproducibility of Scientific Results], ''Stanford Encyclopedia of Philosophy'', 2018
:[https://www.vox.com/future-perfect/21504366/science-replication-crisis-peer-review-statistics Science has been in a “replication crisis” for a decade]
:[https://www.youtube.com/watch?v=HhDGkbw1FdwThe Irreproducibility Crisis and the Lehman Crash], Barry Smith, Youtube 2020


Are Large Language Models a threat to humanity?
==Friday May 17 (9:30-12:15) Student Presentations and Concluding Survey==
 
Capabilities, or: What do IQ tests measure?
:[https://buffalo.box.com/v/What-do-IQ-tests-2022 Slides]


Is Psychology Finished?
:Room: A23
:[https://buffalo.box.com/v/Is-Psychology-Finished? Slides]


==Thursday May 16 (14:30 - 18:15) Transhumanism, Digital Immortality and the Meaning of Life==
:9:45 Julien Mommer, What is the Intelligence in "Artificial Intelligence"
'''ChatGPT and its Future'''


:Max More and Natasha Vita-More (Eds.), ''The Transhumanist Reader: Classical and Contemporary Essays on the Science, Technology, and Philosophy of the Human Future'', Wiley-Blackwell, 2013.
'''The Indispensability of Human Creativity


==Friday May 17 (9:30-12:15) Student Presentations and Concluding Survey==
'''Capabilities: The Interesting Version of the Story'''


:'''Student Presentations'''
:'''Student Presentations'''


Aaron Wirt: Politics and Digital Technologies
==Background Material==
 
Sven Eichholtz: A Critique of Cross-modal Vector Space Alignment for Capturing Referential Semantics
 
Jahmaira Archbold: AI to Understand Animal Communication
 
​David Alarcon and ​Davide Casnici: I​n Turing's and Gödel's Shadows: The Inaccessible Horizons of Artificial Intelligence
 
Qianbo Zang: Would machine intelligence, if there is such a thing, be something comparable to human intelligence or something quite different?
 
==Background Reading==


'''An Introduction to AI for Philosophers'''
'''An Introduction to AI for Philosophers'''
:[https://www.youtube.com/watch?v=cmiY8_XVvzs Video]
:[https://www.youtube.com/watch?v=cmiY8_XVvzs Video]
:[https://buffalo.box.com/v/Why-not-robot-cops Slides]
:[https://buffalo.box.com/v/Why-not-robot-cops Slides]
(AI experts are invited to criticize what I have to say here)
(AI experts are invited to criticize what I have to say in this talk)


'''An Introduction to Philosophy for Computer Scientists'''
'''An Introduction to Philosophy for Computer Scientists'''
:[https://buffalo.box.com/v/What-is-philosophy Video]
:[https://buffalo.box.com/v/What-is-philosophy Video]
:[https://buffalo.box.com/v/Crash-Course-Introduction Slides]
:[https://buffalo.box.com/v/Crash-Course-Introduction Slides]
(Philosophers are invited to criticize what I have to say here)
(Philosophers are invited to criticize what I have to say in this talk)


'''[https://www.cp.eng.chula.ac.th/~prabhas/teaching/cbs-it-seminar/2012/aiphil-mccarthy.pdf John McCarthy, "What has AI in common with philosophy?"]
'''[https://www.cp.eng.chula.ac.th/~prabhas/teaching/cbs-it-seminar/2012/aiphil-mccarthy.pdf John McCarthy, "What has AI in common with philosophy?"]

Latest revision as of 15:57, 25 September 2024

Philosophy and Artificial Intelligence 2024

Jobst Landgrebe and Barry Smith

MAP, USI, Lugano, Spring 2024

Background

Philosophy and Artificial Intelligence 2025

Artificial Intelligence (AI) is the subfield of Computer Science devoted to developing programs that enable computers to display behavior that can (broadly) be characterized as intelligent. On the strong version, the ultimate goal of AI is to create what is called General Artificial Intelligence (AGI), by which is meant an artificial system that is as intelligent as a human being.

Since its inception in the middle of the last century AI has enjoyed repeated cycles of enthusiasm and disappointment (AI summers and winters). Recent successes of ChatGPT and other Large Language Models (LLMs) have opened a new era popularization of AI. For the first time, AI tools have been created which are immediately available to the wider population, who for the first time can have real hands-on experience of what AI can do.

These developments in AI open up a series of questions such as:

Will the powers of AI continue to grow in the future, and if so will they ever reach the point where they can be said to have intelligence equivalent to or greater than that of a human being?
Could we ever reach the point where we can accept the thesis that an AI system could have something like consciousness or sentience?
Could we reach the point where an AI system could be said to behave ethically, or to have responsibility for its actions.
Can quantum computers enable a stronger AI than what we have today?

We will describe in detail how stochastic AI work, and consider these and a series of other questions at the borderlines of philosophy and AI. The class will close with presentations of papers on relevant topics given by students.

Some of the material for this class is derived from our book

Why Machines Will Never Rule the World: Artificial Intelligence without Fear (Routledge 2022).

and from the companion volume

Symposium on Why Machines Will Never Rule the World — Guest editor, Janna Hastings, University of Zurich

which will appear as a special issue of the public access journal Cosmos + Taxis in early 2024.


Faculty

Jobst Landgrebe is the founder and CEO of Cognotekt, GmBH, an AI company based in Cologne specialised in the design and implementation of holistic AI solutions. He has 20 years experience in the AI field, 8 years as a management consultant and software architect. He has also worked as a physician and mathematician, and he views AI itself -- to the extent that it is not an elaborate hype -- as a branch of applied mathematics. CUrrently his primary focus is in the biomathematics of cancer.

Barry Smith is one of the world's most widely cited philosophers. He has contributed primarily to the field of applied ontology, which means applying philosophical ideas derived from analytical metaphysics to the concrete practical problems which arise where attempts are made to compare or combine heterogeneous bodies of data.

Course Description

Artificial Intelligence (AI) is the subfield of Computer Science devoted to developing programs that enable computers to display behavior that can (broadly) be characterized as intelligent. On the strong version, the ultimate goal of AI is to create an artificial system that is as intelligent as a human being. Recent striking successes such as AlphaFold have convinced many not only that this objective is obtainable but also that in a not too distant future machines will become even more intelligent than human beings.

The actual and possible developments in AI open up a series of striking questions such as:

  • Can a computer have a conscious mind?
  • Can a computer have desires, a will, and emotions?
  • Can a computer have responsibility for its behavior
  • Would machine intelligence, if there is such a thing, be something comparable to human intelligence or something quite different?

In addition, new developments in the AI field make it possible for us to consider a series of philosophical questions in a new light, including:

  • Could a machine have something like a personal identity? Would I really survive if the contents of my brain were uploaded to the cloud?
  • What is it for a human to behave in an ethical manner? (Could there be something like machine ethics? Could machines used in fighting wars be programmed to behave ethically?)
  • What is a meaningful life? If routine, meaningless work in the future is performed entirely by machines, will this make possible new sorts of meaningful lives on the part of humans?

After introducing the relevant ideas and tools from both AI and philosophy, all the aforementioned questions will be thoroughly addressed in class discussions. The class will close with presentations of papers on relevant topics given by students.

Grading

Essay with presentation: 80%
Essay with no presentation: 95%
Presentation: 15%
Class Participation 5%

Draft Schedule

Tuesday, February 20 (14:30-17:15) Introduction: Philosophy and Artificial Intelligence

Room: A23

We begin with a survey of the development of AI research from 1970 to today, paying attention especially to the background role of ontology (Knowledge Graphs) in this development.

We then outline the main theses of the recent book, Why Machines Will Never Rule the World, by Landgrebe and Smith, before moving on to discuss the relation between a human mind and the intelligence that might be ascribed to a machine.

Slides

Wednesday February 21 (14:30-17:15): The Glory and the Misery of ChatGPT

Room: A23

Part 1: What is intelligence?

All students are expected to have some familiarity with Searle's Chinese Room Argument.

Machines cannot have intentionality; they cannot have experiences which are about something. Searle: Minds, Brains, and Programs

Slides

What are the essential marks of human intelligence? 

The classical psychological definitions of intelligence are:  

A. the ability to adapt to new situations (applies both to humans and to animals) 
B. a very general mental capability (possessed only by humans) that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience 

Can a machine be intelligent in either of these senses?

Readings:

Linda S. Gottfredson. Mainstream Science on Intelligence. In: Intelligence 24 (1997), pp. 13–23.

Human and machine intelligence

Jobst Landgrebe and Barry Smith: There is no Artificial General Intelligence

Part 2: An introduction to ChatGPT. How is it built? How does it work? Is it intelligent?

Can ChatGPT become intelligent?

Are Large Language Models a threat to humanity?

Capabilities, or: What do IQ tests measure?

Slides

Is Psychology Finished?

Slides

The human brain and the Theory of complex systems

Jobst Landgrebe and Barry Smith: Making AI Meaningful Again
S. Thurner et al. (2018): Introduction to the theory of complex systems (Oxford)

Thursday, February 22 (14:30 - 17:15): Can an Artificial Intelligence Act?

Room: A23
AI Ethics Slides

What is agency?

Featuring Emanuele Martinelli. Emanuele is a PhD student in philosophy at the University of Zurich, co-affiliated with the Chair of Political Philosophy and the Digital Society Initiative. He has a bachelor's in philosophy and a master's in philosophy and economics, both from USI.
What are the different types of agency?
Examples of collective agency, government agency, agency of socio-technical systems (armies, corporations, ...)
Relation between agency and responsibility. (Responsibility as the origin of ethics.)
Can an AI be responsibe?
Can there be such a thing as an AI will?

Agency and the capacities and limits of AI

Case study: AI and economic planning
Hayek's knowledge problem
The price system and market competition
Market economies vs planned economies: the agents at stake
Proposed ways to use AI to plan the economy
The role of the entrepreneur
Can AI be entrepreneurial

Background reading:

"On the Feasibility of Technosocialism"
"Group Agency and Artificial Intelligence"
"Toward a General Model of Agency"

Friday, February 23 (9:30 - 12:15) No Machine Will

Room: A23

Computers cannot have a will, because computers don't give a damn. Therefore there can be no machine ethics

The lack of the giving-a-damn-factor is taken by Yann LeCun as a reason to reject the idea that AI might pose an existential risk to humanity – an AI will have no desire for self-preservation “Almost half of CEOs fear A.I. could destroy humanity five to 10 years from now — but ‘A.I. godfather' says an existential threat is ‘preposterously ridiculous’” Fortune, June 15, 2023. See also here.

Implications of the absence of a machine will:

The problem of the singularity (when machines will take over from humans) will not arise
The idea of digital immortality will never be realized Slides
The idea that human beings are simulations can be rejected
There can be no AI ethics (only: ethics governing human beings when they use AI)
Fermi's paradox is solved

Monday, May 13 (9:30 - 12:15) The absolute limits of AI

Room: A23

Topics to be dealt with include:

What is AI?
How does it work?
What are its limits?
And what about ChatGPT?

Background: Will AI Destroy Humanity? A Soho Forum Debate (Spoiler: Jobst won)

Slides

Tuesday, May 14 (9:30 - 12:15) The ontology of physics

Room: A23

The ontology of physics

Slides

Wednesday May 15 (9:30 - 12:15): Are we living in a simulation? (II), digital twins and and Certifiable AI

Room: A23

On David Chalmers' theory of reality and the role of physics Slides

Thursday May 16 (14:30 - 18:15) The Replication Problem

Room: A23

Complex Systems and Cognitive Science: Why the Replication Problem is here to stay

The 'replication problem' is the the inability of scientific communities to independently confirm the results of scientific work. Much has been written on this problem especially as it arises in (social) psychology, and on potential solutions under the heading of 'open science'. But we will see that the replication problem has plagued medicine as a positive science since its beginnings (Virchov and Pasteur). This problem has become worse over the last 30 years and has massive consequences for healthcare practice and policy.

Slides

Background:

Reproducibility of Scientific Results, Stanford Encyclopedia of Philosophy, 2018
Science has been in a “replication crisis” for a decade
Irreproducibility Crisis and the Lehman Crash, Barry Smith, Youtube 2020

Friday May 17 (9:30-12:15) Student Presentations and Concluding Survey

Room: A23
9:45 Julien Mommer, What is the Intelligence in "Artificial Intelligence"

ChatGPT and its Future

The Indispensability of Human Creativity

Capabilities: The Interesting Version of the Story

Student Presentations

Background Material

An Introduction to AI for Philosophers

Video
Slides

(AI experts are invited to criticize what I have to say in this talk)

An Introduction to Philosophy for Computer Scientists

Video
Slides

(Philosophers are invited to criticize what I have to say in this talk)

John McCarthy, "What has AI in common with philosophy?"

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