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'''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.
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:
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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'''


:This is an introduction to the book, with an emphasis on the relation between a human mind and the intelligence that might be ascribed to a machine
==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
 
''Part 1: What is intelligence?''


==Wednesday February 21 (9:30-12:15 noon):  ==
All students are expected to have some familiarity with [https://www.youtube.com/watch?v=tt-JzB50sJE Searle's Chinese Room Argument].


:Room:
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]
'''Artificial General Intelligence'''


An introduction to ChatGPT. How is it built? How does it work? Is it intelligent?
:[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]
''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?


'''The human brain and the Theory of complex systems'''
Capabilities, or: What do IQ tests measure?
:[https://buffalo.box.com/v/What-do-IQ-tests-2022 Slides]


:Jobst Landgrebe and Barry Smith: [https://arxiv.org/pdf/1901.02918.pdf Making AI Meaningful Again]
Is Psychology Finished?
:S. Thurner et al. (2018): Introduction to the theory of complex systems (Oxford):
:[https://buffalo.box.com/v/Is-Psychology-Finished? Slides]


==Thursday, February 22 (14:30 - 17:15): Language and Natural Intelligence ==
The human brain and the Theory of complex systems


Language Structure and Language Economy
:Jobst Landgrebe and Barry Smith: [https://arxiv.org/pdf/1901.02918.pdf Making AI Meaningful Again]
:[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)]


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


Natural Intelligence
:Room: A23


==Friday, February 23 (9:30 - 12:15) The Missing Human Will==
:[https://buffalo.box.com/s/n70b84o813hp0jsfnznczeg8sid9mtnv AI Ethics Slides]


[https://buffalo.box.com/v/Digital-Immortality-2023 Slides]
''What is agency?''


Questions of AI ethics
: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.


The 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?


The missing machine 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


Consequences for the limits of AI
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]"


Preliminary Remarks on ChatGPT and other Large Language Models
==Friday, February 23 (9:30 - 12:15) No Machine Will ==
<!-- This is a comment
:The Limits of Mathematical Models and the Limits of AI
:[https://buffalo.box.com/s/xnmc8zi1btpnku365bysxmowcgk99epd Slides]


::'''Models'''
:Room: A23
:::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'''
Computers cannot have a will, because computers ''don't give a damn''. Therefore there can be no machine ethics
::[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 ==
: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].


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
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 [https://buffalo.box.com/v/Digital-Immortality-2023 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


2. Classical logic-gate based computation: binary logic of computers, registers, logic gates and circuits, examples of circuits
==Monday, May 13 (9:30 - 12:15) Does AI Pose a Threat to Humanity?==


3. Quantum mechanics: superposition, double slit, uncertainty, Stern-Gerlach, Hamiltonian, Hilbert space
:Room: A23


Source: Nielsen and Chuang, ''[https://csis.pace.edu/~ctappert/cs837-19spring/QC-textbook.pdf Quantum Computation and Quantum Information]''
Motion: Artificial Intelligence Poses a Threat to the Survival of Humanity that must be Actively Addressed by Government


[https://youtu.be/_mvoS_H_kA8 Video]
Topics to be dealt with include:
:Is "AI ethics" a misnomer (rather like "gun ethics" or "car ethics")?
:How, if at all, can we regulate the use of AI for military purposes?
:Are efforts to regulate AI naive?
:Are efforts on the part of big companies to regulate AI in fact attempts by those big companies to block new entrants into the market?


[https://buffalo.box.com/v/Quantum-Computing-1 Slides for Parts 1 and 2]
Background: '''[https://www.youtube.com/watch?v=1rnam1w8ztM Will AI Destroy Humanity? A Soho Forum Debate]''' (Spoiler: Jobst won)


==Tuesday, May 14 (9:30 - 12:15) Quantum Computation 2 ==
==Tuesday, May 14 (9:30 - 12:15) Are we living in a simulation? ==


Continues Wednesday's lecture:
:Room: A23


4. Quantum computing: quantum bits, registers, quantum gates, simple quantum algorithm, quantum error (correction), future of quantum computing
David Chalmers' theory of (virtual) reality (''Reality+'', 2022)
:Chalmers' main arguments
:A refuation of the brain-in-a-vat theory
:Why modern physics is incomplete


5. Philosophical interpretation of quantum computing
==Wednesday May 15 (9:30 - 12:15): Are we living in a simulation? (II), digital twins and and Certifiable AI  ==


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]''
More on David Chalmers' theory of reality


[https://youtu.be/BB89YcLeAko Video]
Digital twins


==Wednesday May 15 (9:30 - 12:15): The Use of AI in Scientific and Medical Research =
Certifiable AI vs Explainable AI


==Thursday May 16 (14:30 - 18:15) Transhumanism, Digital Immortality and the Meaning of Life==
==Thursday May 16 (14:30 - 18:15) The Replication Problem==


: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.
:Room: A23


==Friday May 17 (9:30-12:15) Student Presentations and Concluding Survey==
''Complex Systems and Cognitive Science: Why the Replication Problem is here to stay''


:'''Student Presentations'''
: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.


Aaron Wirt: Politics and Digital Technologies
Background:


Sven Eichholtz: A Critique of Cross-modal Vector Space Alignment for Capturing Referential Semantics
:[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


Jahmaira Archbold: AI to Understand Animal Communication
==Friday May 17 (9:30-12:15) Student Presentations and Concluding Survey==


​David Alarcon and ​Davide Casnici: I​n Turing's and Gödel's Shadows: The Inaccessible Horizons of Artificial Intelligence
:Room: A23


Qianbo Zang: Would machine intelligence, if there is such a thing, be something comparable to human intelligence or something quite different?
:'''Student Presentations'''


==Background Reading==
==Background Material==


'''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 19:11, 4 May 2024

Philosophy and Artificial Intelligence 2024

Jobst Landgrebe and Barry Smith

MAP, USI, Lugano, Spring 2024

Background

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) Does AI Pose a Threat to Humanity?

Room: A23

Motion: Artificial Intelligence Poses a Threat to the Survival of Humanity that must be Actively Addressed by Government

Topics to be dealt with include:

Is "AI ethics" a misnomer (rather like "gun ethics" or "car ethics")?
How, if at all, can we regulate the use of AI for military purposes?
Are efforts to regulate AI naive?
Are efforts on the part of big companies to regulate AI in fact attempts by those big companies to block new entrants into the market?

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

Tuesday, May 14 (9:30 - 12:15) Are we living in a simulation?

Room: A23

David Chalmers' theory of (virtual) reality (Reality+, 2022)

Chalmers' main arguments
A refuation of the brain-in-a-vat theory
Why modern physics is incomplete

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

Room: A23

More on David Chalmers' theory of reality

Digital twins

Certifiable AI vs Explainable AI

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.

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
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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