Philosophy and Artificial Intelligence 2024: Difference between revisions

From NCOR Wiki
Jump to navigationJump to search
(Created page with "Philosophy and Artificial Intelligence 2024 Artificial Intelligence (AI) is the subfield of Computer Science devoted to developing programs that enable computers to display...")
 
mNo edit summary
Line 10: Line 10:


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.
'''Jobst Landgrebe and Barry Smith'''
[https://www.usi.ch/en/education/master/philosophy MAP, USI, Lugano], Spring 2023
'''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). The March 1-2 sessions of the class will be accompanied by afternoon sessions devoted to a conference on the book.
[https://buffalo.app.box.com/v/AI-Without-Fear Table of contents, first chapter and references]
'''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.
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.
'''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.
'''Draft Schedule'''
==Tuesday, February 14 (14:30-17:15pm) Why machines will never rule the world ==
:Barry Smith:  Overview of the arguments and introduction to the human mind.
:Room:
:::Announcement: ''[https://buffalo.app.box.com/v/AI-Without-Fear Why Machines Will Never Rule the World]''
Introduction to the class
:[https://buffalo.box.com/v/Smith-Introduction Smith Slides]
:[https://buffalo.box.com/v/Smith-Audio-Feb28 Smith Audio]
Readings:
: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]
: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.
==Wednesday March 1 (9:30-12:00 noon): Artificial General Intelligence and Introduction to Stochastic AI ==
:Room:
'''Artificial General Intelligence'''
[https://buffalo.box.com/v/Landgrebe-March-1-2023 Landgrebe Slides]
[https://buffalo.box.com/v/Bibliography-LandS Bibliography of ''Why Machines Will Never Rule the World'']
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 
What are the essential marks of human intelligence? 
Readings:
:Linda S. Gottfredson. [https://www1.udel.edu/educ/gottfredson/reprints/1994WSJmainstream.pdf Mainstream Science on Intelligence]. In: ''Intelligence'' 24 (1997), pp. 13–23.
:[https://buffalo.box.com/v/Hutter-Definition Slides from 2022]
:[https://www.youtube.com/watch?v=ReoyoinaKUE Video from 2022]
'''The Legg-Hutter Definition of Intelligence'''
What is it that researchers and engineers are trying to do when they talk of achieving ‘Artificial Intelligence’?
To what extent can AI be achieved? 
Problems with the Legg-Hutter Definition of Intelligence
'''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]
:S. Thurner et al. (2018): Introduction to the theory of complex systems (Oxford):
==Wednesday, 21 February (9:30-12:15): Part 1 of Conference on ''Why Machines Will Never Rule the World''==
14:30 – 14:45 Welcome
14:45 – 15:15 Barry Smith (Buffalo, USI): Summary of the Book
==Thursday, February 22 (14:30-17:15): Language and Natural Intelligence ==
[https://buffalo.box.com/v/Landgrebe-March-1-2023 Landgrebe Slides]
Language Structure and Language Economy (Landgrebe)
Large Language Models (Landgrebe)
Natural Intelligence (Landgrebe)
==Friday, February 23 (9:30 - 12:15pm) Digital Immortality and the Meaning of Life==
[https://buffalo.box.com/v/Digital-Immortality-2023 Slides]
==Monday, May 9 (9:30 - 12:15pm) The Human Will; and the Limits of AI ==
[https://buffalo.box.com/v/The-Human-Will Slides]
Simple and complex systems
The human will
The missing machine will
Consequences for the limits of AI
Preliminary Remarks on ChatGPT and other Large Language Models
<!-- This is a comment
:The Limits of Mathematical Models and the Limits of AI
:[https://buffalo.box.com/s/xnmc8zi1btpnku365bysxmowcgk99epd Slides]
::'''Models'''
:::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'''
::[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] -->
==Tuesday, May 14 (9:30 - 13:00) Quantum Computation 1 ==
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
2. Classical logic-gate based computation: binary logic of computers, registers, logic gates and circuits, examples of circuits
3. Quantum mechanics: superposition, double slit, uncertainty, Stern-Gerlach, Hamiltonian, Hilbert space
Source: Nielsen and Chuang, ''[https://csis.pace.edu/~ctappert/cs837-19spring/QC-textbook.pdf Quantum Computation and Quantum Information]''
[https://youtu.be/_mvoS_H_kA8 Video]
[https://buffalo.box.com/v/Quantum-Computing-1 Slides for Parts 1 and 2]
==Thursday, May 11 (9:30 - 12:00 noon) Quantum Computation 2 ==
Continues Wednesday's lecture:
4. Quantum computing: quantum bits, registers, quantum gates, simple quantum algorithm, quantum error (correction), future of quantum computing
5. Philosophical interpretation of quantum computing
6. Why quantum computers are Turing machines
Mikhail Dyakonov, ''[https://spectrum.ieee.org/the-case-against-quantum-computing The Case Against Quantum Computing]''
[https://youtu.be/BB89YcLeAko Video]
==Wednesday May 15 (9:30 - 12:15pm): The Nature of Intelligence: Humans vs. ChatGPT ==
Human and machine intelligence
Can ChatGPT become intelligent?
Are Large Language Models a threat to humanity?
Capabilities, or: What do IQ tests measure?
:[https://buffalo.box.com/v/What-do-IQ-tests-2022 Slides]
Is Psychology Finished?
:[https://buffalo.box.com/v/Is-Psychology-Finished? Slides]
==Thursday May 16 (14:30 - 18:15) TBD==
==Friday May 17 (9:30-12:15) Student Presentations and Concluding Survey==
:'''Student Presentations'''
Aaron Wirt: Politics and Digital Technologies
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'''
:[https://www.youtube.com/watch?v=cmiY8_XVvzs Video]
:[https://buffalo.box.com/v/Why-not-robot-cops Slides]
(AI experts are invited to criticize what I have to say here)
'''An Introduction to Philosophy for Computer Scientists'''
:[https://buffalo.box.com/v/What-is-philosophy Video]
:[https://buffalo.box.com/v/Crash-Course-Introduction Slides]
(Philosophers are invited to criticize what I have to say here)
'''[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?"]

Revision as of 18:05, 2 November 2023

Philosophy and Artificial Intelligence 2024


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. 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.

Jobst Landgrebe and Barry Smith

MAP, USI, Lugano, Spring 2023

Background

Much of the material for this class is derived from our book Why Machines Will Never Rule the World: Artificial Intelligence without Fear (Routledge 2022). The March 1-2 sessions of the class will be accompanied by afternoon sessions devoted to a conference on the book.

Table of contents, first chapter and references

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 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.

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.


Draft Schedule

Tuesday, February 14 (14:30-17:15pm) Why machines will never rule the world

Barry Smith: Overview of the arguments and introduction to the human mind.
Room:
Announcement: Why Machines Will Never Rule the World

Introduction to the class

Smith Slides
Smith Audio

Readings:

John Searle: Minds, Brains, and Programs
Jobst Landgrebe and Barry Smith: There is no Artificial General Intelligence
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.

Wednesday March 1 (9:30-12:00 noon): Artificial General Intelligence and Introduction to Stochastic AI

Room:

Artificial General Intelligence

Landgrebe Slides

Bibliography of Why Machines Will Never Rule the World

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 

What are the essential marks of human intelligence? 

Readings:

Linda S. Gottfredson. Mainstream Science on Intelligence. In: Intelligence 24 (1997), pp. 13–23.
Slides from 2022
Video from 2022

The Legg-Hutter Definition of Intelligence

What is it that researchers and engineers are trying to do when they talk of achieving ‘Artificial Intelligence’?

To what extent can AI be achieved? 

Problems with the Legg-Hutter Definition of Intelligence

Theory of complex systems

Readings:

Shane Legg and Marcus Hutter: Universal Intelligence: A Definition of Machine Intelligence
Jobst Landgrebe and Barry Smith: Making AI Meaningful Again
S. Thurner et al. (2018): Introduction to the theory of complex systems (Oxford):

Wednesday, 21 February (9:30-12:15): Part 1 of Conference on Why Machines Will Never Rule the World

14:30 – 14:45 Welcome

14:45 – 15:15 Barry Smith (Buffalo, USI): Summary of the Book

Thursday, February 22 (14:30-17:15): Language and Natural Intelligence

Landgrebe Slides

Language Structure and Language Economy (Landgrebe)

Large Language Models (Landgrebe)

Natural Intelligence (Landgrebe)

Friday, February 23 (9:30 - 12:15pm) Digital Immortality and the Meaning of Life

Slides

Monday, May 9 (9:30 - 12:15pm) The Human Will; and the Limits of AI

Slides

Simple and complex systems

The human will

The missing machine will

Consequences for the limits of AI

Preliminary Remarks on ChatGPT and other Large Language Models

Tuesday, May 14 (9:30 - 13:00) Quantum Computation 1

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

2. Classical logic-gate based computation: binary logic of computers, registers, logic gates and circuits, examples of circuits

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

Source: Nielsen and Chuang, Quantum Computation and Quantum Information

Video

Slides for Parts 1 and 2

Thursday, May 11 (9:30 - 12:00 noon) Quantum Computation 2

Continues Wednesday's lecture:

4. Quantum computing: quantum bits, registers, quantum gates, simple quantum algorithm, quantum error (correction), future of quantum computing

5. Philosophical interpretation of quantum computing

6. Why quantum computers are Turing machines

Mikhail Dyakonov, The Case Against Quantum Computing

Video

Wednesday May 15 (9:30 - 12:15pm): The Nature of Intelligence: Humans vs. ChatGPT

Human and machine intelligence

Can ChatGPT become intelligent?

Are Large Language Models a threat to humanity?

Capabilities, or: What do IQ tests measure?

Slides

Is Psychology Finished?

Slides

Thursday May 16 (14:30 - 18:15) TBD

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

Student Presentations

Aaron Wirt: Politics and Digital Technologies

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

Video
Slides

(AI experts are invited to criticize what I have to say here)

An Introduction to Philosophy for Computer Scientists

Video
Slides

(Philosophers are invited to criticize what I have to say here)

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

Retrieved from "https://ncorwiki.buffalo.edu/index.php?title=Philosophy_and_Artificial_Intelligence_2024&oldid=73980"