Philosophy and Artificial Intelligence 2023

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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, Feb 28 (15:30-18:00pm) 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 March 1 (14:30-18:00): 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

Smith Slides

Landgrebe Slides

Video of Opening Presentation by Landgrebe and Smith

15:15 – 15:30 Jobst Landgrebe (Buffalo, USI) "The Core Mathematical Argument"

15:30 –16:00 Landgrebe: "Large Language Models (Galactica, ChatGPT)", Smith: "ChatGPT heuristics" (Examples of ChatGPT hallucinations)

16:00 – 16:15 Q&A

16:15 – 16:30 Coffee Break

16:30 – 18:00 Tim Crane (CEU, Vienna) “Is Artificial General Intelligence Possible?”

Thursday, March 2 (9:30-12:00 noon): Language and Natural Intelligence

Landgrebe Slides

Language Structure and Language Economy (Landgrebe)

Large Language Models (Landgrebe)

Natural Intelligence (Landgrebe)

Thursday March 2 (14:00-18:00): Part 2 of Conference on Why Machines Will Never Rule the World

14:30 – 16:00 Emma Tieffenbach (USI, Zürich) “Making Sense of Singularity”

16:00 – 16:15 Coffee Break

16:15 – 17:45 Stefan Wolf (USI) “agAInst”

17:45 – 18:15 Concluding replies by Jobst Landgrebe & Barry Smith

Friday, March 3 (13:30 - 16:00pm) Digital Immortality and the Meaning of Life

Slides

Tuesday, May 9 (15:30 - 18:00pm) The Machine Will

The Turing test

What is the mind?

Can machines have a consciousness?

Searle’s wall
The Lucas-Penrose argument against machine consciousness
Bringsjord’s defence of machine consciousness
Other approaches in philosophy of mind, computation and AI
Computational theory of the mind

Objectifying intelligence and theoretical thinking

Why machines will not master human language
Neural Machine Translation
Human language as a complex system
Properties of the language system
AI conversation emulation
Challenges to machine conversation-->
Initial utterance production
Modelling dialogue dynamics mathematically
Mathematical models of human conversations
Current state-of-the-art in dialogue systems
Why conversation machines are doomed to fail
Chapter 11 Why machines will not master social interaction 224
No AI emulation of social behaviour
Some examples
No machine intersubjectivity
No machine social norms
AI and legal norms
No machine emulation of morality
No explicit ethical agents
No AGI in the kill chain


What is will?

Can machines have a will?

Why no Robot Cops?

Slides

Could a machine have goals?

Slides
Video

Questions


Readings:

Moor: Four kinds of ethical robots
Crane: The AI Ethics Hoax

Wednesday, May 10 (9:30 - 13:00) Logic and Complex Systems: Computation

Implementing mathematical models in computers
Classical computation
Turing machines
Classical logic-gate based computation
Quantum computation
Quantum mechanics
Quantum computing
Why quantum computers are Turing machines

Thursday, May 11 (9:30 - 12:00 noon) Logic and Complex Systems

The Limits of Mathematical Models
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
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
Preliminary Video

Tuesday May 16 (15:30 - 18:00pm): 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

Wednesday May 17 (9:30 - 12:00 noon) Student Presentations and Concluding Survey

Files
Student Presentations

Aaron Wirt: Politics and Digital Technologies

Sven Eichholtz

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?"