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.

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
Landgrebe Slides

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): Intelligence, Complex Systems

Room:
Jobst Landgrebe: Animal, human and machine intelligence; Complex systems


Intelligence

Landgrebe Slides (start half way through)

Landgrebe-Mar2-Audio

Bibliography of Why Machines Will Never Rule the Earth

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
Video

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

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): Mathematical models of intelligence

Jobst Landgrebe:

Mathematical models of complex systems

No machine intelligence

No machine language

Argument against David Chalmers

Slides
Video

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) AI will, AI Ethics - Why Not Robot Cops?

The Turing test

What is will?

Can machines have a will?

Why no Robot Cops?

Slides

Could a machine have goals?

Slides
Video

Questions

What is the basis of ethics as applied to humans?

Utilitarianism
Value ethics

On what basis should we build an AI ethics?

AI ethics is (a) impossible? (b) unnecessary?

Readings:

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

Jobs for Philosophers

Slides

Digital Immortality

Slides

The Meaning of Life

Slides

Tuesday, May 9 (15:30 - 18:00pm) Intelligence and Other Capabilities

Capabilities, or: What do IQ tests measure?

Slides

Is Psychology Finished?

Slides

Wednesday, May 10 (9:30 - 12:00 noon) Logic and Complex Systems: Part 1

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
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

Thursday, May 11 (9:30 - 12:00 noon) Logic and Complex Systems: Part 2

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

Student Presentations

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

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

Files Student Presentations

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)

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