Philosophy and Artificial Intelligence 2023

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) Quantum Computation 1

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?"