Philosophy and Artificial Intelligence 2021

Barry Smith

MAP, USI, Lugano, Spring 2021

Schedule Philosophy and Artificial Intelligence 2022

Monday February 22 2021 14:30 - 17:15: Some examples of philosophical problems

Slides

Introduction to the class

What is computation?

What is a language

The Turing Test and the problem of natural language production

What is consciousness?

What is will?

Can machines have a will?

What is intentionality?

Readings:

John Searle: Minds, Brains, and Programs

Jobst Landgrebe and Barry Smith: There is no Artificial General Intelligence

Tuesday February 23 2021 14:30 - 17:15 The Impossibility of Digital Immortality

Slides

Part One: Immortality

Transhumanism and Identity: Can we download the contents of our brains onto a computer and become immortal?

Why you cannot exist outside your body

Readings:

Martine Rothblatt: Mind is Deeper Than Matter [TO BE SUPPLIED AT USI SITE]

Scott Adams: We are living in a simulation

AI and The Matrix

Part Two: 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 

What are the essential marks of human intelligence? 

For consideration in Wednesday's session: to what extent can artificial intelligence be achieved? 

Readings:

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

Wednesday February 24, 2021 14:30 - 16:00: The Legg-Hutter Definition of 'Universal Intelligence'

(with Jobst Landgrebe)

Slides

Video

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 16 years experience in AI field, 8 years as a management consultant and software architect. He has also worked as a physician and mathematician.

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

Readings:

Shane Legg and Marcus Hutter: Universal Intelligence: A Definition of Machine Intelligence

Jobst Landgrebe and Barry Smith: Making AI Meaningful Again

Friday February 26 2021 16:30 - 18:00 AI Ethics

(with Jobst Landgrebe)

Slides

Video

What is the basis of ethics as applied to humans?

Utilitarianism

Value ethics

On what basis should we build an AI ethics?

On why AI ethics is (a) impossible, (b) unnecessary

Readings:

Moor: Four kinds of ethical robots

Jobst Landgrebe and Barry Smith: No AI Ethics

Crane: The AI Ethics Hoax

Monday May 17 2021 14:30 - 18:00 (Room A12) Some Philosophical Questions About AI

Student presentations

Tommaso Soriani: Of (Zombie) Mice and Animats

Maria Andromachi Kolyvaki: Statistical Learning Theory as a Framework for the Philosophy of Induction.

Ismaele Affini: The Ugly Truth About Ourselves and Our Robot Creations: The Problem of Bias and Social Inequity

Anita Buckley: The limits of machine intelligence

Osama Khalil: Trolleyology: "Would you kill the fat man?"

There Will Be No Singularity: A Survey of the Argument

The Dreyfus case against the possibility of AGI

The Landgrebe-Smith case against the possibility of AGI

Three Types of Impossibility: Technical, Physical, Mathematical

Structure of the book:

Part I: Properties of the Human Mind

Nomological materialistic monism

Alternative views on the mind-body problem

Human and machine intelligence

Capabilities

Primal intelligence

Objectifying intelligence

Definitions of intelligence in AI

The Legg-Hutter definition (see Feb. 24, above)

Defining useful machine intelligence

What is language?

Language and intentions

Speech as sensorimotor activity

Language and dialect change

The variance and complexity of human language

Reading: There Will Be No AGI

Conversation and contexts

Language production (explicit); language interpretation (implicit)

The Turing test

Context horizon

Social, spatial, temporal context

Conversation flow and interruptions

Social and ethical behaviour (see Feb. 26, above)

Can we build an AI by emulating the brain?

David Chalmers on Brain Emulation

Can we build an AI by some other method?

David Chalmers on Artificial Evolution

David J. Chalmers: The Singularity: A Philosophical Analysis

David J. Chalmers: The Singularity: A Reply to Commentators

Tuesday May 18 2021 14:30 - 18:00 (Room A12)

Student presentations

Rwiddhi Chakraborty: The Myth of Hypercomputation

Amir Sulic: Why general AI will not be realized

Brian Pulfer: The Singularity and Machine Ethics

Peter Buttaroni: Adversarial Examples and the Deeper Riddle of Induction

The Limits of Mathematical Models

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

AI and the Mathematics of Complex Systems

Preliminary Slides

Wednesday May 19 2021 14:30 - 18:00 (Room A21) First Dialogue with Jobst Landgrebe

AI and the Mathematics of Complex Systems

Preliminary Slides

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

Thursday May 20 2021 12:30 - 16:00 (Room A12) Second Dialogue with Jobst Landgrebe

AI and the Ontology of Power, Social Interaction and Ethics

Preliminary Video

Friday May 21 2021 12:30 - 14:00 (Room A12) Concluding Survey

Student Presentations

Giacomo De Colle: Mind Embodied and Embedded

Rocco Felici: On Black Box Models in AI Ethics

Julius Schulte: Explainable AI: How Disciplines Talk Past Each Other

Gabriel Carraretto: Backpropagation and the Brain

Michele Damian: Performance vs. Competence in Human–Machine Comparisons

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 characterised 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 AlphaGo 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 it have desires and emotions?
• Would machine intelligence, if there is such a thing, be something comparable to human intelligence or something quite different?

In addition, these developments make it possible for us to consider a series of philosophical questions in a new light, including:

• What is personal identity? 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 following lectures by Drs Facchini and Smith and presentations of relevant papers by the students.

Further Background Reading

Jordan Peterson's Essay Writing Guide

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.