Philosophy and Artificial Intelligence 2021: Difference between revisions

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


:''There Will Be No Singularity'': A Survey of the Argument
'''''There Will Be No Singularity'': A Survey of the Argument'''


:The Dreyfus case against the possibility of AGI
:The Dreyfus case against the possibility of AGI


:Our case against the possibility of AGI
:The Landgrebe-Smith case against the possibility of AGI


::Three Types of Impossibility: Technical, Physical, Mathematical
::Three Types of Impossibility: Technical, Physical, Mathematical
Line 115: Line 115:
:Structure of the book:  
:Structure of the book:  
::Part I: Properties of the Human Mind
::Part I: Properties of the Human Mind
:::Nomological materialistic monism
::'''Nomological materialistic monism'''
::::Alternative views on the mind-body problem
::::Alternative views on the mind-body problem
:::Human and machine intelligence
::'''Human and machine intelligence'''
::::Primal intelligence
:::Capabilities
::::Objectifying intelligence
:::Primal intelligence
:::Objectifying intelligence
:::Definitions of intelligence in AI
:::Definitions of intelligence in AI
::::The Legg-Hutter definition (see Feb. 24, above)
::::The Legg-Hutter definition (see Feb. 24, above)
:::Defining ''useful'' machine intelligence
:::Defining ''useful'' machine intelligence
:::What is language?
::'''What is language?'''
::::Language and intentions
::::Language and intentions
::::Speech as sensorimotor activity
::::Speech as sensorimotor activity
::::Language and dialect change
::::Language and dialect change
::The variance and complexity of human language
::::The variance and complexity of human language
:::Reading: [https://arxiv.org/pdf/1906.05833.pdf There Will Be No AGI]
:::::Reading: [https://arxiv.org/pdf/1906.05833.pdf There Will Be No AGI]
::Conversation and contexts
::'''Conversation and contexts'''
:::Language production (explicit); language interpretation (implicit)
:::Language production (explicit); language interpretation (implicit)
:::The Turing test
:::The Turing test
Line 136: Line 137:
:::Conversation flow and interruptions
:::Conversation flow and interruptions
:::Social and ethical behaviour (see Feb. 26, above)
:::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: [http://consc.net/papers/singularity.pdf The Singularity: A Philosophical Analysis]
::::David J. Chalmers: [http://consc.net/papers/singreply.pdf The Singularity: A Reply to Commentators]


Background:
==Tuesday May 18 2021 14:30 - 18:00 (Room A12) ==
:What sorts of problems can AI solve?
::[https://arxiv.org/pdf/1901.02918.pdf Making AI Meaningful Again]
:What sorts of problems can AI not solve?
::[https://arxiv.org/pdf/1906.05833.pdf There is no general AI]
 
==Tuesday May 18 2021 14:30 - 18:00 (Room A12) Language+ ==


Student presentations
Student presentations
Line 151: Line 152:
:Peter Buttaroni: Adversarial Examples and the Deeper Riddle of Induction
:Peter Buttaroni: Adversarial Examples and the Deeper Riddle of Induction


:Part 2 (continued): The Limits of Mathematical Models
:'''The Limits of Mathematical Models'''
::
::'''Models'''
 
:::All science requires mathematical models
:Can we build an AI by emulating the brain?
:::Types of models 1: descriptive, explanatory, predictive
::David Chalmers on Brain Emulation
:::Types of models 2: qualitative, quantitative
:Can we build an AI by some other method?
::::All predictive models are quantitative
::David Chalmers on Artificial Evolution
::::Synoptic models
 
::::Adequate models
Readings:
:::Computability
:David J. Chalmers: [http://consc.net/papers/singularity.pdf The Singularity: A Philosophical Analysis]
:::All AI engineering requires mathematical models
:David J. Chalmers: [http://consc.net/papers/singreply.pdf The Singularity: A Reply to Commentators]
::::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
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-->
:AI and the Mathematics of Complex Systems
:[https://buffalo.box.com/v/AI-Limits-and-Impact Preliminary Slides]


==Wednesday May 19 2021 14:30 - 18:00 (Room A21) First Dialogue with Jobst Landgrebe==
==Wednesday May 19 2021 14:30 - 18:00 (Room A21) First Dialogue with Jobst Landgrebe==
:AI and the Mathematics of Complex Systems
:AI and the Mathematics of Complex Systems
:[https://buffalo.box.com/v/AI-Limits-and-Impact Preliminary Slides]
:[https://buffalo.box.com/v/AI-Limits-and-Impact 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 ==
==Thursday May 20 2021 12:30 - 16:00 (Room A12) Second Dialogue with Jobst Landgrebe ==


:AI and the Ontology of Power
:AI and the Ontology of Power, Social Interaction and Ethics
:[https://www.youtube.com/watch?v=EiBBS8ueyz4 Preliminary Video]
:[https://www.youtube.com/watch?v=EiBBS8ueyz4 Preliminary Video]


Line 179: Line 241:
:Julius Schulte: Explainable AI: How Disciplines Talk Past Each Other
:Julius Schulte: Explainable AI: How Disciplines Talk Past Each Other
:Gabriel Carraretto: Backpropagation and the Brain
:Gabriel Carraretto: Backpropagation and the Brain
:Michelle Damian: Performance vs. Competence in Human–Machine Comparisons
:Michele Damian: Performance vs. Competence in Human–Machine Comparisons


==Course Description==
==Course Description==

Latest revision as of 18:10, 3 February 2022

Barry Smith

MAP, USI, Lugano, Spring 2021

Schedule

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.