Philosophy and Artificial Intelligence 2024
Philosophy and Artificial Intelligence 2024
Jobst Landgrebe and Barry Smith
MAP, USI, Lugano, Spring 2024
Background
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 what is called General Artificial Intelligence (AGI), by which is meant an artificial system that is as intelligent as a human being.
Since its inception in the middle of the last century AI has enjoyed repeated cycles of enthusiasm and disappointment (AI summers and winters). Recent successes of ChatGPT and other Large Language Models (LLMs) have opened a new era popularization of AI. For the first time, AI tools have been created which are immediately available to the wider population, who for the first time can have real hands-on experience of what AI can do.
These developments in AI open up a series of questions such as:
- Will the powers of AI continue to grow in the future, and if so will they ever reach the point where they can be said to have intelligence equivalent to or greater than that of a human being?
- Could we ever reach the point where we can accept the thesis that an AI system could have something like consciousness or sentience?
- Could we reach the point where an AI system could be said to behave ethically, or to have responsibility for its actions.
- Can quantum computers enable a stronger AI than what we have today?
We will describe in detail how stochastic AI work, and consider these and a series of other questions at the borderlines of philosophy and AI. The class will close with presentations of papers on relevant topics given by students.
Much of the material for this class is derived from our book
and from the companion volume
- Symposium on Jobst Why Machines Will Never Rule the World — Guest editor, Janna Hastings, University of Zurich
which will appear as a special issue of the public access journal Cosmos + Taxis in early 2024.
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.
Very Early Draft Schedule
Tuesday, February 20 (14:30-17:15) Why Machines Will Never Rule the world
This is an introduction to the book, with an emphasis on the relation between a human mind and the intelligence that might be ascribed to a machine
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.
Human and machine intelligence
- Jobst Landgrebe and Barry Smith: There is no Artificial General Intelligence
Wednesday February 21 (9:30-12:15 noon): The Glory and the Misery of ChatGPT
- Room:
An introduction to ChatGPT. How is it built? How does it work? Is it intelligent?
Can ChatGPT become intelligent?
Are Large Language Models a threat to humanity?
Capabilities, or: What do IQ tests measure?
Is Psychology Finished?
The human brain and the Theory of complex systems
- Jobst Landgrebe and Barry Smith: Making AI Meaningful Again
- S. Thurner et al. (2018): Introduction to the theory of complex systems (Oxford)
Thursday, February 22 (14:30 - 17:15): Language and Natural Intelligence
Language Structure and Language Economy
Large Language Models
Natural Intelligence
Friday, February 23 (9:30 - 12:15) The Missing AI Will
Machines cannot have intentionality; they cannot have experiences which are about something.
- John Searle: Minds, Brains, and Programs
Computers cannot have a will, because computers don't give a damn:
The lack of the giving-a-damn-factor is taken by Yann LeCun as a reason to reject the idea that AI might pose an existential risk to humanity – an AI will have no desire for self-preservation “Almost half of CEOs fear A.I. could destroy humanity five to 10 years from now — but ‘A.I. godfather' says an existential threat is ‘preposterously ridiculous’” Fortune, June 15, 2023. See also here.
Implications of the absence of a machine will:
- The problem of the singularity (when machines will take over from humans) will not arise
- The idea of digital immortality will never be realized Slides
- The idea that human beings are simulations can be rejected
- There can be no AI ethics (only: ethics governing human beings when they use AI)
Monday, May 13 (9:30 - 12:15) From Turing Machines to Quantum Computation
1. Introduction to the theory of computation and of Turing machines: What is a Turing machine?, Turing machine elements and structure, example of a Turing machine, recursive functions, non-recursive functions, Church-Turing computability
2. Classical logic-gate based computation: binary logic of computers, registers, logic gates and circuits, examples of circuits
3. Quantum mechanics: superposition, double slit, uncertainty, Stern-Gerlach, Hamiltonian, Hilbert space
Source: Nielsen and Chuang, Quantum Computation and Quantum Information
Tuesday, May 14 (9:30 - 12:15) Quantum Computation 2
Continues Wednesday's lecture:
4. Quantum computing: quantum bits, registers, quantum gates, simple quantum algorithm, quantum error (correction), future of quantum computing
5. Philosophical interpretation of quantum computing
6. Why quantum computers are Turing machines
Mikhail Dyakonov, The Case Against Quantum Computing
Wednesday May 15 (9:30 - 12:15): The Use of AI in Scientific and Medical Research
Thursday May 16 (14:30 - 18:15) Models
What does it mean to say that Large Language Models are models?
How do we define 'model'?
- The Limits of Mathematical Models and the Limits of AI
- Slides
- 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
- Why we ain’t rich
- 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 -->
Friday May 17 (9:30-12:15) Student Presentations and Concluding Survey
- Student Presentations
Aaron Wirt: Politics and Digital Technologies
Sven Eichholtz: A Critique of Cross-modal Vector Space Alignment for Capturing Referential Semantics
Jahmaira Archbold: AI to Understand Animal Communication
David Alarcon and Davide Casnici: In Turing's and Gödel's Shadows: The Inaccessible Horizons of Artificial Intelligence
Qianbo Zang: Would machine intelligence, if there is such a thing, be something comparable to human intelligence or something quite different?
Background Reading
An Introduction to AI for Philosophers
(AI experts are invited to criticize what I have to say here)
An Introduction to Philosophy for Computer Scientists
(Philosophers are invited to criticize what I have to say here)
