Center for Analysis and Design of Intelligent Agents

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[[/public:t-709-aies:AIES-24:main|DCS-T-709-AIES-2024 Main]]


===== T-709-AIES-2024 READINGS & STUDY MATERIAL  =====



[[/public:t-709-aies:AIES-24:readings?#readings_readme|Readings README]] (Do not skip!)
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===== Intelligence & Agents [4,5] =====

//What is intelligence? \\ How is intelligence realized in the physical world? \\ What uniquely separates the phenomenon of intelligence from other similar phenomena?//


  * [[https://en.wikipedia.org/wiki/Intelligent_agent|Intelligent Agents]] on Wikipedia
  * [[https://en.wikipedia.org/wiki/Cognitive_architecture|Cognitive Architecture]] on Wikipedia
  * [[https://arxiv.org/pdf/0706.3639.pdf|A Collection of Definitions of Intelligence]] by Legg & Hutter
  * [[https://bigthink.com/starts-with-a-bang/universe-made-pure-mathematics/|No, The Universe Isn't Made of Pure Mathematics]] by E. Siegel
  * [[https://www.npr.org/2024/06/07/nx-s1-4994426/wild-elephants-individual-names|Wild Elephants Give Names to Each Other]] on NPR


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===== Artificial Intelligence =====

//What is AI? \\ How is AI used in the physical world? \\ What is required to make the use of AI ethical? //

  * [[https://atmos.earth/using-ai-to-decode-animal-communication/|AI Could Help Us Talk to Animals—But Should It?]] by B. Warner
  * [[https://sciendo.com/article/10.2478/jagi-2019-0002|On Defining Artificial Intelligence]] by P. Wang
  * [[https://cdn.prod.website-files.com/669550d38372f33552d2516e/66bc918b580467717e194940_The%20AI%20Risk%20Repository_13_8_2024.pdf|AI risk repository]] at [[https://airisk.mit.edu/|MIT]]
  * [[https://www.csee.umbc.edu/courses/471/papers/turing.pdf|Computing Machinery and Intelligence]] by A. M. Turing
  * [[https://www.unesco.org/en/artificial-intelligence/recommendation-ethics/cases|Artificial Intelligence: examples of ethical dilemmas]] by UNESCO
  * [[https://arxiv.org/pdf/2305.18654.pdf|Limits of Transformers on Compositionality]] by Dziri et al.




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===== Reasoning, Learning & Meaning [3,5] =====
// No accepted theory of meaning and understanding exists \\ Systematic action requires knowledge of cause-effect relations \\ Reasoning in the physical world can only be non-axiomatic //

  * [[https://en.wikipedia.org/wiki/Reason| Reasoning]] on Wikipedia
  * [[https://core.ac.uk/download/pdf/82164736.pdf|The limitation of Bayesiansm]] by P. Wang
  * {{/public:t-709-aies:aies-24:theoryoffoundationalmeaning-thorisson-talevi-2024.pdf|A Theory of Foundational Meaning Generation, Natural & Artificial}} by K. R. Thórisson & G. Talevi
  * {{/public:chatgptcantreason.pdf|ChatGPT Can't Reason}} by K. Arkoudas
  * [[https://www.informationphilosopher.com/freedom/adequate_determinism.html|Adequate Determinism]] on the Information Philosopher
  * [[https://ftp.cs.ucla.edu/pub/stat_ser/r284-reprint.pdf|Bayesianism and Causality, or, Why I am Only a Half-Beyesian]] by J. Pearl

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===== Transparency & Trustworthiness of AI  =====
// Transparency means explanation \\ Explanation means cause-effect relations  \\ AI systems that can represent cause-effect relations are few  //

  * [[https://alumni.media.mit.edu/~kris/ftp/Explicit_Goal-Driven_Autonomous_Self-Explanation_Generation-2023.pdf|Explicit Goal-Driven
Autonomous Self-Explanation Generation]] by K.R.Thorisson & G. Talevi
  * [[https://proceedings.mlr.press/v159/thorisson22b/thorisson22b.pdf|The 'Explanation Hypothesis' in General Self-Supervised Learning]] by K.R.Thórisson
  * [[https://alumni.media.mit.edu/~kris/ftp/AGI16_understanding.pdf|About Understanding]] by K. R. Thórisson et al.
  * [[https://bigthink.com/the-present/gary-marcus-ai-transparency/|Big tech fails transparency test]] by Gary Marcus on The Big Think
  * [[https://unu.edu/cpr/blog-post/ai-global-governance-no-one-should-trust-ai|No One Should Trust AI]] by J. Bryson
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===== Philosophy & Ethics of Technology  =====
//  //

  * [[https://arxiv.org/pdf/2205.10785|Responsible Artificial Intelligence – from
Principles to Practice]] by V. Dignum
  * [[https://www.researchgate.net/publication/361151812_The_Uselessness_of_AI_Ethics|The Uselessness of AI Ethics]] by L. Munn
  * [[https://www.informationphilosopher.com/freedom/responsibility.html|Responsibility]] on The Information Philosopher
  * [[https://www.researchgate.net/publication/335579286_The_global_landscape_of_AI_ethics_guidelines|The global landscape of AI ethics guidelines]] by Jobin, et al. 
  * [[https://plato.stanford.edu/entries/technology/|Philosophy of Technology]] on Stanford Encyclopedia of Philosophy
  * [[https://plato.stanford.edu/entries/ethics-ai/|Ethics of Artificial Intelligence and Robotics]] on Stanford Encyclopedia of Philosophy




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===== Engines of Invention  =====
//  //

  * [[https://proceedings.mlr.press/v192/thorisson22b/thorisson22b.pdf|The Future of AI Research]] by K. R. Thórisson and H. Minsky
  * [[https://scalar.usc.edu/works/uiuc-macs410-media-information-ethics-/media/DoMachinesMakeHistory1967.pdf|Do Machines Make History?]] by R. L. Heilbroner
  * {{/public:t-709-aies:holborn1942.pdf|Printing and the Growth of a Protestant Movement in Germany from 1517 to 1524}} by L. W. Holborn
  * [[https://en.wikipedia.org/wiki/Futures_studiesFutures Studies]] on Wikipedia.



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===== Democracy & Society  [ 6,7 ]=====
//  //

  * {{/public:t-709-aies:aies-24:democracy_and_artificial_general_intelligence.pdf|Democracy & Artificial General Intelligence}} by E. Contio & J. Salmi
  * [[https://www.government.is/library/01-Ministries/Prime-Ministrers-Office/Fjorda-idnbyltingin-skyrsla-enska_HQ.pdf|Iceland & The Fourth Industrial Revolution]] by H. F. Thorsteinsson et al. 
  * [[https://link.springer.com/chapter/10.1007/978-3-030-69978-9_4|Ethical Issues of AI]] by Bernd Carsten Stahl: Chapters 3, 4 (except 4.5 Metaphysical Issues) and 5
  * [[https://learning.eupati.eu/mod/book/tool/print/index.php?id=353|Example of ethical review panel principles]] at EUPATI Open Classroom
  * [[https://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.29.3.3|Why Are There Still So Many Jobs? The History and Future of Workplace Automation]] by D. H. Autor
  * [[https://assets.pubpub.org/1iqvp0dp/c8d3cba5-8f10-4a00-894c-3a3b886ad844.pdf| unified framework of five principles for AI in society]] by L. Floridi and J. Cowls.
  * [[https://www.privanova.com/resources/artificial-intelligence-and-ethics-in-eu-funded-projects?/artificial-intelligence-and-ethics-in-eu-funded-projects|AI in EU-funded projects]] on Privanova
  * [[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445726/|Understanding Ethical and Legal Obligations in a Pandemic: A Taxonomy of “Duty” for Health Practitioners]] by Sheahan & Lamont on the NIH Website. 


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===== Supporting Topics  ======

====Artificial Neural Networks====
  * [[https://arxiv.org/pdf/2307.01850.pdf|Self-Consuming Generative Models Go MAD]] by S. Alemohammad et al.
  * [[https://garymarcus.substack.com/p/what-was-60-minutes-thinking-in-that?r=8tdk6&utm_campaign=post&utm_medium=web|Gary Marcus' commentary blog on 60 Minutes interview with Geoffrey Hinton]] by G. Marcus
  * [[https://ftp.cs.ucla.edu/pub/stat_ser/R246.pdf|Beyesian Networks]] by J. Pearl
  * [[https://monoskop.org/images/9/90/Wiener_Norbert_The_Human_Use_of_Human_Beings_1950.pdf|The Human Use of Human Beings]] by N. Wiener (1950) -- possibly the world's first treatise on AI & ethics. "The 'mechanical brain' and similar machines can destroy human values or enable us to realize them as never before."
  * [[https://thumbland.blogspot.com/2015/12/claude-shannon-and-norbert-wiener.html|Claude Shannon and Norbert Wiener (cybernetics)]] by B. Collins. 
  * [[https://www.youtube.com/watch?v=vPKkXibQXGA&t=18s|Claude Shannon demonstrates machine learning in 1952]] on YouTube

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====The Singularity====

  * [[https://www.forbes.com/sites/robertbtucker/2024/08/22/the-singularity-is-coming-soon-heres-what-it-may-mean/|The Singularity Is Coming Soon. Here’s What It May Mean.]] in Forbes magazine

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=====Readings README=====
**How to Use This Page**
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//Note: DO NOT SKIP READING THE BELOW TEXT//

Papers under each section are ordered from most to least important, so start counting from the top.

[ x,y ] \\
x: necessary mandatory number of papers to be read -- absolute minimum number. \\
y: the recommended number. \\
No number: Read all the papers listed. 

It is your responsibility to ensure that you grasp the **concepts covered** in this class; the readings are //my top choices// (suggestions) for getting this done. However, if you are aware of alternative sources of treatment of the concepts covered in these you may prefer to read about them from your preferred source. If in doubt, ask me. 

Assigned readings should be read //before// class. \\
If you do so you will already have some familiarity with the subject matter, which not only means you will //remember it better// but also that you can //ask questions for clarification during the lecture// and partially //steer its direction//. 

Reading the papers after class //is less effective//. 

You are expected to read all of the papers assigned in this course, **at least** 2-3 papers per week (4 recommended). //Keep at it and you'll be fine!// 

Warning: Do not attempt to read papers **during** the group sessions as this is the absolute worst way to cover this material if you truly are interested in learning (you may of course have it open for reference). 

Reading the assigned readings **not at all** should generally be avoided.

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**As you read papers from each of the following categories I want you ask yourself a few questions:** 

  * For each paper in each category X, ask yourself:
    * What is X? 
    * How does the human mind do X? 
    * Do current computers do X?
    * ...and ...
    * Do we need (to replicate or capture) what the human mind does to achieve X to create a machine that rivals the ability of humans to do X? 

If you can answer them satisfactorily when you're done reading you're good! Even if you can't you'll be fine if you: Write down the discrepancies and //bring them to class in the form of questions//. There is no such thing as a 'stupid question' when you're learning something new. 

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//EOF//