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Explainable AI (xAI) & Future of Artificial Intelligence/ML (HLAI & AGI)

1st/old version presented @ CODECON 2023 #CODECON, #CODECON2023

Radovan Kavický, AIslovakIA & GapData Institute

21. 2. 2024

(#AIslovakIA, #AIRadioMeetup, Bratislava, Slovakia) #AIslovakIA @ sli.do

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Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

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Structure of the talk

- 1. Current development and what’s next/what to do now? [15 min.]

Sora, Gemini 1.5, Copilot/ChatGPT & GitHub Copilot

- 2. Future of AI (path towards HLAI/AGI, when? why?) [20 min.]

Strong/Wide AI vs. Weak/Narrow AI, Machine Learning vs. Machine Reasoning

- 3. Ethics & Transparency in AI/Trustworthy AI/Responsible AI/Applied AI/Growth potential [10 min.]

Brain/Neuroscience Research and theory of consciousness

- 4. Explainable AI/xAI, Shapley values, Mathematics of AI [20 min.]

- 5. Conclusion & position of Slovakia/Europe [10 min. + Q&A/15-20 min]

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- Data Science (definition): collection of scientific results and methods for transformation of data from raw form to meaningful information, knowledge and wisdom, which should support better decisions

- AI (definition) - theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, translation and others

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Which programming language do you prefer for AI? (Python, C, Scala, R, Julia, MATLAB, whatever)

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Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

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About me

    • Economist (Ing./Macro, Finance/NHF); Slovak Economic Association (SEA)
    • AI Expert, PhD. (xAI & Data Science/TUKE, prof. Sinčák), AI & Data Science Evangelist @ AIslovakIA (National platform for AI development in Slovakia), President & Principal Data Scientist (GapData), Consulting (public, private)
    • Member of Slovak.AI (currently AIslovakIA), CLAIRE, European AI Alliance, TAILOR (TrustworthyAI @ EU)
    • Data Science Instructor @ DataCamp, BaseCamp.ai, Learn2Code/Skillmea, robime.it, GapData +others
    • Founder of PyData Slovakia/Bratislava (#PyDataBA), R <- Slovakia (#RSlovakia),
    • Julia Users Group Slovakia (#JUGSlovakia) & SK/CZ Tableau User Group (#skczTUG)
    • Analýza systému súdnictva a jeho výkonnosti do r. 2010 - Ministerstvo spravodlivosti SR (gov.sk), https://www.justice.gov.sk/tlacovespravy/tlacova-sprava-1581/

Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

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What IDE you are using for your AI projects/where you create/train your models? (cloud, locally, etc.)

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AI, AGI, HLAI > Palantir, Flawless, Sora and beyond… Frankie.AI goes to Hollywood

- Complex, modern-day ML algorithms, where deep learning & ensemble methods dominate

- really hard to fully understand, but the decision process behind them

- ChatGPT is not transparent/open (at all/bans and restrictions)

- can & need to be transparent and trustworthy for decision makers

- AI & BI coming together

- critical domains as finance, healthcare or public sector & governmental services, where TRUST is a MUST

- Explainability vs. Simplicity

- growing regulatory pressure also outside these areas Explainable AI (xAI) will be necessity for any organization soon

- understand the inner workings of these ML algorithms & how to design systems that imitate intelligence in a transparent way

- overview of current trends in Explainable AI/ML & the challenges that are ahead of us

- Next big thing?

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Global GDP ≈ $100 Trillion USD

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Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

$100,562,000,000,000 (2022, nominal/per year)

US: 25.5 Trillion USD/year (GDP)

China: 17.9 Trillion USD/year (GDP)

Japan: 4.2 Trillion USD/year (GDP)

Germany: 4 Trillion USD/year (GDP)

India: 3.4 Trillion USD/year (GDP) +UK, France,

Russia, Canada, Italy (about 2 Trillion USD/year)

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Explainable Machine Learning/AI (xAI), Era of Chatbots, AI & BI collide

- Complex, modern-day ML algorithms, where deep learning & ensemble methods dominate

- really hard to fully understand, but the decision process behind them

- ChatGPT is not transparent/open (at all/bans and restrictions)

- can & need to be transparent and trustworthy for decision makers

- AI & BI coming together

- critical domains as finance, healthcare or public sector & governmental services, where TRUST is a MUST

- Explainability vs. Simplicity

- growing regulatory pressure also outside these areas Explainable AI (xAI) will be necessity for any organization soon

- understand the inner workings of these ML algorithms & how to design systems that imitate intelligence in a transparent way

- overview of current trends in Explainable AI/ML & the challenges that are ahead of us

- Next big thing?

7/24 #AIslovakIA @ sli.do

Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

Source: Andrew Ng, deeplearning.ai

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Explainable Machine Learning/AI (xAI), Era of Chatbots, AI & BI collide

- Complex, modern-day ML algorithms, where deep learning & ensemble methods dominate

- really hard to fully understand, but the decision process behind them

- ChatGPT is not transparent/open (at all/bans and restrictions)

- can & need to be transparent and trustworthy for decision makers

- AI & BI coming together

- critical domains as finance, healthcare or public sector & governmental services, where TRUST is a MUST

- Explainability vs. Simplicity

- growing regulatory pressure also outside these areas Explainable AI (xAI) will be necessity for any organization soon

- understand the inner workings of these ML algorithms & how to design systems that imitate intelligence in a transparent way

- overview of current trends in Explainable AI/ML & the challenges that are ahead of us

- Next big thing?

8/24 #AIslovakIA @ sli.do

Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

Source: HLAI Conference | GoodAI https://www.goodai.com/hlai/ Ben Goertzel, 2018 (Good.AI & GapData Institute, PyData Slovakia/partnership)

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Explainable Machine Learning/AI (xAI), Era of Chatbots, AI & BI collide

- Complex, modern-day ML algorithms, where deep learning & ensemble methods dominate

- really hard to fully understand, but the decision process behind them

- ChatGPT is not transparent/open (at all/bans and restrictions)

- can & need to be transparent and trustworthy for decision makers

- AI & BI coming together

- critical domains as finance, healthcare or public sector & governmental services, where TRUST is a MUST

- Explainability vs. Simplicity

- growing regulatory pressure also outside these areas Explainable AI (xAI) will be necessity for any organization soon

- understand the inner workings of these ML algorithms & how to design systems that imitate intelligence in a transparent way

- overview of current trends in Explainable AI/ML & the challenges that are ahead of us

- Next big thing?

9/24 #AIslovakIA @ sli.do

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Explainable Machine Learning/AI (xAI), Era of Chatbots, AI & BI collide

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Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

“The year is 2052 and the world is a dangerous and chaotic place. Terrorists operate openly - killing thousands; drugs, disease and pollution kill even more. The world's economies are close to collapse and the gap between the insanely wealthy and the desperately poor grows ever wider.”

Source: Warren Spector/Deus Ex (6/2000) + https://www.youtube.com/watch?v=tffX3VljTtI

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Explainable Machine Learning/AI (xAI), Era of Chatbots, AI & BI collide

- Complex, modern-day ML algorithms, where deep learning & ensemble methods dominate

- really hard to fully understand, but the decision process behind them

- ChatGPT is not transparent/open (at all/bans and restrictions)

- can & need to be transparent and trustworthy for decision makers

- AI & BI coming together

- critical domains as finance, healthcare or public sector & governmental services, where TRUST is a MUST

- Explainability vs. Simplicity

- growing regulatory pressure also outside these areas Explainable AI (xAI) will be necessity for any organization soon

- understand the inner workings of these ML algorithms & how to design systems that imitate intelligence in a transparent way

- overview of current trends in Explainable AI/ML & the challenges that are ahead of us

- Next big thing?

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AI & Ethics (food for thought & main challenges for the future)

- we should all be humble & think all the time about ethical implications of our work

- data in not (at least our) reality & need of transparency (explainable AI/HLAI/Superintelligence)

- we have no programming of common sense (fails/CYC)

- we need both left and right brain/lobe thinking

- we don't know how we really think (and if you think you know, well… good luck)

- we don't know what intelligence is (unknown processes)

- we are not walking neural nets (but if some of you are, please, let me know)

- design perceptron (imitate brain without knowing how the brain really works), real research of brain started (Brain Initiative/public and private research, 2013 +DARPA, IARPA)

- we need to rethink the basic design of neural nets (mathematics of deep learning)

- we can count all the neurons in our brains (10's of billions and 1000’s of billions synapses)

- we need rules (ethical & law standards/technology is currently before ethics)

“But the big feature of human-level intelligence is not what it does when it works but what it does when it's stuck.”

-- Marvin Minsky

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Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

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Explainable Machine Learning/AI (xAI), Era of Chatbots, AI & BI collide

- Complex, modern-day ML algorithms, where deep learning & ensemble methods dominate

- really hard to fully understand, but the decision process behind them

- ChatGPT is not transparent/open (at all/bans and restrictions)

- can & need to be transparent and trustworthy for decision makers

- AI & BI coming together

- critical domains as finance, healthcare or public sector & governmental services, where TRUST is a MUST

- Explainability vs. Simplicity

- growing regulatory pressure also outside these areas Explainable AI (xAI) will be necessity for any organization soon

- understand the inner workings of these ML algorithms & how to design systems that imitate intelligence in a transparent way

- overview of current trends in Explainable AI/ML & the challenges that are ahead of us

- Next big thing?

12/24 #AIslovakIA @ sli.do

Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

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Explainability & Tools (LIME, SHAP & others)

- LIME (Local Interpretable Model-agnostic Explanations)

- explainable AI method that helps to illuminate a machine learning model

- make its predictions individually comprehensible

- method explains the classifier for a specific single instance (suitable for local explanations)

- model agnostic tool which can give explanations for any supervised learning model

- one of the most popular XAI tools out there due to its simplicity and intuitiveness

https://github.com/marcotcr/lime

- SHAP (SHapley Additive exPlanations)

- game theoretic approach to explain the output of any machine learning model.

- connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions

https://github.com/slundberg/shap

+

Others (100+ tools), f.e.:

- Alibi (Algorithms for explaining machine learning models)

https://github.com/SeldonIO/alibi

- Captum (Model Interpretability for PyTorch)

https://captum.ai/

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Explainable AI/xAI + key literature

  • Source: https://christophm.github.io/interpretable-ml-book/

  • https://www.amazon.com/Machine-Learning-High-Risk-Applications-Responsible/dp/1098102436

  • https://www.amazon.com/Interpretable-Machine-Learning-Python-hands/dp/180323542X/

Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

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AI & Slovakia or why should you even care?

+

+

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AI & Slovakia, what exactly are you talking about? What future?

- OECD.AI that provides an overview of AI strategies and policies in Slovakia. It includes an action plan for the transformation of Slovakia into a successful digital country and development of the digital single market. The action plan offers a set of concrete steps on how to start building a sustainable and human centric, and trustworthy AI.

- AIslovakIA, which is a neutral, independent and non-profit platform with an ambition to develop excellence and bring together experts and those interested in artificial intelligence in Slovakia.

- The national platform of artificial intelligence (AIslovakIA) is part of the Center for Artificial Intelligence (hereinafter referred to as “CAI”), a non-profit organization

- AI/ML augmented analytics (scenarios for data-driven decision making)

- build and deploy highly accurate machine learning models without writing a single line of code, experiment, simulate and compare different scenarios using various models/scenarios to identify the best strategy or test ideas before committing resources

- focus on the right data to analyze, get predictive insights with explanations in your dashboards + run simulations to get actionable prescriptive guidance on what to do next and get instant visual response

- Alphaa.ai (world’s 1st AI voice analyst/not just regular “chat bot”)

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- OECD.AI that provides an overview of AI strategies and policies in Slovakia. It includes an action plan for the transformation of Slovakia into a successful digital country and development of the digital single market. The action plan offers a set of concrete steps on how to start building a sustainable and human centric, and trustworthy AI.

- AIslovakIA, which is a neutral, independent and non-profit platform with an ambition to develop excellence and bring together experts and those interested in artificial intelligence in Slovakia.

- The national platform of artificial intelligence (AIslovakIA) is part of the Center for Artificial Intelligence (hereinafter referred to as “CAI”), a non-profit organization

- AI/ML augmented analytics (scenarios for data-driven decision making)

- build and deploy highly accurate machine learning models without writing a single line of code, experiment, simulate and compare different scenarios using various models/scenarios to identify the best strategy or test ideas before committing resources

- focus on the right data to analyze, get predictive insights with explanations in your dashboards + run

#AIslovakIA @ sli.do

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Who's on the picture?

Click Present with Slido or install our Chrome extension to activate this poll while presenting.

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Future of AI/ML and Data Science

- Back to Basics

What Machine Learning/Artificial Intelligence is? What Data Science is?

“Artificial intelligence is the science of making machines do things that would require intelligence if done by men.”

-- Marvin Minsky

- Data Science (definition): collection of scientific results and methods for transformation of data from raw form to meaningful information, knowledge and wisdom, which should support better decisions

- Data Science: Statistics + programming; data analysis + Computer Science, modelling + Econometrics, Big Data, ML/DL

- Expectation/Prediction: Data Scientists, one of the first “victims” of automation

- Is Data Reality? Do we model reality? (noise/signal)

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Is data reality?

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Data is not reality. �And if you think so, you should quit doing so… right now.

Source: Me :), H2O.ai Meetup, Prague 2019, https://www.meetup.com/Prague-Artificial-Intelligence-Deep-Learning/events/264335458/

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AI & Ethics of AGI (Transhumanism & Empathy/future challenges)

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Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

Source: https://edition.cnn.com/2023/09/20/tech/musk-neuralink-human-trials/index.html

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AI, Consciousness & Ethics of AGI (Transhumanism & Empathy/future challenges)

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Future is awesome. �All we have to do now is to build it.

Source: PyData Berlin 2017 (w/Marek Rosa), Talk on YouTube: https://www.youtube.com/watch?v=I5578BhU4sE

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#AIslovakIA @ sli.do

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PyData Slovakia & activities within CEE + V4

    • 300+ members
    • 3000+ on mailing list
    • 800+ followers
    • Partners: O'Reilly, robime.it, codecon.sk, TouchIT.sk
    • Sponsors: H2O.ai, Microsoft, kiwi.com
    • WeAreDevelopers World Congress (“GAPDATA-25” & “PYDATA-25”), Berlin, 17.-19. July 2024
    • Machine Learning Prague (“pydatask15” for 15% discount), Prague/O2 , 22.-24. April 2024
    • WebExpo, Prague/Lucerna, 29.-31. May 2024 (“pydatask15” for 15% discount)
    • Our meetups (26.2., 15:00 PyData Slovakia & Bratislava 16:00 skczTUG/SK & CZ Tableau User)

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GapData Institute (GDI) and how to support us.

    • Economic Research & Public Policy & Data Science + AI think-tank (data-tank)
    • Data. Think. Change.
    • GapData Institute (GDI) is a non-profit nonpartisan research institution harnessing power of data & wisdom of economics for public good.
    • Transparent account (from day #1; SK7383300000002200933920 https://www.fio.sk/ib2/transparent?a=2200933920)
    • Partnership (openness, transparency)
    • Slides (this talk): tinyurl.com/slides-xAI
    • https://github.com/radovankavicky/aislovakia2024

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Thank you for your attention

Contact:

Radovan Kavicky

radovan.kavicky@aislovakia.com

radovan.kavicky@gapdata.org

radovan.kavicky@gmail.com

radovan.kavicky@student.tuke.sk

+421 949 716 214 (SK)

+420 777 595 262 (CZ)

http://www.linkedin.com/in/radovankavicky

https://gapdata.slack.com/

https://github.com/radovankavicky

https://www.facebook.com/groups/356635138031671

@radovankavicky, @PyDataBA, @GapDataInst

In case you have any question, feel free to ask.

#AIslovakIA @ sli.do

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Oh, and one more thing… :)

    • Meetup.com

https://www.meetup.com/Julia-Users-Group-Slovakia/

    • Facebook

https://www.facebook.com/groups/379292635993253/

Hashtag: #JUGSlovakia

More to come... soon. Stay tuned.

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How would you rate this talk? (scale 1-10, 10/awesome, 5/meh, 1/worst talk ever, but "try again, fail again, fail better")

Click Present with Slido or install our Chrome extension to activate this poll while presenting.

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(xAI) English Exam (translation/Slovak)

  • Thank you MIRRI/MIRDI & AIslovakIA
  • (Viera Borðoy
  • & Nikola Dobrovská)!
  • Source: http://www.bcs-sgai.org/ai2023/

AI-2023 Forty-third SGAI International Conference on Artificial Intelligence

  • CAMBRIDGE, ENGLAND 12-14 DECEMBER 2023

AI-2023 is the 43-rd Annual International Conference of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI)

Alan Turing studied (math, 1931, Cambridge)

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(xAI) English Exam (translation/Slovak)

  • Source: Jana Novohradská, MIRRI/MIRDI

  • AI-2023 Forty-third SGAI International Conference on Artificial Intelligence
  • CAMBRIDGE, ENGLAND 12-14 DECEMBER 2023

AI-2023 is the 43-rd Annual International Conference of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI)

Alan Turing studied (math, 1931, Cambridge), Stephen Hawking lived few meters from Peterhouse College

Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

#AIslovakIA @ sli.do

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(xAI) English Exam (translation/Slovak)

  • AI-2023 Forty-third SGAI International Conference on Artificial Intelligence
  • CAMBRIDGE, ENGLAND 12-14 DECEMBER 2023

AI-2023 is the 43-rd Annual International Conference of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI)

Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

#AIslovakIA @ sli.do

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Audience Q&A Session

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Explainable Machine Learning/AI (xAI) & Future of Artificial Intelligence

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