This is my talk delivered 06/04/2024 at the CUBE event (https://www.uni-corvinus.hu/post/landing-page/cube/?lang=en) at the Gellért Campus of the Corvinus University.

1. Viktor Dörfler

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• Creativity and intuition
• Levels of mastery
• The nature of talent
and how to nurture it
• Grandmasters: Nobel
Laureates and top chefs
• Knowledge engineering
• Decision support
• Spearheading expert
system development
• Intelligent portals and
the knowledge factory
Dual career
SCHOLAR PRACTITIONER
Complex systems
Business
Philosophy
Mathematics
Engineering
Education
Management

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81% of executives believe that “data should be at
the heart of all decision-making” (EY study)
“Big data can eliminate reliance on ‘gut feel’ decision-making” (EY conclusion)
big data - small insight
small data - big thinking
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Logic Theorist, GPS
38 out of 52 – eventually
1 more elegant
What is the common part of all
problem solving?
Allen Newel & Herbert Simon
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Expert Systems
Knowledge representations
To outperform human experts
To support human experts
Edward Feigenbaum
Artificial Neural Networks
Pre-AI mathematical approximator
Reproduce the statistical frequency
of learning examples
Marvin Minsky & Seymour Papert

6. the human brain
100 billion neurons
7,000 connections on average
1,000 trillion synapses in total (1015)
not so simple connection either
a nonlinear statistical data modelling
largest: 16 million neurons (frog’s brain)
weighted sum of “firing”
what is the resemblance?
a lot of simple elements
complex web of connections
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7. the algorithms that run upon those ANN-s
getting to perform what is not explicitly programmed
unsupervised learning
no label on data, can group similar ones into clusters
possible to find unexpected/unsuspected patterns
supervised learning
your data is labelled, future case classified by labels
ANN vs non-ANN machine learning
in ANN the statistical frequency is reproduced
in symbolic the rules that classify are induced
symbolic is “explainable AI”
CAT
CAT
CAT
CAT
CAT
NOT
CAT
NOT
CAT
NOT
CAT
NOT
CAT
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8. ontologies and meta-data
structuralism
semiotics
syntax vs semantics
so, perhaps the human stuff can be mathematicised
human and social studies → human and social sciences
dictionary of phrases rather than words
sentiment analysis ≠ understanding
is there a deterministic process underlying it all?
subjective experiences, free will, symbol creation
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9. big problem of machine learning: huge
number of examples needed for training
let’s do part of the job in advance, on “generic”
data, e.g. Wikipedia, Internet Archives, etc.
then the last bit on the kind data we need, e.g.
assignments on data analytics
what is data of the same kind just “generic”
why AI cannot write top quality stuff?
what would be the “generic” writing for
Shakespeare sonnets?
how do we recognise ChatGPT assignments?
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10. discriminative vs generative models
clustering and classification of data
generating new instance in a distribution
generate the next suitable token
based on the previous one(s)
today I am going to…
Variational Autoencoder (VAE)
the essence of cat-ness and variations
Generative Adversarial Network (GAN)
generate a new instance (generative) and
compare to the originals (discriminative)
≠
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13. Qualia: the lived experience of values
directly
Intuition: sensing + sensemaking
“We pour ourselves out into them
and assimilate them as parts of our
own existence.” (Polányi)
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All knowledge is either tacit or rooted in tacit. (Polányi)
≡? =? ≥? ≤? ≈? ≠?
HUMAN MACHINE
≈
Humans are
not logical
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Behaviourist psychology
I call it the dark ages,
we know better today
DeepMind
Learns the same way as humans
do – by reinforcement learning
Demis Hassabis
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Deep Blue, AlphaGo, AlphaZero deliver extraordinary performance
But can AI be creative? Can AI produce an original (new) and useful idea?
AI can find unexpected patterns but not judge/understand their significance.
AI can help us think ‘outside the box’.
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17. Want to do the right thing
Don’t really know what is right
Many other things impact
The road to hell is also paved with
good intentions
The struggle matters
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Midjourney wins an art prize, 2022
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Chess-robot breaks 7-year old
boy’s finger, as he was “too
fast”, 2022
Rocket
Bumb-bell
Stop
Picture recognition gets confused
with slight changes in position or
alteration of several pixels that
would make no difference for the
human viewer, 2014-2020
Kellin Pelrine, American amateur Go player, ranked one level below the top in amateurs,
beats top Go computer 14 out of 15 games, 2023
(NOTE: no AI support during the game, but AI played a role in the preparation)
Nabla (GPT-3) recommends sui-
cide to a “patient”, 2020. Bing
AI chatbot calls a CNN reporter
“rude and disrespectful” and
declares love to NYT journalist,
2023
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