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Gerard Rego
Why or why not AI? After AI what?
Homo-Heuristicus Evolutionary-Heuristics Singularity
All information present...
Gerard Rego
Artificial Intelligence 101, Fundamentally Flawed?
https://www.fer.unizg.hr/_download/repository/AI-1-Introduc...
Gerard Rego
Human Behaviour is… Heuristics
AI
https://www.fer.unizg.hr/_download/repository/AI-1-Introduction.pdf
Heuristi...
Gerard Rego
4
EMT (Rational) – A Nobel Prize? Heuristics Suggest Otherwise
EMT (Heuristic)
https://www.nobelprize.org/priz...
Gerard Rego
5
Heuristics, Less is More – Uncertainty Thinking vs. Complexity
Markowitz Used Heuristics (Not MPT) Markowitz...
Gerard Rego
6
Heuristics, Better Decision Making
Being applied across industries
Heuristics Decision Making
https://hbr.or...
Gerard Rego
7
Heuristics are;
i. adaptive tools that ignore
information to make fast
and frugal decisions
ii. that are acc...
Gerard Rego
8
Why Static Models Work on Static Data, Not People
Based on Static Data & Risk Based on Behavior & Uncertaint...
Gerard Rego
9
Era of VUCA (Volatility, Uncertainty, Complexity & Ambiguity)
https://www.forbes.com/sites/jeroenkraaijenbri...
Gerard Rego
10
•Tasks that map well-defined
inputs to well-defined outputs, -
e.g., labeling images of specific
animals, t...
Gerard Rego
https://searchenterpriseai.techtarget.com/definition/Turing-test https://en.wikipedia.org/wiki/Alan_Turing
Tur...
Gerard Rego
12
Evolution, Behaviours & Computing
Darwin, Transmutation of species
CUL-DAR121.- Transcribed by Kees Rookmaa...
Gerard Rego
Evolutionary Computing - History
Evolutionary Programming - L. Fogel 1962
(San Diego, CA):
Genetic Algorithms ...
Gerard Rego
Evolutionary Computing
• Broad Applicability
• Inherently Parallel
• Outperform Classic Methods on Real
Proble...
Gerard Rego
• Heuristic responses
• Bounded Rationality/Predictably Irrational
• Behaviours of Maximizers/Satisficers
• Ec...
Gerard Rego
AI= Heuristic & Ecological Rationality
https://www.fer.unizg.hr/_download/repository/AI-1-Introduction.pdf htt...
Gerard Rego
Heuristic Computing & Tradeoffs
Tradeoff (Necessary?)
• Optimality – Is the Optimal Solution necessary?
• 40 T...
Gerard Rego
Evolutionary Intelligence = Ecosystem Heuristics
To have achieved Biological Intelligence is when computing is...
Gerard Rego
Human Intelligence & Ecosystem Heuristics
Artificial Intelligence = Heuristic
& Ecological Rationality
Evoluti...
Gerard Rego
Singularity
Heuristically Rational & Ecosystem Heuristics
1. Behavioural Heuristic Responses & Genetics Heuris...
Gerard Rego
Heuristic & Evolutionary Computing Applications
Behavioural Economics
Dynamic Optimization
Parallelization
Unc...
Gerard Rego
Open House for the Heuristically Rational J
All information presented is acknowledged and any data, informatio...
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Heuristic ad Evolutionary intelligence

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How Heuristics and Evolutionary Intelligence and Computing will unbundle value for ecosystems of society, business and governance.

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Heuristic ad Evolutionary intelligence

  1. 1. Gerard Rego Why or why not AI? After AI what? Homo-Heuristicus Evolutionary-Heuristics Singularity All information presented is acknowledged and any data, information, images, etc. not acknowledged by sources is by oversight.
  2. 2. Gerard Rego Artificial Intelligence 101, Fundamentally Flawed? https://www.fer.unizg.hr/_download/repository/AI-1-Introduction.pdf
  3. 3. Gerard Rego Human Behaviour is… Heuristics AI https://www.fer.unizg.hr/_download/repository/AI-1-Introduction.pdf Heuristically Maximizers/Satisficers Bounded Rationality/ Predictably Irrational https://www.ethz.ch/content/dam/ethz/special-interest/gess/chair-of-sociology-dam/documents/icsd2013/0_3_gigerenzer.pdf Ecological Rationality
  4. 4. Gerard Rego 4 EMT (Rational) – A Nobel Prize? Heuristics Suggest Otherwise EMT (Heuristic) https://www.nobelprize.org/prizes/economic-sciences/2013/fama/lecture/ Price reflects all Public information? Strong Form(er When?) No No Markets are Weak (Always) Price reflects all Past information? Semi-Strong Form(er When?) Weak Form(All the Time!!!) Price reflects all Public & Private? information? https://www.thisismoney.co.uk/money/markets/article-2369171/City-watchdog-targets-banks-Libor-fixing.html https://www.treasury.gov/resource-center/data-chart-center/Documents/20120413_FinancialCrisisResponse.pdf Eugene F. Fama The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2013 Prize motivation: "for their empirical analysis of asset prices." https://www.nobelprize.org/prizes/economic-sciences/2013/fama/facts/
  5. 5. Gerard Rego 5 Heuristics, Less is More – Uncertainty Thinking vs. Complexity Markowitz Used Heuristics (Not MPT) Markowitz Nobel Prize (MPT) https://en.wikipedia.org/wiki/Modern_portfolio_theory https://www.nobelprize.org/prizes/economic-sciences/1990/press-release/http://arno.uvt.nl/show.cgi?fid=129399 Markowitz used a simple model 1/n Approach to Investment, allocating equally to ”n” options Harry Markowitz is awarded the Prize Modern portfolio theory (MPT), or mean-variance analysis, * Need 500 years of data to prove the model (assuming all conditions, stocks and variables exists! No evidence is found of the outperforming of a model by another model. This implies that the 1/n asset allocation strategy, often called the naïve strategy, is not outperformed by a more sophisticated models. Bachelor Thesis Finance Is the 1/n asset allocation strategy undervalued? 16 October 1990
  6. 6. Gerard Rego 6 Heuristics, Better Decision Making Being applied across industries Heuristics Decision Making https://hbr.org/2014/06/instinct-can-beat-analytical-thinking https://www.youtube.com/watch?v=4VSqfRnxvV8&t=2654s https://faculty.washington.edu/jmiyamot/p466/pprs/gigerenzer%20heuristic%20decis%20making.pdf https://en.wikipedia.org/wiki/Uncertainty https://en.wikipedia.org/wiki/Bias%E2%80%93variance_tradeoff
  7. 7. Gerard Rego 7 Heuristics are; i. adaptive tools that ignore information to make fast and frugal decisions ii. that are accurate and robust under conditions of uncertainty. iii. considered ecologically rational when it functionally matches the structure of environment. https://link.springer.com/content/pdf/10.1007%2Fs41412-017-0058-z.pd http://www.dangoldstein.com/papers/RecognitionPsychReview.pdf f Ecological rationality: The recognition heuristic is ecologically rational if ⍺>0.5 Heuristics 101 – That’s how “People” make decisions
  8. 8. Gerard Rego 8 Why Static Models Work on Static Data, Not People Based on Static Data & Risk Based on Behavior & Uncertainty 101 Examples Analysis Unbundling Roadmap Data https://www.accionlabs.com/articles/2018/4/18/is-your-business-prepared-to-use-machine-learning https://slideplayer.com/slide/14594172/ https://www.amazon.com/Animal-Spirits-Psychology-Economy-Capitalism-ebook-dp-B0037YLBMM/dp/B0037YLBMM/ref=mt_kindle
  9. 9. Gerard Rego 9 Era of VUCA (Volatility, Uncertainty, Complexity & Ambiguity) https://www.forbes.com/sites/jeroenkraaijenbrink/2018/12/19/what-does-vuca-really-mean/#73a9d80717d6 https://blog.irvingwb.com/blog/2018/09/social-physics-making-ai-predictions-easily-accessible.html https://www.ethz.ch/content/dam/ethz/special-interest/gess/chair-of-sociology-dam/documents/icsd2013/0_3_gigerenzer.pdf • VUCA is a concept that originated with students at the U.S. Army War College after the Cold War. • And now, the concept is gaining new relevance to characterize the current environment and the leadership required to navigate it successfully. Homo HeuristicusVUCA Accelerating Unbundling
  10. 10. Gerard Rego 10 •Tasks that map well-defined inputs to well-defined outputs, - e.g., labeling images of specific animals, the probability of cancer in medical record, the likelihood of defaulting on a loan application; •Large data sets exist or can be created containing such input- output pairs, - the bigger the training data sets the more accurate the learning;. When Complex Models Work? When it’s all Static! But we live in a world of “People’s & Behaviours” •The capability being learned should be relatively static, - If the function changes rapidly, retraining is typically required, including the acquisition of new training data; and •No need for detailed explanation of how the decision was made, - the methods behind a machine learning recommendation, - subtle adjustments to the numerical weights that interconnect its huge number of artificial neurons, - are difficult to explain because they’re so different from those used by humans http://science.sciencemag.org/content/358/6370/1530/tab-pdf 101 Examples Analysis Unbundling Roadmap Data
  11. 11. Gerard Rego https://searchenterpriseai.techtarget.com/definition/Turing-test https://en.wikipedia.org/wiki/Alan_Turing Turing to Singularity Alan Turing Singularity • Singularity has been reached, Kurzweil says that machine intelligence will be infinitely more powerful than all human intelligence combined • The Singularity is also the point at which machines intelligence and humans would merge.
  12. 12. Gerard Rego 12 Evolution, Behaviours & Computing Darwin, Transmutation of species CUL-DAR121.- Transcribed by Kees Rookmaaker. (Darwin Online, http://darwin-online.org.uk/ https://due.com/blog/not-strongest-species-survive-charles-darwin/ ) Evolution • Heritable characteristics over successive populations • Expression of genes passed on from generation to generation • Different characteristics, rare or common in a population • Gives rise to Biodiversity, Variety & Variability ~ Genetic, Species & Ecosystem
  13. 13. Gerard Rego Evolutionary Computing - History Evolutionary Programming - L. Fogel 1962 (San Diego, CA): Genetic Algorithms - J. Holland 1962 (Ann Arbor, MI): Evolution Strategies -I. Rechenberg & H.-P. Schwefel 1965 (Berlin, Germany): Genetic Programming - J. Koza 1989 (Palo Alto, CA): Recombination Mutation Population Offspring Parents Selection Replacement
  14. 14. Gerard Rego Evolutionary Computing • Broad Applicability • Inherently Parallel • Outperform Classic Methods on Real Problems • Evolve with Uncertainty • Potential to Hybridize • Capability for Self-Optimization • Can Solve Problems with no known Solutions https://pdfs.semanticscholar.org/8c87/d26f409cd56f109b5c0c59f91a5f3e9d632b.pdf https://www.uio.no/studier/emner/matnat/ifi/INF3490/h18/timeplan/slides/lecture3-1pp.pdf Evolutionary Computing Evolutionary Computing - Utility
  15. 15. Gerard Rego • Heuristic responses • Bounded Rationality/Predictably Irrational • Behaviours of Maximizers/Satisficers • Ecological Rationality Intelligence 101 – The Way We See It http://web.cecs.pdx.edu/~mperkows/CLASS_479/LECTURES479/EVO01.PDF https://hbr.org/2014/06/instinct-can-beat-analytical-thinking Biological • Genetic Heuristics • Ecosystem Diversity • Feedforward • Uncertainty Human
  16. 16. Gerard Rego AI= Heuristic & Ecological Rationality https://www.fer.unizg.hr/_download/repository/AI-1-Introduction.pdf https://www.ethz.ch/content/dam/ethz/special-interest/gess/chair-of-sociology-dam/documents/icsd2013/0_3_gigerenzer.pdf To have achieved Human Intelligence is when computing is able to; 1. Heuristic responses =:True Create and Respond to Stimuli 2. Bounded Rationality/Predictably Irrational =:True Rationality 3. Behaviours of Maximizers/Satisficers =: True Satisficing 4. Ecological Rationality =:True Under Certainty & Uncertainty When all of the above characteristics have been achieved by computing we would define this state as being equal to Human Intelligence or Heuristical Intelligence Heuristic Intelligence
  17. 17. Gerard Rego Heuristic Computing & Tradeoffs Tradeoff (Necessary?) • Optimality – Is the Optimal Solution necessary? • 40 Trillions of combinations to find the right investing strategy to buy a stock? https://www.youtube.com/watch?v=a80gPs-ZKp0 • Completeness – Are all solutions necessary? • UPS - 120 stops – how many permutations & combinations to deliver a package 6,689,502,913,449,135,000, 000, 000,000,000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, https://www.esri.com/~/media/Files/Pdfs/events/ses/2017%20SES/03_SES2017_Jack_Levis.pdf • Accuracy & Precision – Do we need a high Confidence-Interval for all situations? • Where to land the plane with no engines? https://www.wired.com/2009/02/sully- calmly-to/ • Execution Time – Intractable challenge or NP-Hard problem • A simple heuristic of Index Investing or complex MPT/Algorithmic Investing? https://en.wikipedia.org/wiki/NP-hardness https://pdfs.semanticscholar.org/8c87/d26f409cd56f109b5c0c59f91a5f3e9d632b.pdf https://www.uio.no/studier/emner/matnat/ifi/INF3490/h18/timeplan/slides/lecture3-1pp.pdf Heuristic Computing • Large Search Spaces • Heuristic Architectures • Self-learning • Evolve with Uncertainty • Can Solve Problems with no known Solutions
  18. 18. Gerard Rego Evolutionary Intelligence = Ecosystem Heuristics To have achieved Biological Intelligence is when computing is able to; 1. Genetic Heuristics =:True Evolve based on ecosystem stimuli 2. Ecosystem Diversity =:True Create and evolve Genetics (Increase population diversity – Mutation & Recombination = Novelty) & Selection (Decrease population diversity ~ Parents & Survivors = Quality) 3. Feedforward =: True Internal and External Ecosystem Diversity 4. Uncertainty=:True Evolutionary Genetics & Ecosystems When all of the above has been achieved by computing we would define this as being equal to Biological Intelligence or Evolutionary Intelligence
  19. 19. Gerard Rego Human Intelligence & Ecosystem Heuristics Artificial Intelligence = Heuristic & Ecological Rationality Evolutionary Intelligence = Ecosystem Heuristics 1. Heuristic responses =:True How People Respond to Stimuli 2. Bounded Rationality/Predictably Irrational =:True Rationality 3. Behaviours of Maximizers/Satisficers =: True Satisficing 4. Ecological Rationality =:True Under Uncertainty 1. Genetic Heuristics =:True Evolve based on ecosystem stimuli 2. Ecosystem Diversity =:True Create and evolve Genetics (Increase population diversity – Mutation & Recombination= Novelty) & Selection (Decrease population diversity ~ Parents & Survivors = Quality) 3. Feedforward =: True Internal and External Ecosystem Diversity 4. Uncertainty=:True Evolutionary Genetics & Ecosystems
  20. 20. Gerard Rego Singularity Heuristically Rational & Ecosystem Heuristics 1. Behavioural Heuristic Responses & Genetics Heuristics 2. Behavioural Rationality & Ecosystem Diversity 3. Satisficing Behaviours & Feedforward 4. Ecological Rationality Behaviours & Evolutionary Genetics & Ecosystems
  21. 21. Gerard Rego Heuristic & Evolutionary Computing Applications Behavioural Economics Dynamic Optimization Parallelization Uncertain Environments Dynamic Routing Problem Behavioral BFSI Dynamic Experiences Behavioural Governance Behavioural Security Evolutionary Robotics GOFAI (Good Old Fashioned AI) Behavioural Health
  22. 22. Gerard Rego Open House for the Heuristically Rational J All information presented is acknowledged and any data, information, images, etc. not acknowledged by sources is by oversight.

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