Tag: AI

• Learning by thinking

  Learning by thinking in natural and artificial minds:Canonical cases of learning involve novel observations external to the mind, but learning can also occur through mental processes such as explaining to oneself, mental simulation, analogical comparison, and reasoning. Recent advances in artificial intelligence (AI) reveal that such learning is not restricted to human minds: artificial minds…

  walterstiers

  2024-09-27

  Life Ideas, Science, Social-Technical

  #DecisionIntelligence, #ProblemSolvingMind, #TheInformationLens, AI, artificial-intelligence, education, learning, teaching

• regulation of motivated behavior

  in “A unified theoretical framework underlying the regulation of motivated behavior“, Yu-Been Kim, Young Hee Lee, Shee-June Park and Hyung Jin Choi explain that multiple psychological components have evolved in order to orchestrate behaviors for survival. Despite several theories regarding behavior regulation, these theories do not clearly distinguish distinct components and do not explain the…

  walterstiers

  2024-09-26

  #Sensemaking, Biology of Information, Decision Intelligence, Life Ideas, Neurobiology/psychology

  #DecisionIntelligence, #TheInformationLens, AI, artificial-intelligence, health, machine-learning, technology

•  The Edge of Sentience

  “The Edge of Sentience: Risk and Precaution in Humans, Other Animals, and AI.” by Jonathan Birch Can octopuses feel pain and pleasure? What about crabs, shrimps, insects, or spiders? How do we tell whether a person unresponsive after severe brain injury might be suffering? When does a fetus in the womb start to have conscious experiences?…

  walterstiers

  2024-07-29

  #Sensemaking, Biology of Information, Complexity, Decision Intelligence, Life Ideas, Neurobiology/psychology, Science

  #DecisionIntelligence, #emergence, #TheInformationLens, #Wicked, AI, artificial-intelligence, consciousness, sentience

• Why the simplest explanation isn’t always the best

  Eva L. Dyer and Konrad Kording discuss in a commentary article “Why the simplest explanation isn’t always the best” an essential learning related to the article Phantom oscillations in principal component analysis (also available on BioRXiv) Dimensionality reduction simplifies high-dimensional data into a small number of representative patterns. One dimensionality reduction method, principal component analysis (PCA), often selects oscillatory…

  walterstiers

  2024-04-18

  Biology of Information, Complexity, Information Technology, Neurobiology/psychology, Science

  #DecisionIntelligence, #TheInformationLens, AI, artificial-intelligence, data-science, machine-learning, unsupervised-learning

• the problem of algorithmic recommendations

  I just want to point out an MIT Technology Review article on three new books warn against turning into the person the algorithm thinks you are “A machine-learning algorithm walks into a bar. The bartender asks: ‘What’ll you have?’ The algorithm says: ‘What’s everyone else having?’” Chet Haase (Google) Software engineer Chet Haase’s joke sums…

  walterstiers

  2024-03-12

  #sense-making, AI, Decision Intelligence, Information Technology, Policy, Social-Technical

  #DecisionIntelligence, #HumanAI, #TheInformationLens, AI, artificial-intelligence, data-science, machine-learning, technology

• The past as a stochastic process

  The concept of history unfolding stochastically is not new; in the context of the history of life on Earth, Stephen J. Gould famously asked what would happen if we could “replay the tape”, which implicitly supposes that an underlying stochastic process generated that tape. Similarly, stochastic process modeling of environmental dynamics has been used to…

  walterstiers

  2024-02-09

  #Sensemaking, #Wicked, Complexity, Science, Social-Technical

  #DecisionIntelligence, #TheInformationLens, #Wicked, AI, artificial-intelligence, data-science, machine-learning, technology