MSGID: 1:317/3 64acdb21   
   PID: hpt/lnx 1.9.0-cur 2019-01-08   
   TID: hpt/lnx 1.9.0-cur 2019-01-08   
    Unraveling the humanity in metacognitive ability: Distinguishing human   
   metalearning from AI    
      
     Date:   
         July 10, 2023   
     Source:   
         University of Tsukuba   
     Summary:   
         'Metarecognition' is the ability to objectively monitor, control,   
         and improve one's learning ability. Researchers demonstrated that   
         the human brain exhibits metacognitive abilities that regulate   
         implicit motor learning to maximize monetary rewards. Unlike   
         artificial intelligence, which is perpetually optimal, human   
         metacognition exhibits an asymmetric bias in managing rewards   
         (monetary gain) and punishments (monetary loss).   
      
      
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   FULL STORY   
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   Monitoring and controlling one's own learning process objectively   
   is essential for improving one's learning abilities. This ability,   
   often referred to as "learning to learn" or "metacognition," has been   
   studied in educational psychology. Owing to the tight coupling between   
   the higher meta-level and the lower object-level cognitive systems, a   
   conventional reduction approach has difficulty understanding the neural   
   basis of metacognition. To overcome this limitation, the researchers   
   employed a novel research approach where they compared the metacognition   
   of artificial intelligence (AI) to that of humans.   
      
   First, they demonstrated that the metacognitive system of AI, which aims   
   to maximize rewards and minimize punishments, can effectively regulate   
   learning speed and memory retention in response to the environment and   
   task. Second, they demonstrated the metacognitive behavior of human   
   motor learning, which demonstrates that providing monetary feedback as   
   a function of memory can either promote or suppress motor learning and   
   memory retention. This constitutes the first-ever empirical demonstration   
   of the bi-directional regulation of implicit motor learning abilities   
   by economic factors. Notably, while AI exhibited equal metacognitive   
   abilities for reward and punishment, humans exhibited an asymmetric   
   response to monetary gain and loss; humans adjust their memory retention   
   in response to gain and their learning speed in response to loss. This   
   asymmetric property may provide valuable insights into the neural   
   mechanisms underlying human metacognition.   
      
   Researchers anticipate that these findings could be effectively applied   
   to enhance the learning abilities of individuals engaging in new sports   
   or motor- related activities, such as post-stroke rehabilitation training.   
      
   This work was supported by the Japan Society for the Promotion of Science   
   KAKENHI (JP19H04977, JP19H05729, and JP22H00498). TS was supported by a   
   JSPS Research Fellowship for Young Scientists and KAKENHI (JP19J20366). NS   
   was supported by NIH R21 NS120274.   
      
       * RELATED_TOPICS   
             o Mind_&_Brain   
                   # Educational_Psychology # Memory # Intelligence #   
                   Learning_Disorders   
             o Computers_&_Math   
                   # Educational_Technology # Computer_Science #   
                   Mobile_Computing # Mathematical_Modeling   
       * RELATED_TERMS   
             o Learning_disability o Hallucination o Pyromania o Cognition o   
             Aptitude o Artificial_intelligence o Dyslexia o Computer_vision   
      
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   Journal Reference:   
      1. Taisei Sugiyama, Nicolas Schweighofer, Jun Izawa. Reinforcement   
      learning   
         establishes a minimal metacognitive process to monitor and control   
         motor learning performance. Nature Communications, 2023; 14 (1)   
         DOI: 10.1038/ s41467-023-39536-9   
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   Link to news story:   
   https://www.sciencedaily.com/releases/2023/07/230710113618.htm   
      
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