Chosun Center for Data Science in Humanities (조선대 인문데이터과학연구소) Annual Workshop 2023-2024
Learning in Babies and Machines:
Reciprocal Insights and Methodological Synergies
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Workshop Rationale
Workshop Rationale
Recognizing both the shared features and distinctions in the learning mechanisms of infants and artificial intelligence (AI), this workshop explores how infants' learning could inform and be informed by machine learning. It is intriguing to observe how infants naturally grasp the meaning of words and the grammar of language, for example, without extensive data or training. While contemporary AI showcases remarkable power, it lacks certain innate abilities that infants effortlessly develop. Deciphering this inherent learning mechanism in babies holds the promise of not only significantly enhancing AI capabilities but also providing reciprocal advantages, as AI technologies contribute to a deeper understanding of how infants learn language. This workshop serves as a collaborative platform, bringing together experts from developmental science and AI technology to exchange insights and methodologies. The overarching goal of the workshop is to address essential questions, such as: How can AI technologies advance our understanding of infants' language development? What insights from developmental science can inform the design of more effective AI applications? Ultimately, how can the answers to these questions propel our understanding and implementation of learning in both babies and machine? Breaking down disciplinary barriers, the workshop encourages active exchange of ideas, fostering innovative solutions and advancements in both developmental science and machine learning.
Invited Speakers
Invited Speakers
Youngki Lee (Seoul National University): Key note speaker
Janet Bang (San Jose State University)
Hiromichi Hagihara (Osaka University)
Katie Von Holzen (Technical University of Braunschweig)
Margarethe McDonald (University of Kansas): Discussant
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