AI for chemistry teaching: responsible AI and ethical considerations
This paper discusses the ethical considerations surrounding generative artificial intelligence (GenAI) in chemistry education, aiming to guide teachers toward responsible AI integration. GenAI, driven by advanced AI models like Large Language Models, has shown substantial potential in generating edu...
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| Format: | Article |
| Language: | English |
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De Gruyter
2024-10-01
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| Series: | Chemistry Teacher International |
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| Online Access: | https://doi.org/10.1515/cti-2024-0014 |
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| author | Blonder Ron Feldman-Maggor Yael |
| author_facet | Blonder Ron Feldman-Maggor Yael |
| author_sort | Blonder Ron |
| collection | DOAJ |
| description | This paper discusses the ethical considerations surrounding generative artificial intelligence (GenAI) in chemistry education, aiming to guide teachers toward responsible AI integration. GenAI, driven by advanced AI models like Large Language Models, has shown substantial potential in generating educational content. However, this technology’s rapid rise has brought forth ethical concerns regarding general and educational use that require careful attention from educators. The UNESCO framework on GenAI in education provides a comprehensive guide to controversies around generative AI and ethical educational considerations, emphasizing human agency, inclusion, equity, and cultural diversity. Ethical issues include digital poverty, lack of national regulatory adaptation, use of content without consent, unexplainable models used to generate outputs, AI-generated content polluting the internet, lack of understanding of the real world, reducing diversity of opinions, and further marginalizing already marginalized voices and generating deep fakes. The paper delves into these eight controversies, presenting relevant examples from chemistry education to stress the need to evaluate AI-generated content critically. The paper emphasizes the importance of relating these considerations to chemistry teachers’ content and pedagogical knowledge and argues that responsible AI usage in education must integrate these insights to prevent the propagation of biases and inaccuracies. The conclusion stresses the necessity for comprehensive teacher training to effectively and ethically employ GenAI in educational practices. |
| format | Article |
| id | doaj-art-a288ed3a114642afb5924d21db77fb87 |
| institution | Kabale University |
| issn | 2569-3263 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Chemistry Teacher International |
| spelling | doaj-art-a288ed3a114642afb5924d21db77fb872025-02-02T15:45:10ZengDe GruyterChemistry Teacher International2569-32632024-10-016438539510.1515/cti-2024-0014AI for chemistry teaching: responsible AI and ethical considerationsBlonder Ron0Feldman-Maggor Yael1Department of Science Teaching, The Weizmann Institute of Science, Rehovot, IsraelEECS – School of Electrical Engineering and Computer Science, Media Technology & Interaction Design, KTH Royal Institute of Technology, Stockholm, SwedenThis paper discusses the ethical considerations surrounding generative artificial intelligence (GenAI) in chemistry education, aiming to guide teachers toward responsible AI integration. GenAI, driven by advanced AI models like Large Language Models, has shown substantial potential in generating educational content. However, this technology’s rapid rise has brought forth ethical concerns regarding general and educational use that require careful attention from educators. The UNESCO framework on GenAI in education provides a comprehensive guide to controversies around generative AI and ethical educational considerations, emphasizing human agency, inclusion, equity, and cultural diversity. Ethical issues include digital poverty, lack of national regulatory adaptation, use of content without consent, unexplainable models used to generate outputs, AI-generated content polluting the internet, lack of understanding of the real world, reducing diversity of opinions, and further marginalizing already marginalized voices and generating deep fakes. The paper delves into these eight controversies, presenting relevant examples from chemistry education to stress the need to evaluate AI-generated content critically. The paper emphasizes the importance of relating these considerations to chemistry teachers’ content and pedagogical knowledge and argues that responsible AI usage in education must integrate these insights to prevent the propagation of biases and inaccuracies. The conclusion stresses the necessity for comprehensive teacher training to effectively and ethically employ GenAI in educational practices.https://doi.org/10.1515/cti-2024-0014ethics in scienceartificial intelligenceweb based learningteacher educationteacher professional development |
| spellingShingle | Blonder Ron Feldman-Maggor Yael AI for chemistry teaching: responsible AI and ethical considerations Chemistry Teacher International ethics in science artificial intelligence web based learning teacher education teacher professional development |
| title | AI for chemistry teaching: responsible AI and ethical considerations |
| title_full | AI for chemistry teaching: responsible AI and ethical considerations |
| title_fullStr | AI for chemistry teaching: responsible AI and ethical considerations |
| title_full_unstemmed | AI for chemistry teaching: responsible AI and ethical considerations |
| title_short | AI for chemistry teaching: responsible AI and ethical considerations |
| title_sort | ai for chemistry teaching responsible ai and ethical considerations |
| topic | ethics in science artificial intelligence web based learning teacher education teacher professional development |
| url | https://doi.org/10.1515/cti-2024-0014 |
| work_keys_str_mv | AT blonderron aiforchemistryteachingresponsibleaiandethicalconsiderations AT feldmanmaggoryael aiforchemistryteachingresponsibleaiandethicalconsiderations |