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Artificial Intelligence (AI) in Education: Addressing Societal and Ethical Challenges in K-12 Settings

EasyChair Preprint no. 8935

4 pagesDate: October 3, 2022


Artificial intelligence (AI) incorporates the applications of algorithms, machine learning, and natural language processing. AI has several applications in education, such as automated assessment and facial recognition systems, personalized learning tools and microblogging systems. These AI applications have the potential to increase capacity within education by supporting the social and cognitive development of students. Despite these affordances, AI applications pose critical ethical and societal drawbacks which are rarely considered in K-12 education. Integration of these algorithms in education may amplify societies’ existing systemic biases and discrimination, perpetuate privacy, autonomy, and surveillance concerns for students from marginalized and underserved groups, and amplify existing gender and racial bias. In this paper, we interrogate applications of AI in K-12 education, highlighting their ethical risks. We introduce instructional resources to help educators navigate the challenges of integrating AI and advance K-12 students’ understanding of AI and ethics. The paper concludes with recommendations for research.

Keyphrases: AI and ethics, Artificial intelligence (AI) in education, teacher education

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Selin Akgun and Christine Greenhow},
  title = {Artificial Intelligence (AI) in Education: Addressing Societal and Ethical Challenges in K-12 Settings},
  howpublished = {EasyChair Preprint no. 8935},

  year = {EasyChair, 2022}}
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