Don't do Evil: Implementing Artificial Intelligence in Universities Cover Image

Don't do Evil: Implementing Artificial Intelligence in Universities
Don't do Evil: Implementing Artificial Intelligence in Universities

Author(s): Mark Nichols, Wayne Holmes
Subject(s): Social Sciences, Education, Higher Education
Published by: European Distance and E-Learning Network
Keywords: Institutional case study; Institutional innovation and development, case study; New ICT and media applications in learning

Summary/Abstract: Artificial Intelligence (AI) is changing the ways in which we experience everyday tasks, and its reach is extending into education. Promises of AI-driven personalised learning, learner agency, adaptive teaching and changes to teacher roles are increasingly becoming realistic but the ethical considerations surrounding these, and even simpler innovations are far from clear. Various ethical standards are proposed for AI, though these tend to be high-level and generic and do not serve to guide education practice. The multiple agencies concerned with AI analytics are also yet to provide a strong sense of direction. The Open University UK has established an AI working group to explore the contribution AI might make to improving student retention, success and satisfaction. With a specific emphasis on Artificial Intelligence in Education (AIEd), this paper proposes eight principles constituting an open ethical framework for implementing AI in educational settings in ways that empower students and provide transparency.

  • Issue Year: 2018
  • Issue No: 2
  • Page Range: 110-118
  • Page Count: 9
  • Language: English