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The Human-Algorithmic Question:
A Media Literacy Education Exploration

Call for Abstracts - Proposals due by March 15th

 

Algorithms - the building blocks to machine learning and artificial intelligence - have begun to take on a life of their own in our communities and come with many questions. Through the lens of media literacy, how can we conceptualize, analyze, evaluate or process the impact of algorithms, machine learning, and artificial Intelligence locally, culturally, and globally? What are the ethical uses? How do they relate to other domains? We are being conditioned to think algorithms are complex, but they are not. Yet, there is a need for all of us to understand the relationships between engineers who design algorithms, machines that can learn and make new algorithms, and how we are impacted by these processes.  This issue of the JML seeks to address some of these components, along with understanding how young people think about the scope of AI, algorithms, and the costs involved. As media literacy educators, we need to address issues of justice related to data or lack thereof which is a growing field, the complexity of disinformation whether in the automation of information or even the automation of climate disinformation, and the role of AI in education. 

 

Potential Topics of Consideration:

  • Coded Bias in Media

  • Contributions of Artificial Intelligence: Improving? Limiting? Media Binds or Blinds?

  • Ethical Implications of AI and Questions of Justice

  • Automated Advertising Systems

  • The Role of AI in Mis/Disinformation

  • Technological Determinism Theories

  • Posthumanism Philosophies

  • Future Thinking and the Power of Humanity 

  • Insights from Learning Theories and Computer Science

  • Computational Thinking and Algorithms in Education

  • Transdisciplinary conversation - How are other fields addressing issues of AI? 

  • Trends and Issues in AI and Education

    • Expanding Learning Environments through AI

    • Pedagogical Principles and Computational Methods

    • Predicting Academic Performance: Data Driven Instruction

    • The role of AI in Assessment and Evaluation

  • Youth Voices 

*Editors are open to other topic considerations.

JML is looking for a variety of types of articles. We recommend the average length of a traditional article to be between 2000-5000 words. For more guidelines, please see our Author Information page.