Students are growing up in a world where such technologies are increasingly being applied in ways that affect what information they see, what choices are available to them and what decisions are made about them.
"Social media and commercial platforms such as Google are classifying and individualising content to a point which could have a direct impact on an individual's life. Whether it's creating filter bubbles which polarise political debate or presenting fixed prices based on a person's past shopping habits, students need to be able to understand how this data is being used," Moses said in a statement.
"While not every high school student needs to be able to code a Machine Learning (ML) algorithm, young people need to understand what's going on behind these systems so they can properly assess their use as future citizens, consumers or in a professional capacity," Moses added.
Alongside broader computational thinking skills, students who can apply ethical reasoning and diverse knowledge and skills to applications of machine learning and statistics will be in a better position to challenge potentially harmful forces of automation, the paper suggested.
The paper argued that it's crucial for schools to offer learning opportunities -- whether embedded in a regularly scheduled class or at a special day of activities -- where students can engage in problem-based and interdisciplinary thinking about important contemporary issues which cut across the curriculum.