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General Paper · JC 2

Active learning ideas

Ethics of Scientific and Technological Advancements

This topic evaluates the ethical boundaries of scientific and technological progress. As we move further into the era of Artificial Intelligence, gene editing, and automation, the question is no longer just 'can we do it?' but 'should we do it?'. Students explore the need for robust ethical frameworks to guide innovation and prevent unintended consequences.

MOE Syllabus OutcomesSyllabus 8881 LO1: Explore a range of key issues of global and local significanceSyllabus 8881 LO2: Evaluate arguments and opinions
20–50 minPairs → Whole Class3 activities

Activity 01

Role Play50 min · Small Groups

Role Play: The AI Ethics Committee

Students act as board members of a tech company developing a new facial recognition software. They must debate the potential biases and privacy risks before deciding whether to launch the product.

Should there be limits to scientific research?
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Activity 02

Gallery Walk40 min · Small Groups

Gallery Walk: The Future of Biotech

Stations feature different biotech advancements (e.g., CRISPR, cloning, lab-grown meat). Students rotate to identify the 'Pros' for humanity and the 'Ethical Red Flags' for each technology.

What are the ethical implications of artificial intelligence?
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Activity 03

Think-Pair-Share20 min · Pairs

Think-Pair-Share: Technology, Master or Servant?

Students reflect on a piece of technology they use daily. They discuss in pairs whether this tech has made them more 'free' or more 'dependent,' then share their conclusions with the class.

Does technology solve more problems than it creates?
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A few notes on teaching this unit


Watch Out for These Misconceptions

  • Science is 'neutral' and ethics is just a personal opinion.

    Scientific research is often driven by societal values and funding priorities. Using a 'values-clarification' exercise helps students see that ethical frameworks are essential for ensuring science serves the common good.

  • Artificial Intelligence will eventually 'think' exactly like a human.

    AI is based on pattern recognition and data, not consciousness or empathy. Collaborative investigations into how algorithms work help students understand the fundamental differences between human and machine intelligence.


Methods used in this brief