CAS Secondary TC Meeting: Teaching Tomorrow's Technology: Ethics

If you were unable to join us for the "Teaching Tomorrow’s Technology: Ethics, Bias, and Digital Responsibility" thematic community meeting, don't worry! You can catch up on all the content and a recording of the session below.

Key Takeaways:

1. Ethics is a critical component of computer science, shaping how future developers address societal challenges.
2. Real-world examples, such as AI bias and autonomous vehicles, demonstrate the impact of ethical decision-making.
3. Teachers play a pivotal role in equipping students to navigate ethical dilemmas in technology.
4. Tools like generative AI can support teaching but must be used with transparency and responsibility.
5. Green computing highlights the environmental impacts of software and hardware, encouraging sustainable practices.

On January 20, educators, practitioners, and enthusiasts gathered for a CAS thematic community session led by Neil Gordon, exploring the pressing issues of ethics, bias, and digital responsibility in computer science education. With technology increasingly embedded in every aspect of our lives, understanding the ethical implications of its use has never been more important.

Neil opened the session by discussing the essential role of ethics in shaping the next generation of technologists. He introduced topics such as AI bias, data privacy, and the broader societal impacts of digital tools. Using real-world examples, such as the Horizon Post Office scandal and the ethical dilemmas of autonomous vehicle programming, participants were invited to reflect on the consequences of technological decisions.

The session also emphasised the importance of critical thinking and personal responsibility. Attendees engaged in interactive polls and hypothetical scenarios, tackling questions like: Should autonomous vehicles prioritize passenger safety over pedestrians? And how do we reconcile technological advancements with ethical practices?

One highlight was the discussion on generative AI and its implications for teaching. From concerns about biased training data to the ethical challenges of using AI-generated content, the conversation underscored the need for transparency. The group also explored green computing, examining how software efficiency and responsible hardware use can reduce the environmental impact of technology.

Next Steps:
To integrate these insights into your teaching, consider asking:

• How can I make ethical discussions more prominent in my curriculum?
• What real-world case studies can I use to illustrate the importance of ethics in computing?
• Are my students aware of the biases embedded in the tools they use?

Here are some exercises to try with your students:

• Debate: Assign groups to argue for or against the use of facial recognition in public spaces.
• Scenario Analysis: Present a moral dilemma involving AI, such as bias in hiring algorithms, and discuss possible solutions.

Further Resources:

• BBC Bitesize: Ethics in Computer Science
• CAS Resources
• BCS Report: Living with AI
• CAS Secondary Community
• Event Recording 
• Event Slideshow