This unit is organised into two parts
Foundations and Regulatory frameworks
Part 1: Foundations
The Foundations of AI Ethics introduces key principles guiding responsible AI use.
Activity: Play the video introducing AI ethics. Make a list of your concerns /issues
The core principles of ethical AI are shown in the diagram. They include fairness, transparency, accountability, privacy and bias mitigation.
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Image source: Cogent Info
Ethical uses of AI requires human-centred usability, inclusivity and trust.
The impacts of AI should minimise any potential harm and foster responsible innovation.
Ethical Challenges in AI
The issues involving the rising uses of AI are varied, they include:
– Data Ethics: Issues around where the data was collected, consent, and potential misuse of data.
– Job Displacement: Understanding AI’s impact on employment and preparing students for ethical discussions about AI and automation for example.
– Deepfakes and Misinformation: How AI can create deceptive content and the ethical concerns it raises.
– Inequality: Uneven access to AI technologies and the potential for exacerbating disparities.
Activity: Play the video which examines the issues concerning AI, bias and inequality
AI-powered geographic tools rely on data that may reflect biases, leading to distorted representations of places or populations. For example, historical and social biases in datasets can result in the unequal mapping of the needs of marginalised communities, reinforcing stereotypes.
Biases in geographical data gathering and mapping can affect analytical activities in, for example, urban planning, disaster management and ecological monitoring.
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Image source