lesson

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Imagine a self-driving car's brakes fail as a pedestrian steps into the road โ should the car swerve to protect the pedestrian and risk its passenger, or stay straight?
This is an ethical dilemma: a situation where a choice must be made between two moral options, neither of which is completely right or wrong.
๐An interactive card illustrating the difference between Law and Ethics. Left card: 'Legal Rules' showing a gavel icon with caption 'What society says you MUST do (enforced by laws)'. Right card: 'Ethical Questions' showing a balance scale icon with caption 'What society considers MORALLY right or fair (guided by human values)'. A central question badge: 'Just because code CAN do something, SHOULD it?'. Light background (#f8fafc), clean borders (#e2e8f0), deep navy text (#1e293b), vibrant teal (#0d9488) and indigo (#6366f1) accents.
While laws tell us what we legally can or cannot do, ethics asks whether an action is morally right, fair, and beneficial for human beings.
How do these ethical questions change when computers start making decisions instead of humans?
AI and Algorithmic Bias
Artificial Intelligence (AI) refers to computer systems designed to perform tasks that normally require human intelligence, such as recognizing faces or making hiring decisions.
Because AI models learn by finding patterns in historical training data, any human prejudice in that data creates algorithmic bias, leading the system to make unfair or discriminatory decisions.
๐A visual flow diagram showing how bias enters an AI system. Step 1: Historical Data (icon: folder with predominantly one group of applicants) -> Step 2: Machine Learning Model (icon: neural network gear processing data) -> Step 3: Biased Output (icon: reject stamp unfairly targeting underrepresented groups). Below is an accountability question box: 'Who is to blame if an AI denies a loan unfairly? The programmer, the company, or the data trainer?'. Light background (#f8fafc), cards in white with subtle shadows.
This creates the issue of accountability: when an autonomous algorithm makes a harmful mistake, it is difficult to determine whether the software developer, the data provider, or the business is responsible.
What happens when computers not only make decisions, but also take over human jobs entirely?
Automation and the Workforce
Automation is the use of software and robotics to carry out tasks with minimal or no human intervention.