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Responsible: This means taking accountability for the decisions AI makes. If an AI system used
in schools to grade assignments makes a mistake and grades unfairly, it’s important to know
who will fix it. Ethical AI makes sure there is always someone responsible for correcting errors.
ETHICS AND AI BIAS Safe: AI systems must not cause harm to anyone. For example, self-driving cars are powered
AWARENESS by AI. If the car makes a decision, it must ensure the safety of the driver, pedestrians and
everyone around. Ethical AI ensures that the system avoids accidents and protects lives.
Ethical AI ensures that the AI systems we use are helpful, safe and fair. It makes sure that AI is not
only smart but also responsible, so it doesn’t cause harm to anyone. Let’s look at the importance
of ethics in AI:
Prediction about disease risk: AI should never make decisions based on race or income.
Everyone must be treated fairly, no matter their background. AI should predict health risks
using medical information, not unfair factors.
Screening of job applications by AI: AI should not favour certain groups of people. For
example, imagine an AI system used to hire people for jobs. It should treat all applicants
equally, whether male or female, from any background.
Content recommended by algorithms: Algorithms should not promote harmful or false
information. For instance, if you use an AI system to recommend videos or articles online,
ethical AI ensures it suggests content that is true, helpful and safe for everyone.
21 st
Century #Critical Thinking
AI BIAS IN SELECTION Skills
The school uses an AI system to help select students for a special club, like a science or
tech club. The AI looks at things like students' past achievements, grades and interests to
decide who should be in the club. The system is designed to choose students based on their skills
and interests. However, there's a problem. The data the AI was trained on comes from previous years,
where the club mostly selected boys for leadership positions. Over time, this biased data causes the AI
to recommend more boys for the club, even when girls have similar or better qualifications.
In this case, the AI system is not being fair. It’s treating boys and girls unequally by choosing more boys
for the club, even though the girls have the same or better qualifications. The school wants to make
sure they select the best students for the club, regardless of gender.
Based on the above case answer the following questions:
1. What is the issue with the AI system in this situation?
2. How could this affect the girls who are applying to join the club?
3. What changes can the school make to ensure the AI is fair and treats all students equally?
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