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                      1.  Fill in the blanks:
                         a.  Ethical AI promotes fairness and           .
                         b.  Machines learn ethics and bias from           .

                      2.  Name any 2 pillars of AI Ethics.



                      3.   In 2018, Amazon scrapped its AI recruiting tool that showed bias against women. Which ethical AI
                         principle was not being followed?

                      4.  Define privacy.








                        Bias, Bias Awareness, AI Bias and Sources of Bias


                 A facial recognition algorithm might find it easier to identify a white person compared to a dark complexion person
                 due to the prevalence of white faces in the training data. This discrepancy can unfairly impact individuals from distinct
                 groups, reinforcing inequality and oppression. The challenge lies in the unintentional nature of these biases, which
                 often go unnoticed until they manifest in the software.


                 Bias
                 Bias is defined as prejudice against individuals or groups, especially in
                 ways that are considered unfair. “Bias in AI” has long been a key area
                 of research and attention in the machine learning community. It refers
                 to situations where ML-based data analysis systems are biased against
                 certain  groups  of  people.  These  biases  usually  reflect  the  prevailing
                 social  biases  related to race, gender, biological sex,  age, and culture.
                 AI systems learn to make decisions based on training data, which may
                 include biased human decisions or reflect historical or social inequities.

                 Bias Awareness
                 In today’s connected world, AI technologies are becoming more important in different areas of our lives, such as
                 healthcare, finance, and criminal justice. However, as AI systems become more common, it’s crucial to recognise and
                 address the biases they may have. Bias awareness means understanding that AI systems can show unfair preferences
                 due to factors like training data used to train the AI models, rules they follow, the algorithms they use, or the principles
                 with which the AI model was designed. This awareness involves understanding that AI may occasionally make biased
                 decisions because of how AI model was developed or trained.






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