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     Algorithmic bias: Algorithmic bias happens when the design of the AI system itself causes
                         unfair decisions. This can happen if the AI system focuses too much on one factor and ignores
                         others. For example, in a video game, an AI system might reward players who make quick
                         decisions, but not those who take their time to think carefully. This would be unfair to players
                         who play thoughtfully. Algorithmic bias happens when the system favours one style of play
                         over another.

                       Human bias: AI systems are created by people and if the people designing the AI have their
                         own biases, those biases can affect the AI. For example, if someone who loves rock music
                         creates an AI that suggests songs, it might suggest rock music to everyone, ignoring other
                         types like pop, classical or jazz. This is human bias, where the personal preferences of the
                         creator influence the AI’s decisions.
                                                                                                      21 st
                                                                                                     Century   #Critical Thinking
                                                                 ai in action                        Skills
                      The AI Bias Game shows how bias can affect decision-making. In this game, you work for
                      the World Sports Board and need to pick lucky fans to win free tickets to a game. You will
                      receive test results from different people who claim to be sports fans. Visit the given link
                      https://ai-bias.sustainablelivinglab.org/ or scan the OR code to play the game):

                      How Bias Affects AI

                      When AI systems are biased, they can make unfair decisions. This can cause harm, especially in
                      important areas like healthcare, education and jobs. Here are some examples of biased decisions
                      in AI:

                       Biased decisions when  giving  loans: An AI system  could  unfairly deny  someone  a loan
                         because it was trained on biased data.
                       Unfair hiring or recruitment decisions: If AI is used to decide who gets a job, it might be unfair
                         if it’s trained on data that favours certain groups of people over others.

                       Wrong predictions about crime risks: If AI is used to predict crime, it might unfairly target
                         certain communities based on biased data.

                       Incorrect medical or health advice: If AI systems are used to give health advice, they might
                         make wrong suggestions if the data is biased or incomplete.

                       Mistakes in identifying people: Facial recognition systems can make mistakes, especially if
                         they haven’t been trained on diverse data, leading to wrong identifications.

                      CASE EXAMPLES OF AI BIAS

                      Artificial intelligence (AI) is being used in many areas of lives, from hiring people to helping doctors.
                      But sometimes, AI systems can be unfair. This happens when the data used to train these systems
                      has hidden biases or when the system is not designed properly. These biases can cause the AI to
                      make unfair decisions, which can affect certain groups of people more than others. Let us explore
                      few examples of AI bias.

                       74        Artificial Intelligence (CT & AI)-VII

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