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b.  Economic Disruption: Workers who lose their jobs may struggle financially, face higher unemployment,
                     and find it harder to get new jobs without the required skills.
              3.  Privacy and Data Security Risks
                  a.  Sensitive Information: AI can inadvertently or maliciously generate sensitive personal information, like
                     social security numbers or medical records, which can be exploited for identity theft or fraud.

                  b.  Data Breaches:  The  misuse  of  AI  to  access  or  generate  personal  data  poses  significant  risks  to  an
                     individual's privacy and security.

              4.  Ethical and Moral Concerns
                  a.  Bias and Discrimination: AI models trained on biased data can produce biased outputs, reinforcing
                     stereotypes and discrimination.

                  b.  Dehumanisation: Relying too much on AI for tasks that need human understanding and compassion
                     can make services and interactions feel less personal and caring.

              5.  Security Threats
                  a.  Cyber Attacks: AI can be used to develop sophisticated cyber-attacks, including generating malicious
                     code or automated phishing schemes.
                  b.  Weaponisation:  Generative AI could be used to create harmful technologies or weapons, posing
                     significant national security risks.

              6.  Environmental Impact

                  a.   Training and running large AI models require significant computational resources, contributing to high
                     energy consumption and environmental impact.

                  b.  Many devices are being exchanged due to outdated hardware leading to increase in e-waste.

                             Reboot



                    1.  Provide examples illustrating instances where biases in Generative AI are evident.



                    2.   What is deepfake?












                       Responsible Use of Generative AI


              The responsible use of Generative AI involves:
                 • Ensuring that the training data used are diverse and representative. Use datasets that reflect a wide range
                of demographics, cultures, and contexts to avoid biases in AI outputs. Regularly audit and adjust datasets to
                address and reduce biases.

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