Robotics & Artificial Intelligence

Ethics in AI refers to the moral implications and principles that guide the use of AI technologies. Issues such as bias, fairness, accountability, and transparency are essential to address when developing AI systems. Ethical considerations ensure AI is used responsibly, minimising harm and maximising benefits for society.

Mention two ethical issues in AI with their significance.

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Two ethical issues in AI and their significance are:

  1. Bias – Bias in AI refers to the tendency of an AI system to give results based on data that is not collected fairly. If biased data is used to train an AI system, it may produce unfair or partial outcomes, leading to discrimination against certain individuals or groups. Addressing bias is significant to ensure fair and just decision-making in AI systems.

  2. Accountability – Accountability refers to who is responsible for the decisions and outcomes of AI systems, including their creators, operators, and organisations. It is significant because it ensures that there are clear guidelines of responsibility in case AI systems cause harm or make incorrect decisions, and it helps in monitoring, auditing, and improving AI systems for safe and reliable use.

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