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Answer :
One of the challenges associated with building Agentic AI systems is ensuring responsibility in autonomous systems.
Agentic AI systems refer to artificial intelligence that can act independently or autonomously, making decisions and taking actions without direct human intervention. While these systems have the potential to revolutionize various industries by improving efficiency and performance, they also present several challenges, particularly in terms of responsibility.
Complexity of Decision Making: These systems are designed to operate in complex environments, making decisions based on a multitude of variables. Establishing a framework to ensure that the decisions made are ethical and in line with societal norms is a significant challenge.
Accountability: When AI systems make decisions autonomously, determining who is held accountable for the outcomes of those decisions becomes difficult. Is it the developer, the user, or the AI itself? This question of accountability is crucial in both the legal and ethical domains.
Transparency: Agentic AI systems often function as 'black boxes' where the decision-making process is not easily understood by humans. Ensuring transparency about how decisions are made is essential for trust and verification purposes.
Bias and Fairness: AI systems learn from data, and if the training data is biased, the AI can also make biased decisions. Ensuring fairness and avoiding discriminatory outcomes is a core challenge.
Addressing these challenges requires multidisciplinary efforts involving computer science, law, ethics, and policy-making to create frameworks and regulations that ensure AI systems operate responsibly and beneficially.
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