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Artificial intelligence is no longer a distant curiosity — it’s embedded in every product we use daily.
As systems grow more capable, particularly in NLP and automated decision-making, we must confront deep ethical questions about bias, transparency, and accountability…
Key ethical implications: fairness testing, explainability in black-box models, accountability frameworks for automated decisions.
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Navigating the Ethics of Intelligent Machines: AGI, NLP, and Automation
Artificial intelligence is no longer a distant curiosity — it’s embedded in every product we use daily, from chatbots answering customer questions to algorithms optimising factory floors.
What we mean by AGI, NLP, and automation
- AGI: hypothetical systems that match or exceed human cognitive abilities across a broad range of tasks
- NLP: a branch of AI focused on understanding, generating, and interacting through human language
- Automation: the use of technology to perform tasks without human intervention
Key ethical implications
Even before AGI becomes realistic, current AI systems are shifting power, work, and knowledge in profound ways. Ethical considerations are therefore urgent — harms can be widespread, subtle, and hard to reverse.
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