Issues and Concerns in the AI Era

Overview

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In this part, we examine the societal and ethical challenges posed by large language models, from legal questions around training data and ownership through technical issues like hallucination and bias to broader concerns about privacy, environmental impact, and the future of work.

The chapters in this part are as follows.

• Data, Copyright, and Ownership explores legal disputes around training on copyrighted material and ownership of AI-generated outputs.
• Hallucination, Bias, and Misinformation examines how models generate false content, inherit societal biases, and can spread misinformation.
• Privacy and Security Risks discusses data exposure, prompt injection attacks, and other security vulnerabilities.
• Infrastructure and Environment outlines the computational resources, energy consumption, and environmental costs of training and deploying large language models.
• Human Skills and Future of Work considers how AI reshapes work, which human capabilities remain essential, and alternative futures based on AI integration.
• Summary summarizes the key takeaways from this part.