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Users’ Perspectives on Content Moderation of Web Search Autocomplete Suggestions

The prospect of moderating Autocomplete suggestions raises a range of ethical, technical, and political questions, such as how to distinguish between appropriate and inappropriate suggestions, who should have the power to make such distinctions, and how these decisions should be communicated to end-users. This article takes a user-centered approach to interrogating these questions. By conducting semi-structured interviews with 20 regular users of search platforms, I examine how users make sense of Autocomplete moderation, what concerns they have about its procedures, and how they seek to assert greater agency within the process.

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The Power and the Pitfalls of Large Language Models: A fireside chat with Ricardo Baeza-Yates.

Have you ever wondered how Google helps you complete your search query by suggesting the next terms of your query? Large Language Models (LLMs) power this feature. But LLMs go beyond that feature. Today, LLMs are used in building AI systems and applications ranging from recognizing speech to writing poetry. They have become very powerful, but there are also pitfalls.

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