Tag: Human-Computer Interaction
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GIGO – Garbage In, Garbage Out
The principle “Garbage In, Garbage Out” (GIGO) asserts the essential link between input data quality and output reliability, emphasizing the need for careful data validation. Rooted in computing history, its relevance spans across fields, advocating for meticulous data handling to ensure accurate outcomes.
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LLM – Large Language Model
Large Language Models (LLMs) are sophisticated AI systems designed for language processing. They learn from vast text datasets, excelling in tasks like translation and content creation, and continuously evolve based on new data and user interactions.
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Nudging
Nudge theory, developed by Thaler and Sunstein, utilizes subtle cues to influence decision-making, applied in fields like public policy and health. It operates on the principle that small environmental or informational adjustments can significantly impact behavior, prioritizing ethical application and individual autonomy.
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Shibboleth
Shibboleths are specialized identifiers, linguistic, cultural, or technical, that distinguish members within specific groups. Originating from historical linguistic tests, they have evolved to serve critical roles in modern contexts ranging from military identification to social customs, effectively managing inclusion and exclusion.
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Cognitive Load
Cognitive load denotes the mental strain within working memory. It’s segmented into three kinds: intrinsic, based on subject complexity; extraneous, from delivery; and germane, fostering deep learning. Individual differences, such as age and expertise, and factors like task difficulty affect its impact.