AP Computer Science Principles · Unit 5 · Ethics & Society
Impact of AI & Computing: every key term you need (+ practice quiz)
20 flashcard terms for AP Computer Science Principles Unit 5, written to match the course framework. Study them here, then drill them as interactive flashcards, or test yourself with the 5-question quiz — free, no account needed.
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Artificial Intelligence Computer systems performing tasks requiring intelligence: learning, reasoning, problem-solving.
Machine Learning AI subfield where algorithms learn patterns from data and improve through experience.
Neural Network Machine learning model mimicking brain structure; layers of interconnected nodes learning patterns.
Deep Learning Neural networks with multiple hidden layers enabling learning of complex patterns.
Supervised Learning Training on labeled data (input-output pairs); algorithm learns to predict outputs.
Unsupervised Learning Training on unlabeled data; algorithm discovers hidden patterns and groupings.
Reinforcement Learning Algorithm learns through trial-and-error; rewards for good actions, penalties for bad.
Training Data Dataset used to teach algorithm; larger, diverse datasets improve accuracy.
Overfitting Model learns training data too well, including noise; performs poorly on new data.
Underfitting Model too simple; fails to capture patterns; poor performance on all data.
Accuracy Percentage of correct predictions; does not always indicate fair or representative model.
Precision Among predictions classified as positive, how many were actually correct.
Recall Among actual positives, how many did model identify correctly.
Generalization Model performs well on new, unseen data; indicates good learning without overfitting.
Transparency Ability to understand how an AI system makes decisions; important for accountability.
Explainability Providing understandable explanations for AI decisions; why did model choose that?
Accountability Responsibility for AI outcomes; who is responsible if algorithm fails or harms?
Ethical AI Developing AI systems considering fairness, transparency, privacy, and human values.
AI Ethics Field examining moral implications of AI: bias, privacy, autonomy, job displacement.
Autonomous Systems AI systems making decisions and taking actions without human control.
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