Data Ethics
What are the three pillars of data ethics?
Fairness, Accountability, and Transparency.
What is it called when a model is too complex?
Overfitting.
What type of software interface allows different applications to communicate and integrate services?
APIs.
This term refers to the unethical or illegal use of personal or sensitive data, often violating privacy, security, or consent agreements.
Data misuse.
This term refers to understanding and explaining how a machine learning model makes its predictions.
Interpretability.
What ethical concern arises from AI-generated work?
Plagiarism.
What technique prevents overfitting?
Regularization.
What Python library is widely used for data analysis?
Pandas.
What political consulting firm was involved in a 2018 scandal for improperly harvesting Facebook user data?
Cambridge Analytica.
What statistical technique is used to ensure models generalize well by preventing overfitting?
Regularization.
What document, established by the Association for Computing Machinery, provides a framework for responsible professional conduct?
ACM Code of Ethics
What measures the effect of an independent variable?
Coefficient.
What process involves identifying and resolving errors in software to ensure correct functionality?
Debugging.
This 1979 report laid out ethical principles for research involving human subjects, focusing on respect, beneficence, and justice.
The Belmont Report.
This type of visualization highlights which features of an input had the most influence on an AI model’s prediction.
Heatmap.
This California law created a state agency to enforce data privacy rights and strengthen consumer protections.
CPPA
What process involves selecting a subset of individuals from a population to draw conclusions about the entire group?
Sampling Methods.
What AI research lab, originating from China, focuses on open-source large language models?
Deepseek.
This committee reviews and approves research proposals to ensure ethical standards when human participants are involved.
Institutional Review Board (IRB).
What term describes machine learning models whose decision-making processes are not easily interpretable?
Black-box models.
This ethical challenge arises when AI-generated content, such as deepfakes or synthetic media, is used to deceive or manipulate public opinion.
Misinformation.
What statistical technique determines the minimum sample size required for detecting an effect?
Power Analysis.
Developed by Meta, this family of open-weight large language models is named after a South American animal.
LLaMA.
This process provides participants with all necessary study information, ensuring voluntary agreement with full understanding of risks.
Informed Consent.
In time series analysis, this term refers to when past values are used as predictors for future values, introducing delays.
Lagging.