Question 1

A tech company is developing an AI tool for educational institutions in Europe, which includes emotion recognition technology to analyze student engagement. Under the EU AI Act, what should the company consider?

Options :

A : Only deploy the technology after collecting sufficient data on student reactions.

B : Ensure that the tool is easily accessible to all students and teachers.

C : Market the technology broadly as a tool for all learning environments.

D : Avoid deploying the tool as emotion recognition in educational settings is likely prohibited under the AI Act.

Answer: D

Question 2

A tech company uses a small set of labeled network data to detect anomalous activities while most of the dataset remains unlabeled. They aim to detect anomalies in real time but are unsure if their data labeling will scale. Which learning method would best balance accuracy and scalability?

Options :

A : Supervised learning on labeled data only

B : Semi-supervised learning to leverage both labeled and unlabeled data

C : Unsupervised learning on all data, ignoring labels

D : Manually label all data before applying supervised learning

Answer: B

Question 3

An analyst uses stepwise regression to build a predictive model for house prices. After starting with an empty model, the analyst adds features one by one until no further reduction in the Akaike Information Criterion (AIC) is achieved. Which method is the analyst using?

Options :

A : Backward stepwise selection

B : Forward stepwise selection

C : LASSO regularization

D : Ridge regression

Answer: B

Question 4

A data scientist is tuning the ridge regression model’s hyperparameter, λ, to control the trade-off between model fit and complexity. If λ is set too high, what effect is most likely?

Options :

A : The model will overfit the data

B : The model will be underfit, as coefficients are heavily penalized

C : The model will become equivalent to OLS regression

D : The model will ignore the penalty term entirely

Answer: B

Question 5

A generative AI provider in China is designing its service to align with Chinese regulations. What is a key obligation it must meet under the Generative AI Measures?

Options :

A : Ensure all content generated is free from any factual errors.

B : Prioritize content generation for government-endorsed topics only.

C : Prevent the generation of illegal and discriminatory content, respecting privacy rights.

D : Avoid transparency in algorithm usage to maintain competitive advantage.

Answer: C