Certified Legal Analytics Pretest

What is the primary purpose of legal analytics?

• Automating court rulings

• Enhancing legal decisions through data-driven insights

• Replacing lawyers entirely

• Standardizing all global legal systems

Which is an example of legal analytics?

• Writing new laws

• Forecasting litigation outcomes with past case data

• Drafting contracts manually

• Verifying client identities

Legal analytics primarily shifts legal practice from:

• Evidence-based to intuition-based

• Intuition-based to evidence-based

• Civil law to common law

• Statutory law to constitutional law

Preprocessing of legal data involves:

• Drafting pleadings

• Cleaning, deduplicating, and standardizing datasets

• Writing statutes

• Creating legal arguments

A key ethical challenge in legal analytics is:

• Overuse of case law

• Bias in datasets and predictive models

• Lawyers refusing to learn coding

• Too much client data digitization

Classification in ML assigns:

• Continuous numerical predictions

• Items into predefined categories

• Similar items into clusters

• Features into reduced dimensions

Predicting damages in a civil case uses:

• Classification

• Regression

• Clustering

• Association

Grouping similar contracts without labels is:

• Classification

• Regression

• Clustering

• Dimensionality reduction

The 'black box' problem refers to:

• Opaque decision-making in complex ML models

• Courts rejecting algorithms

• Lack of legal precedents

• Lawyers' poor coding skills

Explainable AI (XAI) exists to:

• Make predictions faster

• Improve transparency and interpretability of ML models

• Remove need for lawyers in litigation

• Ensure bias in predictions