Question

To reduce backlog in district courts, a few Indian states have introduced pilot projects that use AI tools to assist judges in case-sorting and bail-recommendation processes. Preliminary data suggest faster disposal rates, but legal scholars caution that algorithmic suggestions may replicate human biases if trained on historical judgments. The judiciary stresses that AI is only advisory and final decisions still rest with judges. Which of the following best explains the cause–effect relationship implied in the passage?

The passage links bias in past data to bias in AI output, establishing the cause effect relationship.

A Because AI models rely on historical data, any bias in past judgments can cause biased AI recommendations.

B Since AI tools improved case-disposal speed, judges no longer need to review minor cases.

C As AI is advisory, the responsibility for wrongful bail decisions shifts entirely to developers.

D Because courts face backlog, AI projects are free from ethical scrutiny.

E Since AI recommendations are faster, they are also necessarily more accurate.

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