Not able to spot the odd one in this set. Can someone help figure which sentence doesn’t fit?

Question

A. Machine learning models are prone to learning human-like biases from the training data that feeds these algorithms.
B. Hate speech detection is part of the on-going effort against oppressive and abusive language on social media.
C. The current automatic detection models miss out on something vital: context.
D. It uses complex algorithms to flag racist or violent speech faster and better than human beings alone.
E. For instance, algorithms struggle to determine if group identifiers like "gay" or "black" are used in offensive or prejudiced ways because they're trained on imbalanced datasets with unusually high rates of hate speech.

Divakshi Arora · Accepted Answer

The overall theme across the sentences is the use of machine learning algorithms in detecting hate speech and the problems they face, especially due to bias in training data. Sentence B introduces hate speech detection. Sentence D continues by describing how algorithms are used for this task. Sentence A and E highlight the flaws in the algorithms,  how they can pick up human biases or struggle due to skewed data.
Sentence C, however, talks about the lack of context in automatic models. While it&rsquo;s related to detection, it shifts the focus away from bias and dataset limitations, which is the core thread linking the others. It doesn&rsquo;t connect directly to the examples or flow established by the rest.
So sentence C stands out as the odd one, and the rest,  B, D, A, E &mdash; can form a coherent paragraph.

T Mehta · Answer

To find the odd one, try grouping ideas logically.

Sentence B introduces hate speech detection as a social media concern
Sentence D says algorithms are used to flag such content faster than humans
Sentence A explains that these models often pick up human-like bias from the data
Sentence E gives a concrete example where biased datasets lead to misjudgement

Now compare this to sentence C. It talks about missing context, which is a separate issue from biased training data or imbalanced representation. It doesn&rsquo;t align with the bias-focused angle that connects the rest.
That makes sentence C the odd one out. The others follow a consistent thread from purpose to mechanism to limitation.