Recency bias

As explained in The Art of AI Product Development

Recency bias is a tendency for a model to replicate outputs associated with examples appearing later in a prompt.

Recency bias is a few-shot prompting failure mode in which a model favors outputs associated with examples near the end of the prompt. A final positive sentiment example, for instance, can pull later classifications toward positive. section 6.2.1

Reduce the risk with deliberate example design:

• Slightly underrepresent the label assigned to the final example in the list. section 6.2.1
• Vary example order and combinations during prompt development, then document and version the results. section 6.2.1

Sentiment classification

A prompt ends with a positive sentiment demonstration. The model may classify the current input as positive because it recalls the most recent context more strongly, even when earlier examples suggest another label. section 6.2.1

Figure 6.3 Example of a few-shot prompt for sentiment analysis

Use the few-shot sentiment-analysis prompt example to inspect how demonstration ordering can shape model outputs. section 6.2.1

How The Art of AI Product Development covers it

How deep it goes

Defines the bias, gives a sentiment example, and recommends one mitigation without detailing model internals.

Examples

Uses sentiment labels, a final positive example, and a few-shot sentiment-analysis prompt.

What it assumes

Assumes familiarity with prompts and labels while explaining few-shot example ordering directly.

What you can do after

Diagnose/debug with it by varying example order and reducing the final example’s label representation.

How it connects

Connects recency bias with few-shot prompting, sentiment analysis, prompt engineering, and prompt versioning.

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Related concepts

• position biaskind of · Position bias is the systematic influence of an item’s position or order on attention, processing, interaction, or evaluation, independent of its intrinsic content or relevance.
• fairnessaddressed by · Fairness is the principle or property of allocating treatment, opportunities, or outcomes equitably among relevant people, groups, or participants according to appropriate criteria.
• strategic climateaddressed by · Strategic climate is the set of external environmental forces and recurring changes outside an organization’s control that can affect its business landscape.
• prompt engineeringaddressed by · Prompt engineering is the deliberate design and refinement of instructions, context, examples, or other inputs to guide an AI model’s behavior or outputs.
• common token biascontrasts with · Common token bias is a tendency for a language model to produce more probable, frequently observed tokens or labels more often than rare ones.

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.