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A Framework for Auditing Recommendation Engines under the DSA

CORDIS · observation · Publication date unknown

A Framework for Auditing Recommendation Engines under the DSA This proposal presents a novel pipeline framework designed to systematically audit Search Engines (SEs) and chat-based Large Language Models (LLMs), serving as a proof-of-concept tool to support the implementation of Article 40 of the EU's Digital Services Act (DSA). The project addresses two critical goals: 1) to investigate how proprietary algorithms in SEs and LLMs influence electoral processes, and 2) to provide practical guidance to overcome complex DSA implementation challenges. SEs, such as Google, and LLMs, such as ChatGPT, have become primary channels for accessing information. Yet, both rely on opaque and fast-evolving algorithms that are difficult to audit. This raises significant concerns regarding the fairness, transparency, and neutrality of information they offer, particularly in contexts critical to democracy, such as elections: given their widespread use, even minor algorithmic biases can have significant impacts, influencing voter perceptions and electoral outcomes. The proposed frame

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR