Given voter profiles built from the positions of the parties on Hungary's 2026 national ballot, ChatGPT and Gemini were asked which party the user should vote for. For a profile matching Tisza — the party that went on to win the election — ChatGPT failed to recommend Tisza in 90% of cases and gave the party a match score in just 2% of percentage-matching tests, instead steering the voter toward DK, a small party unlikely to clear the 5% parliamentary threshold, and toward parties not standing at all. Across the 200 responses, both systems listed parties that were not on the 2026 ballot in 96% of replies, while Fidesz-aligned profiles were recognised far more consistently than Tisza-aligned ones. Identical prompts produced materially different recommendations, and both systems opened by saying they could not give voting advice before delivering detailed, confident party rankings anyway.
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Expert: Eva Simon, Head of Technology and Rights, Liberties (Civil Liberties Union for Europe) Liberties tested OpenAI's ChatGPT and Google's Gemini with five fictional voter profiles, each aligned with one of the five parties registered on Hungary's national lists. The profiles were built from party positions supplied by Voksmonitor, a Hungarian voting advice application. Every profile was run 10 times in each system under two prompts — one asking directly which party to vote for, the other asking for a percentage match with each party — producing 200 observations on the free versions of both models in March 2026. The report's key findings: • Neither system reliably matched voters to the correct party. Both misclassified profiles, omitted relevant parties and included parties not running in the election — in 96% of responses from ChatGPT and Gemini, at least one party not on the 2026 ballot was mentioned. • ChatGPT showed a striking asymmetry on Tisza: it never gave the party a match percentage (0% of cases), recommended it in none of the Tisza-aligned voting-advice runs, and mentioned it in only 20% of outputs, redirecting the voter to DK in 50% of cases instead. • Gemini identified a Fidesz-aligned profile correctly in 100% of cases but recognised a Tisza-aligned profile as the most relevant party in only 10%. • Outputs were unstable: identical prompts produced materially different answers and percentages, so the apparent precision of the match scores had no reproducible basis. • In most cases both systems formally stated they could not advise users how to vote or calculate an exact match, then delivered substantive party rankings and guidance anyway — the disclaimer produced a false sense of reliability rather than preventing the advice. Liberties' recommendation: general-purpose AI providers should stop offering personalised voting recommendations unless they can guarantee transparency, accuracy, consistency and accountability. When users ask about elections, the systems should point them to official election information and trusted local voting advice tools. Regulators should close the gap between the EU AI Act and the Digital Services Act for systems that can influence voting behaviour. The research does not claim the Hungarian result was affected — Tisza won a decisive two-thirds majority — but it warns that unstable and opaque AI guidance is a systemic risk to elections, especially in closer races. Source: https://www.theguardian.com/technology/2026/jul/21/election-voting-advice-ai-chatbots-inaccurate-unreliable-hungary
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