Every quiz has a topic problem. The host picks what they know, and half the room suffers through questions they never had a chance at. Fair Mix is a different approach: every player votes on topics before the game starts, and the AI builds a quiz that reflects the entire group.
Here's a scenario that plays out at every quiz night, in every group, everywhere in the world.
The host loves football. So there are 15 football questions. The host also likes classic rock, so there are 10 music questions skewed toward the 1970s. The host is weak on science, so there's one token science question about what planet is closest to the sun.
The three people in the room who know everything about biology, astronomy, and modern pop music? They never get their moment. They score poorly not because they lack knowledge, but because the quiz was never designed for them.
This isn't the host's fault. It's structurally inevitable. When one person selects topics, they select based on their own knowledge and interests. Even well-intentioned hosts have blind spots. A perfectly balanced quiz requires knowing what everyone in the room cares about — information the host simply doesn't have.
Fair Mix solves this by making topic selection a group activity rather than a solo decision. The process is simple:
Step 1: Everyone submits topics. When a Fair Mix game starts, every player gets a prompt: "What topics do you want in this quiz?" Each person submits two to five topics they're interested in. These can be broad ("History") or specific ("Formula 1 racing"). There are no wrong answers.
Step 2: The system counts votes. Behind the scenes, QUIZT tallies topic popularity. If eight players are in the game and four of them submitted "Movies," that topic has strong demand. If only one person submitted "Ancient Rome," that topic has a single advocate.
Step 3: Questions are distributed proportionally. Here's the key: the number of questions per topic is weighted by how many players chose it. In a 30-question game where four people picked "Movies" and one person picked "Ancient Rome," you might get eight movie questions and two Ancient Rome questions. The majority interest is reflected, but the minority interest isn't erased.
Step 4: AI generates fresh questions. Based on the weighted topic distribution, QUIZT's AI generates unique questions for each category. No question banks, no repeats from last time. Every Fair Mix game is built from scratch for your specific group.
You could solve the topic problem by simply including every suggested topic equally. But that creates its own issues.
Imagine eight players. Seven submit "Pop Culture" and one submits "Organic Chemistry." In an equal distribution, half the quiz is organic chemistry — a topic only one person wanted. That's not fair either. It's just unfair in a different direction.
Proportional distribution reflects the group's actual composition. If most people want pop culture, most questions are pop culture. But the organic chemistry fan still gets their moment — a couple of questions where they have an edge that nobody else does.
This creates a fascinating dynamic during the game. When an organic chemistry question appears, seven people are guessing and one person is grinning. That reversal — the underdog moment — is one of the most enjoyable things that can happen in a quiz.
Fair Mix adds strategy that doesn't exist in traditional quizzes. Consider these scenarios:
The niche play. You submit "Medieval Scandinavian History" as one of your topics. Nobody else does. When those questions appear, you're the only person with a genuine advantage. The downside: there won't be many of those questions. But the ones that appear are almost guaranteed points for you.
The popular play. You submit "Movies" knowing that several others will too. More movie questions will appear, which is good because you're strong there. But so are several other players. You get more opportunities, but face stiffer competition on each one.
The knowledge gap. You notice that your friend group always picks sports and entertainment. You submit "Geography" and "Science" — topics you know well that others tend to neglect. Even if only you and one other person chose those topics, the questions that appear play to your strengths.
This strategic dimension emerges naturally from the voting mechanic. Players aren't just answering questions — they're shaping the quiz itself before it begins.
Fair Mix doesn't just rebalance topics. It fundamentally changes how people experience a quiz.
Mixed-knowledge groups feel fairer. When a history PhD plays against casual trivia fans, a traditional quiz either caters to the expert (boring for everyone else) or avoids academic topics (frustrating for the expert). Fair Mix naturally includes both because both perspectives contributed to topic selection.
Regular game nights stay fresh. Groups that play together weekly or monthly often fall into topic ruts. Fair Mix shakes this up because different combinations of players produce different topic mixes. When a new person joins, the entire quiz shifts to include their interests.
International groups work better. When players come from different countries, their knowledge bases differ dramatically. A Swede, a Brazilian, and a Japanese player all submitting topics creates a quiz that none of them could have experienced elsewhere — a genuine cross-cultural mix.
Competitive balance improves. In traditional quizzes, the same person often wins because the topics consistently favor their knowledge profile. With Fair Mix, the topic landscape shifts every game. Last week's winner might struggle this week because the group composition changed.
QUIZT offers a second topic-selection mode called Common Ground that takes a different approach. While Fair Mix distributes questions proportionally across all suggested topics, Common Ground uses AI to find the semantic intersection of everyone's interests.
If three players submit "Space," "Sci-fi movies," and "Rocket engineering," Common Ground recognizes the shared thread and might generate questions about "Space exploration in popular culture" or "Real science behind science fiction." It creates a quiz that sits at the center of the Venn diagram of everyone's interests.
Fair Mix is best when your group has diverse interests and you want everyone's niche represented. Common Ground works when you want to discover shared passions you didn't know you had.
Both modes solve the same core problem — the host shouldn't be the only person deciding what the quiz is about. They just solve it differently.