Theory of Side-Choosing Games to Create and Disseminate Knowledge in Formal Science Domains

How do we create knowledge? We use the language of side-choosing games to instruct humans about which knowledge needs to be created, i.e., which problem needs solving. The language of side-choosing games becomes the domain-specific language for the human computation system. Our: side-choosing game (SCG) language uses a programming language to express game states and their transitions. What is unique about our approach to create knowledge? To support a claim, a game is played. Playing a game only involves cleverly assigning values to variables and not knowledge about a formal proof system to support the claim. The side-choosing game approach supports a low key approach to defending a claim and is suitable for many skill levels. “Amateur Scientists” can help to gain insights into claims before they are passed on to the expert scientists. How do we disseminate knowledge? Indirectly through curiosity! If a player loses a game although they predicted that they would win it, they become curious. They try to acquire the knowledge that the winning player has. What is our theory: We study how to map side-choosing game results into ranking relations between players with guaranteed and desirables properties. We borrow ideas from social choice theory instead of using heuristics. Our theory informs the design of socio-technical systems for problem solving and teaching. Our main contributions are (1) the concept of a side-choosing game with an illustration of its usefulness, (2) a representation theorem for an axiomatic treatment of ranking relations for side-choosing games, and (3) a meritocracy theorem showing that quasi-perfect players will be top-ranked iff the critical property of collusionresistance holds.