What we know is that human based genetic algorithms can utilize the Darwinian process of “natural selection” to evolve a candidate solution. Human based genetic algorithms utilize the human as the selector and innovator. The data itself represents the sequence.
The sequence is a data pattern. The human beings contribute data patterns such as the”unique content” which makes the human beings the innovators. The human beings also are the selectors because they determine which content is “fit” or “unfit”. This can be managed by “like and dislike” or “upvote and downvote”.
An example of this would be an Ask site where human beings can ask questions and where answers selected up. Additional examples would include sites like Digg, Reddit, and Stumbleupon. The problem with these kinds of human based genetic algorithms is that there are centralized entities which means the website can be shut down. Distributed Human-based Genetic Algorithms would be not have a single point of failure and can be run on decentralized autonomous platforms such as Ethereum, NXT and any similar platform which allows for scriptability.
Okano, J., Hamano, K., Ohnishi, K., & Koppen, M. (2014, October). Particular fine-grained parallel GA for simulation study of distributed human-based GA. InSystems, Man and Cybernetics (SMC), 2014 IEEE International Conference on(pp. 3508-3513). IEEE.