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This paper is a preliminary exploration of secure distributed human computation. We consider the general paradigm of using large-scale distributed computation to solve difficult problems, but where humans can act as agents and provide candidate solutions. We are especially motivated by problem classes that appear to be difficult for computers to solve effectively, but are easier for humans; e.g., image analysis, speech recognition, and natural language processing. This paradigm already seems to be employed in several real-world scenarios, but we are unaware of any formal and unified attempt to study it. Nonetheless, this concept spawns interesting research questions in algorithm design, human computer interfaces, and programming language / API design, distributed systems, and cryptography, among other fields. There are also interesting implications for Internet commerce and the B24b model. We describe this research area and suggest a basic framework for the design of such systems. We analyze security and reliability against malicious parties using standard probability theory tools. We then derive design principles using standard decision-theory concepts. Finally, we list extensions and open problems.