Which foundational element of blockchain distributes computation across multiple systems so that no individual system can read the other parties' data?

The foundational element of blockchain that distributes computation across multiple systems while ensuring that no individual system can read the other parties' data is multiparty computation. This technique allows multiple parties to jointly compute a function over their inputs while keeping those inputs private from one another. In the context of blockchain, it ensures that even though computations are distributed over various nodes in the network, the confidentiality of each participant's data is preserved. This is crucial for maintaining privacy and security in decentralized environments where sensitive information may be shared among different parties.

Multiparty computation is particularly relevant in scenarios where participants must collaborate on computations without exposing their individual datasets, creating a trust model that is integral to the functioning of blockchain technology.

Other concepts, such as hashing, distributed consensus, and object storage, do play important roles in the blockchain ecosystem, but they do not specifically highlight the feature of performing computations in a way that protects the privacy of individual data inputs across different systems. Hashing is primarily used for ensuring data integrity, distributed consensus addresses agreement on transaction validation among nodes, and object storage refers to how data is stored rather than how it is computed across multiple parties.