Please describe your proposed solution
Science is facing a crisis.
What we consider truth may not actually be true.
70% of science can't be reproduced and as we move into an era of more AI generated articles and data this number may continue to rise. Science relies heavily on human honesty, but this is vulnerable to errors and intentional manipulation.
Help us build a scientific future we can verifiably trust in.
Our protocol adds a machine-derived layer of trust to data from IoT devices. This means the data is designated as "trustworthy."
With generative AI being able to generate large authentic-looking data sets, this problem is going to get worse, and there needs to be a solution to "How can I trust the data?"
The core issue we aim to address is the lack of a reliable, tamper-proof data collection protocol in scientific experiments.
Proposed Solution:
- Causality Network is a chain agnostic protocol for IoT devices used in scientific experiments (such as wearables, EEG, bioreactors, blood test machines, environment sensors and more)
- It verifies data at source (eg, via secure enclave signatures)
- This means each data point has proof of its authenticity
- It stores this data privately via zK (on or off-chain)
- Data products are built on top (eg data marketplaces and analysis layers)