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Web 3.0 Requires Data Integrity - Coggle Diagram
Web 3.0 Requires Data Integrity
What is Data Integrity? - Data Integrity is basically ensuring no one can modify data and encompasses "Accuracy, completeness, and quality of data".
Types of Webs and What they prioritize/d
Web 2.0 - confidentiality (protecting the data of today such as personal information or user data)
Web 3.0 - integrity (specifically of the tools that we use today that make searches, summarizations, and a lot of other things easier to do)
Web 1.0 - availability (a basic building foundation where organizations are uploading their resources to the internet) (1990s)
What does Web 3.0 entail?
AI systems need integrity controls preserving connection between data and ground truth.
Building systems that maintain verifiable chains of trust between their inputs, processing, and outputs, so we can understand.
Clean consistent and verifiable control processes to learn + make decisions effectively.
Things to consider
Defense-in-depth strategies from cryptographic verification of training data
AI systems if not programmed correctly may produce flawed outputs that appear valid on surface.
W3C protocols address
verifiable credentials data model for expressing digital credentials
ActivityPub - decentralized social networking
decentralized identifiers for verifiable digital identity
Web Authn - strong authentication standards
Four areas where data integrity is paramount
authentication
data ownership
granular access
access standardization