AI and blockchain represent a powerful combination of technologies that can transform numerous sectors, yet they raise important discussions about security and trust.
AI’s Blind Spots: Trust, Bias, and Security Risks
Modern AI systems function as "black boxes", often opaque and lacking transparency. This raises serious issues of bias that can enter models through faulty data. Moreover, vulnerabilities can be intentionally embedded. These flaws may threaten safety, particularly in critical systems.
The Need for Blockchain AI Transparency
Blockchain can offer a solution to AI trust issues due to its immutable and distributed architecture. Permanent records of all AI development steps render them auditable and prevent unauthorized changes. Projects like Ocean Protocol and SingularityNET utilize blockchain to create transparent data marketplaces.
Real World Examples of AI and Blockchain
There are many real-life examples of using blockchain to ensure AI transparency. The Voatz platform employs biometric authentication to create secure electoral records while in healthcare, blockchain logs combine with AI diagnostics to protect patient data.
Integrating blockchain into AI decision-making processes represents a reliable step towards developing ethical and secure systems. This collaboration opens prospects for a more transparent, secure, and fair digital future.
