# Decentralised Data Labelling

At Timeworx.io, the approach to data labelling is set to be distinctly different, ethical and innovative. The focus is on decentralising the system to create a financial model where prices are dictated by the market, not by the platform. This shift ensures that prices are transparent and public. While it doesn't necessarily guarantee higher earnings for everyone, it does promise more transparency for all participants in the process.

Moreover, we aim to transform data labelling into a fun and engaging activity that people can enjoy and earn from in their spare time. The goal is to reach larger communities, educating them about data labelling, its implications, and how it contributes to AI development. This approach is designed to reduce friction and lower barriers to entry, thereby attracting a more diverse group of people. This diversity is key to reducing bias and increasing fairness in AI.

The main user interface for Human Agents is our native mobile application, available on both Android and iOS. The main complexity of the app resides in the capability of “translating” complex data processing tasks into a set of clear and actionable operations that users have to perform in a simple and intuitive user interface. Thus, the mobile application represents the entry point for Human Agents in joining the decentralised data processing protocol.

Whenever data processing pipelines are activated, the generated Tasks are distributed to our scalable crowdsource of Human Agents, which are responsible for solving them in exchange for a TIX reward. Agents, in turn, can choose to process tasks based on the offered price, complexity, and their personal preferences or expertise. Upon completion, the outputs are proposed to enter a Consensus round. The outcome of the Consensus round is delivered back to the platform, and it also determines the performance of each Human Agent which is further stored as an on-chain proof.

<br>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.timeworx.io/ai-that-is-fair/decentralised-data-labelling.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.