Uncovering the importance of data labeling

At the Training Data Project, we are championing a future where everyone can make informed choices about the quality of the data that powers their AI initiatives. To unlock the full potential of automation and achieve the economic, political and social benefits of Human-Machine Teaming, we must prioritize openness, reliability and set the highest standards for data labeling. We must prioritize TRUST. 

T

Transparent and
well-documented
data practices.

R

Readily available,
accessible, and
open data whenever
possible.

U

Unbiased data
with robust test
and evaluation
methods.

S

Standards-based
data to encourage interoperability.

T

Traceable data
to confirm
responsible and
ethical sourcing.

Join us as we pave the way toward a new future for public and private sector AI. Help shape a pioneering approach to training data where empowerment and choice fuels investments in our AI future.