Our Guiding Ethical Principles
PRINCIPLE OF RESPONSIBLE DATA COLLECTION AND SOURCING
Data Scientists have a responsibility to understand how data was collected, ensure
the data has been sourced legally and ethically, confirm that use of the data is consistent
with how it was intended to be used, and verify that no group(s) of people are intentionally
statistically mis/under-represented.
PRINCIPLE OF PROTECTION
Data Scientists have a responsibility to protect and defend integrity of the data
entrusted to them.
PRINCIPLE OF TRANSPARENCY and REPRODUCIBILITY
Data Scientists have a responsibility to ensure that the transformation of data into
products (e.g., algorithms) is as transparent as possible. The process should be
well-documented, explainable, and reproducible.
PRINCIPLE OF FORESIGHT
Data Scientists have a responsibility to provide evidence that any products they have
developed do not exhibit bias or potential harm against any demographic subgroups
such as race, gender or ethnicity or subgroups defined by genetic markers or socio-economic
status.
PRINCIPLE OF COMPETENCE
While Data Scientists come from multiple educational backgrounds, all individuals engaged in the practice of transforming data into analytical products should accurately represent their qualifications, the limits of their expertise and commit to continued education.