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.