Indigenous Scientist: Digital & Health Science Transformation

Area of Science:

• Informatics
• Public Policy
• Data Science

Background:

• Personal reflection on data privacy's impact on an indigenous scientist's journey.
• Early experiences highlight the dehumanizing effect of being reduced to data points.

Purpose of the Study:

• To share personal experiences on data privacy and its implications.
• To underscore the importance of protecting vulnerable individuals' data.

Main Methods:

• Qualitative reflection on personal and student experiences.
• Analysis of data modeling in the context of poverty measurement.
• Examination of data privacy as a human right and UN development goal.

Main Results:

• Vulnerable individuals, identified by data points (e.g., socioeconomic status, ethnicity), require enhanced privacy protection.
• Data modeling can risk discrimination if not balanced with human dignity and individual context.
• Personal experience demonstrates deviation from initial data modeling through education and scientific pursuit.

Conclusions:

• Scientists must prioritize privacy and human dignity when handling data from vulnerable populations.
• Adherence to digital privacy standards is essential for accurate scientific interpretation and real-world impact.
• Protecting user, patient, and citizen data is an ethical obligation aligned with international development goals.