2021-09-30-海外发展研究所-数字身份_生物特征和纳入人道主义反应难民危机（英）_45页_783kb

报告摘要

Summary of "Digital Identity, Biometrics and Inclusion in Humanitarian Responses to Refugee Crises"

This report analyzes the use of digital identity systems and biometrics in humanitarian aid, focusing on refugee populations. It highlights the trade-offs between efficiency gains and risks, based on qualitative research in Jordan. Key themes include inclusion, privacy, and ethical considerations. Below is a structured summary.

Key Findings from the Study

The research, conducted in Jordan with Syrian refugees, reveals practical challenges and experiences with biometric systems. Refuges primarily use iris scans or ATM cards for assistance, with many preferring cards due to ease of access and fewer technical issues. Biometrics are seen as a necessity for aid, not a choice, and refugees face exclusion due to factors like age, health, geography, and technological failures. No clear evidence supports biometric fraud reduction, and failures often unfairly blame beneficiaries. Overall, the systems prioritize aid delivery over user rights and dignity.

Areas of Concern

Choice and Informed Consent: End users rarely give truly informed consent; explanations are minimal, and biometrics are often mandatory. Alternatives should be freely available.
Privacy and Data Protection: Data sharing and surveillance risks are high, with poor protection measures by agencies. End users distrust institutions and fear misuse, especially by governments or donors.
Ethics and Data Responsibility: Biometric use raises ethical issues like lack of transparency and potential for harm. Organizations need to minimize data collection, ensure accountability, and involve affected people in data governance.

Recommendations for the Humanitarian Sector

Assess whether biometrics are appropriate for specific contexts, avoiding unnecessary risks.
Co-design systems with refugees to address their concerns and ensure inclusivity.
Ensure equitable access by offering alternatives and adapting modalities to diverse needs.
Practice data minimization, limit data retention, and conduct regular audits to mitigate risks.
Embed data responsibility principles, including transparency and stakeholder accountability, to protect end users.