What are the ethical concerns with facial recognition and predictive policing, and how should agencies respond?

• A. They are always accurate; no bias; no oversight.
• B. Risks of misidentification, discrimination, erosion of civil liberties; address via bias testing, limiting use, publish criteria, oversight.
• C. They should replace human judgment entirely.
• D. They should be used widely without transparency.

Answer: (B)

Misidentification, bias, and the erosion of civil liberties are the main concerns here. Facial recognition and predictive policing can misidentify people, especially those from marginalized communities, leading to wrongful investigations or charges. If the data or models reflect societal biases, those biases get amplified in police practices, producing discriminatory outcomes. Expansive surveillance also threatens privacy and other freedoms, creating a chilling effect where people alter their behavior out of fear of constant monitoring.

To address these issues, agencies should implement rigorous bias testing and independent audits to understand how the tools perform across different groups. They should limit use to clearly justified purposes rather than broad, indiscriminate deployment. They should publish the criteria, thresholds, and methodologies so the public can scrutinize how decisions are made. And they should establish strong oversight with accountability—transparent reporting, external reviews, and avenues for redress when harms occur. Ongoing evaluation, data minimization, and privacy protections should accompany any use.

Choices that claim perfect accuracy, remove human judgment entirely, or push for widespread, nontransparent use miss the essential safeguards that protect civil liberties and ensure trustworthy policing.