How should CJ leaders approach data privacy when collecting data for performance or crime analysis?

• A. Collect as much data as possible and share publicly to increase transparency.
• B. Apply data governance, minimize collected data, restrict access, use aggregated/de-identified data, and ensure non-discrimination.
• C. Ignore governance; share raw data with all staff.
• D. Only restrict access after a data breach occurs.

Answer: (B)

Prioritizing privacy in data collection means building a proactive governance approach that keeps data use purposeful, secure, and fair. The best option centers on data governance: set clear policies and roles, define what data is collected and why, and establish controls for how it’s accessed and protected. Minimizing collected data ensures you only gather what’s truly needed for performance or crime analysis, reducing risk if something goes wrong and helping stay within legal and ethical boundaries. Restricting access means only those who need the data to do their job can see it, lowering the chance of misuse or accidental exposure. Using aggregated or de-identified data lets you analyze trends and performance without exposing individuals, preserving usefulness while protecting privacy. Ensuring non-discrimination keeps analyses from producing biased or unfair outcomes, maintaining public trust and legitimacy of decisions.

Choosing to collect as much data as possible and share raw data publicly heightens privacy risks and can enable misuse. Ignoring governance and sharing raw data with all staff removes essential controls, increasing exposure and potential harm. Waiting to restrict access until after a breach is reactive and insufficient—proactive governance is needed to prevent harm and maintain credibility.