The Rise of Predictive Policing: How Facial Recognition is Reshaping Retail Security in New Zealand
New Zealand retailers are quietly entering a new era of security, one powered by increasingly sophisticated surveillance technology. While Auror, a leading crime intelligence platform, insists its new facial recognition capabilities won’t be used for tracking or marketing, the rapid expansion of these systems – coupled with a government open to “pragmatic policy interventions” – raises critical questions about the future of privacy and the balance between safety and civil liberties. Police are now tapping into Auror’s automated number-plate recognition (ANPR) system a staggering 700 times a day, a fourfold increase in recent years, signaling a broader shift towards proactive, data-driven policing.
From Number Plates to Faces: The Evolution of Surveillance
For years, Auror’s ANPR technology has been a mainstay for major retailers like Briscoes, Mitre 10, and Z Energy, helping to identify stolen vehicles and track criminal activity. But the introduction of ‘Subject Recognition’ – Auror’s facial recognition offering – marks a significant escalation. This isn’t simply about identifying shoplifters; it’s about proactively identifying individuals deemed “high-harm” or “prolific offenders” before they commit a crime. The technology boasts a 99%-plus accuracy rate, a key factor in Auror’s decision to move beyond ANPR, particularly as retail crime becomes increasingly violent.
The Privacy Balancing Act
The rollout hasn’t been without scrutiny. The Privacy Commissioner gave the technology a “cautious tick” following a trial by Foodstuffs, but concerns remain. A legal challenge is currently underway regarding the police’s use of Auror’s ANPR system, with lawyers arguing for greater oversight and a requirement for warrants. Auror maintains strict controls: biometric data isn’t stored by the retailer or Auror themselves, residing solely with the third-party facial recognition provider. Furthermore, law enforcement access to the ‘Subject Recognition’ module and associated offender lists is explicitly prohibited. However, the fundamental question remains: how do we ensure these safeguards are effective and prevent mission creep?
The Axon Partnership and the Expanding Surveillance Ecosystem
Auror’s recent $82 million funding round, led by Axon – the US company known for tasers and body cameras – is a crucial piece of the puzzle. This partnership isn’t just about capital; it’s about integration. Police already utilize Axon tasers and store evidence, including sensitive data from family violence cases, on Axon’s ‘evidence.com’ platform. This creates a potentially comprehensive surveillance ecosystem, raising concerns about data consolidation and the potential for function creep. The convergence of these technologies could lead to a future where individuals are tracked and monitored across multiple platforms, even if Auror’s stated limitations on data usage are strictly adhered to.
The Role of Government and Policy
Justice Minister Paul Goldsmith has held multiple meetings with Auror to discuss “pragmatic policy interventions” regarding facial recognition. He’s also commissioned a review of the Privacy Act to determine if it poses barriers to the technology’s implementation. This signals a clear willingness from the government to explore ways to facilitate the use of facial recognition, despite the inherent privacy risks. The challenge lies in crafting legislation that balances the need for effective crime prevention with the fundamental rights of citizens. A key consideration will be defining “high-harm” and “prolific offenders” to prevent arbitrary or discriminatory targeting.
Looking Ahead: The Future of Retail Security
The trend towards predictive policing is undeniable. As facial recognition technology becomes more accurate and affordable, its adoption will likely accelerate, not just in retail but across various sectors. We can expect to see increased integration with other surveillance systems, such as CCTV cameras and social media monitoring tools. The debate will shift from whether to use these technologies to how to use them responsibly. Transparency, robust oversight, and clear legal frameworks will be essential to maintain public trust and prevent the erosion of privacy. The success of Auror’s mission to reduce violent retail crime by 50% in the next five years may hinge on navigating these complex ethical and legal challenges effectively.
What safeguards do you believe are essential to ensure responsible use of facial recognition technology? Share your thoughts in the comments below!
