Welcome to the second chapter of our AI in public safety series. In this blog, we are addressing:
- The role of AI in policing reform and four Veritone tools that help increase transparency
- Enhancing community engagement with improved online presence and conversational interfaces
- Ethical and moral considerations that need to be taken into account when considering AI for modern policing
- The next steps needed in police reform and why AI can help LEAs attain these goals
Need for Police Reform: A Brief Overview
In recent years, the need for police reform has become increasingly urgent in the eyes of the public. High-profile incidents of police brutality and police misconduct have sparked widespread outrage and demands for change, playing a significant role in driving the push for police reform and calling for more accountability and greater transparency from law enforcement.
One of the more prominent demands for reform comes from social movements, such as the Black Lives Matter movement, that address issues such as the use of force, racial profiling, and accountability for officer misconduct.
Social movements have played a crucial role in driving this demand for change; from organizing protests and rallies to advocating for policy changes at local and national levels, these movements have created platforms that help amplify the voices of those who have been historically marginalized and oppressed by the American criminal justice system.
Another key factor in police reform is the use of technology, particularly artificial intelligence (AI) by police departments, to promote greater transparency and accountability. For example, body-worn cameras, CCTV, and other forms of surveillance can help ensure that law enforcement follows protocols correctly and that incidents of misconduct are properly documented and investigated—but the volume of footage that requires review can create bottlenecks and slow down processes.
With the right solutions, law enforcement agencies (LEAs) can use AI to streamline workflows and analyze and redact video and audio evidence, which can help:
- Create greater transparency and trust with their communities
- Process data with greater accuracy and fewer opportunities for bias and misconduct
- Accelerate workflows and save costs so more time and money can be spent on more important tasks
All of these points can help address some of the root issues and ethical concerns behind the call for law enforcement reform. Now, let’s dive into real use cases and opportunities that AI solutions can make a positive impact in policing.
Role of AI in Modern Policing
Artificial intelligence in law enforcement offers a wide range of benefits in terms of efficiency, accuracy, and transparency, which can help to create a more effective and accountable criminal justice system.
Key benefits of the use of AI in law enforcement include:
- Enhanced efficiency and accuracy
AI-powered software analyzes large amounts of data and identifies patterns or anomalies that may be missed by human analysts. This helps to speed up investigations, reduce the risk of errors or oversights, and ultimately improve outcomes for both law enforcement and the public.
- Reduced human error and bias
By automating routine tasks and providing officers with data-driven insights, AI helps to eliminate some of the most common sources of error in policing. It also helps to identify and address unconscious biases that may impact decision-making, ensuring that officers are making decisions based on objective criteria rather than subjective or potentially discriminatory factors.
- Improved decision-making
Predictive policing software helps officers to identify high-risk areas or individuals and allocate resources accordingly, while biometric recognition technology helps to quickly identify suspects or missing persons.
However, the use of AI in policing is not without its challenges and potential drawbacks. Concerns have been raised about the potential for AI to perpetuate existing biases or be misused in ways that violate civil liberties or privacy rights, and there have been issues with early iterations of facial recognition technology in the past.
It is therefore crucial that any use of AI in policing is subject to rigorous oversight, transparency, and accountability, and that it is used in a way that is consistent with the principles of fairness, impartiality, and respect for human rights.
Any use of AI in policing must be subject to appropriate safeguards and oversight to ensure that it is used in a way that is consistent with fundamental rights and values. By pairing data-driven policing with less human error and systemic bias and greater officer support, AI can play a valuable role in creating a more effective and accountable criminal justice system.
Four Solutions From Veritone for AI-Enhanced, Data-Driven Policing
1. AI-Powered Suspect Identification: Veritone IDentify
For public safety and justice agencies, intelligent and rapid suspect identification is crucial. Despite the public perception that criminals caught on camera can easily be identified, law enforcement still faces significant challenges to connect suspects to the crime. Many agencies rely on manual processes such as sifting through masses of arrest records, seeking intel from colleagues, and even promoting the case publicly to identify a person of interest.
However, many agencies lack the necessary resources and tools to effectively search against their databases of known offenders and previously arrested individuals, resulting in a significant waste of time and resources. This often leads to only prioritizing serious or high-profile crimes, leaving many cases unsolved.
To address this challenge, Veritone IDentify leverages the power of the enterprise AI platform, aiWARE to streamline investigative workflows and enable faster suspect identification. With Veritone IDentify, agencies can automate the identification process and significantly reduce the time and resources required to identify suspects. Unlike other solutions that scrape the internet and social media sites, Veritone IDentify only uses an agency’s existing arrest records. This encompasses only individuals who’ve been arrested, fingerprinted, and had their photo taken as part of the process. By utilizing aiWARE’s powerful AI capabilities, LEAs can substantially increase their operational effectiveness while accelerating investigations, and improving the safety of the community.
2. Automating RIPA Stop Data Collection: Veritone Contact
Veritone Contact is an intelligent stop data collection application used by law enforcement officers for pedestrian and vehicle stops. Designed and adopted by California law enforcement agencies, Contact helps agencies meet the requirements of the California Racial and Identity Profiling Act (RIPA), serving as a solution for agencies across the nation as RIPA-like laws go into effect elsewhere.
Once the stop data is collected, LEAs must ensure that no PII is included in the data set and then securely transmit the information to the California State Department of Justice. However, the process of collection and review is significantly impacting the time officers have available for patrol. Additionally, records management teams are struggling to keep up with increased open records requests for redacted body-worn camera footage and other evidence requests, which now includes PII review of this information.
Many agencies find that state-provided or third-party stop data collection applications are time-consuming and challenging, whereas Veritone Contact simplifies the process of creating stop data reports. Orange Police Department adopted Veritone Contact to reduce the time officers take to produce RIPA reports by up to 2 hours each day.
Veritone Contact streamlines the process of collecting and reviewing demographic information during traffic or pedestrian stops. This solution simplifies the collection and review process as officers can submit one report, for multiple contacts, in two minutes or less.
By reducing the burden of stop data collection and review, Veritone Contact enables law enforcement agencies to allocate more time and resources to patrol and other critical tasks. Lengthy stops can affect community safety, so it’s imperative to get the officers back on patrol as quickly as possible.
3. Protecting Privacy and Building Trust With Redaction: Veritone Redact
Public safety agencies face a significant challenge in redacting sensitive information from audio and video evidence. While it is essential to comply with freedom of information laws (FOIA) and protect witnesses, redacting sensitive information can be expensive and time-consuming.
Veritone Redact is an AI-driven solution that helps expedite this process by detecting:
- Human heads and other forms of Personal Identifiable Information (PII)
- License plates
- Sensitive imagery and objects within a scene
After auto-detecting the selected information, this solution can redact them from audio and video evidence. Users can then download the redacted evidence with logs to support chain of custody requirements and share it with colleagues, public defenders, or other key stakeholders.
Developed specifically for public safety and justice agencies, cloud-based Veritone Redact, featured in the Police1 publication, significantly improves manual, time-intensive, frame-by-frame, redaction workflows. By automatically tracking sensitive imagery, the tool quickly tackles massive volumes of video content with incredible speed and efficiency. The Pasadena Police Department adopted Veritone Redact to accelerate their redaction workflows, increase efficiency, and cut down time while maintaining greater transparency with the public.
In addition to the application, Veritone also offers Redaction Managed Service which is the perfect level of help when you need your staff handling other important responsibilities, and our staff can redact your video files.
By helping LEAs manage redaction workloads, Veritone Redact and Redaction Managed Service also enable agencies to provide answers to the public through FOIA and media requests on a timely basis, increasing trust and transparency between the agency and their community.
4. Biometric Markers Beyond Facial Recognition: Veritone Tracker
The use of AI facial recognition technology raises concerns over privacy, accuracy, and bias as there have been instances of misidentification and potential misuse, leading to calls for regulation and ethical guidelines. Other ethical considerations include the risk of reinforcing systemic biases in law enforcement and exacerbating racial profiling.
Using Veritone Tracker, LEAs can quickly and easily track an individual’s movements through footage from multiple cameras, which can be particularly useful for identifying persons of interest, missing persons, and perpetrators. This allows them to identify important information such as whereabouts, build a timeline, and plan their next course of action without the need for using PII or face recognition.
Veritone Tracker’s AI engines identify human-like objects (HLOs) without using biometric markers and create profiles of individuals with similar features, allowing LEAs to set specific parameters and review POI’s quickly with confidence-based detection software. This ensures that they remain compliant with privacy laws while also protecting the privacy of all individuals involved and increasing public safety.
Enhancing Community Engagement With AI Technology
Community engagement is a critical element of police reform, as it helps to build trust, improve transparency, and ensure that law enforcement is accountable to the communities it serves. AI technology can play an important role in enhancing police community relations by analyzing and responding to feedback in real time and providing insights that can inform police culture, policy, and decision-making.
Improved Online Presence
One way that AI can be used to enhance community engagement is by analyzing and responding to feedback from social media and other online platforms. By monitoring social media activity and sentiment, LEAs gain valuable insights into community perceptions and concerns and can respond in a timely and intentional manner. Helping to build trust and transparency and ensuring that law enforcement is responsive to the needs and priorities of the communities it serves.
Offer Conversational Interfaces
Another way AI can enhance community engagement is through the use of chatbots and other conversational interfaces. By providing information and support to community members in a way that is accessible and convenient, LEAs and local police departments can strengthen their relationships with their community. Chatbots can be programmed to answer common questions, provide information about local resources and services, and even offer tips on crime prevention and safety in multiple languages or modes of accessibility.
These are only two examples of how AI technology can be a valuable tool for enhancing community engagement in policing. By quickly analyzing and responding to community feedback, and providing user-friendly, accessible interfaces for communication and support, LEAs can build stronger relationships with the communities they serve and ensure they are responsive to the needs and priorities of those communities. This is becoming increasingly important in an era of immediacy and the demand for prompt responses.
Ethical Considerations of AI in Policing
As AI becomes more prevalent in policing, there are ethical considerations that must be addressed to ensure its use is fair, just, and respectful of individual rights and liberties. Some key ethical considerations include:
- Balancing privacy and security concerns:
One of the primary ethical considerations of AI in policing is balancing privacy and security concerns—and rightly so. As AI systems collect and analyze more data on individuals, there is a risk that personal information could be misused or improperly shared. It’s crucial for LEAs to establish clear guidelines and protocols for the collection, storage, and use of data, and ensure these guidelines are aligned with fundamental principles of privacy and data protection.
- Addressing potential bias in AI systems:
Another key ethical consideration is addressing bias detection in AI solutions and tools. AI algorithms are only as objective and fair as the data that is used to train them, so there can be a risk that biases or prejudices could be built into these systems. It is important for LEAs to select high-quality AI solutions such as Veritone that use more diverse and representative data sets, implement safeguards to prevent discrimination, and regularly review and update the systems to ensure they are fair and equitable.
- Ensuring transparency and accountability in how AI is used:
LEAs must be transparent about the data they collect, the algorithms they use, and the decisions that are made based on this data in order to ensure openness and transparency. They must also be accountable for their actions, and be prepared to explain and justify their use of AI to the public. This may include establishing oversight mechanisms to monitor the use of AI, engaging in public consultation and dialogue, and regularly reviewing and evaluating the impact of AI on policing outcomes.
In conclusion, the ethical considerations of AI in policing are complex and multifaceted, but by taking these steps, LEAs can help ensure that their use of AI is consistent with fundamental principles of fairness, justice, and respect for individual rights and liberties.
Looking to the Future: Next Steps in AI-Driven Police Reform
The potential for AI to revolutionize law enforcement is significant, and there are many exciting opportunities to explore as we look to the future of AI-driven police reform. By harnessing the power of AI, law enforcement agencies can improve efficiency, accuracy, and effectiveness, while also promoting transparency and accountability.
One important next step in AI-driven police reform is to continue developing ethical and responsible AI solutions. As we have seen, AI systems can be vulnerable to bias and discrimination, and it is important to ensure that these systems are designed and used in a way that is consistent with fundamental principles of fairness, justice, and respect for individual rights and liberties. This includes continuing to develop more sophisticated algorithms that can detect and mitigate bias, establishing clear guidelines and protocols for the use of AI in law enforcement, and ensuring that the public is engaged and informed about how AI is being used.
Another next step should be to foster collaborative efforts between law enforcement, AI companies, and communities. By working together, these groups can share knowledge and expertise, build trust and transparency, and develop innovative solutions to complex challenges. This may include partnering with tech companies to develop new AI tools and platforms, engaging in community outreach and consultation to gather feedback and insights, and establishing cross-functional teams to ensure that AI solutions are aligned with all the prevalent needs and priorities.
Lastly, it’s important to recognize that AI-driven police reform is a dynamic and ongoing process and that there is and always will be room for improvement and innovation. LEAs must be open to new ideas and approaches, and must be willing to experiment, iterate, and learn from their experiences—and communities must also be open to observing how their local LEAs are actively making changes. By adopting a growth mindset and embracing a culture of continuous improvement, LEAs can ensure they remain at the forefront of ethical, AI-driven police reform and they are delivering the best possible outcomes for the communities they serve.
Conclusion: AI Is a Proven Tool in Police Reform
As we can see, police reform goes beyond what can be accomplished through technology, but the proper implementation and use of high-quality AI solutions can help LEAs address and fix issues that can harm their relationships with the people and communities that they serve.
AI solutions such as Veritone IDentify, Contact, Redact, and Tracker can help improve efficiency, accuracy, and accountability in law enforcement. Here are a few examples of how AI is being used in this context:
- Facial recognition technology, human-like object detection, and head detection can help police officers identify suspects and potential threats in real-time. By analyzing biometric features and matching them against a database of known faces, AI-powered systems can help police officers make faster and more accurate identifications, while also reducing the risk of errors or biases.
- Streamlining workflows during mandatory stops can increase officer accuracy, minimize human bias, and allow officers to work quickly and efficiently so they can spend less time on administrative work and more time protecting and serving their city.
- By automating the process of video and audio redaction to obscure PII from evidence and protect the privacy of individuals involved in cases, LEAs can save time and resources while also ensuring that they are complying with privacy regulations and protecting individual rights.
- AI can also help LEAs complete administrative work faster and more accurately by automating routine tasks like data entry and report writing. This can reduce the workload for officers, enabling them to focus on more complex and high-priority tasks, and help improve overall efficiency in law enforcement while reducing the risk of errors and bias.
AI’s wide range of applications can help improve efficiency, accuracy, and accountability in law enforcement, all of which can help LEAs redirect more time, money, and energy into community efforts. By using AI solutions for mandatory stops, video redaction, human detection, and administrative work, LEAs can also reduce the risk of errors, biases, and human rights violations while also improving the quality and effectiveness of policing operations.
As technology continues to advance, we can expect to see even more innovative uses of AI in policing in the years to come. Reach out to learn more about Veritone IDentify, Veritone Contact, Veritone Redact, and Veritone Tracker today.