Artificial intelligence (AI) is a rapidly evolving technology that has the potential to revolutionize various aspects of police work, from enhancing situational awareness and decision making in the field to streamlining evidence collection and analysis to improving data security and privacy. AI can also help law enforcement agencies cope with the increasing volume and complexity of digital evidence, which poses significant challenges for storage, management and use.
However, to fully leverage the benefits of AI, law enforcement agencies need to adopt digital evidence management systems (DEMS) that can support the current and future applications of AI and equip their officers with rugged, powerful and sophisticated devices that can handle the daily demands of police work and the back-end data storage and security required for today’s sophisticated applications.
How AI and generative AI are impacting police operations
AI is the ability of machines or software to perform tasks that normally require human intelligence, such as recognition, reasoning, learning and decision making. Generative AI is a subset of AI that can create new content or data, such as images, videos, text or audio, based on existing data or models. Both AI and generative AI can have various applications for police operations in the field, such as:
- Facial recognition: AI can help identify suspects, victims or missing persons by comparing their faces with databases of images, such as mugshots, driver’s licenses or social media profiles. Generative AI can also help create realistic facial composites based on witness descriptions or sketches or enhance low-quality images or videos to improve identification.
- Speech recognition and translation: AI can help transcribe and translate speech in real time, enabling officers to communicate with people who speak different languages, or generate accurate and timely reports based on voice recordings. Generative AI can also help synthesize speech and generate realistic voice samples for various purposes, such as voice biometrics, voice cloning or voice phishing.
- Object detection and recognition: AI can help detect and recognize objects in images or videos, such as weapons, vehicles, license plates or evidence. This can help officers locate and track suspects, vehicles or items of interest and automate the process of evidence collection and documentation. Generative AI can also help create realistic images or videos of objects based on descriptions or manipulate or enhance existing images or videos to improve detection and recognition.
- Behavior analysis and prediction: AI can help analyze and predict human behavior based on various factors, such as facial expressions, body language, speech patterns and biometric data. This can help officers assess the risk level of a situation or anticipate the actions or intentions of a person. Generative AI can also help create realistic simulations or scenarios based on behavior models and generate synthetic data for training and testing purposes.
- Decision support and optimization: AI can help provide officers with relevant information, suggestions and recommendations based on various data sources, such as databases, sensors and social media. This can help officers make informed and timely decisions and optimize their actions or strategies. Generative AI can also help generate alternative solutions and outcomes based on different criteria or constraints and evaluate the effectiveness or impact of different decisions and actions.
WHY LAW ENFORCEMENT AGENCIES NEED A DEMS
Digital evidence is any information or data that is stored or transmitted in digital form and can be used in an investigation or prosecution. Digital evidence can include images, videos, audio, text and metadata from various sources, such as body-worn cameras, dash cams, drones, smartphones, computers and social media. Digital evidence can provide valuable insights and information for law enforcement agencies, but it also poses significant challenges for storage, management and use. Some of these challenges are:
- Volume and variety: The amount and diversity of digital evidence is increasing exponentially. This creates a huge demand for storage space, bandwidth and processing power, as well as a need for standardization and interoperability among different formats and systems.
- Quality and integrity: The quality and integrity of digital evidence can vary depending on the source, device or method of capture, transmission or storage. This can affect the accuracy, reliability and admissibility of digital evidence, as well as the possibility of tampering, alteration or deletion. Therefore, there is a need for quality assurance, verification and authentication of digital evidence, as well as a secure chain of custody and audit trail.
- Accessibility and usability: The accessibility and usability of digital evidence can depend on the availability, compatibility and functionality of the software, hardware or network used to access and share it. This can affect the efficiency, effectiveness and collaboration of law enforcement agencies, as well as the privacy, security and rights of the people involved. Therefore, there is a need for easy, fast and secure access, retrieval and sharing of digital evidence, as well as a user-friendly and intuitive interface and tools.
To address these challenges, law enforcement agencies need to move to digital evidence management systems that can support the current and future applications of AI. A DEMS is a software platform that can store, manage and use digital evidence in a centralized, standardized and secure way. A DEMS can offer various benefits for law enforcement agencies, such as:
- Reducing the cost and complexity of storing and managing digital evidence by using cloud-based or hybrid solutions that can scale up or down.
- Legacy solutions, which store digital evidence on local servers or devices, are expensive, inflexible and hard to maintain. They also have security risks, such as data loss, theft and tampering, especially if the devices are not encrypted. Moreover, legacy solutions may not cope with the growing amount and diversity of digital evidence and demand for AI applications that can process and analyze it. Further physical demands of electricity, environment, climate control and square footage in facilities are often unaccounted for in the expense matrix.
- A hybrid solution, which stores some digital evidence on premises and some in the cloud, can have some benefits over a purely legacy solution. For example, a hybrid solution can let police agencies store sensitive or confidential digital evidence on premises and less sensitive or public digital evidence in the cloud. This can lower storage costs and security risks and improve the performance and scalability of the system. A hybrid solution can also give more flexibility and control over the data governance and compliance policies and the choice of cloud service providers and features.
However, a hybrid solution can also have some drawbacks, such as the difficulty and inconsistency of managing different systems and platforms, possible compatibility and interoperability issues between legacy and cloud solutions, and reliance on an internet connection. Therefore, a hybrid solution may not be ideal for all law enforcement agencies, especially those that have limited resources, expertise or bandwidth to implement and maintain it.
Ultimately, a cloud-based solution, which stores all digital evidence in the cloud, can be the best and safest option for law enforcement agencies, even if it has a higher initial cost. A cloud-based solution can provide several advantages over legacy and hybrid solutions, such as:
- Lower maintenance and operational costs, as the cloud service provider takes care of the system and the data.
- Higher scalability and elasticity, as the system and data can be easily changed according to the demand and budget.
- Greater accessibility and usability, as the system and data can be accessed from any device, location or network with an internet connection.
- Enhanced quality and integrity, as the system and data are protected by encryption and authentication mechanisms and monitored by audit logs and alerts.
- Increased value and impact, as the system and data can use the advanced AI features and capabilities the cloud service provider can offer, such as image recognition, face detection, object identification, speech transcription, natural language processing, sentiment analysis and so on.
- Continuity of operations regardless of catastrophic incidents.
Therefore, law enforcement agencies should consider moving to a cloud-based digital evidence management system, as it can offer the best performance, security and functionality for their needs. A cloud-based solution can also enable law enforcement agencies to fully use the potential of AI to improve the collection, management and use of digital evidence in their operations by:
- Improving the quality and integrity of digital evidence by using AI-based features that can enhance, verify and authenticate digital evidence, as well as ensuring a secure chain of custody and audit trail.
- Enhancing the accessibility and usability of digital evidence by using AI-based features that can analyze, categorize and index it, as well as providing easy, fast and secure access, retrieval and sharingand a user-friendly and intuitive interface and tools.
- Increasing the value and impact of digital evidence by using AI-based features that can provide insights, suggestions or recommendations based on it, as well as enabling collaboration and integration with other systems and stakeholders.
What factors to consider when choosing technology To fully leverage the benefits of AI and a DEMS, law enforcement agencies need to equip their officers with rugged, powerful and sophisticated devices that can handle the daily demands of police work and the back-end data storage and security required for today’s sophisticated applications. Some factors to consider when choosing technology to accommodate the current and future applications of AI are:
- Durability and reliability: The devices should be able to withstand the harsh and unpredictable conditions of the field, such as dust, water, shock, vibration and extreme temperatures. They should also have a long battery life, robust design and high-quality display and camera.
- Performance and functionality: The devices should be able to run the latest and most advanced AI-based applications, such as facial recognition (it doesn’t mean you’ll use it yet, but plan for the future), speech recognition, object detection and behavior analysis. They should also have high processing power, a large storage capacity and fast and stable connectivity.
- Security and privacy: The devices should be able to protect the data and information stored or transmitted on them, as well as the identity and rights of the users and people involved. They should also have strong encryption, a biometric authentication and a remote wipe or lock feature.
- Compatibility and interoperability: The devices should be able to work seamlessly with the DEMS and other systems and platforms used by police agencies, such as databases, sensors and social media. They should also have a standard and open architecture and a flexible and customizable configuration.
Plan for the future now
AI is a rapidly evolving technology that has the potential to revolutionize various aspects of police work, from enhancing situational awareness and decision making in the field to streamlining evidence collection and analysis to improving data security and privacy. However, to fully leverage the benefits of AI, law enforcement agencies need to adopt digital evidence management systems that can support the current and future applications of AI and equip their officers with rugged, powerful and sophisticated devices that can handle the daily demands of police work and the back-end data storage and security required for today’s sophisticated applications. By doing so, law enforcement agencies can futureproof their mobile and on-premises computer systems to take advantage of AI-enabled applications and improve their efficiency, effectiveness and impact in the field.
