Security and Law Enforcement

AI ensures that national security and law enforcement teams are better able to respond to incidents, prevent threats, and investigate and analyze criminal activity.

Adopting AI to Boost Prevention, Preparedness, Recovery, and Relief

AI ensures that national security and law enforcement teams are better able to respond to incidents, prevent threats, and investigate and analyze criminal activity. But despite all these benefits, there is also strong public scrutiny to ensure that security and law enforcement measures don’t overstep on citizen privacy or incorporate bias. DataRobot’s Trusted AI platform and services ensure that law enforcement can continue its growth in AI adoption, while establishing guardrails for overstepping ethical limits and biases that could jeopardize the public’s trust.

Improve defensive capabilities with AI-enabled cybersecurity.

DataRobot is helping agencies understand how AI and machine learning can enhance their cybersecurity arsenal and how AI can help them find threats more quickly and accurately. Whether ingesting open-source data at scale or showing how abnormal network traffic can indicate adversary activity within a network, AI can predict whether a particular type of communication is associated with malware. In addition, AI-enabling, cyber intrusion detection can also quickly identify network threats and reduce data theft due to adversary exfiltration attacks.

Bolster disaster resilience by utilizing AI to strengthen disaster preparation, response, and recovery.

Disaster resilience is heavily dependent on information collection, analysis, and dissemination — all of which are areas where AI can bolster government and first responder team efforts. By leveraging AI, teams can be better equipped to forecast future and impending disasters in real time, assess damage in the aftermath, and predict and evaluate impacts. AI can be applied to assess the impact of natural disasters, using data on people and details about communities, such as the age or height of structures, the number of hospital beds, or the location of fire stations. By analyzing current data against historical data, AI can ultimately identify areas that are most likely to be vulnerable to certain events or predict how quickly a neighborhood can be evacuated from the path of a disaster. Looking at movements of people returning home in the aftermath of a disaster could shed light on areas where destruction was the greatest versus those areas that are still habitable. And AI can supplement sensor data to help predict fast-moving disaster events like forest fires. 

Safeguard individual rights and mitigate bias when using AI-enabled surveillance and pattern analysis.

Video and image analysis is typically used to obtain information regarding people, objects, and actions to support targeted surveillance and criminal investigations. However, the analysis of video and image information is very labor-intensive, requiring a significant investment in personnel with subject matter expertise. AI has the potential to be a permanent part of our public safety ecosystem, providing investigative assistance and acting as a “second pair of eyes” to increase the accuracy of expert human facial examiners and to triage data. While these “second pair of eyes” can certainly increase a team’s productivity, bias and ethics risks often become a critical concern. Because AI depends on pattern recognition, an AI model can learn trends from data that it shouldn’t use – like race, sex or age – leading to biased or unfair decisions that could jeopardize a citizen’s rights and privacy. DataRobot’s AI platform includes an impact assessment to identify how its decisions will affect people and to ensure that it aligns with an organization’s values. With a platform that embeds this proactive action, we help customers make decisions that are fairer, more ethical, and more trustworthy.

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