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Security professionals are under increasing pressure to reduce risk, accomplish their mission with limited resources and demonstrate ROI on security initiatives. Workplace violence and active shooter threats are commonplace, and security professionals are charged with protecting their executives, employees, places of work, public spaces and customers.
Most security-related technologies are narrowly focused on cyber security or hardening/surveillance solutions for physical security. In order to take a proactive approach, security professionals need modern software technology that is purpose-built for Protective Intelligence.
In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity.