This case study examines how one Artificial Intelligence (AI) security software team made the decision to abandon a core feature of the product – an interactive Knowledge Graph visualization deemed by prospective buyers as “cool,” “impressive,” and “complex” – in favor of one that its users – security analysts – found easier to use and interpret. Guided by the results of ethnographic and user research, the QRadar Advisor with Watson team created a new knowledge graph (KG) visualization more aligned with how security analysts actually investigate potential security threats than evocative of AI and “the way that the internet works.” This new feature will be released in Q1 2020 by IBM and has been adopted as a component in IBM’s open-source design system. In addition, it is currently being reviewed by IBM as a patent application submission. The commitment of IBM and the team to replace a foundational AI component with one that better aligns to the mental models and practices of its...
University of North Texas MOLLY SHADE
University of North Texas
Information Technology (IT) professionals are racing to keep up with cyber-security threats in the workplace. But, as any cyber-security expert will tell you, security technology is only as good as the people who use it. And, people are a mystery to most cyber-security professionals making them the weak link for security interventions in organizations. To broadly impact current cyber-security awareness, interventions and education, it is crucial to understand how security is understood and applied by the users of technology. Thus, it is no surprise that more and more cyber-security studies are focusing on the individual employee to understand computer-user risk mediation. However, users and their actions do not exist in a vacuum, and their perceptions and subsequent behaviors regarding security risk are shaped by a vast array of beliefs, social relations and workplace practices. This paper reports on a fresh theoretical approach to cyber-security as a group...