"Insider Threat" is a major area of risk for many organisations, in both the government and commercial spheres. Employees, contract staff and suppliers are often in a strong position to perpetrate fraud, steal secret information or intellectual property, or sabotage computer systems, and effectively evade detection for long periods. After-the-fact investigation is often challenging and labour intensive, and early prediction and positive mitigation, which may be far more effective, is even more difficult to automate. To trained eyes, text sources like chat and email often contain signals that insiders are on a path to hostile action. However, making use of these sources in ways that respect individual rights and improve trust is as much of a challenge as the technical one of extracting the signal. Mr. Stewart outlines the role and limitations of text analysis in the automation of predicting insider threat by discussing key results in the area of intent detection, and argues that (given the projected state of the art) many organizations might achieve greater harm reduction by developing or adopting what IBM has called "Systems of Engagement".