| Abstract: | In the age of ‘Big Data’, the potential value of open-source information for intelligence-related purposes is widely recognised. Of late, progress in this space has increasingly become associated with software that can expand our ability to gather, filter, interrelate and manipulate data through automated processes. The trend towards automation is both innovative and necessary. However, techno-centric efforts to replace human analysts with finely crafted algorithms across the board, from collection to synthesis and analysis of information, risk limiting the potential of OSINT rather than increasing its scope and impact. Effective OSINT systems must be carefully designed to facilitate complementarity, exploit the strengths, and mitigate the weaknesses of both human analysts and software solutions, obtaining the best contribution from both. Drawing on insights from the field of cognitive engineering, this article considers at a conceptual level how this might be achieved. |
