AI Arms Race Against Terrorism

In early June, 28 officers and experts from 11 countries gathered in Tunis to extract more than 108,000 facial images from jihadist propaganda and sort them with AI tools. When INTERPOL, the international police cooperation organisation, announced the results on 18 September, the tools had narrowed the pile to 6,362 usable images, and 126 foreign terrorist fighters had been identified. Operation Shams II was billed as the first operation of its kind.   Terrorist groups have rarely been technological pioneers, yet they have repeatedly proved to be capable adopters of tools built by others. AI, which now writes, translates, speaks, and generates images on demand, is the latest example, and governments are working to turn the same technology against the people using it. This is not a story of one side pulling ahead. Because AI is dual-use, meaning the same capability serves attackers and defenders, every advance by one side reshapes the options of the other.   The common assumption is that the winner will be whoever deploys the best tools first. However, that assumption overlooks how differently the two sides adapt. Terrorists move cheaply and largely in the information space, where failure costs them little. States move slowly, at high expense, and under legal and public scrutiny. Adapting faster therefore depends less on who adopts a tool first than on who can sustain its use where violence actually happens, without losing the trust that gives state action its authority. That is where the contest will be won or lost.