The Department of Homeland Security is spending $40 million dollars to fund a “quantitative analysis” program for its Science and Technology Directorate. In a grant proposal published this month, DHS calls on colleges and universities to submit plans to support the Center for Homeland Security Quantitative Analysis.
According to the documents, grant winners will support “real-time decision making to address homeland security-related threats and hazards” by conducting research and developing “mission-relevant science and technology.”
“It is DHS’s intent to produce new capabilities and work with partners and stakeholders at all levels to test these capabilities in operational and strategic settings, and then take steps to make these solutions available and useful to agencies at all levels.”
If it sounds Orwellian, it’s because it is Orwellian. It’s no secret that DHS faces more challenges than it can handle. When we talk about intelligence and complex problems, I often bring up efficiency. In order to compete, organizations have to be efficient, otherwise they fall behind, and inefficiencies are a great contributor to falling behind. Analysis is nearly always the bottleneck in the flow of information to decision makers. Organizations can collect massive amounts of data, but it’s rarely useful until the information is evaluated by an analyst. A shortage of analysts typically leads to a shortage of analysis. When decision makers don’t have evaluated information and insight into the data — what we can call “intelligence” — they often make poor decisions.
The Center for Homeland Security Quantitative Analysis (CHSQA) shall develop the next generation of mathematical, computational, and statistical theories, as well as algorithms, methods, and tools to advance the quantitative analysis capabilities [of DHS].
For the past ten years, organizations have been realizing that the solution to that bottleneck is Big Data analytics — or “quantitative analysis”. The DHS Quantitative Analysis program is a big data approach to problem-solving that requires massive amounts of data (open source information, especially social media) being fed into databases for storage, retrieval, and analysis. Algorithms will scan and organize data, find patterns, and then direct analysts to high priority data points. This greatly speeds up the analysis process — removing the traditional bottleneck — because analysts no longer have to sift through all the collected data. In other words, this technology will help sift through the haystack and deliver some needles to the analyst.
There’s no doubt that DHS is becoming a domestic intelligence agency. Whatever reason DHS was created — ostensibly to find terrorists and keep the homeland secure — it’s taking steps that should give us pause. Does DHS really need these capabilities?
But perhaps the most troubling part of this project is that DHS asks:
At what point do private individuals accept biometrics and data collection as an accepted social process?
Biometrics is going to have a profound and growing impact on American society, as foreshadowed by the desire of DHS to normalize biometric collection of Americans. I should know. My last assignment was a Senior Analyst on the Defense Department’s Biometrics Intelligence Program where we tracked down insurgents in Iraq and Afghanistan.
By collecting location information (via cell phones, for instance), social media posts and other open source information, along with biometrics, DHS is going to be able to build a pattern of life analysis for any member of the public. (To see part of what that looks like, see SPACE Analysis.) America is entering a Brave New World.
Grant proposals for the Center of Excellence for Homeland Security Quantitative Analysis must be submitted by November. You can download the Grant Opportunity here.