Pentagon’s Secret Pre-Crime Program To Know Your Thoughts, Predict Your Future

The US Department of Defense (DoD) wants contractors to mine your social media posts to develop new ways for the US government to infer what you’re really thinking and feeling — and to predict what you’ll do next.

Pentagon documents released over the last few months identify ongoing classified research in this area that the federal government plans to expand, by investing millions more dollars.

The unclassified documents, which call on external scientists, institutions and companies to submit proposals for research projects, not only catalogue how far US military capabilities have come, but also reveal the Pentagon’s goals: building the US intelligence community’s capacity to forecast population behavior at home and abroad, especially groups involved in political activism.

They throw light on the extent to which the Pentagon’s classified pre-crime R&D has advanced, and how the US military intends to deploy it in operations around the world.

Could your social media signature reveal your innermost thoughts?

A new Funding Opportunity Announcement document issued by the DoD’s Office of Naval Research (ONR) calls for research proposals on how mining social media can provide insight on people’s real thoughts, emotions and beliefs, and thereby facilitate predictions of behavior.

The research for Fiscal Year 2016 is part of the Pentagon’s Multidisciplinary Research Program of the University Research Initiative (MURI), which was initiated over 25 years ago, regularly producing what the DoD describes as “significant scientific breakthroughs with far reaching consequences to the fields of science, economic growth, and revolutionary new military technologies.”

The document calls for new work “to understand latent communication among small groups.” Social meaning comes not just from “the manifest content of communication (i.e., literal information), but also from latent content — how language is structured and used, as well as how communicators address each other, e.g., through non-verbal means — gestures, head nods, body position, and the dynamics in communication patterns.”

The Pentagon wants to understand not just what we say, but what is “latent” in what we say: “Subtle interactions such as deception and reading between the lines, or tacit understanding between communicators, relative societal position or relationship between communicators, is less about what is said and more about what is latent.”

All this, it is imagined, can be derived from examining social media, using new techniques from the social and behavioral sciences.

The Pentagon wants to:

“… recognize/predict social contexts, relationships, networks, and intentions from social media, taking into account non-verbal communication such as gestures, micro-expressions, posture, and latent semantics of text and speech.”

By understanding latent communication, the Pentagon hopes to develop insight into “the links between actors, their intentions, and context for use of latent signals for group activity.” The idea is to create:

“… algorithms for prediction and collection of latent signals and their use in predicting social information.”

These algorithms also need to “accurately detect key features of speech linked to these structural patterns (e.g., humor, metaphor, emotion, language innovations) and subtle non-verbal elements of communication (e.g., pitch, posture, gesture) from text, audio, and visual media.”

The direct military applications of this sort of information can be gleaned from the background of the administrator of this new research program, Dr. Purush Iyer, who is Division chief of Network Sciences at the US Army Research Laboratory (USARL).

Among the goals of Dr. Iyer’s research at the US Army are expanding “Intelligent Networks” which can “augment human decision makers with enhanced-embedded battlefield intelligence that will provide them with tools for creating necessary situational awareness, reconnaissance, and decision making to decisively defeat any future adversarial threats.”

Creeping police state

The allure of co-opting Big Data to enhance domestic policing is already picking up steam in the US and UK.

In the US, an unknown number of police authorities are already piloting a software called ‘Beware’, which analyses people’s social media activity, property records, the records of friends, family or associates, among other data, to assign suspects a so-called “threat-score.”

That “threat-score” can then be used by police to pre-judge if a suspect is going to be dangerous, and to adapt their approach accordingly.

Given the police’s discriminatory track record with shootings of unarmed black people skyrocketing, the extent to which such ‘Minority Report’-style policing could backfire by justifying more discriminatory policing is alarming.

In the UK, Home Secretary Theresa May just last week told the Police ICT Suppliers Summit that polices forces should use predictive analytics to “identify those most at risk of crime, locations most likely to see crimes committed, patterns of suspicious activity that may merit investigation and to target their resources most effectively against the greatest threats.”

Noting that the police have yet to catch up with the “vast quantities of data” being generated by citizens, she complained: “Forces have not yet begun to explore the crime prevention opportunities that data offers.”

In reality, the shift to predictive policing in the UK is well underway, with Greater Manchester, Kent, West Midlands, West Yorkshire and London’s Metropolitan Police having undertaken trials of a software known as “PredPol.”

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