Watch those tweets, and Facebook anti-government rants folks. Quite possibly in the near future, a brainless killer robot may bust down your door and kill your ass for the words you write and speak.

self aware’ killer robot army fueled by social media 2

Official US defence and NATO documents confirm that autonomous weapon systems will kill targets, including civilians, based on tweets, Facebook blogs and Instagram postings.

This is not a conspiracy, but facts based on an unclassified 2016 Department of Defense (DoD) document, the Human Systems Roadmap Review, which shows the US military plans to create artificially intelligent (AI) autonomous weapon systems, that will use Big Data such as predictive social media analytics to make decisions on lethal force with minimal human involvement.

self aware’ killer robot army reports:

The 2016 human systems roadmap explains that the Pentagon’s “vision” is to use “effective engagement with the dynamic human terrain to make better courses of action and predict human responses to our actions” based on “predictive analytics for multi-source data.”

self aware’ killer robot army fueled by social media

In a slide entitled, ‘Exploiting Social Data, Dominating Human Terrain, Effective Engagement,’ the document provides further detail on the Pentagon’s goals:

“Effectively evaluate/engage social influence groups in the op-environment to understand and exploit support, threats, and vulnerabilities throughout the conflict space. Master the new information environment with capability to exploit new data sources rapidly.”

The Pentagon wants to draw on massive repositories of open source data that can support “predictive, autonomous analytics to forecast and mitigate human threats and events.”

Medium further reports:

The document refers to the use of social media data to forecast future threats and, on this basis, automatically develop recommendations for a “course of action” (CoA).

Under the title ‘Weak Signal Analysis & Social Network Analysis for Threat Forecasting’, the Pentagon highlights the need to:

“Develop real-time understanding of uncertain context with low-cost tools that are easy to train, reduce analyst workload, and inform COA [course of action] selection/analysis.”

In other words, the human input into the development of course of action “selection/analysis” must be increasingly reduced, and replaced with automated predictive analytical models that draw extensively on social media data.

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