The Department of Defense is poised to spend nearly $1 billion on artificial intelligence in the next year.<\/p>\n\n\n\n
The Pentagon\u2019s proposed budget for fiscal 2020 includes some $927 million for AI, as well as machine learning, according to Ainikki Riikonen, a research assistant for the Technology and National Security Program at the Center for a New American Security.<\/p>\n\n\n\n
This includes $208 million earmarked for the Joint Artificial Intelligence Center, which was created in 2018. The Center\u2019s initial efforts have delivered \u201ca very mature, insightful high-level view\u201d of issues surrounding AI, said Ian McCulloh, chief data scientist at Accenture Federal Services.<\/p>\n\n\n\n
AI encompasses hardware, software, people and processes. With nearly a $1 billion bankroll, Defense Department leaders and the intelligence community are now looking for the best ways to leverage this emerging capability most effectively.<\/p>\n\n\n\n
Starting point<\/b><\/p>\n\n\n\n
A deep dive into the numbers shows an early emphasis on basic research. The Defense Advanced Research Projects Agency\u2019s budget request includes $138 million for advanced land systems technology, up from $109 million in fiscal 2019. That program includes research into urban reconnaissance and AI-driven subterranean operations. DARPA\u2019s budget also includes $10 million for the Highly Networked Dissemination of Relevant Data Project, a situational awareness tool, as well as $161 million for the AI Human Machine Symbiosis Project, up from $97 million. <\/p>\n\n\n\n
\u201cThat\u2019s all about creating systems and people that actually understand each other,\u201d Riikonen said.<\/p>\n\n\n\n
These foundational research efforts could yield practical results for the war fighter. But before the Pentagon can make use of AI\u2019s analytic and predictive powers, military leaders will need to ensure they have the underlying infrastructure in place.<\/p>\n\n\n\n
\u201cThere\u2019s so much data available to the military, but it\u2019s stored all over the place, and rarely in a format that is easily transferrable into an algorithm,\u201d said Todd Probert, vice president for Raytheon Intelligence, Information and Services. \u201cIf the military wants to set itself up for success, they should focus on data curation, labeling and cleaning, as well as recruiting and training the data scientists necessary to make use of it.\u201d<\/p>\n\n\n\n
Good data requires good technical people, and those aren\u2019t easy to come by. \u201cTalent isn\u2019t cheap and it\u2019s in high demand. The government will be competing directly with industry for a very small pool of people,\u201d Probert said. This indicates a need for early investments on talented professionals. <\/p>\n\n\n\n
From there, defense can begin to look at funding specific projects and programs that take advantage of AI\u2019s capabilities.<\/p>\n\n\n\n
AI applications<\/b><\/p>\n\n\n\n
The Pentagon might begin by considering the potential for AI as a weapon of war. \u201cWe are only starting to scratch the surface on the impact of AI and how it can be manipulated by adversaries for nefarious purposes,\u201d said Rahul Kashyap, president and chief executive of network traffic analysis company Awake Security. <\/p>\n\n\n\n
Machine learning might help military systems be more effective, but the reliance on data could also make those systems vulnerable to new kinds of attack. \u201cWith the adversarial use of AI, there are already discussions about ways in which data we have come to rely on may be poisoned to trick the machine inputs and algorithms,\u201d Kashyap said.<\/p>\n\n\n\n
Some experts suggest that any early investments should address this potential risk, building in a defensive capability as part of AI\u2019s foundational layer.<\/p>\n\n\n\n
Others say that the low-hanging fruit lies in the military\u2019s ability to leverage AI in support of mundane, but nonetheless critical, tasks.<\/p>\n\n\n\n
In the near term, for example, AI spending could help provide transparency around inventory and supply chain management. <\/p>\n\n\n\n
\u201cAI could help manage the complexity behind the connectivity and flow between transportation, people, facilities and supplies including equipment, spare parts and fuel in a predictive manner,\u201d said Brigham Bechtel, chief strategy officer for intelligence and defense at big data applications firm MarkLogic.<\/p>\n\n\n\n
In this scenario, AI would leverage existing data on materiel availability and equipment performance to drive preventative maintenance, as well as parts procurement \u2014 \u201ckeeping records of millions of screws, wire couplers, and even tank gun barrels to support scaling to operational demand,\u201d Bechtel said. That\u2019s a task for which machine-scale intelligence is ideally suited.<\/p>\n\n\n\n
In the realm of ISR, some industry representatives point to \u201copen-source intelligence\u201d (such as social media) as a prime target for AI investments. <\/p>\n\n\n\n
Sources such as Facebook and Twitter contain \u201csignificant intelligence that is beyond the scale of humans or classic computation analysis,\u201d said Chad Steelberg, chief executive and chairman of AI-based analysis company Veritone.<\/p>\n\n\n\n
As in logistics, open-source intelligence offers ample data in a space where machine-scale analytics could have a deep impact. \u201cThe war of ideas, ranging from ISIS recruiting to state-sponsored propaganda, is the most dangerous battlefronts today,\u201d Steelberg said. \u201cWith the source of ideas now being influenced by AI, the countries that harness this new weapon most effectively will have a distinct advantage.\u201d<\/p>\n\n\n\n
The intelligence community also could benefit from AI\u2019s analytic powers to manage the sheer volume of sensor data in the field.<\/p>\n\n\n\n
\u201cIs the analyst overwhelmed with data? If so, AI has the potential to help,\u201d said Graham Gilmer, a principal in Booz Allen Hamilton\u2019s analytics business. \u201cGenerating a more robust search capability, fusing data from multiple sources, and generally doing the heavy lifting to cue the analyst are the most immediate applications.\u201d<\/p>\n\n\n\n
In addition to addressing external data, the intelligence community could score an early win by building AI models that scrutinize conversations amongst analysts themselves.<\/p>\n\n\n\n
\u201cIn an ISR suite there can be as many as 15 chat rooms going at any time, with info coming in from various units and intelligence agencies,\u201d Probert said. \u201cThat\u2019s too much data and crosstalk for a person to manage, so information is inevitably going to be missed. We need machine learning tools that can flag critical data and alert analysts to what\u2019s important.\u201d<\/p>\n\n\n\n
All these represent valid points of inquiry and the Pentagon likely will pursue diverse variations on these themes. In the short term, though, analysts predict AI will mostly be about robots.<\/p>\n\n\n\n
\u201cAdvanced automation is the fastest growing category in AI, with the rise of unmanned systems,\u201d Riikonen said, noting it would be a natural evolution for the military to leverage private sector learning to utilize AI in support of autonomous systems. \u201cThat fits very well with the overall U.S. defense strategy, which is all about having more of these autonomous systems that support war fighters in denied and contested environments.\u201d<\/p>\n\n\n\n
In order to achieve those goals, the Defense Department may have to adopt a new way of investing in technology.<\/p>\n\n\n\n
Rather than a single development effort that leads to a completed product, however, AI requires an iterative process in which the computers learn over time.<\/p>\n\n\n\n
\u201cYou do small chunks, you do small bites,\u201d said Paul Johnson, Grant Thornton public sector senior strategic adviser for the defense and intelligence community.<\/p>\n\n\n\n
In this light, AI investment will require not just algorithmic development, but investment in organizational change, to spur deep interactions between stakeholders. \u201cWe need to get the coders in the same room with the end users and start having the conversation about the art of the possible,\u201d Johnson said. \u201cYou have to have that conversation early, often and repeatedly, for the coders to understand what they need to do.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"
With nearly a $1 billion bankroll, Defense Department leaders and the intelligence community are looking for the best ways to leverage this emerging capability most effectively.<\/p>\n","protected":false},"author":7,"featured_media":32123,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_yoast_wpseo_meta-robots-noindex":"","_yoast_wpseo_meta-robots-nofollow":"","_yoast_wpseo_canonical":"","_acf":"","_yoast_wpseo_primary_category":6,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","_smg_distribution_targets":[]},"categories":[6,106,29,32],"tags":[],"coauthors":[2063],"class_list":["post-11262","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-daily-brief","category-home","category-newsletters"],"acf":{"subheadline":"","legacy_arc_id":"BGO7SHC37FCAXHNA36CQ2ZHRPA","arc_canonical_url":"\/artificial-intelligence\/2019\/08\/16\/whats-the-best-way-for-the-pentagon-to-invest-in-artificial-intelligence\/","remove_feature_photo":false,"is_sponsored":false,"subtype":"","redirect_url":"","disable_inline_ads":false,"native_logo_pretext":"Presented By:"},"yoast_head":"\n