Meet the Future-Makers

Question: Why did Elon Musk just change his Twitter profile photo? I notice he’s now seeming to evoke James Bond or Dr. Evil:

twitter photos, Elon v Elon

I’m not certain, but I think I know the answer why. Read on…

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“Prediction is very difficult, especially about the future.”

      – Niels Bohr, winner of the 1922 Nobel Prize for Physics

“History will be kind to me for I intend to write it.”

      – Winston Churchill

If you take those two quotations to heart, you might decide to forego the difficulty of predicting the future, instead aiming to bend the future’s story arc yourself. In a nutshell, that’s what R&D is all about: making the future.

Who makes the future for the intelligence community? Who has more influence on the future technologies which intelligence professionals will use: government R&D specialists, or private-sector industry?

On the one hand, commercial industry’s R&D efforts are pulled by billions of invisible consumer hands around the globe, driving rapid innovation and ensuring that bold bets can be rewarded in the marketplace. Recent examples are things like Web search, mobile phones and tablets, and SpaceX launches.

To be fair, though, the US IC and DoD have the ability to focus intently on specific needs, with billions of dollars if necessary, and to drive exotic game-changing R&D for esoteric mission use. During my time in government I saw great recent successes which are of course classified, but they exist.

If you want to explore both sides and you have a Top Secret clearance, you’re in luck, because you can attend what I expect will be an extraordinary gathering of Future-Makers from inside and outside the IC, at next month’s AFCEA Spring Intelligence Symposium.

Spring IntellLast fall, the organizing committee for this annual classified Symposium began our planning on topics and participants. We decided that this year’s overall theme had to be “IC Research & Development” – and we decided to depart from tradition and bring together an unprecedented array of senior leaders from inside and outside, to explore the path forward for IC innovation and change.

The May 20-21 Symposium, held at NGA’s Headquarters, will be a one-of-a-kind event designed to set the tone and agenda for billions of dollars in IC investment.  On the government front, attendees will witness the roll-out of the new (classified) Science & Technology 2015-2019 Roadmap; see this article for some background on that. Attendees will also meet and hear R&D leaders from all major IC agencies, including:

  • Dr. David Honey, Director of Science and Technology, ODNI
  • Dr. Peter Highnam, Director, Intelligence Advanced Research Projects Activity (IARPA)
  • Glenn Gaffney, Deputy Director for Science & Technology, CIA
  • Stephanie O’Sullivan, Principal Deputy Director of National Intelligence
  • Dr. Greg Treverton, Chairman, National Intelligence Council
  • The IC’s functional managers for SIGINT, MASINT, GEOINT, HUMINT, OSINT, and Space

Meanwhile from the private sector, we’ll have:

  • Elon Musk, CEO/CTO of SpaceX, CEO/Chief Product Architect of Tesla Motors, CEO of SolarCity, Co-founder of PayPal
  • Gilman Louie, Partner at Alsop Louie Venture Capital, former CEO of In-Q-Tel
  • Bill Kiczuk, Raytheon VP, CTO, and Senior Principal Engineering Fellow
  • Zach Lemnios, IBM VP for Research Strategy and Worldwide Operations
  • Pres Winter, Oracle VP, National Security Group

When I first proposed that we invite an array of “outside” future-makers to balance the government discussion with a different perspective, I said to my colleagues on the planning committee, “Wouldn’t it be awesome to get someone like Elon Musk…”

Well, we did, and next month I’ll be welcoming him on stage.

These are dark and challenging times in international security, but for scientists, technologists, and engineers, there’s never been a more exciting time – and like them, intelligence professionals should stretch their horizons.

I’m looking forward to the conference… and here’s your link to register to join us.

PS: Just to whet your appetite: new video of this week’s SpaceX revolutionary Falcon9 first-stage landing attempt on a drone barge at sea – nearly made it, very exciting:

Debating Big Data for Intelligence

I’m always afraid of engaging in a “battle of wits” only half-armed.  So I usually choose my debate opponents judiciously.

Unfortunately, I recently had a contest thrust upon me with a superior foe: my friend Mark Lowenthal, Ph.D. from Harvard, an intelligence community graybeard (literally!) and former Assistant Director of Central Intelligence (ADCI) for Analysis and Production, Vice Chairman of the National Intelligence Council – and as if that weren’t enough, a past national Jeopardy! “Tournament of Champions” winner.

As we both sit on the AFCEA Intelligence Committee and have also collaborated on a few small projects, Mark and I have had occasion to explore one another’s biases and beliefs about the role of technology in the business of intelligence. We’ve had several voluble but collegial debates about that topic, in long-winded email threads and over grubby lunches. Now, the debate has spilled onto the pages of SIGNAL Magazine, which serves as something of a house journal for the defense and intelligence extended communities.

SIGNAL Editor Bob Ackerman suggested a “Point/Counterpoint” short debate on the topic: “Is Big Data the Way Ahead for Intelligence?” Our pieces are side-by-side in the new October issue, and are available here on the magazine’s site.

Mark did an excellent job of marshalling the skeptic’s view on Big Data, under the not-so-equivocal title, Another Overhyped Fad.”  Below you will find an early draft of my own piece, an edited version of which is published under the title A Longtime Tool of the Community”:

Visit the National Cryptologic Museum in Ft. Meade, Maryland, and you’ll see three large-machine displays, labeled HARVEST and TRACTOR, TELLMAN and RISSMAN, and the mighty Cray XMP-24. They’re credited with helping win the Cold War, from the 1950s through the end of the 1980s. In fact, they are pioneering big-data computers.

Here’s a secret: the Intelligence Community has necessarily been a pioneer in “big data” since inception – both our modern IC and the science of big data were conceived during the decade after the Second World War. The IC and big-data science have always intertwined because of their shared goal: producing and refining information describing the world around us, for important and utilitarian purposes

What do modern intelligence agencies run on? They are internal combustion engines burning pipelines of data, and the more fuel they burn the better their mileage. Analysts and decisionmakers are the drivers of these vast engines, but to keep them from hoofing it, we need big data.

Let’s stipulate that today’s big-data mantra is overhyped. Too many technology vendors are busily rebranding storage or analytics as “big data systems” under the gun from their marketing departments. That caricature is, rightly, derided by both IT cognoscenti and non-techie analysts.

I personally get the disdain for machines, as I had the archetypal humanities background and was once a leather-elbow-patched tweed-jacketed Kremlinologist, reading newspapers and HUMINT for my data. I stared into space a lot, pondering the Chernenko-Gorbachev transition. Yet as Silicon Valley’s information revolution transformed modern business, media, and social behavior across the globe, I learned to keep up – and so has the IC. 

Twitter may be new, but the IC is no Johnny-come-lately in big data on foreign targets.  US Government funding of computing research in the 1940s and ‘50s stretched from World War II’s radar/countermeasures battles to the elemental ELINT and SIGINT research at Stanford and MIT, leading to the U-2 and OXCART (ELINT/IMINT platforms) and the Sunnyvale roots of NRO.

In all this effort to analyze massive observational traces and electronic signatures, big data was the goal and the bounty.

War planning and peacetime collection were built on collection of ever-more-massive amounts of foreign data from technical platforms – telling the US what the Soviets could and couldn’t do, and therefore where we should and shouldn’t fly, or aim, or collect. And all along, the development of analog and then digital computers to answer those questions, from Vannevar Bush through George Bush, was fortified by massive government investment in big-data technology for military and intelligence applications.

In today’s parlance big data typically encompasses just three linked computerized tasks: storing collected foreign data (think Amazon’s cloud), finding and retrieving relevant foreign data (Bing or Google), and analyzing connections or patterns among the relevant foreign data (powerful web-analytic tools).

Word Cloud Big Data for IntelligenceThose three Ft. Meade museum displays demonstrate how NSA and the IC pioneered those “modern” big data tasks.  Storage is represented by TELLMAN/RISSMAN, running from the 1960’s throughout the Cold War using innovation from Intel. Search/retrieval were the hallmark of HARVEST/TRACTOR, built by IBM and StorageTek in the late 1950s. Repetitive what-if analytic runs boomed in 1983 when Cray delivered a supercomputer to a customer site for the first time ever.

The benefit of IC early adoption of big data wasn’t only to cryptology – although decrypting enemy secrets would be impossible without it. More broadly, computational big-data horsepower was in use constantly during the Cold War and after, producing intelligence that guided US defense policy and treaty negotiations or verification. Individual analysts formulated requirements for tasked big-data collection with the same intent as when they tasked HUMINT collection: to fill gaps in our knowledge of hidden or emerging patterns of adversary activities.

That’s the sense-making pattern that leads from data to information, to intelligence and knowledge. Humans are good at it, one by one. Murray Feshbach, a little-known Census Bureau demographic researcher, made astonishing contributions to the IC’s understanding of the crumbling Soviet economy and its sociopolitical implications by studying reams of infant-mortality statistics, and noticing patterns of missing data. Humans can provide that insight, brilliantly, but at the speed of hand-eye coordination.

Machines make a passable rote attempt, but at blistering speed, and they don’t balk at repetitive mindnumbing data volume. Amid the data, patterns emerge. Today’s Feshbachs want an Excel spreadsheet or Hadoop table at hand, so they’re not limited to the data they can reasonably carry in their mind’s eye.

To cite a recent joint research paper from Microsoft Research and MIT, “Big Data is notable not because of its size, but because of its relationality to other data.  Due to efforts to mine and aggregate data, Big Data is fundamentally networked.  Its value comes from the patterns that can be derived by making connections between pieces of data, about an individual, about individuals in relation to others, about groups of people, or simply about the structure of information itself.” That reads like a subset of core requirements for IC analysis, whether social or military, tactical or strategic.

The synergy of human and machine for knowledge work is much like modern agricultural advances – why would a farmer today want to trudge behind an ox-pulled plow? There’s no zero-sum choice to be made between technology and analysts, and the relationship between CIOs and managers of analysts needs to be nurtured, not cleaved apart.

What’s the return for big-data spending? Outside the IC, I challenge humanities researchers to go a day without a search engine. The IC record’s just as clear. ISR, targeting and warning are better because of big data; data-enabled machine translation of foreign sources opens the world; correlation of anomalies amid large-scale financial data pinpoint otherwise unseen hands behind global events. Why, in retrospect, the Iraq WMD conclusion was a result of remarkably-small-data manipulation.

Humans will never lose their edge in analyses requiring creativity, smart hunches, and understanding of unique individuals or groups. If that’s all we need to understand the 21st century, then put down your smartphone. But as long as humans learn by observation, and by counting or categorizing those observations, I say crank the machines for all their robotic worth.

Make sure to read both sides, and feel free to argue your own perspective in a comment on the SIGNAL site.

Increasing Jointness and Reducing Duplication in DoD Intelligence

Today I’m publishing an important guest-essay, with a brief introduction.  Last month the Wall Street Journal published a 12-part online series about college graduates and their paths to success, featuring surveys and input from job recruiters. One thing caught my eye, at least when blogged by an acquaintance, Prof. Kristan Wheaton of the Mercyhurst College Institute Of Intelligence Studies. The WSJ’s study included a look at recent graduates’ job satisfaction in their new careers, and as Prof. Wheaton strikingly put it in his own blogpost:

Intelligence Analysts are Insanely Happy.” 

I’m pretty sure that’s not really true by and large; Prof. Wheaton seems slightly dubious as well. Many readers of this blog are intelligence analysts themselves, so I’d love to hear from you (in comments or email) about your degree of giddyness….

We all know that the intelligence-analysis field as currently practiced in U.S. agencies bears many burdens weighing heavily on job satisfaction, and unfortunately weighing on successful performance.  Our youngest and our most experienced intelligence analysts have been battling those burdens. 

One analyst has now put constructive thoughts on paper, most immediately in response to a call by Defense Secretary Bob Gates asking DoD military and civilian employees to submit their ideas to save money, avoid cost, reduce cycle time and increase the agility of the department (see more about the challenge here).  

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Contributing to Intelligence Innovation

Below are two ways to contribute to innovation in government, and specifically in intelligence matters. One is for you to consider, the other is a fun new path for me.

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Bing vs Google, the quiet semantic war

On Wednesday night I had dinner at a burger joint with four old friends; two work in the intelligence community today on top-secret programs, and two others are technologists in the private sector who have done IC work for years. The five of us share a particular interest besides good burgers: semantic technology.

Oh, we talked about mobile phones (iPhones were whipped out as was my Windows Phone, and apps debated) and cloud storage (they were stunned that Microsoft gives 25 gigabytes of free cloud storage with free Skydrive accounts, compared to the puny 2 gig they’d been using on DropBox).

But we kept returning to semantic web discussions, semantic approaches, semantic software. One of these guys goes back to the DAML days of DARPA fame, the guys on the government side are using semantic software operationally, and we all are firm believers in Our Glorious Semantic Future.

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Slate of the Union Day

Today is “Slate of the Union” day, when the two most charismatic individuals in recent American history go on stage and attempt to reclaim mantles as innovators. I’ll leave aside the fellow with lower poll numbers for now (President Obama). More eyes in the tech world will be watching as Steve Jobs makes his newest product announcement, the Apple tablet/Tabloid/iSlate thing iPad (it’s official).

Back in the late 1980s I worked for the legendary “Mayor of Silicon Valley” Tom McEnery (he was actually the mayor of San Jose), and we did many joint projects with Apple, particularly with CEO John Sculley, a great guy.

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To fix intelligence analysis you have to decide what’s broken

“More and more, Xmas Day failure looks to be wheat v. chaff issue, not info sharing issue.” – Marc Ambinder, politics editor for The Atlantic, on Twitter last night.

Marc Ambinder, a casual friend and solid reporter, has boiled down two likely avenues of intelligence “failure” relevant to the case of Umar Farouk Abdulmutallab and his attempted Christmas Day bombing on Northwest Airlines Flight 253.  In his telling, they’re apparently binary – one is true, not the other, at least for this case.

The two areas were originally signalled by President Obama in his remarks on Tuesday, when he discussed the preliminary findings of “a review of our terrorist watch list system …  so we can find out what went wrong, fix it and prevent future attacks.” 

Let’s examine these two areas of failure briefly – and what can and should be done to address them.

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