Weekly QuEST Discussion Topics and News11 July 2014

1.) We will start by discussing some work by our colleagues in the Sensors directorate associated with QuEST applications to SAR and EO data exploitation and specifically tracking. The QuEST position going in is that a dual process tracker (Type 1 and Type 2 components) can our perform a single process data driven tracker. I would suggest that advances like feature aided tracking (FAT) and context aided tracking (CAT) support this position. But I would suggest that a better Type 2 representation, more QuEST like could do even better since it would not be so bound to the variabilities of the data. But current approaches using those ideas are still focused in the measured data world versus attempting to generate a hypothetical representation and blending that with the data driven tracking. Work that attempts to track through obscurations uses this idea and then often confirms the results using features / context – but again they do not attempt to use our guiding tenets for the add-on representation / processes.2.) We also want to discuss some of the ideas in the current draft of the Erik Blasch led effort for an article for NAECON. *** we might defer much of this discussion as Eric will be out on Fridaywelcoming into the world his new child! ** His bold attempt to get down on paper how what we are doing is related to fusion and narratives inspired some dialogue that the group may want to chime in on. The first topic is where does QuEST fit in the mission space when we are talking PCPAD. Specifically can we achieve an artificially conscious decision aid if we don’t allow that agent / agents the ability to interact with the sensing apparatus. Another topic is where does QuEST fit in the levels of information fusion – there are some obvious places but maybe we need to articulate how it could fit at all of the levels and thus be more integrated in the system of systems. Then there is the discussion of activity based intelligence versus object based production versus a far more general approach to ‘event based content management’ or what I would like to call ‘Qualia based content management’. Then there is the discussion on mapping our construct onto the situational awareness levels. Then explaining the QuEST tenets in a manner a non-QuEST person could get the gist of them. Eventually leading to a QuEST model for information fusion.

3.) The third topic is a continuation of the discussion of implementing QuEST solutions using existing cognitive architectures and their infrastructures. Last week we discussed briefly a recent publication by one of our colleagues Robert Patterson and Kennedy – Modeling Intuitive Decision Making in ACT-R. the reason I want to discuss that article is it has many of the facets we’ve been discussing associated with the proposed work of our colleague Sandy V. specifically we want to use the Patterson approach to interfacing a virtual world to ACT-R and some of their use of the existing ACT-R modules.

a. Abstract: One mode of human decision-making is considered intuitive i.e., unconscious situational pattern recognition. Implicit statistical learning, which involves the sampling of invariances from the environment and is known to involve procedural (i.e., non-declarative) memory, has been shown to be a foundation of this mode of decision making. We present an ACT-R model of implicit learning whose implementation entailed a declarative memory-based learner of the classification of example strings of an artificial grammar. The model performed very well when compared to humans. The fact that the simulation of implicit learning could not be implemented in a straightforward way via a non-declarative memory approach, but rather required a declarative memorybased implementation, suggests that the conceptualization of procedural memory in the ACT-R framework may need to be expanded to include abstract representations of statistical regularities. Our approach to the development and testing of models in ACT-R can be used to predict the development of intuitive decision-making in humans.

4.) We want to extend the discussion this week to include another Kennedy article that implements dual process solution using ACT-R. ‘Integrating Fast and Slow Cognitive Processes’

a. Abstract - Human reactions appear to be controlled by two separate types of mental processes: one fast, automatic, and unconscious and the other slow, deliberate, and conscious. With the attention in the literature focused on the taxonomy of the two processes, there is little discussion of

how they interact. In this paper, we focus on modeling the slower process’s ability to inhibit the fast process. We present computational cognitive models in which different strategies allow a human to consciously inhibit an undesirable fast response. These general strategies include (a) blocking sensory input, (b), blocking or interrupting the fast process’s response, and (c) slowing down or delaying processing by introducing additional task. Furthermore, we discuss an approach to learning such strategies based on the inference of the causes and effects of the fast process.

News Articles

http://www.nytimes.com/2014/07/03/upshot/a-25-question-twitter-quiz-to-predict-retweets.html?ref=technology&_r=0

Why Computers Won’t Be Replacing You Just Yet

A 25-Question Twitter Quiz to Predict Retweets

JULY 1, 2014

Consider these two tweets by Al Gore, both promoting the same article:

40% of smartphone users connect to Internet immediately upon awakening, before leaving bed. #TheFuture http://t.co/pnRaaeET @TheAtlantic — Al Gore (@algore) Jan. 25, 2013 Cybercrime market now greater than annual global market for marijuana, cocaine, and heroin #TheFuture http://t.co/pnRaaeET @TheAtlantic — Al Gore (@algore) Jan. 25, 2013

Can you guess which one was retweeted more often?

Three computer scientists, Chenhao Tan, Lillian Lee and Bo Pang, have built an algorithm that also makes these guesses, as described in a recent paper, and the results are impressive. You can think of the pair of Gore tweets as a

practice round for a 25-question quiz that The Upshot has created based on their algorithm. (The answer: Gore’s first tweet got more retweets).

That an algorithm can make these kinds of predictions shows the power of “big data.” It also illustrates a fundamental limitation of big data: Specifically, guessing which tweet gets retweeted is significantly easier than creating one that gets retweeted.

To see why, it is useful to see how the algorithm was built. It used a data set of around 11,000 paired tweets — two tweets about the same link sent by the same person — to learn which word patterns looked predictive and then tested whether these patterns hold in new data. This is usually how “smart” algorithms are created from big data: Large data sets with known correct answers serve as a training bed and then new data serves as a test bed — not too differently from how we might learn what our co-workers find funny.

Continue reading the main story

Interactive Feature

Quiz: Can You Tell What Makes a Good Tweet?

A quiz tests your skill at picking which of two tweets would be shared more.

OPEN Interactive Feature

The end result is an algorithm that guesses well. It can guess which tweet gets retweeted about 67 percent of the time, beating humans, who on average get it right only 61 percent of the time.

This is striking when you think of the enormous handicap the algorithm has. Yes, it could learn from 11,000 pairs of tweets. But it has no other knowledge. It has none of the wealth of contextual information you have accumulated over the years. It has never heard friends’ complaints about spouses checking their phone the first thing in the morning. It does not have a sense of humor or know what a pun is. It does not know what makes a turn of phrase elegant or awkward.

It must rely on a few crude features, such as length of the tweet, the presence of certain words (“retweet” or “please”) or the use of indefinite articles. Yet with so little, it does so much. This is one of the miracles of big data: Algorithms find information in unexpected places, uncovering “signal” in places we thought contained only “noise.”

But we do not need to roll out the welcome mat for our machine overlords just yet. While the retweet algorithm is impressive, it has an Achilles’ heel, one shared by all prediction algorithms.

We care about predicting retweets mainly because we want to write better tweets. And we assume these two tasks are related. If Netflix can predict which movies I like, surely they can use the same analytics to create better TV shows. But it doesn’t work that way. Being good at prediction often does not mean being better at creation.

One barrier is the oldest of statistical problems: Correlation is not causation. Changing a variable that is highly predictive may have no effect. For example, we may find the number of employees formatting their résumés is a good predictor of a company’s bankruptcy. But stopping this behavior hardly seems like a fruitful strategy for fending off creditors.

…http://www.technologyreview.com/news/528741/a-speech-synthesizer-direct-to-the-brain/

Biomedicine News

A Speech Synthesizer Direct to the Brain

Recordings from the brain’s surface are giving scientists unprecedented views into how the brain controls speech.

By Courtney Humphries on July 9, 2014

Why It Matters

Brain-machine interfaces could restore speech to “locked-in” patients.

Mind recorder: A sheet of electrodes picks up electrical activity from the surface of the brain.Could a person who is paralyzed and unable to speak, like physicist Stephen Hawking, use a brain implant to carry on a conversation?That’s the goal of an expanding research effort at U.S. universities, which over the last five years has proved that recording devices placed under the skull can capture brain activity associated with speaking.While results are preliminary, Edward Chang, a neurosurgeon at the University of California, San Francisco, says he is working toward building a wireless brain-machine interface that could translate brain signals directly into audible speech using a voice synthesizer.The effort to create a speech prosthetic builds on success at experiments in which paralyzed volunteers have used brain implants to manipulate robotic limbs using their thoughts (see “The Thought Experiment”). That technology works because scientists are able to roughly interpret the firing

of neurons inside the brain’s motor cortex and map it to arm or leg movements. *** completely disagree – every example I’ve seen of this it is the human mind adapting to the signals via feedback watching / experiencing the movement – thus developing the right signals to control the device **Chang’s team is now trying to do the same for speech. It’s a trickier task, in part because complex language is unique to humans and the technology can’t easily be tested in animals.…http://www.iflscience.com/brain/researchers-may-have-discovered-consciousness-onoff-switch

Researchers May Have Discovered The Consciousness On/Off Switch

July 3, 2014 | by Justine Alford

Photo credit: Gontzal García del Caño, via Flickr

Researchers from the George Washington University have managed to switch consciousness on and off in an epileptic woman by stimulating a single region of the brain with electrical impulses. While this is a single case study, it provides an exciting insight into the neural mechanisms behind consciousness, a subject of great interest that is poorly understood despite decades of research. The study has been published in Epilepsy & Behavior.

Consciousness is a fascinating topic that has both intrigued and puzzled scientists and philosophers for centuries. Despite significant advances in our understanding of the brain, little is known about the neural networks that underpin consciousness. However, research has hinted that consciousness is likely the result of an integration of activity from numerous different areas of the brain, marrying all of our perceptions together into one experience. But what is the central hub to this process?

A few years back, Francis Crick, one of the scientists involved in deciphering the structure of DNA, and colleague Christof Koch proposed that a brain region known as the claustrum may be at the heart of consciousness, stringing together the constant input of information arriving from different brain networks.

Now, in the latest study, researchers demonstrate that their hypothesis might be correct after all. The scientists stumbled upon this finding whilst stimulating different areas of the brain of an epileptic woman and measuring resultant activity in order to find the epicenter of her seizures. They discovered that electrical stimulation with an electrode placed between the left claustrum and anterior-dorsal insula caused the woman to lose consciousness. She completely stopped moving, became unresponsive and her breathing slowed.

When the researchers stopped the stimulation, she regained consciousness and couldn’t remember the event. Furthermore, the effects were reproducible as the same outcome occurred each time they stimulated this region over a period of two days. To make sure they were not merely interfering with motor control or speech, they asked the woman to repeat a particular word or perform a certain movement as the stimulation commenced. The woman gradually spoke more quietly and moved less and less as she became unconscious, rather than immediately stopping,

suggesting this was affecting consciousness. They also did not identify any associated epileptic activity, suggesting it was not merely a seizure.

…http://www.technologyreview.com/news/528796/neuroscientists-object-to-europes-human-brain-project/

Project

Critics call emphasis on large-scale computer simulations in EU brain project premature.

By Antonio Regalado on July 7, 2014

Why It Matters

Europe’s largest brain research project may be flawed.More than 180 neuroscientists have signed an open letter to the European Commission calling on it to reconsider the technical goals and oversight of one of the world’s largest brain-mapping projects, predicting it is likely to fail.The European Union agreed last year to invest more than one billion Euros in the Human Brain Project (HBP), a 10-year effort involving dozens of research institutions to create a simulation using supercomputers of how the human brain works.But according to a letter released by dissenting scientists, the project is doomed by opaque management and the pursuit of goals not widely shared by neuroscientists. “We believe the HBP is not a well-conceived or implemented project and that it is ill suited to be the centerpiece of European neuroscience,” the letter says.Governments, including those of the United States and China, have all launched large neuroscience projects to study the brain (see “Brain Mapping”). But the brain is so massively complex—it has roughly 86 billion neurons and trillions of connections—that there’s little consensus on how to study it.Europe’s HBP has been particularly controversial because it emphasizes large-scale mapping of the brain and computer simulations over traditional, small-scale bench research. The project’s core goal, according to its

website, is “to build a completely new information computing technology infrastructure for neuroscience.”…http://www.technologyreview.com/news/528706/facebooks-emotional-manipulation-study-is-just-the-latest-effort-to-prod-users/

Users

With emotion-triggering effort, Facebook pushes beyond data-driven studies on voting, sharing, and organ-donation prompts, to make people feel good or bad.

By David Talbot on July 1, 2014

Why It Matters

Facebook is the world’s largest online social network, with data on more than a billion users. Facebook’s controversial study exploring whether it could manipulate people’s moods by tweaking their news feeds to favor negative or positive content produced a particularly negative emotional response, but it is far from the social network’s first effort to control user behavior.With huge amounts of data flooding in from more than a billion users, the company has a unique position to study their every move, and to perform experiments by measuring how behavior changes under different conditions (see “What Facebook Knows”). This helps Facebook persuade users to spend more time on the site. But in the past three years it has also been probing everything from voting to the effect of encouraging people to make organ donations.The company has a data science team dedicated to running experiments, both to advance its business aims and to do social-science research on the side, often with collaborators in academia. Other academics perform research on Facebook without collaborating with the company—either by simply observing users, or creating apps that ask them to take part in a project.The recent study, done in January 2012 but published only recently, hit a nerve partly because it had a negative effect on some users, but also

because the affected users were not asked for permission to participate (agreeing to Facebook’s terms and conditions was taken as consent).…http://www.technologyreview.com/qa/528271/what-am-i-thinking-about-you/

Q+ARebecca Saxe

Knowing how the brain deals with other people could lead to smarter computers.

By Courtney Humphries on June 17, 2014 Portrait by Jared Leeds

***Recently watching a utube video from Saxe she used the following example – great ToM example

“ I know you think you understand what you thought I said but I'm not sure you realize that what you heard is not what I meant”

― Alan Greenspan <http://www.goodreads.com/author/show/1334.Alan_Greenspan ***

The ability to discern what other people are thinking and feeling is critical to social interaction and a key part of the human experience. So it’s not surprising that the human brain devotes a lot of resources to so-called social cognition. But only recently has neuroscience begun to tease apart which brain regions and processes are devoted to thinking about other people.

Understanding how the brain perceives, interprets, and makes decisions about other people could help advance treatments and interventions for autism and other disorders in which social interactions are impaired. It could also help us build more socially intelligent computers. So far, artificial intelligence has struggled to program computers that make the kinds of

social judgments that come easily to us, such as interpreting ambiguous facial expressions or deciding whether a person’s words convey anger or sadness.More than a decade ago, neuroscientist Rebecca Saxe discovered a brain region that develops a “theory of mind”—a sense of what other people are thinking and feeling. More recently, she became an investigator in MIT’s Center for Minds, Brains, and Machines, and she’s been studying autism and social cognition in children and adults. Saxe and MIT Technology Review contributing editor, Courtney Humphries discussed the implications of this new research on the social brain.…http://www.wired.com/2014/07/hacking-google-maps/?mbid=social_fb

How Google Map Hackers Can Destroy a Business at Will

By Kevin Poulsen

Rene Bertagna blames Google for the death of his restaurant, Serbian

Crown. Courtesy Rene Bertagna

Washington DC-area residents with a hankering for lion meat lost a valuable source of the (yes, legal) delicacy last year when a restaurant called the Serbian Crown closed its doors after nearly 40 years in the same location. The northern Virginia eatery served French and Russian cuisine in a richly appointed dining room thick with old world charm. It was best known for its selection of exotic meats—one of the few places in the U.S. where an adventurous diner could order up a plate of horse or kangaroo. “We used to have bear, but bear meat was abolished,” says proprietor Rene Bertagna. “You cannot import any more bear.”But these days, Bertagna isn’t serving so much as a whisker. It began in early 2012, when he experienced a sudden 75 percent drop off in customers on the weekend, the time he normally did most of his business. The slump continued for months, for no apparent reason. Bertagna’s profits plummeted, he was forced to lay off some of his staff, and he struggled to understand what was happening. Only later did Bertagna come to suspect that he was the victim of a gaping vulnerability that made his Google listings open to manipulation.He was alerted to that possibility when one of his regulars phoned the restaurant. “A customer called me and said, ‘Why are you closed on Saturday, Sunday and Monday? What’s going on?’” Bertagna says.It turned out that Google Places, the search giant’s vast business directory, was misreporting the Serbian Crown’s hours. Anyone Googling Serbian Crown, or plugging it into Google Maps, was told incorrectly that the restaurant was closed on the weekends, Bertagna says. For a destination restaurant with no walk-in traffic, that was a fatal problem.“This area where the restaurant is located is kind of off the beaten path,” says Bertagna’s lawyer, Christopher Rau. “It’s in a wealthy subdivision of northern Virginia where a lot of government employees live on these estates and houses with two- or three-acre lots … It’s not really on the way to anything. If you’re going there, it’s because you’ve planned to go there. And unless you know that the place is going to be open, you’re probably not going to drag yourself out.”Bertagna immigrated to the U.S. from northern Italy when he was young. He’s 74 now, and, he says, doesn’t own a computer—he’d heard of the

Internet and Google but used neither. Suddenly, a technological revolution of which he was only dimly aware was killing his business. His accountant phoned Google and in an attempt to change the listing, but got nowhere. Bertagna eventually hired an Internet consultant who took control of the Google Places listing and fixed the bad information—a relatively simple process.But by then, Bertagna says, his business was in a nose dive from which he couldn’t recover—service suffered after the layoffs, and customers stopped coming back. He shuttered the Serbian Crown in April 2013.Bertagna puts the blame for his restaurant’s collapse on Google, and he’s suing the company in federal court in Virginia. His lawyer’s theory is that a competing restaurant sabotaged the Google Places listing to drive away the Serbian Crown’s customers, and he argues that Google turns a blind eye to such shenanigans. Google’s lawyers scoff at the lawsuit. “The Serbian Crown should not be permitted to vex Google or this Court with such meritless claims,” they wrote in a filing last month. (Google didn’t respond to repeated inquiries for this story)For a number of reasons, the claim is probably doomed in court. But the premise of the lawsuit—that the Serbian Crown was sabotaged online—isn’t as farfetched as it might seem.

A screenshot of the false FBI and Secret Service listings Bryan Seely created.

Beneath its slick interface and crystal clear GPS-enabled vision of the world, Google Maps roils with local rivalries, score-settling, and deception. Maps are dotted with thousands of spam business listings for nonexistent locksmiths and plumbers. Legitimate businesses sometimes see their listings hijacked by competitors or cloned into a duplicate with a different phone number or website. In January, someone bulk-modified the Google Maps presence of thousands of hotels around the country, changing the website URLs to a commercial third-party booking site (which siphons off the commissions).