Phil 2.17.18

Snow today

Random thought. Marches help because they literally put people in the same position, align them in a direction and enforce a common velocity.

Found this item about compromised Trump company servers. I think this could be framed as an example of excessive trust bringing high social inertia. This would be different from explicit command and control.

So why would the organization allow this? If it’s not fear, then it’s trust. Kramer describes trust arising from incremental and repeated exchanges. I’d like to extend that thought. These incremental and repeated exchanges need to happen in dimension-reduced spaces that are similar or appear to map to each other, and occur with respect to orientation alignment, position, and velocity. The more alignment in these three axis, the greater the trust, and the lower the perceived need for awareness outside the relationship.

Twitter is just full of this stuff today: How A Russian Troll Fooled America

  • Reconstructing the life of a covert Kremlin influence account (TEN_GOP)
  • The Atlantic Council’s Digital Forensic Research Lab (DFRLab) has operationalized the study of disinformation by exposing falsehoods and fake news, documenting human rights abuses, and building digital resilience worldwide.

 

Phil 2.16.18

7:00 – 3:00 ASRC MKT

  • Finished the first draft of the CI 2018 extended abstract!
  • And I also figured out how to run the sub projects in the Ultimate Angular src collection. You need to go to the root directory for the chapter, run yarn install, then yarn start. Everything works then.
  • Trolls on Twitter: How Mainstream and Local News Outlets Were Used to Drive a Polarized News Agenda
    • This is the kind of data that compels us to rethink how we understand Twitter — and what I feel are more influential platforms for reaching regular people that include Facebook, Instagram, Google, and Tumblr, as well as understand ad tech tracking and RSS feed–harvesting as part of the greater propaganda ecosystem.
  • NELA News credibility classification toolkit
    • The News Landscape (NELA) Toolkit is an open source toolkit for the systematic exploration of the news landscape. The goal of NELA is to both speed up human fact-checking efforts and increase the understanding of online news as a whole. NELA is made up of multiple indepedent modules, that work at article level granularity: reliability prediction, political impartiality prediction, text objectivity prediction, and reddit community interest prediction. As well as, modules that work at source level granularity: reliability prediction, political impartiality prediction, content-based feature visualization. 
  • New benchmarks for approximate nearest neighbors
    • I built ANN-benchmarksto address this. It pits a bunch of implementations (including Annoy) against each other in a death match: which one can return the most accurate nearest neighbors in the fastest time possible. It’s not a new project, but I haven’t actively worked on it for a while.
  • Systems of Global Governance in the Era of Human-Machine Convergence
    • Technology is increasingly shaping our social structures and is becoming a driving force in altering human biology. Besides, human activities already proved to have a significant impact on the Earth system which in turn generates complex feedback loops between social and ecological systems. Furthermore, since our species evolved relatively fast from small groups of hunter-gatherers to large and technology-intensive urban agglomerations, it is not a surprise that the major institutions of human society are no longer fit to cope with the present complexity. In this note we draw foundational parallelisms between neurophysiological systems and ICT-enabled social systems, discussing how frameworks rooted in biology and physics could provide heuristic value in the design of evolutionary systems relevant to politics and economics. In this regard we highlight how the governance of emerging technology (i.e. nanotechnology, biotechnology, information technology, and cognitive science), and the one of climate change both presently confront us with a number of connected challenges. In particular: historically high level of inequality; the co-existence of growing multipolar cultural systems in an unprecedentedly connected world; the unlikely reaching of the institutional agreements required to deviate abnormal trajectories of development. We argue that wise general solutions to such interrelated issues should embed the deep understanding of how to elicit mutual incentives in the socio-economic subsystems of Earth system in order to jointly concur to a global utility function (e.g. avoiding the reach of planetary boundaries and widespread social unrest). We leave some open questions on how techno-social systems can effectively learn and adapt with respect to our understanding of geopolitical complexity.

Phil 2.15.18

ASRC MKT 7:00 – 8:00

  • Taking most of the day off, but spent the early morning tweaking the CI 2018 paper and sending it out to the Fika writing group
  • We have discussions, but we do not have discussions about the axis that we are choosing to decide along

Sent this to my representative:

Dear Rep. Cummings,

I would like to suggest a simple piece of legislation that may begin to address gun violence.

“For every student killed or wounded with a firearm in the preceding year, a 1-cent tax will be added to the price of the type of bullet used in the attack. The funds collected will be used to support the victims.”

This approach will do two things: 1) It will incentivize gun owners to demand action, since it could substantially increase the cost of using their guns. 2) It will place the onus of determining effective gun control within the gun community. As a result, there should be no second amendment concerns.

I realize that this is small in scope, and targeted at only the most innocent victims of gun violence, but I’m hoping that the simplicity and strength of the message may help moving the process forward.

 

Phil 2.14.18

7:00 – 4:00 ASRC

  • Stampede? Herding? Twitter deleted 200,000 Russian troll tweets. Read them here.
    • Twitter doesn’t make it easy to track Russian propaganda efforts — this database can help
  • Add a “show all trajectories” checkbox.
    • That’s a nice visualization that shows the idea of the terrain uncovered by the trajectories: 2018-02-14
  • Continue with paper – down to 3 pages!
  • Continue with slides. Initial walkthrough with Aaron
  • 3:00 – 4:00 A2P meeting

Phil 2.13.18

7:00 – 4:00 ASRC MKT

  • UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
    • UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based in Riemannian geometry and algebraic topology. The result is a practical scalable algorithm that applies to real world data. The UMAP algorithm is competitive with t-SNE for visualization quality, and arguably preserves more of the global structure with superior run time performance. Furthermore, UMAP as described has no computational restrictions on embedding dimension, making it viable as a general purpose dimension reduction technique for machine learning.
  • How Prevalent are Filter Bubbles and Echo Chambers on Social Media? Not as Much as Conventional Wisdom Has It
    • Yet, as Rasmus points out, conventional wisdom seems to be stuck with the idea that social media constitute filter bubbles and echo chambers, where most people only, or mostly, see political content they already agree with. It is definitely true that there is a lot of easily accessible, clearly identifiable, highly partisan content on social media. It is also true that, to some extent, social media users can make choices as to which sources they follow and engage with. Whether people use these choice affordances solely to flock to content reinforcing their political preferences and prejudices, filtering out or avoiding content that espouses other viewpoints, is, however, an empirical question—not a destiny inscribed in the way social media and their algorithms function.
  • He Predicted The 2016 Fake News Crisis. Now He’s Worried About An Information Apocalypse.
    • That future, according to Ovadya, will arrive with a slew of slick, easy-to-use, and eventually seamless technological tools for manipulating perception and falsifying reality, for which terms have already been coined — “reality apathy,” “automated laser phishing,” and “human puppets.”
  • Finish first pass at DC slides – done!
  • Begin trimming paper – good progress.
  • Add a slider that lets the user interactively move a token along the selected trajectory path – done. Yes, it looks like a golf ball on a tee… Capture
  • Sprint planning

Phil 2.12.18

7:00 – 4:00 ASRC MKT

  • The social structural foundations of adaptation and transformation in social–ecological systems
    • Social networks are frequently cited as vital for facilitating successful adaptation and transformation in linked social–ecological systems to overcome pressing resource management challenges. Yet confusion remains over the precise nature of adaptation vs. transformation and the specific social network structures that facilitate these processes. Here, we adopt a network perspective to theorize a continuum of structural capacities in social–ecological systems that set the stage for effective adaptation and transformation. We begin by drawing on the resilience literature and the multilayered action situation to link processes of change in social–ecological systems to decision making across multiple layers of rules underpinning societal organization. We then present a framework that hypothesizes seven specific social–ecological network configurations that lay the structural foundation necessary for facilitating adaptation and transformation, given the type and magnitude of human action required. A key contribution of the framework is explicit consideration of how social networks relate to ecological structures and the particular environmental problem at hand. Of the seven configurations identified, three are linked to capacities conducive to adaptation and three to transformation, and one is hypothesized to be important for facilitating both processes.
  • Starting to trim paper down to three pages
  • Starting on CHIIR slide stack – Still need to add future work
  • Springt Review
  • Rwanda radio transcripts
    • From October 1993 to late 1994, RTLM was used by Hutu leaders to advance an extremist Hutu message and anti-Tutsi disinformation, spreading fear of a Tutsi genocide against Hutu, identifying specific Tutsi targets or areas where they could be found, and encouraging the progress of the genocide. In April 1994, Radio Rwanda began to advance a similar message, speaking for the national authorities, issuing directives on how and where to kill Tutsis, and congratulating those who had already taken part.
  • Fika
    • Set up Fika Writing group that will meet Wednesdays at 4:00. We’ll see how that goes.

Phil 2.11.18

Introduction to Learning to Trade with Reinforcement Learning

  • In this post, I’m going to argue that training Reinforcement Learning agents to trade in the financial (and cryptocurrency) markets can be an extremely interesting research problem. I believe that it has not received enough attention from the research community but has the potential to push the state-of-the art of many related fields. It is quite similar to training agents for multiplayer games such as DotA, and many of the same research problems carry over. Knowing virtually nothing about trading, I have spent the past few months working on a project in this field.
  • This sounds to me like reinforcement learning figuring out game theory. Might be useful for NOAA as well

Worked on getting the MapBuilder app into a useful standalone app: 2018-02-11 (1)

2.9.18

7:00 – 5:00 ASRC MKT

  • Add something about a population of ants – done
  • Add loaders for the three populations, and then one for trajectories
    • Promoted WeightWidget to JavaUtils
    • Moving 3d and UI building out of start
    • Ugh, new IntelliJ
    • Made the graph pieces selectable
    • Got drawmode (LINE) working
    • Reading in trajectories
    • Need to load each as a child and then draw all of them first, then make that selectable. Done!
  • Go over draft with Aaron. Hand off for rewrite 1? Nope – family emergency
  • 2:00 meeting with Aaron and IC team? Nope
  • Intro to deep learning course from MIT: introtodeeplearning.com
    • An introductory course on deep learning methods with applications to machine translation, image recognition, game playing, image generation and more. A collaborative course incorporating labs in TensorFlow and peer brainstorming along with lectures. Course concludes with project proposals with feedback from staff and panel of industry sponsors.
  • Topics, Events, Stories in Social Media
    • This thesis focuses on developing methods for social media analysis. Specifically, five directions are proposed here: 1) semi-supervised detection for targeted-domain events, 2) topical interaction study among multiple datasets, 3) discriminative learning about the identifications for common and distinctive topics, 4) epidemics modeling for flu forecasting with simulation via signals from social media data, 5) storyline generation for massive unorganized documents.
  • Communication by virus
    • The standard way to think about neurons is somewhat passive. Yes, they can exciteor inhibit the neurons they communicate with but, at the end of the day, they are passively relaying whatever information they contain. This is true not only in biologicalneurons but also in artificial neural networks. 

Phil 2.8.18

7:00 – 5:00 ASRC MKT

  • I need to put together an equation that describes group cohesion. Something like
    • C = Var(L) * Var(O) * Avg(V)/Var(V) * Si, for some population p, over a period of time t, where
      • C is group cohesion
      • Var(x) is the variance
      • Avg(x) is the average
      • L is location
      • O is orientation
      • V is velocity
      • Si is social influence, which is in turn a function of awareness and reach. In network terms, the range is from unconnected through partially connected to fully connected
    • C should have (at least?) three phases: Nomad (low), Flocking(mid), and Stampede(high). The intuition here is that the higher the velocity, the lower the variance has to be in location and orientation to obtain the same level of cohesion. A high velocity, tightly clustered group is a stampede, where social influence overrides environmental awareness.
  • The Shape of Art History in the Eyes of the Machine (Many mapping implications)
  • More writing
    • Citations are all in

Phil 2.7/18

7:30 – 5:30 ASRC MKT

  • Freezing rain and general ick, so I’m working from home. Thus leading to the inevitable updating of IntelliJ
  • Working on the 3D mapping app.
    • Reading in single spreadsheet with nomad graph info
    • Building a NodeInfo inner class to keep the nomad positions for the other populations
    • Working! 2018-02-07
    • Better: 2018-02-07 (2)
    • Resisting the urge to code more and getting back to the extended abstract. I also need to add a legend to the above pix.
  • Back to extended abstract
    • Added results and future work section
    • got all the pictures in
    • Currently at 3 pages plus. Not horrible.
  • Demographics and Dynamics of Mechanical Turk Workers
    • There are about 100K-200K unique workers on Amazon. On average, there are 2K-5K workers active on Amazon at any given time, which is equivalent to having 10K-25K full-time employees. On average, 50% of the worker population changes within 12-18 months. Workers exhibit widely different patterns of activity, with most workers being active only occasionally, and few workers being very active. Combining our results with the results from Hara et al, we see that MTurk has a yearly transaction volume of a few hundreds of millions of dollars.

Phil 2.6.18

7:30 – 5:00 ASRC MKT

  • Took four much needed days off on Sanibel island. Forgot to pack some things? Need to call the hotel at (239) 215-3401
  • Starting CI 2018 abstract. And oddly, the abstract isn’t showing??? Sent a note to the conference chair. IN the meantime, I have a subsection for the abstract. It appears to be acmlarge for the most part, so maybe use that????
  • Was going to get back to Angular, but stuck with 404s on CRUD operations: 404
  • Working on the 3D map application. Decided to go with JavaFX and their 3d implementation. It’s going quickly. MapApp1
  • I’ve also gotten the graph generator creating spreadsheets that the map app can read in. So the next job will be to wire everything together, where the position information is based off the nomad trajectories, with the size and visitor (height) data being overlayed with the different colors.

Phil 2.1.18

7:00 – 3:30 ASRC MKT

  • Communications Handbook for IPCC scientists
  • The Barnes-Hut Approximation
    • Efficient computation of N-body forces
      By: Jeffrey Heer
      Computers can serve as exciting tools for discovery, with which we can model and explore complex phenomena. For example, to test theories about the formation of the universe, we can perform simulations to predict how galaxies evolve. To do this, we could gather the estimated mass and location of stars and then model their gravitational interactions over time.
  • Need to get started on the extended abstract for Collective Intelligence 2018! One month! March 2, 2018!
    • Set up the LaTex template for the conference. Done
    • Think I want to call it Mapping Simon’s Anthill
  • Need to contact the CHIIR 2018 folks to see what is expected for the DC
  • More Angular, feeling my way through the Http code, which has been deprecated. Looked at the similar code in Tour of Heroes. We’ll see if the old stuff works and then try to update? Need to ask Jeremy.
  • Back to BIC. Evolutionary reasons for cooperation as group fitness, where group payoff is maximized. This makes the stag salient in stag hunt.
  • A thorough explanation of synchronization/phase locking. My mental model is this: Imaging a set of coaxial but randomly oscillating identical weights sliding back and forth in their section of lightweight tubing. From the outside, the tube would be stationary, as all the forces would be cancelling. If the weights can synchronize, then the lightweight tube will be doing most of the moving. Since the mass of the tube is lower than the mass of the combined weights,   The force required for the whole system will be lower, and as a result (I think?) the system will run more efficiently and longer. Need to work out the math.

Phil 1.31.18

7:00 – 7:00 ASRC MKT

  • The Matrix Calculus You Need For Deep Learning
    • Most of us last saw calculus in school, but derivatives are a critical part of machine learning, particularly deep neural networks, which are trained by optimizing a loss function. Pick up a machine learning paper or the documentation of a library such as PyTorch and calculus comes screeching back into your life like distant relatives around the holidays. And it’s not just any old scalar calculus that pops up—you need differential matrix calculus, the shotgun wedding of linear algebra and multivariate calculus.
  • Continuing BIC
    • Explaining the evolution of any human behavior trait (say, a tendency to play C in Prisoner’s Dilemmas) raises three questions. The first is the behavior selection question: why did this trait, rather than some other, get selected by natural selection? Answering this involves giving details of the selection process, and saying what made the disposition confer fitness in the ecology in which selection took place. But now note that ‘When a behavior evolves, a proximate mechanism also must evolve that allows the organism to produce the target behavior. Ivy plants grow toward the light. This is a behavior, broadly construed. For phototropism to evolve, there must be some mechanism inside of ivy plants that causes them to grow in one direction rather than in another’ (Sober and Wilson 1998, pp. 199-200). This raises the second question, the production question: how is the behavior produced within the individual-what is the ‘proximate mechanism’? In the human case, the interest is often in a psychological mechanism: we ask what perceptual, affective and cognitive processes issue in the behavior. Finally, note that these processes must also have evolved, so an answer to the second question brings a third: why did this proximate mechanism evolve rather than some other that could have produced the same behavior? This is the mechanism selection question. (pg 95)
      • These are good questions to answer, or at least address. Roughly, I thing my answers are
        • Selection Question: The three phases are a very efficient way to exploit an environment
        • Production Question: Neural coupling, as developed in physical swarms and moving on to cognitive clustering
        • Mechanism Question: Oscillator frequency locking provides a natural foundation for  collective behavior. Dimension reduction is how axis are selected for matching.
  • Value Orientations, Expectations and Voluntary Contributions in Public Goods
    • ValueOrientation
  • Discussion with Aaron about JuryRoom design
  • Observable is a better way to code.
    • Discover insights faster and communicate more effectively with interactive notebooks for data analysis, visualization, and exploration.
  • More Angular. Finished with module communication, starting with services
  • Meeting with Wayne
    • Submit to JASS
    • Abstract to CI 2018 July 7-8, 2018 at the University of Zurich, Switzerland

Phil 1.30.18

7:00 – 5:00 ASRC MKT

  • Big thought for today.In a civilization context, the three phases of collective intelligence work like this. These phases relate to computational effort which is proportional to the number of dimensions that an individual has to consider in their existential calculus. The assumption is that lower computational effort is selected for at natural explore/exploit ratios.
    • Exploration phase. Nomadic explorers are introduced to a new environment. Can be physical, informational, cognitive, etc. This phase has the highest dimensional processing required for the individual.
    • Exploitation phase. Social patterns increase the hill climbing power of agents in the environment. This results in a sufficiently optimal access to resources. This employs lower dimensions to support consensus and polarization.
    • Inertial phase. Social influence becomes dominant and environmental influence wains. Local diversity drops as similar agents cluster tightly together. Resources wane. This employs the most dimension reduction and the highest polarization, resulting in high implicit coordination.
    • Collapse. Implied, since the Inertial phase is unsustainable. If the previous population produced explorers that found new, productive environments, the cycle can repeat elsewhere.
  • Continuing BIC
    • “We need to know, in detail, what deliberations are like that people engage in when they group-identify”. Also, agency transformation. AgencyTransformation
  • Rules, norms and institutional erosion: Of non-compliance, enforcement and lack of rule of law
    • What I am seeing right now in the US (a steady and slow erosion of democratic norms and a systematic violation of rules by the President Elect, in particular as though “they don’t apply to him“) is something that I’ve seen in other countries where I have studied formal and informal rules and institution building (and decay). This, in my view, is worrisome. If the US is going to want to continue having a functioning democracy where compliance with rules and norms is an expectation at the societal level, it’s going to have to do something major to stop this systematic rule violation.
  • Evaluation of Interactive Machine Learning Systems
    • The evaluation of interactive machine learning systems remains a difficult task. These systems learn from and adapt to the human, but at the same time, the human receives feedback and adapts to the system. Getting a clear understanding of these subtle mechanisms of co-operation and co-adaptation is challenging. In this chapter, we report on our experience in designing and evaluating various interactive machine learning applications from different domains. We argue for coupling two types of validation: algorithm-centered analysis, to study the computational behaviour of the system; and human-centered evaluation, to observe the utility and effectiveness of the application for end-users. We use a visual analytics application for guided search, built using an interactive evolutionary approach, as an exemplar of our work. We argue that human-centered design and evaluation complement algorithmic analysis, and can play an important role in addressing the “black-box” effect of machine learning. Finally, we discuss research opportunities that require human-computer interaction methodologies, in order to support both the visible and hidden roles that humans play in interactive machine learning.
  • Jensen–Shannon divergence – I think I can use this to show the distance between a full coordination matrix and one that contains only the main diagonal.
  • Evolution of social behavior in finite populations: A payoff transformation in general n-player games and its implications
    • The evolution of social behavior has been the focus of many theoretical investigations, which typically have assumed infinite populations and specific payoff structures. This paper explores the evolution of social behavior in a finite population using a general n-player game. First, we classify social behaviors in a group of n individuals based on their effects on the actor’s and the social partner’s payoffs, showing that in general such classification is possible only for a given composition of strategies in the group. Second, we introduce a novel transformation of payoffs in the general n-player game to formulate explicitly the effects of a social behavior on the actor’s and the social partners’ payoffs. Third, using the transformed payoffs, we derive the conditions for a social behavior to be favored by natural selection in a well-mixed population and in the presence of multilevel selection.
  • Got the data for the verdicts and live verdicts set up right, or at least closer: JuryRoom
  • Booked a room for the CHIIR Hotel
  • Got farther on UltimateAngular:
    •  UltimateAngular

Phil 1.29.18

7:00 – 5:30 ASRC MKT

  • The phrase “Epistemic Game Theory” occurred to me in the shower. Looked it up and found these two things:
  • When it’s easier to agree than discuss, it should be easier to stampede:
  • Like vs. words
  • This is also a piece of Salganik’s work as described in Leading the Herd Astray: An Experimental Study of Self-Fulfilling Prophecies in an Artificial Cultural Market
  • An article on FB optimization and how to change the ratio of likes to comments, etc
  • I don’t think people did. It’s just that it’s easier to not think too much 🙂 people are busy selling tools that do everything for people, and people are happy buying tools to limit thinking. The analogy of replacing cognitive load with perception by VIS misleads in this regard. (Twitter)
  • Continuing BIC
    • Dimension reduction is a form of induced conceptual myopia (pg 89)? Conceptual Myopia
  • AI Roundup workshop today
    • Zenpeng, Biruh, Phil, Aaron, Eric, Eric, Kevin
    • Eric – Introductory remarks. Budget looks good for 2018. Direction, chance to overlap, get leaders together for unique differentiators and something that we can build a business around. There has to be a really good business case with revenue in the out years
    • Aaron – CDS for A2P. Collaborate on analytics, ML, etc. Non corporate focused. Emerging technologies and trends. Helping each other out. Background in IC software dev.
    • Pam Scheller – SW Aegis. BD. EE, MS Computer engineering.
    • Biruh, TF, LIDAR, Generalized AI as hobby.
    • Zhenpeng Lee – Physics, Instrument Data Processing for GOES-R. FFT. GOES_R radiometric analysis. 7k detector rows? Enormous data sets. Attempting to automate processing the analysis of these data sets. Masters in Computer Science from JHU. Written most of his code from scratch.
    • Kevin Wainwright. Software engineering Aegis. C&C, etc. Currently working on a cloud based analytics with ML for big data, anomaly detection, etc. Looking for deviation from known flight paths
    • Eric Velte. History degree. Aegis. Situational awareness. Chief technologists for missions solutions group. Software mostly. Data analytics for the last two years. Big Data Analytics Platform.
    • Cornel as engineer, Zero G heat transfer, spacecraft work. Technology roadmaps for thermal control. Then business development, mostly for DoD. Research Sports research – head of Olympic Committee research kayaks, women’s 8, horse cooling, bobsleds.
    • Mike Beduck. Chemical Engineering and computer science. Visualization, new to big data. Closed system sensor fusion. RFP response, best practices. Repository for analytics
    • George. Laser physics. Cardiac imaging analysis. Software development, 3D graphics. Medical informatics. CASI ground systems. More GOES-R/S. Image and signal processing and analysis.
    • Anton is lurling and listening. Branding and marketing.
  • A2P WIP
    • Put a place on sharepoint for papers and other documents – annotated bibliography.
    • Floated the JuryRoom app. Need to mention that the polarizing discussion closes at consensus.
  • Zhenpeng Lee AIMS – GOES-R. What went wrong and how to fix. ML to find pattern change in 20k sensor streams. Full training on each day’s data, then large scale clustering. Trends are seasonal? Relationships between sensors? Channel has 200-600 detectors. “Machine Learning of Situational Awareness” MLP written in Java. TANH activation function.
    • Eric Haught: Long term quest for condition-based maintenance.
    • Aaron – we are all trying to come up with a useful cross platform approach to anomaly detection.
    • Training size: 100k samples? Sample selection reduce to 200? Not sure what the threshold sensitivity is
  • Eric Velte – Devops. Centralize SW dev and support into a standardized framework. NO SECURITY STACK!!!!!
  • Dataforbio? Video series