7:00 – 5:00 GOES
- Dissertation – finish up the maps chapter – done!
- Try writing up more expensive information thoughts (added to discussion section as well)
- Game theory comes from an age of incomplete information. Now we have access to mostly complete, but potentially expensive information
- Expense in time – throwing the breakers on high-frequency trading
- Expense in $$ – Buying the information you need from available resources
- Expensive in resources – developing the hardware and software to obtain the information (Operation Hummingbird to TPU/DNN development)
- By handing the information management to machines, we create a human-machine social structure, governed by the rules of dense/sparse,stiff/slack networks
- AI combat is a very good example of an extremely stiff network (varies in density) and the associated time expense. Combat has to happen as fast as possible, due to OODA loop constraints. But if the system does not have designed-in capacity to negotiate a ceasefire (on both/all sides!), there may be no way to introduce it in human time scales, even though the information that one side is losing is readily apparent.
- Online advertising is a case where existing information is hidden from the target of the advertiser, but available to the platform, and to a lesser degree, the client. Because this information asymmetry, the user’s behavior/beliefs are more likely to be exploited in a way that denies the user agency, while granting maximum agency to the platform and clients.
- Deepfakes, spam and the costs of identifying deliberate misinformation
- Call to action: the creation of an information environment impact body that can examine these issues and determine costs. This is too complex a process for the creators to do on their own, and there would be rampant conflict of interest anyway. But an EPA-like structure, where experts in this topic perform as a counterbalance to unconstrained development and exploitation of the information ecosystem
- The Knowledge, Analytics, Cognitive and Cloud Computing (KnACC) lab in the Information Systems department in UMBC aims to address challenging issues at the intersection of Data Science and Cloud Computing. We are located in ITE 415.
- Start creating NN that takes pitch/roll/yaw star tracker deltas and tries to calculate reaction wheel efficiency
- input vector is dp, dr, dy. Assume a fixed timestep
- output vector is effp, effr, effy
- once everything trains up, try running the inferencer on the running sim and display “inferred RW efficiency” for each RW
- Broke out the base class parts of TF2OptimizerTest. I just need to generate the test/train data for now, no sim needed
big ending news for the day
Capacity, Bandwidth, and Compositionality in Emergent Language Learning
- Many recent works have discussed the propensity, or lack thereof, for emergent languages to exhibit properties of natural languages. A favorite in the literature is learning compositionality. We note that most of those works have focused on communicative bandwidth as being of primary importance. While important, it is not the only contributing factor. In this paper, we investigate the learning biases that affect the efficacy and compositionality of emergent languages. Our foremost contribution is to explore how capacity of a neural network impacts its ability to learn a compositional language. We additionally introduce a set of evaluation metrics with which we analyze the learned languages. Our hypothesis is that there should be a specific range of model capacity and channel bandwidth that induces compositional structure in the resulting language and consequently encourages systematic generalization. While we empirically see evidence for the bottom of this range, we curiously do not find evidence for the top part of the range and believe that this is an open question for the community.
Radiolab: Tit for Tat
- In the early 60s, Robert Axelrod was a math major messing around with refrigerator-sized computers. Then a dramatic global crisis made him wonder about the space between a rock and a hard place, and whether being good may be a good strategy. With help from Andrew Zolli and Steve Strogatz, we tackle the prisoner’s dilemma, a classic thought experiment, and learn about a simple strategy to navigate the waters of cooperation and betrayal. Then Axelrod, along with Stanley Weintraub, takes us back to the trenches of World War I, to the winter of 1914, and an unlikely Christmas party along the Western Front.
- Need to send a note for them to look into Axelrod’s “bully” saddle point
7:00 – ASRC GOES
- Dissertation – Nearly done with the agent cartography section?
- CTO Rehearsal – 10:30 – 12:00 done
- ML Dinner – 4:30 fun!
- Meeting With Aaron M
- More thinking about what to do with the paper. We decided to try for the CHI4EVIL workshop, and then try something like IEEE Spectrum. I think I’d like to reframe it around the concept of Expensive Information and Automation. Try to tie together AI weapons, spam filters, and deepfakes
- Automation makes negotiation more difficult, locks in trajectories
- Handing off responsibility to automation amplifies opportunities and destructive potential
- OODA loop could be generalized if you look at it from the perspective of attention.
The dynamics of norm change in the cultural evolution of language
- What happens when a new social convention replaces an old one? While the possible forces favoring norm change—such as institutions or committed activists—have been identified for a long time, little is known about how a population adopts a new convention, due to the difficulties of finding representative data. Here, we address this issue by looking at changes that occurred to 2,541 orthographic and lexical norms in English and Spanish through the analysis of a large corpora of books published between the years 1800 and 2008. We detect three markedly distinct patterns in the data, depending on whether the behavioral change results from the action of a formal institution, an informal authority, or a spontaneous process of unregulated evolution. We propose a simple evolutionary model able to capture all of the observed behaviors, and we show that it reproduces quantitatively the empirical data. This work identifies general mechanisms of norm change, and we anticipate that it will be of interest to researchers investigating the cultural evolution of language and, more broadly, human collective behavior.
When Hillclimbers Beat Genetic Algorithms in Multimodal Optimization
- It has been shown in the past that a multistart hillclimbing strategy compares favourably to a standard genetic algorithm with respect to solving instances of the multimodal problem generator. We extend that work and verify if the utilization of diversity preservation techniques in the genetic algorithm changes the outcome of the comparison. We do so under two scenarios: (1) when the goal is to find the global optimum, (2) when the goal is to find all optima.
A mathematical analysis is performed for the multistart hillclimbing algorithm and a through empirical study is conducted for solving instances of the multimodal problem generator with increasing number of optima, both with the hillclimbing strategy as well as with genetic algorithms with niching. Although niching improves the performance of the genetic algorithm, it is still inferior to the multistart hillclimbing strategy on this class of problems.
An idealized niching strategy is also presented and it is argued that its performance should be close to a lower bound of what any evolutionary algorithm can do on this class of problems.
The Danger of AI is Weirder than you Think
Janelle Shane’s website
7:00 – ASRC GOES
- Nice chapter on force-directed graphs here
- Explaining Strava heatmap.
- Also, added a better transition from Moscovici to Simon’s Ant and mapping. This is turning into a lot of writing…
- Explain approach for cells (sum of all agent time, and sum all unique agent visits)
- Explain agent trajectory (add to vector if cur != prev)
- Good discussion with Aaron about time series approaches to trajectory detection
7:00 – 8:00 ASRC / Phd
The Journal of Design and Science (JoDS), a joint venture of the MIT Media Lab and the MIT Press, forges new connections between science and design, breaking down the barriers between traditional academic disciplines in the process.
There is a style of propaganda on the rise that isn’t interested in persuading you that something is true. Instead, it’s interested in persuading you that everything is untrue. Its goal is not to influence opinion, but to stratify power, manipulate relationships, and sow the seeds of uncertainty.
Unreal explores the first order effects recent attacks on reality have on political discourse, civics & participation, and its deeper effects on our individual and collective psyche. How does the use of media to design unreality change our trust in the reality we encounter? And, most important, how does cleaving reality into different camps—political, social or philosophical—impact our society and our future?
This looks really nice: The Illustrated GPT-2 (Visualizing Transformer Language Models)