Homicide is a leading cause of death for pregnant women in US

• Women in the US are more likely to be murdered during pregnancy or soon after childbirth than to die from the three leading obstetric causes of maternal mortality (hypertensive disorders, haemorrhage, or sepsis).1 These pregnancy associated homicides are preventable, and most are linked to the lethal combination of intimate partner violence and firearms. Preventing men’s violence towards women, including gun violence, could save the lives of hundreds of women and their unborn children in the US every year

Book

• Rolling in more edits
• “In the meantime, some great news—the project is now officially approved! I’m now just waiting for a draft of the publishing agreement, so as soon as that’s ready I will send it over.”

GPT Agents

• Finish db access and build a view to see the text and meta info
• Here’s a view that I created to link multiple rows of key/values to a root result. Really proud of this:

create or replace view test_view as
    select tt.*, ttd_k.value as keyword, ttd_c.value as created, ttd_l.value as location, ttd_p.value as probability
    FROM table_text tt
    inner join table_text_data ttd_c on tt.id = ttd_c.text_id and ttd_c.name = 'created'
    inner join table_text_data ttd_k on tt.id = ttd_k.text_id and ttd_k.name = 'keyword'
    inner join table_text_data ttd_l on tt.id = ttd_l.text_id and ttd_l.name = 'location'
    inner join table_text_data ttd_p on tt.id = ttd_p.text_id and ttd_p.name = 'probability';

SBIRs

• 9:15 standup
• 11:30 Touch point
• Work on paper. Reading the DSIAC-BCO-2022-216 report, which is a lot less than I thought it would be considering the page count, but has some good stuff in it.
• Add example paragraph to rationale section
• Add mute() method and flag – done. Also added the publish
• Make publish work with base classes

To Fight Misinformation, We Need to Teach That Science Is Dynamic

• Science is a social process, and teaching students how researchers work in tandem to develop facts will make them less likely to be duped by falsehoods

GPT Agents

• Model Explorer
  • Make it so that seed re-use happens only on new text – Done
  • Add ‘%’ to percentage formatting – Done
  • add parsing of probes to split on commas – Done
  • Get experiment loading working – Done
  • Wire up to db – Not done
    • Created table_text and table_text_data in the gpt_experiments schema
• 4:00 Meeting today – discuss AI combat paper?

Book

• Responded to Katy’s email with ideas for website
• Continue with edits

SBIRs

• Got a good first pass on Rationale
• Working on Piloting AI paper
• Found a good resource with stopkillerrobots.org

SBIRs

• Sprint planning meeting – done. Started on taks
• 3:00 pm MCWL meeting. Delayed until Friday

GPT Agents

• Finish putting in the counters and wire up the model parameters
  • Counters are working and now use regexes
  • Wired up parameters
  • Wired up “save experiment” as json. Need to load back in now
• Start documentation
• Added these and other issues to the GitHub project

{
    "probe_str": "]][[text: ",
    "description": "This is a description",
    "max_len": 128,
    "top_k": 50,
    "top_p": 0.95,
    "num_sequences": 10,
    "batch_size": 1,
    "seed_flag": false,
    "model_path": "D:/Development/models/ivermectin_paxlovid"
}

Book

• Start folding in new edits
• Write up website thoughts for Katy

SBIRs

• 9:00 Demos
• 2:00 MDA Meeting
• Wrote up request to get hours for MORS paper
• Wrote up some scenarios for Rukan

GPT Agents

• Cannot figure out how to select and highlight text so I’m dropping the HTML frame
• Adding the percentage tracking

Book

• 4:30 Meeting with Brenda

Call BSO about ticket for Saturday

Book

• Finish up Money section. Maybe introduce the idea of self-grounded spaces? Either add a section to Belief is a Place, and continue here, or introduce here and continue on with the rest of the book? Not sure

SBIRs

• Add method that handles a particular class and produces a tab in a spreadsheet
• Add overridable “publish” method in BaseController?
• Comment changes in SharedObjects and BaseController
• Document for MDA Q3
• Slides for sprint demos
• 1:00 Meeting

The Slippery Slope: How Small Ethical Transgressions Pave the Way for Larger Future Transgressions

• Many recent corporate scandals have been described as resulting from a slippery slope in which a series of small infractions gradually increased over time (e.g., McLean & Elkind, 2003). However, behavioral ethics research has rarely considered how unethical behavior unfolds over time. In this study, we draw on theories of self-regulation to examine whether individuals engage in a slippery slope of increasingly unethical behavior. First, we extend Bandura’s (1991, 1999) social-cognitive theory by demonstrating how the mechanism of moral disengagement can reduce ethicality over a series of gradually increasing indiscretions. Second, we draw from recent research connecting regulatory focus theory and behavioral ethics (Gino & Margolis, 2011) to demonstrate that inducing a prevention focus moderates this mediated relationship by reducing one’s propensity to slide down the slippery slope. We find support for the developed model across 4 multiround studies. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

SBIRs

• Working on showing controller commands, states, and responses – done!
• Add SharedObject “queries” that create spreadsheets for specified (maybe an array?) types. Got the basics working. Need to break out a method to handle a type and a writer

Book

• 10:00 Meeting! We are going ahead on the book! Submission of the full book at the beginning of December, and a decision 1-2 weeks after that!
• Continue to roll in changes

GPT Agents

• Use the GoogleExplorer as a template for prompt interactions, and try some repeat interactions! Parsed output can easily be rendered as html which should be a nice touch. The text is the main piece, and the meta attributes are <ul> elements
• Add param list for GPT generation
• Add buttons to save current output to db
• Add textarea for description
• 4:00 Meeting
• Progress for today!

SBIRs

• More writing

Book

• Reply to Katy, and try to set up a meeting? Done. 10:00am tomorrow!
• Fold in more changes
• I realize that fiat money is also a self-grounded belief space. I think that means that money, organized religion, and constitutional governments are all related. They are also distinctly different from ungrounded belief spaces. Added a note to the text

Call BSO about parking

scikit-learn and Hugging Face join forces

• “Skops” is the name of the framework being actively developed as the link between the scikit-learn and the Hugging Face ecosystems. With Skops, we hope to facilitate essential workflows:
  • The ability to push scikit-learn models on the Hugging Face Hub
  • The possibility to try out models directly in the browser
  • The automatic creation of model cards, to improve model documentation and understanding
  • The ability to collaborate with others on machine learning projects

My first hearing of the phrase “Counter Autonomy”

GPT Agents

• Stub out ModelExplorer – off to a good start. The App is running, and I’m working out how to parse responses.
• Start documentation of EmbeddingExplorer

SBIRs

• 9:15 Standup, then RCS meeting with Rukan
• Writing for the rest of the day

Book

• I got the proposal reviews back!

• Fold edits in
• Maybe continue on religion chapter? May not have time

Call BSO about parking

How to construct a Nature summary paragraph

Book

• Started to poke at the outlines of a religion chapter
• 4:00 Meeting with Brenda

SBIRs

• Working on 3D viz
• 1:00 LLM Meeting with Isaac and Aaron
• 2:00 MDA meeting

GPT Agents

• Stub out ModelExplorer. Off to a good start. The app framework is up, loading the model and running prompts. Working out how to split the output for analysis
• Start documentation of EmbeddingExplorer

This is not good

I track my temperature every morning, along with weight and blood pressure. What can I say? I like to record data. Anyway, I came down with Covid after I came back from Spain in July, got Paxlovid and (motly) recovered in about two weeks. I still had a lingering cough, which is now completely gon. Looking back over the data, my temperature was slightly raised for two months. Not exactly Long Covid, but this thing took a looooong time to shake.

SBIRs

• 9:00 Meeting with Rukan to go over EntityData
• Work with Aaron on paper?
• Copy over the AI & Weapons paper to Overleaf for updating – done. It turns out that I don’t “own” the paper on Arxiv – Aaron Massey does. Downloaded final from Arxiv and uploaded to Overleaf

GPT Agents

• Added twitter query options to TweetDownloader and a way to disable writes to the db for debugging. I’m afraid to test it given that it’s Friday and all
• Fix excluded clusters – I think it’s backwards
• Not sure if I want to build an App to interact with the model. I think so? If only for quick data gathering
  • Find and load a model
  • Calculate percentages
  • Set prompts, generate text, get embeddings and cluster
  • Save good results to db?

7:00am Transformers talk

7:00pm Suz’s reading!

SBIRs

• Had a good chat with Rukan about kernel methods. Looking at ways to produce information to split out features that the system struggles to learn so that they can be handled differently. This led to thinking about adding that information in as a feature and then testing the reconstruction of the feature (e.g. std dev) vs the calculation based on the output as the loss function.
• Talked to Aaron to work out the experiment design
• Had to do my MORS expenses AGAIN
• 9:15 standup
• 11:30 touch point
• Get 3D viz working, and start on texture import and using lat/long. It looks like I can use the utm package. There are pieces missing from the directory that I don’t want to chase. Made a simpler viztest directory

GPT Agents

• The computational sociology group had a meeting again! Went over stuff, and I managed to break the Embedding explorter by removing tweet_row from the view. It should be this:

• That’s working now
• Getting more embeddings and clusters
• Struggled a bit with getting the files to save correctly
• Generating a model!

Book

• Continue to roll in changes – caught up!

I think that this could be a really interesting way of debugging vision systems around edge cases. Mask out everything but the attribution area and run separate image-to-text models to see what they identify and then check for consensus.

This also makes me think of what it might mean for human-monitored AI systems. People will need to be trained to quickly identify if the model is behaving poorly and flag it, as opposed to if the decision is correct. It’s more like driving a race car where you have to monitor the performance of the vehicle and adapt to that. You can’t stop racing if the tires are wearing out or you’re running out of fuel. You have to adjust your behavior to optimize the behavior of the system as it is. Which implies that we need simulators of AI systems that break a lot.

Third World War: System, Process and Conflict Dynamics

How digital media drive affective polarization through partisan sorting

• Politics has in recent decades entered an era of intense polarization. Explanations have implicated digital media, with the so-called echo chamber remaining a dominant causal hypothesis despite growing challenge by empirical evidence. This paper suggests that this mounting evidence provides not only reason to reject the echo chamber hypothesis but also the foundation for an alternative causal mechanism. To propose such a mechanism, the paper draws on the literatures on affective polarization, digital media, and opinion dynamics. From the affective polarization literature, we follow the move from seeing polarization as diverging issue positions to rooted in sorting: an alignment of differences which is effectively dividing the electorate into two increasingly homogeneous megaparties. To explain the rise in sorting, the paper draws on opinion dynamics and digital media research to present a model which essentially turns the echo chamber on its head: it is not isolation from opposing views that drives polarization but precisely the fact that digital media bring us to interact outside our local bubble. When individuals interact locally, the outcome is a stable plural patchwork of cross-cutting conflicts. By encouraging nonlocal interaction, digital media drive an alignment of conflicts along partisan lines, thus effacing the counterbalancing effects of local heterogeneity. The result is polarization, even if individual interaction leads to convergence. The model thus suggests that digital media polarize through partisan sorting, creating a maelstrom in which more and more identities, beliefs, and cultural preferences become drawn into an all-encompassing societal division.

SBIRs

• 9:00 kernel methods discussion with Rukan. Need to look at a way of using SD to look at “outlier-ness” maybe SD of all points – SD of all other points
• 10:00 experiment logger review
• Got GeoPandas installed!
• An example for a Windows Python 3.7 install in the directory where the whl files are located would be (in order):
  • pip install .\GDAL-3.4.2-cp37-cp37m-win_amd64.whl
  • pip install .\Fiona-1.8.21-cp37-cp37m-win_amd64.whl
  • pip install geopandas
• Integrate GeoPandas and start on a textured-polygon map import that is lat/long accurate. Start with Mercator?
• Start on one of the many papers that are due over the next few weeks

GPT Agents

• Got the EmbeddingExplorer App mostly done yesterday. Need to get author information for the other keywords, generate some corpora, and train a model!
• 4:00 Meeting

Book

• Roll in Brenda’s edits

Slow day. The SBIR meetings got delayed until the afternoon, so I worked on the TweetEmbedExplorer. There is a lot to the schema now:

And tooltips work!

Drop the truck off today

SBIRs

• 9:00 sprint review
• Write stories for next sprint

Book

• 4:00 meeting with Brenda

GPT Agents

• Wire up selections and generate a corpus!