SBIRs

• Big kerfuffle on the report yesterday afternoon. As a result, I just worked on it till it was done. Submitted this morning to show my commitment. Sigh
• Need to work on the slide deck today but my motivation is lacking

World’s First AI Pageant To Judge Winner On Beauty And Social Media Clout

SBIRs

• Fold KillerApps slides into presentation, then start thinking about images
• 9:00 standup
• 2:30 AI ethics maybe?
• Need some guidance on the way to handle the “culling,” which I think is going to be pretty weird unless the writing around the culls are reworked.

Conquering the COVID-19 Infodemic: How the Digital Black Press Battled Racialized Misinformation in 2020

• In 2020, as many Black people around the world fought both anti-Black racism and COVID-19, the Black press in the US was dealing with another widespread problem: an infodemic. Editors of Black digital publications were on the frontlines of dispelling racialized misinformation about COVID-19, all while reporting on a contentious presidential election, ongoing protests for racial justice, and a rising COVID-19 death toll that disproportionately affected African Americans. This mixed-methods study—which includes semi-structured interviews in addition to website and social media analyses—explains the top five tactics that Black outlets used to serve as an advocate for, and an adviser to, their communities during its time of dire need. Their strategies provided an editorial slant that challenged anti-Black racism in public discourse and countered misinformation with factual public interest journalism.

SBIRs

• Driving 4 hours for a 2 hour meeting
• It went pretty well, but Dr. J was a no show. Everyone is very interested in MP-type stuff, so I think we should organize the DTA work to produce a demo along these lines, maybe within the context of the MDBE. That could look very fancy.
• Wrote up a easy to read Monte Carlo Markov Chain description.
• The big use for NNMs (that no one can grok) is the visualization and prediction of mismanagement. It’s all people talk about in these places.

Markov Chain Monte Carlo: Exploring Probability Through Random Walks

Imagine you’re trying to figure out how effective a new drug is at treating a disease. The traditional statistical methods might not work very well because the problem is too complex – there are just too many factors to consider. This is where Markov Chain Monte Carlo (MCMC) can really shine.

MCMC is a powerful technique that combines two key ideas: Markov chains and Monte Carlo simulations.

A Markov chain is a sequence of events where each step only depends on the previous one. It’s like a random walk, where your next move is based only on where you are now, not on your whole history.

Monte Carlo simulations, on the other hand, are all about playing with randomness to find answers. Instead of trying to calculate everything exactly, you take a bunch of random samples and use those to estimate what you want to know.

Put these two ideas together, and you get MCMC. The basic process is:

• Start with an initial guess about the drug’s effectiveness.
• Take a small, random step from that starting point. This step represents the uncertainty or noise in the data.
• Decide whether to keep this new guess based on how well it fits the data you have. The better it fits, the more likely you are to accept it.
• Repeat steps 2 and 3 many, many times.

Over time, as you keep taking these random steps and accepting or rejecting them, your guesses will start to converge towards a meaningful result. This convergence is key – it tells you that the MCMC process has thoroughly explored the probability distribution and found a stable estimate.

MCMC is really powerful because it can handle complex models and uncertainties that would be very difficult to deal with using traditional methods. In our drug example, MCMC could help you estimate the drug’s effectiveness while accounting for all sorts of factors like patient characteristics, side effects, and so on.

The great thing about MCMC is that it’s flexible and can be adapted to all kinds of research problems, from predicting disease progression to optimizing drug combinations for cancer treatment. By leveraging the power of random walks and probability, MCMC can turn complexity into clarity and uncertainty into insight. It’s a truly remarkable tool in the researcher’s toolkit.

Chores:

• Call Jim Donnie’s
• Schedule oil change

SBIRs

• Finishing and submitting CUI paper
• 4:30 Book club
• Installed an ancient printer driver and it worked!

GPT Agents

• 2:00 LLM Meeting

The eclipse was cool. Even with clouds, it’s magical:

That’s the view to where the sun is still shining. We could also see the eclipse faintly through the clouds, which must have been how most people saw it before rapid travel. The light was so faint, it was easy to imagine the sun and the moon fighting. I swear I saw sparks.

SBIRs

• Finish CUI paper (done!) and prep for submit (topics, keywords, etc)
• Add UMBC talk to stories – done
• Contact Ian with info – done. Looks like it is a 1 hour talk!
• Respond to Kate S.

Prepping to go to the Eclipse! The forecast is looking pretty good!

SBIRs

• Need to add a story on the April 22 presentation to the IS Dept. Also need to write up the abstract!
• Work on the CUI 2024 submission. Had some fun with MidJourney making a teaser image. I need to brush up on blending in Photoshop

GPT Agents

• Nice chat, went over the white hat AI concept some more. Maybe something for an NSF proposal?
• 4:00 Meeting at UMBC. I got to play wise sage. Fun!

Dont you (forget NLP): Prompt injection with control characters in ChatGPT

• As part of this work, we recently observed some unusual behavior with two popular large language models from OpenAI, in which control characters (like backspace) are interpreted as tokens. This can lead to situations where user-controlled input can circumvent system instructions designed to constrain the question and information context. In extreme cases, the models will also hallucinate or respond with an answer to a completely different question.

SBIRs

• 2 hour meeting in Moorestown with a 2.5 hour drive each way. Not sure it’s worth it, but the meeting went well,
• Closed out my stories, made slides, and created new stories. Still need to do one for the IS Dept presentation on the 22nd

5:00 power washer

CUI 2024 paper:

• Distorting the truth versus blatant lies: The effects of different degrees of deception in domestic and foreign political deepfakes
• Detecting Video Speed Manipulation
• Situational Awareness of Deepfake Technology
• AI Is Not a Unitary Actor: My Response to the UN Interim Report Consultation: “the limits of the almost supernaturalist framing of AI as a unitary actor, rather than a suite of techniques. More useful for the report overall would be of AI as an extension of our human capacities of reasoning, action, and perception that alters what we can do, and therefore our obligations, especially as governments.“
• Made good progress on “The Voice in the Machine” section

SBIRs

• Slide deck and stories for Monday – put in a story to make a sandbox project using a makefile. cookiecutter, name, venv, and source.

GPT Agents

• 3:00 Alden

Need to move the crown appointment

Review board faults Microsoft for ‘cascade’ of errors in China hack

• The report details what it calls a “cascade of avoidable errors.” For instance, Microsoft had not noticed the presence of an old signing key from 2016 that should have been disabled but wasn’t. “That one just sat for years, kind of forgotten,” a second person said. Part of the problem was that Microsoft was supposed to switch from a manual key rotation to an automated system that minimized the chance of human error. But that switch never happened. “They never prioritized fixing the problem,” the first person said.

SBIRs

• More CUI paper. Bring in papers on dark patterns in CUIs and CSCW
• 9:00 Standup
• Ron’s in today? Maybe more setup. Done! Wrote up a story too.
• AI Ethics?
• MCML?

Call powerwasher

SBIRs

• Working on the CUI paper
• Did the vague letter thing. Still not sure why anything should happen, but it’s an encantation maybe?

Pick up the truck if the rain stays away this morning – done!

Good Organizational Lobotomy writeup: The Descent of Elon Musk

SBIRs

• Made good progress on the LLM notes yesterday. Waiting for the AWS instance to get turned on so I can play with UMAP. Got a lot done, though there are resolution issues that need to be worked out.
• 9:00 Standup – done
• 11:30 CSC touchpoint – done
• 1:00 Cyber COP presentation – done, and went well.

GPT Agents

• LLM Meeting – went over the NNM work with Shimei
• Started on CUI provocation. As part of that, I’ve started reading Tim O’Reily’s biography(?) of Frank Herbert. It’s really good. He also says that Dune is an alternate Foundation, and Paul is The Mule. Fascinating.
  • In Dune, each of the players—the Emperor, the Baron Harkonnen (archenemy of the Atreides), the monopolistic Spacing Guild, even the seemingly wise Bene Gesserit gene manipulators—tries either to dominate the situation or to control it in such a way as to minimize his own risks. And in the end all are overwhelmed. The elemental forces of history can only be ridden, not controlled. Paul alone is victorious, because he chooses to ride the whirlwind. He risks everything. His initiation by the Fremen into riding the sandworms is symbolic of his choice. These predators represent all the elemental forces of Arrakis: their native name means “maker,” and they are the heart of the ecological matrix of the planet, source of the spice, the sand, and thief of water. And, like nature itself, they abhor artificial boundaries; they are drawn irresistibly to destroy the protective energy shields relied on by off-worlders. They close the desert to all who try to isolate themselves from it; only the Fremen “sandriders,” who move with the rhythms of the desert, and mount the fearsome worm, can brave its wilds.
• Start White Hat AI section – tomorrow?

AI experts: Racist audio of Baltimore County principal’s voice is fake – The Baltimore Banner

• The Eiswert audio, Lyu said, shows the danger of the degree to which artificial intelligence could be used to harm individuals. When deepfakes are used on celebrities or well-known political figures, they are easier to detect, both because there’s an abundance of video and audio of their voices and so the public is more likely to believe and spot a fake. “If they are focusing on less prominent people … the damage they are causing is bigger.”

Example: Pandas Excel output with a chart

##############################################################################
#
# An example of converting a Pandas dataframe to an xlsx file with a chart
# using Pandas and XlsxWriter.
#
# SPDX-License-Identifier: BSD-2-Clause
# Copyright 2013-2024, John McNamara, jmcnamara@cpan.org
#

import pandas as pd


# Create a Pandas dataframe from some data.
df = pd.DataFrame({"Data": [10, 20, 30, 20, 15, 30, 45]})

# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter("pandas_chart.xlsx", engine="xlsxwriter")

# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name="Sheet1")

# Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets["Sheet1"]

# Create a chart object.
chart = workbook.add_chart({"type": "column"})

# Get the dimensions of the dataframe.
(max_row, max_col) = df.shape

# Configure the series of the chart from the dataframe data.
chart.add_series({"values": ["Sheet1", 1, 1, max_row, 1]})

# Insert the chart into the worksheet.
worksheet.insert_chart(1, 3, chart)

# Close the Pandas Excel writer and output the Excel file.
writer.close()

SBIRs

• Spent some time adding references to the slide deck
• Add a “to_excel()” method – done
• Meet with Aaron to set up AWS for UMAP? Things are working, but I don’t have an instance. Blocked for now
  • Install ecco
  • Install HFace
  • Maybe langchain?
• 1:30: LLM UI Tools – done

GPT Agents

• Meeting with Alden

Here’s Google’s generative API/playground/documentation site: Vertex AI

SBIRs

• 9:00 standup. Going to go over the IUI conference
• Working on the NNM again. Just getting back into things and generated a cosine similarity (by layer) to the average vector for each layer:

• Although it looks interesting, I think it would make more sense to export as a spreadsheet to show numbers and colors. Also, I’m not convinced that this is the right way to go. I’d like to try UMAP, but can’t get it to behave on my box. Going to try spinning up an instance on AWS

On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

• The development and popularization of large language models (LLMs) have raised concerns that they will be used to create tailor-made, convincing arguments to push false or misleading narratives online. Early work has found that language models can generate content perceived as at least on par and often more persuasive than human-written messages. However, there is still limited knowledge about LLMs’ persuasive capabilities in direct conversations with human counterparts and how personalization can improve their performance. In this pre-registered study, we analyze the effect of AI-driven persuasion in a controlled, harmless setting. We create a web-based platform where participants engage in short, multiple-round debates with a live opponent. Each participant is randomly assigned to one of four treatment conditions, corresponding to a two-by-two factorial design: (1) Games are either played between two humans or between a human and an LLM; (2) Personalization might or might not be enabled, granting one of the two players access to basic sociodemographic information about their opponent. We found that participants who debated GPT-4 with access to their personal information had 81.7% (p < 0.01; N=820 unique participants) higher odds of increased agreement with their opponents compared to participants who debated humans. Without personalization, GPT-4 still outperforms humans, but the effect is lower and statistically non-significant (p=0.31). Overall, our results suggest that concerns around personalization are meaningful and have important implications for the governance of social media and the design of new online environments.

Tasks

• Dentist!
• Truck? – Nope. Should be ready Friday
• Eclipse email

SBIRs

• Expense report
• Put together a set of slides that covered what I thought was interesting at the conference
• CUI Provocation
• Killer Apps post for HCAI Medium Magazine(?)
• 4:00 meeting with Bob S. to go over the MP part of the LM white paper
• Need to get back to NNM