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

Just realized that Fritz Lang’s Metropolis is an example of a deepfake/KillerApp:

 …the false Maria unleashes chaos throughout Metropolis, driving men to murder and stirring dissent among the workers.

https://en.wikipedia.org/wiki/Metropolis_(1927_film)

Deepfake Kari Lake video shows coming chaos of AI in elections

• They brainstormed ideas for about a week and enlisted the help of a tech-savvy friend. On Friday, Stephenson published the piece, which included three deepfake clips of Lake.

Drove back from Greenville NC yesterday. Eleven hours or so. Electric cars are still not common on the long stretches between cities. I live in the Baltimore/DC region, and I’d say 1 in 20 cars that I see on the roads at this point is electric, with a big mix of manufacturers. Still mostly Teslas. On my drive, I only saw Teslas, and not very many of them. Charging infrastructure is solid. Leaving with a full charge, it required 2 SuperCharger recharges to cover the 535 miles. Probably $20 in electricity? And autopilot makes everything much nicer, though you always have to be ready for phantom braking.

Need to ping Mario, Ossi, and James about Eclipse coordination

IUI 2024 Notes

Information visualization and Visual Analytics

• Assessing User Trust in Active Learning Systems: Insights from Query Policy and Uncertainty Visualization – Active learning, where the machine asks for help if uncertain. This is human ESDT. Numeric labels seem to help the most over other graphical visualizations. Like a picture with a xx% confidence seems best.

25% confident

• iScore: Visual Analytics for Interpreting How Language Models Automatically Score Summaries – rates model rating of essays. Word replacement with synonyms allows the model to detect the salience of particular words in the grades. It would be interesting to try this with tests like GPTZero to see what they are looking for. Yes, they do have an API, so this would be straightforward?
• SlopeSeeker: A Search Tool for Exploring a Dataset of Quantifiable Trends. A good point here for our conversational interfaces. We may need to train (or prompt-tune?) models to be able to discriminate behaviors from the simulation in ways that can be articulated by the LLM
• Visual Analytics of Co-Occurrences to Discover Subspaces in Structured Data – a tool for exploring really large datasets. Like the Blackrock problem? It sort of resembles the way that I set up spreadsheets some times? And in fact, I think you could process the data and make it spreadsheet compatible.
• AutoML: A Visual Analytics Tool for Understanding and Validating Automated Machine Learning. Looks like a useful tool for building and evaluating models. I’d be curious how it would work with the JSC data. Worth watching the video, if its available. Shown using AutoSKLearn. Not sure about parallelization like raytune. Code is online.

Applications of Language Models

• Empirical Evidence on Conversational Control of GUI in Semantic Automation – conversational interface to access db. JSON-2-JSON transformer.
• FigurA11y: AI Assistance for Writing Scientific Alt Text – this looks like a really nice tool to generate alt-text and the code exists on GitHub. Not sure how easy to build, but worth trying. It would be interesting to see how the text could be incorporated in the body of the text as well, particularly in cases where the image needs to be pulled for length.

Generative AI: Theory and Applications

Got accepted for my talk at the 92nd MORS symposium!

IUI 2024 Notes

I had an interesting chat yesterday with Ossi about Active Measures Leading up to and since October 7. We need some time to sit down and talk. My sense is that all sides have been under prolonged external influence for a long time with the specific intent to raise the political temperature so that exactly this situation happened.

Keynote: Prof. Krzysztof Gajos (check Google Scholar for references)

• Predictive text can manipulate the users, who wind up reflection the biases of the predictive text model. Change the organization’s model, change the bias of the organization.
• The mere presence of an explanation increases the credibility of AI assistance, regardless of the content. Fact-like assertions increase the perceived competence of the AI. This is a dark pattern that needs to be detected.
• Learning means that cognitive engagement occurs, but AI answers vs. cognitive forcing does not impact the amount of learning
• Providing the material to support a decision but not a decision suggestion, worked better than any answer-based decision aids. This may be a key for complementation
• Denial of a request is treated emotionally, not cognitively. This is another vector that needs to be recognized and adapted to. A source could be paper submission rejects.
• Critical techical practice – question assumptions

HCAI, Bias and Fairness in AI

• BiasEye: A Bias-Aware Real-time Interactive Material Screening System for Impartial Candidate Assessment – really good visualizations for decision support. An interesting use of an LLM to take the data from a form. The rest is mostly statistical comparisone between students. I wonder if this would be another way to have operators rate models. One of the most interesting visualizations was to use TSNE to cluster similar students on a canvas, where each student was a set of concentric pie charts that showed the difference between actual and expected performance. Also, lot’s of culture-specific measures such as “honor”
• Understanding Users’ Dissatisfaction with ChatGPT Responses: Types, Resolving Tactics, and the Effect of Knowledge Level – looks like it might be a really good source of working out a framework for evaluating effective conversational interfaces – what works, what doesn’t, etc.

Lunch ride!

AI Tools, User Interfaces and Interaction

• SpaceEditing: A Latent Space Editing Interface for Integrating Human Knowledge into Deep Neural Networks – This is an interesting take on hand-tweaking the manifold projection. It might be very good for DTA

AI for Health

• How Do Users Experience Traceability of AI Systems? Examining Subjective Information Processing Awareness in Automated Insulin Delivery (AID) Systems – Informational awareness. Nice perspective on AI Operators

Dinner Banquet – fun 🙂

Had a thought for the day. For a learning assignment, have students build a context prompt that lets an LLM answer a question on the rubric correctly. Bonus points if the models is able to answer a question that is outside the domain where a raw LLM has struggled. This way you have a project that requires students learning the topic, and also exposes them to weaknesses and strengths of LLMs. Not sure if this is a good idea, but it could be worth poking at.

Did my talk and demo at HAI-GAN yesterday. It went well, but I had forgotten my poster! I ad-hoc-ed on with the hotel printer and my slide deck:

Some really interesting talks:

• ExpressEdit: Video Editing with Natural Language and Sketching
  • Neat work on a very hard problem
• Intent Elicitation in Mixed-Initiative Co-Creativity
  • Collaborative storytelling with LLMs and Stable Diffusion at Midjourney.
• Deriving Desirable Artistic Generative Distributions from Individual Identity Statements
  • This one in particular had some really novel work. One idea that she mentioned almost in passing was the idea of latent mode collapse, which is a technique that I think I could use to recognize stampede behavior.
• Teaching Middle Schoolers about the Privacy Threats of Tracking and Pervasive personalization: A Classroom Intervention Using Design-Based Research
• Though no one made a presentation about it, the idea of prompt swarms in some form came up multiple times. Still nothing about maps or even about studying the structures that contain knowledge/narratives in LLMs

Main conference starts today. I’ll post notes here:

• Keynote – pathsto effective AI for diverse real people
  • Stumble forward empirracally
  • Draw from the field of education (e.g learning goals imply associated measures)
  • Add “after actin review” to your AI design – one of the things that seems to help is letting users come up with their own labels for things, which helps building abstractions that help overall understanding
  • Measure inclusiveness, and determine the why (GenderMag survey? Also SocioeconomicMag, AgeMag, InclusiveMag)
    • More inclusive designs of humans+AI ecosystem
    • Persona-based AI debugging

Got to chat with Mauro Martino about maps a bit

Sesssion 1:AI in Personalization, Recommendation and Search

Multimodal Models and Interaction

• Conan’s Bow Tie: A Streaming Voice Conversion for Real-Time VTuber Livestreaming – uses RNN for real-time predictive voice conversions. This could be generalizable? Less lag in video chat, or even remote robotics. Need to reach out possibly.
• ReviewFlow: Intelligent Scaffolding to Support Academic Peer Reviewing
• Accuracy-Time Tradeoffs in AI-Assisted Decision Making under Time Pressure
• Impact of Voice Fidelity on Decision Making: A Potential Dark Pattern? Nice chat. Maybe write a provocation for CUI?
• Slicing, Chatting, and Refining: A Concept-Based Approach for Machine Learning Model Validation with ConceptSlicer – definitely something for AI operators
• VMS: Interactive Visualization to Support the Sensemaking and Selection of Predictive Models – nice visualization for AI Operators. And a demo!

Poster session. Met a bunch of nice folks, and had a longer chat with Mauro. Need to follow up.

No idea what to make of this:

• Red Dragon 1949.com is the premiere global web location for all updated information focused on the People’s Republic of China. Our intent is to develop a mutual cooperation and understanding of how the Internet and connected systems can be used by a nation state as a military weapon system.

Dammit

• De Waal, Charles Howard Candler Professor Emeritus of Psychology and former director of the Living Links Center for the Advanced Study of Ape and Human Evolution at the Emory National Primate Research Center, was 75.

Chores

• Drop off truck
• Haircut
• Slide backup
• Laundry
• Get gas for mower
• Weed
• Mow lawn
• Clean house
• Pack!
• Note!
• Trash

Kind of an interesting take on a way that white hat AI could work. Something like AI-generated annotations for all the manipulations we are being exposed to and the way that it is supposed to make you feel. And a knob that replaces the manipulative text with neutral text (possibly with whitelist fact checks):

Yikes: Human-caused climate change fuels hottest February on record, all-time high ocean warming

• “It’s looking like the entirety of the Southern Hemisphere is probably going to bleach this year,” said ecologist Derek Manzello, the coordinator of NOAA’s Coral Reef Watch which serves as the global monitoring authority on coral bleaching risk.

Chores

• Call dentist
• Get gas for mower
• Get Hotel
• Clean house
• Change pedals on Brompton and inflate tires

SBIRs

• Slides for standup and stories
• More content on AI attack vectors: Propaganda is dangerous, but not because it is persuasive
  • mobilisation and coordination (encourage and recruit people to your cause who already agree with you, and/or let’s them find each other)
  • signalling permission (shows the government won’t punish certain actions which might normally be illegal)
  • crowding out dissent (degrades the public conversation, changes the topic, or absorbs everyone’s energy in discussions which are ultimately distracting).
  • sowing distrust, confusion, animosity (hinders coordinated action against the propagandist).
  • helps make dissent less visible (e.g. by signalling what will be punished)
  • loyalty test or status display (some propaganda is so patently untrue that repeating it is a strong sign that you are willing to humiliate yourself in service to those in power).

Happy Pi Day!

Hotels!

A Practical Guide for OSINT Investigators to Combat Disinformation and Fake Reviews Driven by AI (ChatGPT)

• The internet is being flooded with disinformation and fake reviews, generated by users of AI tools such as ChatGPT, with malicious intent. In this report based on firsthand research, ShadowDragon® outlines how to identify AI generated materials online that are intentionally spreading false information or even intended to incite violence.

SBIRs

• 9:00 standup
• 9:30 some proposal thing? Prep and followup.
• Send in poster and other HAI GEN stuff
• Slides for standup and stories

GPT Agents

• Some very promising venues from the IEEE. These are “magazines,” not journals or proceedings, which might mean something arcane?
• IEEE Technology and Society Magazine
  • The following topics describe the scope of IEEE Society on Social Implications of Technology (IEEE SSIT) and of IEEE Technology and Society Magazine: Health and safety implications of technology, Engineering ethics and professional responsibility, Engineering education in social implications of technology, History of electrotechnology, Technical expertise and public policy, Social issues related to energy, Social issues related to information technology, Social issues related to telecommunications, Systems analysis in public policy decisions, Economic issues related to technology, Peace technology, and Environmental implications of technology. Beyond these specific topics, IEEE Technology and Society Magazine is concerned with the broad area of the social implications of technology, especially electrotechnology.
• IEEE Security & Privacy
  • IEEE Security & Privacy is the premier magazine of the IEEE Computer and Reliability Societies for informing their members about recent and forthcoming advances in information technology pertaining to security, privacy, and dependability. The magazine seeks creative and novel perspectives on industry practices, research directions, and policy and regulatory matters.  In addition to feature articles, special and themed issues, columns, and departments, experts from our community of interest provide insightful commentary on current issues and paradigm shifts via virtual roundtables and podcasts. 

Electric Sheep on the Pastures of Disinformation and Targeted Phishing Campaigns: The Security Implications of ChatGPT

• This article explores the potential for the criminal abuse and hybrid-warfare weaponization of ChatGPT technology. The focus is placed on the opportunities for the possible utilization of such tools by malign actors who engage in the orchestration and running of targeted phishing campaigns or who design, produce and propagate disinformation. The author raises the question about the ethical, moral and legal implications of similar technologies and opens the discussion on the responsibility of technology developers for the abuse of their products and on the topic of the IT industry governance.

Home battery visit – and shelving!

SBIRs

• Editing pass through white paper – done. Aaron thinks we should add some JSC and MDA. Done, unless LM provides additional info
• Prep slides – cut down to 16 slides. I have to see if that will fit in 10 minutes.
• Pick up poster

This is brilliant. and it cuts to the heart of the coming pancake printer economy: How Will The Golden Age Of “Making It Worse” End?

SBIRs

• 2:30 AI Ethics?
• Today is pretty much working on the white paper. Still no response from Matt about our questions
• Finished the synthetic logs and VRL sections
• Getting information on the mission planner. Got enough to put something together
• DONE! First draft at least. Waiting for more info. But I think it’s ok even if LM doesn’t respond