We have a National Artificial Intelligence Advisory Committee

It seems like having a national artificial intelligence initiative is popular these days. Back on February 18, 2022, I shared my week 56 Substack post, “Comparative analysis of national AI strategies.” That missive continues to get a good bit of traffic so I thought now would be a good time to go ahead and revisit national AI strategies, advisory committees, institutes, legislation, and the myriad of research institutes or think tanks that are jumping into this area of consideration. This is an area that I think could be a good place for some solid academic contributions. Instead of digging into all of those areas my attention really got focused on one advisory committee. That will become clear here in the next couple of sections of content.

This week I have considered shifting The Lindahl Letter over to being an AI strategy advisory committee after spending a bunch of time reading about them this week. I’m not going to do that as it would limit my creative output to just one area and that sounds intellectually exhausting. One of them you can read about would be the National AI Advisory Committee (NAIAC) [1]. The next committee meeting was about to happen before writing this post. I had plans to listen live and I was totally signed up for everything [2]. Go forward I’m fully registered and signed up for alerts from the NAIAC. I would be happy to provide them guidance on effective national AI strategies from a comparative perspective, but that has not happened so far. This topic is an interesting space to consider at length. We are seeing a huge amount of academic work and companies like Hugging Face democratizing AI through community. Consider for a moment just how fast stable diffusion showed up and then was actively built into things and deployed. We are seeing massive changes within the ML/AI space and the deployment cycle is super-fast based on how interconnected the community happens to be worldwide. That has huge ramifications for any advisory committee considering the national level of AI strategy. Adapting to the rate of change and decentralized nature of things requires a different type of national AI strategy. I’ll be listening to the NAIAC in October to see how things are going. You can find the sessions on YouTube by searching for “NAIAC” pretty easily.

“National Artificial Intelligence Advisory Committee (NAIAC) Meeting”

“National Artificial Intelligence Advisory Committee (NAIAC) Field Hearing”

You could read the meeting minutes from May 4, 2022.

https://www.ai.gov/wp-content/uploads/2022/07/NAIAC-Minutes-05042022.pdf

I went out to Google Scholar and took a look to see if anybody had published or shared anything with this advisory committee referenced [3]. Nothing really came up except the above-mentioned meeting minutes from May 4, 2022. Nothing really showed up during a search of arXiv either [4]. It’s possible in about 6 months more content will show up reacting to the hours of meetings that are linked above. Right now, we appear to be a little bit ahead of things in terms of reactions to the work being done by this advisory committee. I’m going to keep an eye out for more content related to NAIAC. It’s possible sometime next year it will be the right time to dig back into this one.

Links and thoughts:

“5 Practical Machine Learning Lessons You’re NOT Taught in School”

“This Has Never Happened Before - WAN Show October 14, 2022”

“Stanford CS330: Deep Multi-Task & Meta Learning I 2021 I Lecture 4”

“Confusing new Apple products, Netflix password sharing, and NFT cults”

Top 5 Tweets of the week:

Santiago @svpino

I read this book and sent a message to both authors. I asked them a simple question: "What are the most important practical lessons for people in machine learning?" Here is what they answered: youtu.be/_b-zoloQ14s

Dr. Nels Lindahl @nelslindahl

Saturday podcast recording...

The Verge @verge

Elon Musk reportedly wants to fire most of Twitter’s employees theverge.com/2022/10/20/234…

Sports Card Investor @SportsCardInv

What’s the card that Adam Sandler will be chasing after? https://t.co/NB8SMqm5PC

DiscussingFilm @DiscussingFilm

The Safdie Brothers’ next film, starring Adam Sandler, is reportedly set in the world of high-end sports card collecting. (Source: Deadline) https://t.co/fjEboggu0m

Adam Olshansky @adam17amo

Great advice for advocating for yourself! If you don't keep track of your accomplishments, no one else will. I also mark positive feedback emails with a specific tag so they're easy to find for performance reviews

LeeAnne Rimel @leeanndroid

I’ve worked w @MikeGerholdt for 8yrs and he has given great advice. One of his recommendations that I share most often with colleagues and mentees is this: Make it easy to share your wins and advocate for your career. Always be building a brag book. Here’s how I do it

Footnotes:

[1] https://www.ai.gov/naiac/

[2] https://events.nist.gov/profile/form/index.cfm?PKformID=0x17861abcd

[3] https://scholar.google.com/scholar?hl=en&as_sdt=0%2C6&q=National+Artificial+Intelligence+Advisory+Committee&btnG=

[4]

https://search.arxiv.org/?in=&query=%22National%20Artificial%20Intelligence%20Advisory%20Committee%22

What’s next for The Lindahl Letter?

• Week 93: Papers critical of ML

• Week 94: AI hardware (RISC-V AI Chips)

• Week 95: Quantum machine learning

• Week 96: Where are large language models going?

• Week 97: MIT’s Twist Quantum programming language

I’ll try to keep the what’s next list forward looking with at least five weeks of posts in planning or review. If you enjoyed this content, then please take a moment and share it with a friend. If you are new to The Lindahl Letter, then please consider subscribing. New editions arrive every Friday. Thank you and enjoy the week ahead.