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The AI Risk Klog

A risk-centric Knowledge discovery Log of articles, blog posts, podcasts, and observations in the journey to understand and adopt AI-related technology.
Keeping up with the breakneck rate of Artificial Intelligence (AI) innovation since the first public release of ChatGPT is practically impossible while holding a steady job. Everyone is struggling to develop a reasonably accurate and stable mental picture of AI, let alone of emerging applications, risks, and opportunities.
The bias of anything included herein reflects my and interest and expertise in the domain of and risk intelligence.
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Highlights #6: The Inevitability of Multi-modal Battlefield AI
6/14/2023
The focus of this knowledge discovery log remains that of AI applications in the intelligence analysis and decision support functions, all from the perspective of a risk JDM and mitigation professional. (I need to remind myself of this here and there as the emergence of fascinating AI-related conversations and applications only grows by the day - quickly pulling us in unrelated directions as we experiment with methods and tools with measurable value-add.)
The past couple of weeks have convinced me that an LLM-driven battlespace decision-support system appears increasingly inevitable if we consider results like that can move and act freely and purposefully in a simulated (Minecraft) or real environment. It’s an exceptional result that combines distinct tasks and tactical goals within a larger strategic objective. On the heels of and the growing data ingestion and , it seems inevitable that one such system will soon be substituting or, at minimum, complementing current military technology.
The most interesting articles and papers this week:
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Highlights #5: Transformers, Agents, and Toxicity.
5/14/2023
The avalanche of AI-related news and innovations didn't slow down much these past two weeks. From a technical standpoint, the most consequential announcements we saw involve the increasing number and power of ChatGPT/LLMs and - along with - extending (rather, exploding) these models’ power and potential. Early discussions about , and multi-model AI (with the obvious AGI implications) are becoming increasingly real, fast.
Our holds as these remain within the classes and scenarios that have been articulated for some time. That being said, all our on this subject were (astonishingly) accurately and elegantly summed up in an .
Here’s how would summarize the article:
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Highlights #4: AutoGPT, Jailbreaks, ...
4/18/2023
This past week’s release of was followed - as expected and without delay - by the first (and profoundly deflating) deployment of a , and accompanied by various . None of this is surprising or beyond the scope of the and, in fact, it confirms the critical issues of innovation speed and anticipated lack of self-restraint associated with this technology.
Many of us started experimenting with either localized LLM deployment, with open-source projects like , , and , or by bridging ChatGPT and proprietary content with LangChan (). But if all that is too much for you now, you can still get a sense of what a ‘chat’ with a specific/recent public or private document feels like with , which does a terrific job.
If the concept of synthetic relationships fascinates you as well, you may want to hear this with Noam Shazeer of . If you, like us, are approaching this subject from a risk intelligence perspective, you’ll find a certain naiveté about the entire venture (especially around min. 17), which is both disarming and terrifying at the same time.
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Highlights #3: Prompts, Search vs Chat, 3rd Party Apps,...
4/10/2023
"It's the Prompt, Stupid!" And indeed it seems AI-Whisperers and . From overnight marketplaces (, , , and so on) to Youtube classes, private training programs, and free, customizable, no-code apps like (which I found to be a great way to get some practice with structured prompting.)
One more Washington Post story about this:
The two biggest commercial races (at least, for the the next few months) are search integration and proprietary content 'ingestion'. On the former (B2C-first; how to transition from search behavior to a conversation) Bing has taken a bit of a lead on Google (despite what is probably the least imaginative UX solution of the decade), but others like and are trying to reinvent the search box, and they are worth checking out. On the latter front, the ChatGPT and , along with are likely to be carry the widest and most immediate business benefits.
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Highlights #2: Control, LLMs Limits, New/Small Models, ...
4/3/2023
Among the more frequent AI risk debates is that of control. On one extreme is the monopoly and dominance argument - one in which the number of state and commercial entities with the know-how and resources to develop and own such technology is increasingly small, and the race winner may achieve unprecedented hegemony, be it economic or geopolitical. On the other end, is the concern with unrestricted access to code, algorithms, and virtual machines capable of unimaginable harm. How the pendulum swings seems to change by the week, but if there is anyone with an opinion worth listening to is Matey Zaharia, CTO of , who in seems to suggest small models may be capable of achieving greater accuracy with smaller training sets than anticipated (hello VC, Are you listening?)
Directly related to the above, is the enduring debate about the strengths and weakness of Large Language Models (LLMs) vs Symbol Manipulation approaches, and I can't think of a more useful read than Gary Marcus' "Deep Learning Is Hitting a Wall" essay:
In this terrific Making Sense episode Sam Harris speaks with Stuart Russell and Gary Marcus about recent developments in artificial intelligence, the limitations of Deep Learning the long-term risks of producing Artificial General Intelligence (AGI), and of course, the control problem.
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Early Analytical Experiments
4/1/2023
Can ChatGPT facilitate structured (risk) intelligence analytical efforts? By its own response, it can. Yet, by now, we know that might be just an articulate and probabilistic answer. So we're putting some of these to the test, and getting very interesting results. Before stepping into specific methods, what is most impressive is the OpenAI’s capacity to perform content analysis on the fly:
Entity extraction (people, organizations, etc.)
Relationship mapping
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Yellow highlight = added/updated this weeks.
Selected News et al
0
4
Gizmodo
Disinformation
Incident
5/25/2023
5
arXic
Research
Alignment
Safety
5/25/2023
8
Washington Post
Incident
News
Disinformation
5/22/2023
9
Washington Post
News
Disinformation
Discussion
5/22/2023
12
Good Internet
Alignment
Discussion
5/18/2023
13
Discussion
Alignment
5/12/2023
14
arXiv
Research
Safety
Regulation
Discussion
5/11/2023
18
Wired
Alignment
Research
News
5/10/2023
21
BMJ Global Health
Research
Summary
Safety
5/9/2023
24
Politico
Discussion
Regulation
5/9/2023
32
NY Times
Summary
News
5/1/2023
35
The Verge
Regulation
4/29/2023
37
The Atlantic
Disinformation
News
4/28/2023
40
arXiv
Research
4/27/2023
43
Axios
Incident
Disinformation
4/25/2023
48
Simon Wilson’s Blog
Hacks
Safety
4/14/2023
51
NY Times
Disinformation
Discussion
News
4/8/2023
56
MIT Technology Review
News
4/3/2023
61
Center for Humane Technolgy
Alignment
Discussion
News
Research
Summary
3/24/2023
62
Future of Life Institute
Discussion
Safety
Regulation
Alignment
3/22/2023
65
Making Sense Podcast
Alignment
Discussion
Research
News
3/7/2023
68
NIST Artificial Intelligence Risk Management Framework
Regulation
Safety
1/15/2023
69
IARPA
Research
1/1/2023
70
UN Habitat
Regulation
Safety
Research
9/1/2022
74
Brace New Planet Podcast
Disinformation
Discussion
9/12/2020
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