Ethan Mollick Profile picture
May 23, 2022 11 tweets 6 min read Read on X
This paper outlines 7 classes of errors that destroy strategic decisions, ending with the epic-sounding Type VII Iatrogensis Cascade.

If you understand these errors, you will know what questions to ask to avoid strategic failures. So, a 🧵on seven types of errors... 1/9
Type I and II Strategic Errors are the most well-known. Type I Errors happen when decision-makers assume there is a relationship that isn't there. Setting up the Iraq War on the premise that there were weapons of mass destruction, without proof WMDs were real, is one example. 2/9
Type II Errors are when people assume a negative relationship and are wrong. When rolling out New Coke, the Coca-Cola company tested it on people who didn't drink Coke, who liked it more than Pepsi, but never tested it on regular Coke drinkers, assuming they would like it! 3/9
Type III Errors involve "solving the wrong problem very precisely." Technology companies fall prey to this often, rolling out carefully built products for markets that don't exist, and often ignoring larger, more important problems that linger because of misplaced effort. 4/9
Type IV Errors happen when organizations understand the right problem to focus on, but pick the wrong solution. Microsoft was right that computers needed to be easier to use... but they picked Clippy as the solution, rather than a deeper overhaul of how their software worked. 5/9
Type V Errors are taking action when you should not, often because you don't know enough. Think about launching the Challenger, rather than waiting for more information on the state of the O-rings that prevented fuel from leaking. A bias towards action can hurt you. 6/9
Type VI Errors are not acting when you should. Kodak waiting to commit to the digital camera technology it helped invent is one famous example. But there are many cases where decision-makers hesitate when action is needed, allowing windows of opportunity to pass. 7/9
Type VII Errors are worst. They happen when interactions between other errors lead to a failure cascade, turning the original normal problems into “wicked problems” that have complex & overlapping causes without simple solutions. Think the Iraq War & Subprime Mortgage Crisis. 8/9
Type I through Type VI errors can be avoided through good practice. Type VII cascades are hugely damaging & hard to predict.

Decision-makers can avoid cascades by asking yourself 👇 questions. You can also read the article, which is full of examples: 9/9 kimboal.ba.ttu.edu/Selected%20wri…
Cascades happen in complex systems, thus “all of the interesting systems (e.g. transportation, healthcare, power generation) are inherently and unavoidably hazardous.”

Read why complex systems fail. All 3 pages are in the images attached to this tweet. researchgate.net/publication/22…
In some ways, the huge interest on cognitive biases (which are important 👇) has distorted our views about why we fail.

Cognitive biases are generally things that effect individuals, but most large-scale failures are of systems & organizations, where the errors in the 🧵 live!

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More from @emollick

Dec 13
ChatGPT 5.2: "Build an interactive Excel spreadsheet where I can pick two D&D monsters to fight against each other and the spreadsheet simulates the combat somehow, including special abilities. Give a D&D look"

Thinking took 60 minutes(!) & had to have it fix an error, but cool Image
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Claude 4.5 Opus followed the same instructions very quickly, and with style, but simplified the problem to avoid using actual special abilities or status, just straight up rolls for damage Image
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Gemini 3 Pro. I really hope they add consistent ability to work with or download files. Image
Read 4 tweets
Dec 9
I did not expect that the PowerPoint killer would be something called Nano Banana Pro, but that is where its heading

It makes the major efforts by all the other AI companies, including Microsoft, to crack PowerPoint by using python seem like a dead end

ImageGen is all you need? Image
The thing is that NotebookLM can just take source materials, a topic, and an idea and make a very pretty, impactful deck.

Hallucinations are very rare, though there are still some spelling and graphics issues. Editing capability is apparently coming, but the direction is clear.
The slide deck is the result of me throwing my entire book into NotebookLM, by the way.
Read 4 tweets
Nov 23
Voice is one of the most useful ways to interact with AI to do work but it seems to have been semi-abandoned for serious use outside of the “chat with a friend” case.

All of the voice modes only access weak models with low latency, making them zippy & fun but kind of useless.
If you don’t think of voice models as a fun chat, but rather as a way of working, it suggests that pauses are fine, even preferred (don’t talk with me unless you have something to say). And alternative UXs beyond “talk with your AI about the weather” become possible to explore.
Also I want to turn off the breathing, giggling, and disfluencies. Anthropomorphism can be helpful in many cases but it gets to be too much, especially for serious discussions. The tone is off and it feels ingratiating and slows things down.
Read 4 tweets
Nov 21
I think my “otters on a plane using WiFi” may be a saturated benchmark now that nano banana pro can do this. Image
Prompt: Scientists who are otters are using a white board to explain ethan mollicks otter on a plane using WiFi test of AI (you must search for this) and demonstrating it has been passed with a wall full of photos of otters on planes using laptops
Read 4 tweets
Oct 27
Since there are so many AI announcements, my advice is to focus on those expanding what folks can do with AI (& especially tools that democratize who can use AI) rather than every single UX improvement

Skills, connectors & agents with file access/CLIs are especially interesting.
Next up: pay attention to expansions in artifacts/vibe coding for non-coders, specialized AI tools for industries outside of coding (see Claude Finance) and systems that take software people use every day and radically transform how they work using AI (Excel agents, for example)
Also interesting to watch ambitious new applications that are AI-native. What Google is doing with NotebookLM, for example, is basically creating an entirely new interface for working with information that is a pretty strong break with older ways of handling large amounts of info
Read 4 tweets
Oct 14
I don’t have much to add to the bubble discussion, but the “this time is different” argument is, in part, based on the sincere belief of many at the AI labs that there is a race to superintelligence & the winner gets,.. everything.

It is a key dynamic that is not discussed much
You don’t have to believe it (or think this is a good idea), but many of the AI insiders really do. Their public statements are not much different than their private ones.

Without considering that zero sum dimension, a lot of what is happening in the space makes less sense.
This is not the only way folks justify the large spend on AI buildout (and whether there is a bubble seems very far from obvious), but it is a dimension that does not show up in as many economic analyses as it should.
Read 5 tweets

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