Ethan Mollick Profile picture
May 4, 2021 7 tweets 4 min read Read on X
For May 4th, a lesson on how to sell new technology from Star Wars (& Edison). The key to the look of Star Wars ships are greebles: glued-on bits from off-the-shelf model kits of WWII tanks, planes etc. They make a connection with current tech, making Star Wars feel familiar. 1/ Image
To sell electricity, Edison used the same technique as the Star War's greebles by using skeumorphs (a design throwback to an earlier use) connecting his new scary tech to a familiar one: gas. Gas lights gave off light equal to a 12 watt 💡so Edison limited his 💡 to 13 watts. 2/ ImageImage
As another example, lampshades weren't needed for an electric light, since they were originally used to keep gas lamps from sputtering. But Edison added them anyhow. While not required, they are comforting and, again, made a greeble-like connection to the older technology. 3/ Image
He also developed the electric meter as a way of charging (because gas was metered) and insisted on burying electric wires (because gas was underground).

Edison made a trade-off by doing this, as it made the technology more expensive and less powerful, but more acceptable. 4/ Image
The process Edison used, called "robust design," helps make new technologies easier for consumers to adopt. The classic article by Douglas & @andrewhargadon is very readable, and explains a lot about how design helps new technologies get adopted. 5/ psychologytoday.com/sites/default/… Image
Ironically, while Tesla the person never learned this lesson from Edison, Telsa the company has. Electric cars could have plugs anywhere, so why does charging a Tesla feel like putting gas in a regular car? It’s skeuomorphic, linking the old to the new! 6/ Image
The lesson is useful for anyone creating new technologies. Steve Jobs famously insisted on skeuomorphic design in the original iPhone to make a series of complex apps easier to understand & work with at a glance. They might seem "outdated" looking, but they served a purpose! 7/ ImageImageImageImage

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More from @emollick

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
Oct 6
Very soon, the blocker to using AI to accelerate science is not going to be the ability of AI, but rather the systems of science itself, as creaky as they are.

The scientific process is already breaking under a flood of human-created knowledge. How do we incorporate AI usefully? Image
Science isn't just a thing that happens. We can have novel discoveries flowing from AI-human collaboration every day (and soon, AI-led science), and we really have not built the system to absorb those results and translate them into streams of inquiry and translations to practice
A lot of people are worried about a flood of trivial but true findings, but we should be just as concerned about how to handle a flood of interesting and potentially true findings. The selection & canonization process in science has been collapsing already, with no good solution
Read 4 tweets

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