Matt Clancy
@mattsclancy · Des Moines, IA · joined 27 Mar 2012
Abundance and Growth Fund Program Director at @coeff_giving. Creator of https://t.co/dYDulHqlOs. See https://t.co/6EvVGkycU7 for more.
10 045Followers
1 788Following
10 880Posts total
69.2KViews on collected posts
Latest posts
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I have some thoughts on why economists and technologists can't agree here: https://t.co/Lr255Lvxkk
10.8K views · 44 likes
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Part of a thread about how UK college students are changing their majors in the era of generative AI.
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Meanwhile, our analysis also shows that the labour market prospects for juniors have deteriorated for graduates from these programs. Students are thus moving toward subjects in which entry-level jobs are declining. https://t.co/S5zOjXDRg0
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@mattsclancy Sounds more like a sociological explanation. I am more interested in early indicators of which position is right, such as the bet between two opposing economists (https://t.co/zjeeFmSgET), in which @erikbryn's AI optimism seems likely to be validated?
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PS - special thanks to @michael_nielsen for a Twitter exchange (years ago) which pointed me down this train of thought! 9/8
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I give some other examples about how the two sides think about the power and limits of intelligence and technology - check the whole thing out here. https://t.co/Lr255Lvxkk 8/8
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Another example: if you’re an economist, you’ve been taught through years of practice to focus on marginal changes - tweaks to the status quo. A prediction that slightly changes the trend feels better than predicting a discontinuous change. 6/8
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The opposite might be true for a technologist: in Silicon Valley you’re looking for a zero-to-one idea, not an incremental tweak. Predictions about big changes don’t feel as uncomfortable. 7/8
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For example: economists tend to think it’s hard to shift economic growth. Not just because it’s been steady a long time, but also because economists who work on policy or economic development have struggled for decades to find reliable ways to sustainably lift it. It’s hard! 4/8
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For comparison, if you are a technologist, the growth rates of companies might be more resonant than the growth rate of the economy. These are highly volatile but if you find product-market fit, they can go up at explosive rates. 5/8
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But why do they start so far apart?
The piece describes some implicit beliefs economists have, which contribute to their initial skepticism. And I speculate about the different experiences technologists may have had, which makes them receptive. 3/8
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Link: https://t.co/Lr255Lvxkk
I argue the biggest problem is simply that the evidence is ambiguous.
Faced with arguments that are consistent with either explosive growth or business-as-usual, people don’t move very much from where they start. Which is far apart. 2/8 https://t.
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Is AI going to lead to a century of progress over ten years?
I have a new piece in Asterisk’s newsletter about why all the arguing in the world often fails to lead to agreement on questions like this. 1/8 https://t.co/xQPNUYfeUE
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I didn’t know this! The next tweet in the thread notes this is driven by religiosity and when you control for that the correlation disappears.
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GDP per capita is super strongly correlated with life satisfaction across countries - but *negatively* correlated with meaning/purpose
The AI-makes-us-all-rich future: lots of hedonic satisfaction, little eudaimonia?
from @BetseyStevenson https://t.co/fcnhWcbIuQ
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The Abundance and Growth Fund goal is to raise broadly shared economic growth. We support work ranging from research to fieldbuilding to practice, with an initial focus on innovation, energy, clinical trials, housing, and state capacity. More here! https://t.co/Wjv6evohYI
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Against accounts of the same size
15 posts from the last 90 days, next to the 10K–100K follower range. shown far beyond its own audience, and the audience reacts.
Median views766this account924median for 10K–100K
Reach, %7.63%this account3.62%median for 10K–100K
Engagement, %1.96%this account1.52%median for 10K–100K
| Metric | This account | Median for 10K–100K | Ratio |
|---|---|---|---|
| Median views per post | 766 | 924 | 0.83× |
| Reach (views ÷ followers) | 7.63% | 3.62% | 2.11× |
| Engagement rate | 1.96% | 1.52% | 1.29× |
Others in this range → Compare with another account → How these benchmarks are built →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
2.2K18 Aug
21.9K20 Aug
1.3K
766
576
615
534
560
608
584
132
1.8K26 Aug
1.2K
10.8K2 Sep
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.60%18 Aug
0.85%20 Aug
1.59%
1.96%
2.78%
2.44%
2.25%
2.14%
1.97%
2.05%
3.03%
0.38%26 Aug
0.08%
0.49%2 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes64.3%642 in total
Reposts11.6%116 in total
Replies3.6%36 in total
Quotes1.6%16 in total
Bookmarks18.9%189 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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