I personally agree that the future is getting less predictable & AI in particular is going to falsify a huge overhang of extant long-term predictions which have misleadingly-good track records because they are predicated on AI never happening. But to bracket my personal opinions, how would one measure such things as 'people *think* the future is getting more/less predictable' or 'the future *has* been getting more/less predictable than people thought'? Some possibilities:
- prediction market forecasts being systematically overconfident: have PredictIt or Metaculus contracts been expiring with worse Brier or other proper scoring rule results when grouped by year? Is GJP's accuracy decaying? Are the old historical predictions from Tetlock's expert surveys getting worse over time?
- prediction market prices being higher variance: prices reflect information & certainty, so if the future has been getting harder to predict, then price time series should be increasingly volatile
- similarly, futures markets: volatility and the risk premia of long-dated options can either be higher or lower than in earlier time periods. (The future may be richer or poorer, but any change in levels would be reflected in the base price.)
- insurance costs: ditto---the riskier the future, the higher premiums must be charged. (eg.can you still buy cheap longevity insurance or annuities? If so, then insurers apparently don't believe that anti-aging research is going to pay off.)
- interest rates: interest rates reflect the desire to trade less money now for more money later, and incorporate a lot of things like nominal inflation or demographic trends like retirement planning, but also include risk such as expropriation or disaster or just the opportunity cost of being locked into the wrong investment. So at a simple first look, higher interest rates imply a more unpredictable future and vice-versa.
- conversely, debt loads: debt is dangerously fixed, so one will prefer debt to equity if the future is predictable and you can count on the cash flows to service it. On an individual level, things like student loans or house mortgages are commitments to a predictable future.
- social/geographic mobility: people will prefer buying houses to renting or staying put the more predictable the future, because the less the optionality is worth. (If you know the future, you either have moved to the right place already or you know there's nothing better out there.)
- creative destruction and turnover in the economy, especially of large corporations
- increased contracting and regulation, redistributive politics, larger governments as % of GDPs etc
- demographics: the older and more female a population, the less you expect any radical revolutions or uprisings which would spoil your predictions; violence is a young man's game.
Again bracketing AI out, my impression is that over the past 2 decades, pretty much all of these have trends consistent with believing a more rather than less predictable future. What we see is a world where aging populations and governments invest ever more into various kinds of 'insurance' and avoiding any consequences or major changes, spending however many trillions of dollars it takes to satisfy risk aversion. In the 1990s, people thought the future like 2022 would be a lot crazier than it is. In 1995, it was easy to imagine how IBM (or Microsoft) might not exist in 2005; in 2022, can you imagine Google (or the rest of FANG) not existing in 2032? I can't. Stuff like CRISPR is cool and benefiting a few people, but again, stagnant compared to the hopes & dreams of what would happen once the Human Genome Project would finish, and to things that happened back in the 1990s like Dolly or three-parent babies. People were looking forward to debunking Fukuyama with the rise of Russia (eg. Esther Dyson) or China, but he's having the last laugh as they prove to be hollow corrupt authoritarian states which are struggling to maintain middle-income status, and the only people they appeal to as 'a new post-liberal-democratic paradigm' are would-be authoritarian strongmen. Or consider the lockdown response to COVID. So it looks like people expect a more predictable future, have thus far been largely right, and have tended to do things that would cause that.
The counter-arguments here are mostly anecdotal and not even great ones. SBF incinerated $8b? Fine; but the consequences of FTX has thus far been mostly some embarassment. Meanwhile, some dude over at AT&T incinerated up to $100b in a bad merger, which is a lot bigger, while 1MDB was a lot smaller ($1b) and the Guptas ('who?') stole a lot more (>$20b), and those had actual geopolitical consequences.
Some industrialist took over some relatively minor advertising company? Yeah, that's something that used to happen a lot - how nostalgic to see an instance in our latter days, reminds one of the youthful American economy, before all the poison pills (which Twitter had) were legalized and other measures put into place to stop takeovers (and did).
Trump was elected? Sure, that was surprising, but the signature feature of Trump's administration was that it incompetently passed the time for 4 years, so it affected few meaningful predictions, and elections like Trump's forecasting error were within the total forecasting error historically so statistically, a loser candidate like Trump winning isn't even unusual. Let's remember how many shenanigans there have been around presidential elections historically, whether it's Watergate or Literary Digest or the Compromise of 1877 or JFK beating Nixon credited to his (non-social) media savvy or hey remember how crazy 2000 was?
Xi/Putin are awful? Yes, they sure are; are they more awful - and unpredictable - than Mao or Stalin or Pol Pot or Kim Il-Sung or Adolf Hitler, or countless other dictators and tyrants throughout history, and is the awfulness and unpredictability of the current crop of dictators like Modi or Erdogan "increasingly unpredictable"? No.
Love this, especially your choice quantitative measures of predictability via interest rates / predictIt/ insurance are spot on. In fact, I agree with a lot, so will pick out a three points where we might disagree:
1) The point that that the past few decades have been more, not less, predictable "Again bracketing AI out, my impression is that over the past 2 decades, pretty much all of these have trends consistent with believing a more rather than less predictable future. What we see is a world where aging populations and governments invest ever more into various kinds of 'insurance' and avoiding any consequences or major changes, spending however many trillions of dollars it takes to satisfy risk aversion."
2) My cherry picked examples of trump/elon/SBF/Putin/Xi being minor, not major.
3) The choice to bracket AI out of the equation of future unpredictability.
Point 3: Can we bracket AI out of the conversation?
I've read and re-read your awesome comment and get something new out each time, but I'd love to unpack this. Why/how could we factor (assuming that's a synonym for how you're using bracket) AI out of the future unpredictability?
I think trends that could lead to future volatility have been simmering for awhile, but would take events like Covid to show us that global supply chains can be frighteningly brittle and Ukraine to show us that our energy policies have been "bonkers" (https://doomberg.substack.com/p/americas-energy-strategy-is-bonkers).
I think we both agree, if from different angles, that unpredictability increases with or without AI. But some of AI's currently predicted effects (ie, job loss) feel like major drivers of downstream unpredictability. Is there a reason you chose to bracket out AI in your comment?
Point 2: I'd argue my cherrypicked human sources of volatility are significant not for their dollar value, or relative historical nastiness, but for the narratives.
If we go by dollars of fraud then yeah SBF is just another huckster and maybe the TwitElon thing is just business as usual. Enron and Madoff were around $60BB lost, but fascinating how $10-20B could be vaporized by such a small team so fast. The London Whale who lost $6B also comes briefly to mind. For both positive and negative, the reach of single individuals or very small teams (remember when we all were amazed that Instagram sold for $1BB for a team of 13?), so I chose highly public examples.
My friend Rick who I credit for being a reader/editor actually pushed a similar argument to yous: is the Twitter thing a "micro" or "macro" event? Honestly that in itself is actually a fun debate topic. My very brief argument for it being a "macro" event is the value of the Twitter town square (which, granted may be overtaken), the extremely takeover public saga which resulted in the text messages showing how back-of-the-envelope and personality-driven the thing was, and the fact that a formerly-public (eg, subject to shareholder demands for some standard adult behavior in the C-suite) company is now privately owned in a race against debt. As an event, it feels really unpredictable and the outcome is subject to feedbck loops in both the positive and negative direction
Point 1: I'd argue that we're emerging from a point of artificial predictability. If we choose to use interest rates as quantitative measures of uncertainty, then yeah Fed policy has basically said the world is 100% predictable since the Great Financial Crisis (Apparently Europe would be more >100% predictable, lol). This choice of keeping interest rates so low at a point when asset prices are ripping upward is a wild departure from the way we classically thought of the Fed (keep inflation down, employment up, growth at a target rate without overheating). But for whatever reason (political intervention, euphoria, arrogance, "end of history" thinking etc.), the pressure was to keep the free money flowing, which created positive feedback loops (buybacks galore, hype<->price reinforcing, the invention(?) of the gamma squeeze). But now that the music has stopped, we see that the Fed has become an engine of inequality (the author of a book that title was very good on the Hidden Forces pod) causing social pressure, and an increasing percentage of public companies are zombies that can't pay their debt https://www.prnewswire.com/news-releases/the-walking-debt-zombie-companies-unable-to-meet-borrowing-costs-rise-10-in-2022-finds-new-kearney-report-301659386.html . Maybe it's "this time it's different" or maybe this all run-of-the-mill creative destruction, I'm not sure.
Also consider that many things about the "predictable" financial world are difference-of-kind apart from where they used to be. What happens when a few giant "passive" funds of a net 15Trillion wield the powerful voting shares of many major companies (impact is debatable, one fact check here https://www.reuters.com/article/factcheck-business-investment/fact-check-video-claiming-blackrock-and-vanguard-own-all-the-biggest-corporations-in-the-world-is-missing-context-idUSL2N2WI1K4 ) ? What happens if there is a further delisting of Chinese companies? What happens when old people start aging out of their homes and there's no purchasing demand? At what percentage of financial insolvency in the US population does there become significant social uproar? How expensive do European energy bills need to get before the environment is substantially more volatile? What happens with pension giants like CalPERS can't possibly make their promised 7.1% returns anymore?
Aside from economic indicators, I think we take for granted how incredibly peaceful past decades have been on the surface-level. Obama was tested by Xi in the South China Sea (https://www.brookings.edu/opinions/u-s-south-china-sea-policy-after-the-ruling-opportunities-and-challenges/), and Obama chose a path of avoided a path of direct conflict. This may have implications with Taiwan. Just another case of transferring volatility into the future.
So just like the metaphor of Madoff's returns being perfectly predictable until they weren't, and your point of aging populations ensuring policy takes care of them, I think we've done a great job of pushing various forms of volatility off into the future. That may be fine, we may invent new financial tools to get us out of it, or one failure could snowball into the others.
Your strong random individual thesis reminds me of the fractal nature of causality in biology. In most of the universe, a molecular scale event gets washed out in the random thermodynamic fluctuations. Best of luck for the ambitious hydrogen atom in the center of the sun, but it probably will just get crunched into helium like its neighbors. But in biology the system is at edge of chaos and so micro influences have macro effects. Even a quantum event can have societal effects if it swaps a nucleotide in a cancer driver gene that kills Steve Jobs, or adds 20 IQ points to the next John von Neumann. Similarly, our model of evolution is a single fit individual whose selfish gene quickly takes over the population.
The counterargument from biology might be emergence, multiple causality, or both. Things might have a distribution of causes and it's hard for people to fit all the causal factors into their mental models. But a bigger machine learning model might be able to eventually be predictive in theory, with the right data. Or Wolfram might say it's all perfectly predictable, just creates random chaos when you run the program out.
On a tangent I've been thinking a lot about org design and see an interesting connection between Jane Jacobs:Robert Moses::chaos:planning story you tell and the top-down org chart vs Team Topologies and agile services approach.
Awesome post, love all the great references and new reading material. Cool that you used ChatGPT but AI is a long way off from great writing like this!
A warning: many people go to the website and read some stuff superficially and think they understand the model. Consider that might not be the case and you need to dive in deeper.
One of the incredible things from the school is to watch the students or alumni (on Youtubre), They radiate something very powerful.
I'm not convinced. SBF is less influential as a result of his company failing, and Trump less influential as a result of losing re-election. Putin may still be in power, but he's far from a Napoleon. He can't even defeat Ukraine! Stalin was a Russian leader who really changed the world, in contrast. Xi is more powerful than Putin, but even he's having trouble with COVID lockdown protests. He certainly doesn't seem an influential as Mao.
Listening to the Joe Rogan/Steve Jobs interview rn… idk doesn’t seem that good? Open to the possibility that the underlying tech can become eerily good in less than a year though.
Fair criticism - it is both flawed and impressive. On one hand, the replication of the famous Rogan and Jobs tropes was really quite good. On the other, you can see that the output audio sounds like Joe in his studio and Steve Jobs on stage. The conversation is somewhat of a mashup of the two's common talking points, which seems to be in the fairway of what we're seeing in chatGPT: it really comes out as a generalist, tone-neutral voice unless you give it very specific instructions not to.
Me: Can you give me what the first 20 lines of dialog would be if steve jobs went on the joe rogan podcast?
ChatGPT:
Steve Jobs: Hey Joe, thanks for having me on the show.
Joe Rogan: No problem, Steve. It's an honor to have you here.
Steve Jobs: So, what do you want to talk about?
Joe Rogan: Well, I was thinking we could start by discussing your time at Apple, and the impact that your work has had on the technology industry.
Steve Jobs: Sure, that sounds good.
Joe Rogan: So, how did you first become involved with Apple?
Steve Jobs: It all started back in the 1970s, when I was a college dropout working on computers in my garage. I had always been interested in technology and entrepreneurship, and I saw a huge opportunity in the emerging personal computer market.
Joe Rogan: And how did you go from working in your garage to creating one of the most successful technology companies in history?
Steve Jobs: It was a long and winding road. We started out by building and selling computer kits, and eventually we released our first personal computer, the Apple I. It was a big hit, and it really put us on the map.
Joe Rogan: And then you went on to create some of the most iconic products in tech history, like the Macintosh, the iPod, the iPhone, and the iPad.
Steve Jobs: Yeah, it was an incredible journey. Each of those products was a game-changer in its own way, and they really transformed the way people interact with technology.
Joe Rogan: And how did you come up with the ideas for these products? What was your process like?
Steve Jobs: It was a combination of things. I always had a passion for design and user experience, and I was always looking for ways to make technology more intuitive and accessible. I also had a great team at Apple who helped me bring my visions to life.
Joe Rogan: And what was it like working with Steve Wozniak and the other members of the Apple team?
Steve Jobs: It was amazing. Woz and I had a great partnership, and we complemented each other really well. And the rest of the team was incredibly talented and dedicated. We all had a shared vision for what we wanted to accomplish, and we worked tirelessly to make it a reality.
[So, yes, "easy" to generate this safe dialogue, "easy" to put it back in the original audio format of the speaker. Only going to get better from here.]
I personally agree that the future is getting less predictable & AI in particular is going to falsify a huge overhang of extant long-term predictions which have misleadingly-good track records because they are predicated on AI never happening. But to bracket my personal opinions, how would one measure such things as 'people *think* the future is getting more/less predictable' or 'the future *has* been getting more/less predictable than people thought'? Some possibilities:
- prediction market forecasts being systematically overconfident: have PredictIt or Metaculus contracts been expiring with worse Brier or other proper scoring rule results when grouped by year? Is GJP's accuracy decaying? Are the old historical predictions from Tetlock's expert surveys getting worse over time?
- prediction market prices being higher variance: prices reflect information & certainty, so if the future has been getting harder to predict, then price time series should be increasingly volatile
- similarly, futures markets: volatility and the risk premia of long-dated options can either be higher or lower than in earlier time periods. (The future may be richer or poorer, but any change in levels would be reflected in the base price.)
- insurance costs: ditto---the riskier the future, the higher premiums must be charged. (eg.can you still buy cheap longevity insurance or annuities? If so, then insurers apparently don't believe that anti-aging research is going to pay off.)
- interest rates: interest rates reflect the desire to trade less money now for more money later, and incorporate a lot of things like nominal inflation or demographic trends like retirement planning, but also include risk such as expropriation or disaster or just the opportunity cost of being locked into the wrong investment. So at a simple first look, higher interest rates imply a more unpredictable future and vice-versa.
- conversely, debt loads: debt is dangerously fixed, so one will prefer debt to equity if the future is predictable and you can count on the cash flows to service it. On an individual level, things like student loans or house mortgages are commitments to a predictable future.
- social/geographic mobility: people will prefer buying houses to renting or staying put the more predictable the future, because the less the optionality is worth. (If you know the future, you either have moved to the right place already or you know there's nothing better out there.)
- creative destruction and turnover in the economy, especially of large corporations
- increased contracting and regulation, redistributive politics, larger governments as % of GDPs etc
- demographics: the older and more female a population, the less you expect any radical revolutions or uprisings which would spoil your predictions; violence is a young man's game.
Again bracketing AI out, my impression is that over the past 2 decades, pretty much all of these have trends consistent with believing a more rather than less predictable future. What we see is a world where aging populations and governments invest ever more into various kinds of 'insurance' and avoiding any consequences or major changes, spending however many trillions of dollars it takes to satisfy risk aversion. In the 1990s, people thought the future like 2022 would be a lot crazier than it is. In 1995, it was easy to imagine how IBM (or Microsoft) might not exist in 2005; in 2022, can you imagine Google (or the rest of FANG) not existing in 2032? I can't. Stuff like CRISPR is cool and benefiting a few people, but again, stagnant compared to the hopes & dreams of what would happen once the Human Genome Project would finish, and to things that happened back in the 1990s like Dolly or three-parent babies. People were looking forward to debunking Fukuyama with the rise of Russia (eg. Esther Dyson) or China, but he's having the last laugh as they prove to be hollow corrupt authoritarian states which are struggling to maintain middle-income status, and the only people they appeal to as 'a new post-liberal-democratic paradigm' are would-be authoritarian strongmen. Or consider the lockdown response to COVID. So it looks like people expect a more predictable future, have thus far been largely right, and have tended to do things that would cause that.
The counter-arguments here are mostly anecdotal and not even great ones. SBF incinerated $8b? Fine; but the consequences of FTX has thus far been mostly some embarassment. Meanwhile, some dude over at AT&T incinerated up to $100b in a bad merger, which is a lot bigger, while 1MDB was a lot smaller ($1b) and the Guptas ('who?') stole a lot more (>$20b), and those had actual geopolitical consequences.
Some industrialist took over some relatively minor advertising company? Yeah, that's something that used to happen a lot - how nostalgic to see an instance in our latter days, reminds one of the youthful American economy, before all the poison pills (which Twitter had) were legalized and other measures put into place to stop takeovers (and did).
Trump was elected? Sure, that was surprising, but the signature feature of Trump's administration was that it incompetently passed the time for 4 years, so it affected few meaningful predictions, and elections like Trump's forecasting error were within the total forecasting error historically so statistically, a loser candidate like Trump winning isn't even unusual. Let's remember how many shenanigans there have been around presidential elections historically, whether it's Watergate or Literary Digest or the Compromise of 1877 or JFK beating Nixon credited to his (non-social) media savvy or hey remember how crazy 2000 was?
Xi/Putin are awful? Yes, they sure are; are they more awful - and unpredictable - than Mao or Stalin or Pol Pot or Kim Il-Sung or Adolf Hitler, or countless other dictators and tyrants throughout history, and is the awfulness and unpredictability of the current crop of dictators like Modi or Erdogan "increasingly unpredictable"? No.
Love this, especially your choice quantitative measures of predictability via interest rates / predictIt/ insurance are spot on. In fact, I agree with a lot, so will pick out a three points where we might disagree:
1) The point that that the past few decades have been more, not less, predictable "Again bracketing AI out, my impression is that over the past 2 decades, pretty much all of these have trends consistent with believing a more rather than less predictable future. What we see is a world where aging populations and governments invest ever more into various kinds of 'insurance' and avoiding any consequences or major changes, spending however many trillions of dollars it takes to satisfy risk aversion."
2) My cherry picked examples of trump/elon/SBF/Putin/Xi being minor, not major.
3) The choice to bracket AI out of the equation of future unpredictability.
I'll reply separately for each one
Point 3: Can we bracket AI out of the conversation?
I've read and re-read your awesome comment and get something new out each time, but I'd love to unpack this. Why/how could we factor (assuming that's a synonym for how you're using bracket) AI out of the future unpredictability?
I think trends that could lead to future volatility have been simmering for awhile, but would take events like Covid to show us that global supply chains can be frighteningly brittle and Ukraine to show us that our energy policies have been "bonkers" (https://doomberg.substack.com/p/americas-energy-strategy-is-bonkers).
I think we both agree, if from different angles, that unpredictability increases with or without AI. But some of AI's currently predicted effects (ie, job loss) feel like major drivers of downstream unpredictability. Is there a reason you chose to bracket out AI in your comment?
Point 2: I'd argue my cherrypicked human sources of volatility are significant not for their dollar value, or relative historical nastiness, but for the narratives.
If we go by dollars of fraud then yeah SBF is just another huckster and maybe the TwitElon thing is just business as usual. Enron and Madoff were around $60BB lost, but fascinating how $10-20B could be vaporized by such a small team so fast. The London Whale who lost $6B also comes briefly to mind. For both positive and negative, the reach of single individuals or very small teams (remember when we all were amazed that Instagram sold for $1BB for a team of 13?), so I chose highly public examples.
My friend Rick who I credit for being a reader/editor actually pushed a similar argument to yous: is the Twitter thing a "micro" or "macro" event? Honestly that in itself is actually a fun debate topic. My very brief argument for it being a "macro" event is the value of the Twitter town square (which, granted may be overtaken), the extremely takeover public saga which resulted in the text messages showing how back-of-the-envelope and personality-driven the thing was, and the fact that a formerly-public (eg, subject to shareholder demands for some standard adult behavior in the C-suite) company is now privately owned in a race against debt. As an event, it feels really unpredictable and the outcome is subject to feedbck loops in both the positive and negative direction
Point 1: I'd argue that we're emerging from a point of artificial predictability. If we choose to use interest rates as quantitative measures of uncertainty, then yeah Fed policy has basically said the world is 100% predictable since the Great Financial Crisis (Apparently Europe would be more >100% predictable, lol). This choice of keeping interest rates so low at a point when asset prices are ripping upward is a wild departure from the way we classically thought of the Fed (keep inflation down, employment up, growth at a target rate without overheating). But for whatever reason (political intervention, euphoria, arrogance, "end of history" thinking etc.), the pressure was to keep the free money flowing, which created positive feedback loops (buybacks galore, hype<->price reinforcing, the invention(?) of the gamma squeeze). But now that the music has stopped, we see that the Fed has become an engine of inequality (the author of a book that title was very good on the Hidden Forces pod) causing social pressure, and an increasing percentage of public companies are zombies that can't pay their debt https://www.prnewswire.com/news-releases/the-walking-debt-zombie-companies-unable-to-meet-borrowing-costs-rise-10-in-2022-finds-new-kearney-report-301659386.html . Maybe it's "this time it's different" or maybe this all run-of-the-mill creative destruction, I'm not sure.
If you can handle another cherry picked example but using it more as a metaphor, Madoff's returns were, in retrospect, hilariously low variance ... until they weren't https://www.ft.com/content/055bf6d2-70fb-4ed0-b97a-36f412e1aff7
Also consider that many things about the "predictable" financial world are difference-of-kind apart from where they used to be. What happens when a few giant "passive" funds of a net 15Trillion wield the powerful voting shares of many major companies (impact is debatable, one fact check here https://www.reuters.com/article/factcheck-business-investment/fact-check-video-claiming-blackrock-and-vanguard-own-all-the-biggest-corporations-in-the-world-is-missing-context-idUSL2N2WI1K4 ) ? What happens if there is a further delisting of Chinese companies? What happens when old people start aging out of their homes and there's no purchasing demand? At what percentage of financial insolvency in the US population does there become significant social uproar? How expensive do European energy bills need to get before the environment is substantially more volatile? What happens with pension giants like CalPERS can't possibly make their promised 7.1% returns anymore?
Aside from economic indicators, I think we take for granted how incredibly peaceful past decades have been on the surface-level. Obama was tested by Xi in the South China Sea (https://www.brookings.edu/opinions/u-s-south-china-sea-policy-after-the-ruling-opportunities-and-challenges/), and Obama chose a path of avoided a path of direct conflict. This may have implications with Taiwan. Just another case of transferring volatility into the future.
So just like the metaphor of Madoff's returns being perfectly predictable until they weren't, and your point of aging populations ensuring policy takes care of them, I think we've done a great job of pushing various forms of volatility off into the future. That may be fine, we may invent new financial tools to get us out of it, or one failure could snowball into the others.
Your strong random individual thesis reminds me of the fractal nature of causality in biology. In most of the universe, a molecular scale event gets washed out in the random thermodynamic fluctuations. Best of luck for the ambitious hydrogen atom in the center of the sun, but it probably will just get crunched into helium like its neighbors. But in biology the system is at edge of chaos and so micro influences have macro effects. Even a quantum event can have societal effects if it swaps a nucleotide in a cancer driver gene that kills Steve Jobs, or adds 20 IQ points to the next John von Neumann. Similarly, our model of evolution is a single fit individual whose selfish gene quickly takes over the population.
The counterargument from biology might be emergence, multiple causality, or both. Things might have a distribution of causes and it's hard for people to fit all the causal factors into their mental models. But a bigger machine learning model might be able to eventually be predictive in theory, with the right data. Or Wolfram might say it's all perfectly predictable, just creates random chaos when you run the program out.
On a tangent I've been thinking a lot about org design and see an interesting connection between Jane Jacobs:Robert Moses::chaos:planning story you tell and the top-down org chart vs Team Topologies and agile services approach.
Awesome post, love all the great references and new reading material. Cool that you used ChatGPT but AI is a long way off from great writing like this!
Considering alternatives to factory-education: you might want to check out Sudbury Valley School.
www.sudval.com
A warning: many people go to the website and read some stuff superficially and think they understand the model. Consider that might not be the case and you need to dive in deeper.
One of the incredible things from the school is to watch the students or alumni (on Youtubre), They radiate something very powerful.
I'm not convinced. SBF is less influential as a result of his company failing, and Trump less influential as a result of losing re-election. Putin may still be in power, but he's far from a Napoleon. He can't even defeat Ukraine! Stalin was a Russian leader who really changed the world, in contrast. Xi is more powerful than Putin, but even he's having trouble with COVID lockdown protests. He certainly doesn't seem an influential as Mao.
Listening to the Joe Rogan/Steve Jobs interview rn… idk doesn’t seem that good? Open to the possibility that the underlying tech can become eerily good in less than a year though.
Fair criticism - it is both flawed and impressive. On one hand, the replication of the famous Rogan and Jobs tropes was really quite good. On the other, you can see that the output audio sounds like Joe in his studio and Steve Jobs on stage. The conversation is somewhat of a mashup of the two's common talking points, which seems to be in the fairway of what we're seeing in chatGPT: it really comes out as a generalist, tone-neutral voice unless you give it very specific instructions not to.
OK, I couldn't help myself.
Me: Can you give me what the first 20 lines of dialog would be if steve jobs went on the joe rogan podcast?
ChatGPT:
Steve Jobs: Hey Joe, thanks for having me on the show.
Joe Rogan: No problem, Steve. It's an honor to have you here.
Steve Jobs: So, what do you want to talk about?
Joe Rogan: Well, I was thinking we could start by discussing your time at Apple, and the impact that your work has had on the technology industry.
Steve Jobs: Sure, that sounds good.
Joe Rogan: So, how did you first become involved with Apple?
Steve Jobs: It all started back in the 1970s, when I was a college dropout working on computers in my garage. I had always been interested in technology and entrepreneurship, and I saw a huge opportunity in the emerging personal computer market.
Joe Rogan: And how did you go from working in your garage to creating one of the most successful technology companies in history?
Steve Jobs: It was a long and winding road. We started out by building and selling computer kits, and eventually we released our first personal computer, the Apple I. It was a big hit, and it really put us on the map.
Joe Rogan: And then you went on to create some of the most iconic products in tech history, like the Macintosh, the iPod, the iPhone, and the iPad.
Steve Jobs: Yeah, it was an incredible journey. Each of those products was a game-changer in its own way, and they really transformed the way people interact with technology.
Joe Rogan: And how did you come up with the ideas for these products? What was your process like?
Steve Jobs: It was a combination of things. I always had a passion for design and user experience, and I was always looking for ways to make technology more intuitive and accessible. I also had a great team at Apple who helped me bring my visions to life.
Joe Rogan: And what was it like working with Steve Wozniak and the other members of the Apple team?
Steve Jobs: It was amazing. Woz and I had a great partnership, and we complemented each other really well. And the rest of the team was incredibly talented and dedicated. We all had a shared vision for what we wanted to accomplish, and we worked tirelessly to make it a reality.
[So, yes, "easy" to generate this safe dialogue, "easy" to put it back in the original audio format of the speaker. Only going to get better from here.]