#vtaiwan
2025-12-02
關於 OpenAI Democratic Inputs to AI 如何迴避民主本質的好文章：
> *The OpenAI solicitation wants representativeness.* The most popular approach to ensuring this in debates these days is ‘sortition’ - *picking a representative sample of the population so as to create a ‘minipublic’* that notionally resembles the public as a whole (the same rough percentages of liberals and conservatives etc). *The solicitation wants these representative people to engage in “deliberative discussions,” where they politely exchange views with each other, and update their own perspectives when they hear good counter-arguments.* These discussions would center on questions that AI labs have tended to see as a massive pain in the arse, while avoiding topics that are central to their profit models (who decides on the release of new versions? who gets the money?) And all this is to be non-binding, unless OpenAI decides to the contrary at its own discretion, at some indefinite point in the future.
>
> *Such proposals don’t have much to do with real life democracy. […] T*he kind of democracy that deliberation-sortition points toward is one that is likely to be particularly congenial _both_ to sincerely motivated engineers and to those who are more directly self-interested.
> *The OpenAI solicitation wants representativeness.* The most popular approach to ensuring this in debates these days is ‘sortition’ - *picking a representative sample of the population so as to create a ‘minipublic’* that notionally resembles the public as a whole (the same rough percentages of liberals and conservatives etc). *The solicitation wants these representative people to engage in “deliberative discussions,” where they politely exchange views with each other, and update their own perspectives when they hear good counter-arguments.* These discussions would center on questions that AI labs have tended to see as a massive pain in the arse, while avoiding topics that are central to their profit models (who decides on the release of new versions? who gets the money?) And all this is to be non-binding, unless OpenAI decides to the contrary at its own discretion, at some indefinite point in the future.
>
> *Such proposals don’t have much to do with real life democracy. […] T*he kind of democracy that deliberation-sortition points toward is one that is likely to be particularly congenial _both_ to sincerely motivated engineers and to those who are more directly self-interested.
programmablemutter.com
There are plausible reasons for how it ended up that way
- 💯1
- 💡2
- 👍1
Thanks, great share! I've been thinking about this a bit lately, related to polis 1.0 mechanics vs AI-assisted deliberation.
> [...] about the differences between using machine learning for:
>
> 1. Making sense of "human REACTIONS TO language" (polislike tools) versus
> 2. making sense of "language ITSELF" (AI-assisted deliberation tools)
https://www.linkedin.com/posts/patcon-_join-the-polis-user-group-fan-club-discord-activity-7399854513093865473-iBb8
I'm starting to believe there are two layers to politics that we mostly intermix: (1) our reasoned response (which we could call "voting", and (2) our affective non-linguistic response (which we could call "reacting").
Obviously the uniquely human thing (which we're proud of!) is the realm of language and reason. but it all sits on a lower system of wordless "affect" -- away vs toward feelings, valence. These roughly correspond to system 1 and system 2 thinking, from "Thinking Fast and Slow".
One is the realm of the ideal self, that we are at our most self-actualized. The other is more akin to "chemotaxis", how a single cell moves up and down 2D chemical gradients, toward good things and away from bad things.
And while we might like to imagine we can govern exclusively with our most recent form of knowing (language! reason!), I think we're building on sand if we don't also create ways to map the lower layer that system 2 builds on. Because we live the every day in our fast system 1.
Yes, pre-linguistic system 1 is the root of prejudice and bias, but when properly tuned, it's also the instinct and intuition that saves runaway baby carriages and helps people notice both dangerous situations and subtle possibilities. It's efficient and used to great effect when it's in relationship with the higher system.
Things are about to get tough in the world. And as the American expression [kinda] goes " when the going get tough, the tough get system 1". So maybe we should integrate mapping of these lowly systems into our governance, and harvest the inherent wisdom that they have <3
Imho this is what polis 1.0 systems do: using machine learning to help us map simple attraction/repulsion patterns between the black boxes of humans and language, without inviting the machines into the black boxes of ours minds or our meaning. The generated maps (created with very little compute) are for us to do that sensemaking 🙏🏻
> [...] about the differences between using machine learning for:
>
> 1. Making sense of "human REACTIONS TO language" (polislike tools) versus
> 2. making sense of "language ITSELF" (AI-assisted deliberation tools)
https://www.linkedin.com/posts/patcon-_join-the-polis-user-group-fan-club-discord-activity-7399854513093865473-iBb8
I'm starting to believe there are two layers to politics that we mostly intermix: (1) our reasoned response (which we could call "voting", and (2) our affective non-linguistic response (which we could call "reacting").
Obviously the uniquely human thing (which we're proud of!) is the realm of language and reason. but it all sits on a lower system of wordless "affect" -- away vs toward feelings, valence. These roughly correspond to system 1 and system 2 thinking, from "Thinking Fast and Slow".
One is the realm of the ideal self, that we are at our most self-actualized. The other is more akin to "chemotaxis", how a single cell moves up and down 2D chemical gradients, toward good things and away from bad things.
And while we might like to imagine we can govern exclusively with our most recent form of knowing (language! reason!), I think we're building on sand if we don't also create ways to map the lower layer that system 2 builds on. Because we live the every day in our fast system 1.
Yes, pre-linguistic system 1 is the root of prejudice and bias, but when properly tuned, it's also the instinct and intuition that saves runaway baby carriages and helps people notice both dangerous situations and subtle possibilities. It's efficient and used to great effect when it's in relationship with the higher system.
Things are about to get tough in the world. And as the American expression [kinda] goes " when the going get tough, the tough get system 1". So maybe we should integrate mapping of these lowly systems into our governance, and harvest the inherent wisdom that they have <3
Imho this is what polis 1.0 systems do: using machine learning to help us map simple attraction/repulsion patterns between the black boxes of humans and language, without inviting the machines into the black boxes of ours minds or our meaning. The generated maps (created with very little compute) are for us to do that sensemaking 🙏🏻
關於 OpenAI Democratic Inputs to AI 如何迴避民主本質的好文章：
> *The OpenAI solicitation wants representativeness.* The most popular approach to ensuring this in debates these days is ‘sortition’ - *picking a representative sample of the population so as to create a ‘minipublic’* that notionally resembles the public as a whole (the same rough percentages of liberals and conservatives etc). *The solicitation wants these representative people to engage in “deliberative discussions,” where they politely exchange views with each other, and update their own perspectives when they hear good counter-arguments.* These discussions would center on questions that AI labs have tended to see as a massive pain in the arse, while avoiding topics that are central to their profit models (who decides on the release of new versions? who gets the money?) And all this is to be non-binding, unless OpenAI decides to the contrary at its own discretion, at some indefinite point in the future.
>
> *Such proposals don’t have much to do with real life democracy. […] T*he kind of democracy that deliberation-sortition points toward is one that is likely to be particularly congenial _both_ to sincerely motivated engineers and to those who are more directly self-interested.
> *The OpenAI solicitation wants representativeness.* The most popular approach to ensuring this in debates these days is ‘sortition’ - *picking a representative sample of the population so as to create a ‘minipublic’* that notionally resembles the public as a whole (the same rough percentages of liberals and conservatives etc). *The solicitation wants these representative people to engage in “deliberative discussions,” where they politely exchange views with each other, and update their own perspectives when they hear good counter-arguments.* These discussions would center on questions that AI labs have tended to see as a massive pain in the arse, while avoiding topics that are central to their profit models (who decides on the release of new versions? who gets the money?) And all this is to be non-binding, unless OpenAI decides to the contrary at its own discretion, at some indefinite point in the future.
>
> *Such proposals don’t have much to do with real life democracy. […] T*he kind of democracy that deliberation-sortition points toward is one that is likely to be particularly congenial _both_ to sincerely motivated engineers and to those who are more directly self-interested.
Thanks, great share! I've been thinking about this a bit lately, related to polis 1.0 mechanics vs AI-assisted deliberation.
> [...] about the differences between using machine learning for:
>
> 1. Making sense of "human REACTIONS TO language" (polislike tools) versus
> 2. making sense of "language ITSELF" (AI-assisted deliberation tools)
https://www.linkedin.com/posts/patcon-_join-the-polis-user-group-fan-club-discord-activity-7399854513093865473-iBb8
I'm starting to believe there are two layers to politics that we mostly intermix: (1) our reasoned response (which we could call "voting", and (2) our affective non-linguistic response (which we could call "reacting").
Obviously the uniquely human thing (which we're proud of!) is the realm of language and reason. but it all sits on a lower system of wordless "affect" -- away vs toward feelings, valence. These roughly correspond to system 1 and system 2 thinking, from "Thinking Fast and Slow".
One is the realm of the ideal self, that we are at our most self-actualized. The other is more akin to "chemotaxis", how a single cell moves up and down 2D chemical gradients, toward good things and away from bad things.
And while we might like to imagine we can govern exclusively with our most recent form of knowing (language! reason!), I think we're building on sand if we don't also create ways to map the lower layer that system 2 builds on. Because we live the every day in our fast system 1.
Yes, pre-linguistic system 1 is the root of prejudice and bias, but when properly tuned, it's also the instinct and intuition that saves runaway baby carriages and helps people notice both dangerous situations and subtle possibilities. It's efficient and used to great effect when it's in relationship with the higher system.
Things are about to get tough in the world. And as the American expression [kinda] goes " when the going get tough, the tough get system 1". So maybe we should integrate mapping of these lowly systems into our governance, and harvest the inherent wisdom that they have <3
Imho this is what polis 1.0 systems do: using machine learning to help us map simple attraction/repulsion patterns between the black boxes of humans and language, without inviting the machines into the black boxes of ours minds or our meaning. The generated maps (created with very little compute) are for us to do that sensemaking 🙏🏻
> [...] about the differences between using machine learning for:
>
> 1. Making sense of "human REACTIONS TO language" (polislike tools) versus
> 2. making sense of "language ITSELF" (AI-assisted deliberation tools)
https://www.linkedin.com/posts/patcon-_join-the-polis-user-group-fan-club-discord-activity-7399854513093865473-iBb8
I'm starting to believe there are two layers to politics that we mostly intermix: (1) our reasoned response (which we could call "voting", and (2) our affective non-linguistic response (which we could call "reacting").
Obviously the uniquely human thing (which we're proud of!) is the realm of language and reason. but it all sits on a lower system of wordless "affect" -- away vs toward feelings, valence. These roughly correspond to system 1 and system 2 thinking, from "Thinking Fast and Slow".
One is the realm of the ideal self, that we are at our most self-actualized. The other is more akin to "chemotaxis", how a single cell moves up and down 2D chemical gradients, toward good things and away from bad things.
And while we might like to imagine we can govern exclusively with our most recent form of knowing (language! reason!), I think we're building on sand if we don't also create ways to map the lower layer that system 2 builds on. Because we live the every day in our fast system 1.
Yes, pre-linguistic system 1 is the root of prejudice and bias, but when properly tuned, it's also the instinct and intuition that saves runaway baby carriages and helps people notice both dangerous situations and subtle possibilities. It's efficient and used to great effect when it's in relationship with the higher system.
Things are about to get tough in the world. And as the American expression [kinda] goes " when the going get tough, the tough get system 1". So maybe we should integrate mapping of these lowly systems into our governance, and harvest the inherent wisdom that they have <3
Imho this is what polis 1.0 systems do: using machine learning to help us map simple attraction/repulsion patterns between the black boxes of humans and language, without inviting the machines into the black boxes of ours minds or our meaning. The generated maps (created with very little compute) are for us to do that sensemaking 🙏🏻
2025-12-03
Thanks, great share! I've been thinking about this a bit lately, related to polis 1.0 mechanics vs AI-assisted deliberation.
> [...] about the differences between using machine learning for:
>
> 1. Making sense of "human REACTIONS TO language" (polislike tools) versus
> 2. making sense of "language ITSELF" (AI-assisted deliberation tools)
https://www.linkedin.com/posts/patcon-_join-the-polis-user-group-fan-club-discord-activity-7399854513093865473-iBb8
I'm starting to believe there are two layers to politics that we mostly intermix: (1) our reasoned response (which we could call "voting", and (2) our affective non-linguistic response (which we could call "reacting").
Obviously the uniquely human thing (which we're proud of!) is the realm of language and reason. but it all sits on a lower system of wordless "affect" -- away vs toward feelings, valence. These roughly correspond to system 1 and system 2 thinking, from "Thinking Fast and Slow".
One is the realm of the ideal self, that we are at our most self-actualized. The other is more akin to "chemotaxis", how a single cell moves up and down 2D chemical gradients, toward good things and away from bad things.
And while we might like to imagine we can govern exclusively with our most recent form of knowing (language! reason!), I think we're building on sand if we don't also create ways to map the lower layer that system 2 builds on. Because we live the every day in our fast system 1.
Yes, pre-linguistic system 1 is the root of prejudice and bias, but when properly tuned, it's also the instinct and intuition that saves runaway baby carriages and helps people notice both dangerous situations and subtle possibilities. It's efficient and used to great effect when it's in relationship with the higher system.
Things are about to get tough in the world. And as the American expression [kinda] goes " when the going get tough, the tough get system 1". So maybe we should integrate mapping of these lowly systems into our governance, and harvest the inherent wisdom that they have <3
Imho this is what polis 1.0 systems do: using machine learning to help us map simple attraction/repulsion patterns between the black boxes of humans and language, without inviting the machines into the black boxes of ours minds or our meaning. The generated maps (created with very little compute) are for us to do that sensemaking 🙏🏻
> [...] about the differences between using machine learning for:
>
> 1. Making sense of "human REACTIONS TO language" (polislike tools) versus
> 2. making sense of "language ITSELF" (AI-assisted deliberation tools)
https://www.linkedin.com/posts/patcon-_join-the-polis-user-group-fan-club-discord-activity-7399854513093865473-iBb8
I'm starting to believe there are two layers to politics that we mostly intermix: (1) our reasoned response (which we could call "voting", and (2) our affective non-linguistic response (which we could call "reacting").
Obviously the uniquely human thing (which we're proud of!) is the realm of language and reason. but it all sits on a lower system of wordless "affect" -- away vs toward feelings, valence. These roughly correspond to system 1 and system 2 thinking, from "Thinking Fast and Slow".
One is the realm of the ideal self, that we are at our most self-actualized. The other is more akin to "chemotaxis", how a single cell moves up and down 2D chemical gradients, toward good things and away from bad things.
And while we might like to imagine we can govern exclusively with our most recent form of knowing (language! reason!), I think we're building on sand if we don't also create ways to map the lower layer that system 2 builds on. Because we live the every day in our fast system 1.
Yes, pre-linguistic system 1 is the root of prejudice and bias, but when properly tuned, it's also the instinct and intuition that saves runaway baby carriages and helps people notice both dangerous situations and subtle possibilities. It's efficient and used to great effect when it's in relationship with the higher system.
Things are about to get tough in the world. And as the American expression [kinda] goes " when the going get tough, the tough get system 1". So maybe we should integrate mapping of these lowly systems into our governance, and harvest the inherent wisdom that they have <3
Imho this is what polis 1.0 systems do: using machine learning to help us map simple attraction/repulsion patterns between the black boxes of humans and language, without inviting the machines into the black boxes of ours minds or our meaning. The generated maps (created with very little compute) are for us to do that sensemaking 🙏🏻
Replied to a thread: 2025-11-26 15:17:08
前幾天因突發的停水事件，有幾天沒休息得很好。今天小松先請假一次。會再看記錄。
請大家多用紫色麥克風轉錄，謝謝。🙏
請大家多用紫色麥克風轉錄，謝謝。🙏
那今天還有其他人會上線嗎～我可以先開好共筆，不過我等等台灣時間19:00後也有事情，所以如果真的沒有的話這週先暫停一次沒關係！
如果先開好共筆，之後會議取消的話，也可以事後改title為下週的日期。
咦抱歉沒有及時跟到，最後是取消了是嗎
2025-12-05
2025-12-07
對嗚嗚