Thank you for this thoughtful exchange—it’s helped clarify important nuances. I genuinely admire your commitment to ethical transformation. You’re right: the future will need not just technological solutions, but new forms of human solidarity rooted in wisdom and compassion.
While our methodologies differ, your ideas inspire deeper thinking about holistic approaches. To keep this thread focused, I suggest we continue this conversation via private messages—particularly if you’d like to explore:
For other readers: This discussion vividly illustrates how the Time × Scope framework operates in practice—‘high-moral’ ideals (long-term δ, wide-scope w) must demonstrate implementability (↑ρ) before becoming foundational norms. I’d love to hear: What examples of such moral transitions do you see emerging today?
Thank you for elaborating — your vision of creating a rational 'moral elite' is truly fascinating! You’re absolutely right about the core issue: today’s hierarchy, centered on financial achievement and consumption, stifles moral development. Your proposed alternative — a system where status derives from prosocial behavior (‘saintliness without dogma’) — strikes at the heart of the problem.
However, I see two practical challenges:
This is where EA’s evolutionary approach — and your own work — shines:
A timely synthesis: I’m currently drafting a post applying Time × Scope to AI alignment. It explores how a technologically mediated moral hierarchy (not sermons or propaganda) could act as a sociotechnical solution by:
Your insights are invaluable here! If you’d like to deepen this discussion:
Perhaps the ‘lighthouse’ we need isn’t a utopian ideology, but a practical, scalable approach — anchored in evidence, open to all, and built step by step. Would love your thoughts!
I'm not an expert on moral weights research itself, but approaching this rationally, I’m strongly in favour of commissioning an independent, methodologically distinct reassessment of moral weights—precisely because a single, highly-cited study can become an invisible “gravity well” for the whole field.
Two design suggestions that echo robustness principles in other scientific domains:
The result doesn’t have to dethrone RP; even showing that key conclusions are insensitive to modelling choices (or, conversely, highly sensitive) would be valuable decision information for funders.
In other words: additional estimates may not be “better” in isolation, but they increase our collective confidence interval—and for something as consequential as cross-species moral weights, that’s well worth the cost.
Thank you for the thoughtful follow-up. I fully agree that laws and formal rules work only to the extent that people actually believe in them. If a regulation lacks internal assent, it quickly turns into costly policing or quiet non-compliance. So the external layer must rest on genuine, internalised conviction.
Regarding the prospect of a new “behavior-first” ideology: I don’t dismiss the idea at all, but I think such an ideology would need to meet three demanding criteria to avoid repeating the over-promising grand narratives of the past:
You mentioned the possibility of viable formulas that have never been tried. I would be very interested to hear your ideas: what practical steps or pilot designs do you think could meet the inclusivity, transparency, and truthfulness tests outlined above?
Thanks — I’ll DM you an address; I’d love to read the full book.
And I really like the cookie example: it perfectly illustrates how self-prediction turns a small temptation into a long-run coordination problem with our future selves. That mechanism scales up neatly to the dam scenario: when a society “eats the cookie” today, it teaches its future selves to discount tomorrow’s costs as well.
Those two Ainslie strategies — self-prediction and early pre-commitment — map nicely onto Time × Scope: they effectively raise the future’s weight (δ) without changing the math. I’m keen to plug his hyperbolic curve into the model and see how it reshapes optimal commitment devices for individuals and, eventually, AI systems.
Thanks again for offering the file and for the clear, memorable examples!
Thank you for such a thoughtful comment and deep engagement with my work! I’m thrilled this topic resonates with you—especially the idea of moral weight for future sentient beings. It’s truly a pivotal challenge.
I agree completely: standardizing a sentience scale (for animals, AI, even hypothetical species) is foundational for a fair w-vector. As you rightly noted, this will radically reshape eco-policy, agritech, and AI ethics.
This directly ties into navigating uncertainty (which you highlighted!), where I argue for balancing two imperatives:
Where do you see the threshold? For instance:
Thanks for reading the post — and for the pointer! I only know Ainslie’s Breakdown of Will from summaries and some work on hyperbolic discounting, so I’d definitely appreciate a copy if you're open to sharing.
The Time × Scope model currently uses exponential discounting just for simplicity, but it's modular — Ainslie’s hyperbolic function (or even quasi-hyperbolic models like β-δ) could easily be swapped in without breaking the structure.
Curious: what parts of Breakdown of Will do you find most relevant for thinking about long-term moral commitment or self-alignment? Would love to dive deeper into those sections first.
Thank you.
You're absolutely right: an artificial mind trained on our contradictory behavior could easily infer that our moral declarations lack credibility or consistency — and that would be a dangerous misinterpretation.
That’s why I believe it's essential to explicitly model this gap — not to excuse it, but to teach systems to expect it, interpret it correctly, and even assist in gradually reducing it.
I fully agree that moral evolution is a central part of the solution. But perhaps the gap itself isn’t just a flaw — it may be part of the mechanism. It seems likely that human ethics will continue to evolve like a staircase: once our real moral weights catch up to the current ideal, we move the ideal further. The tension remains — but so does the direction of progress.
In that sense, alignment isn't just about closing the gap — it’s about keeping the ladder intact, so that both humanity and AI can keep climbing.