Wiki Contributions


What grants has Carl Shulman's discretionary fund made?

Last update is that they are, although there were coronavirus related delays.

What is an example of recent, tangible progress in AI safety research?

Focusing on empirical results:

Learning to summarize  from human feedback was good, for several reasons.

I liked the recent paper empirically demonstrating objective robustness failures hypothesized in earlier theoretical work on inner alignment.


Help me find the crux between EA/XR and Progress Studies

Side note:  Bostrom does not hold or argue for 100% weight on total utilitarianism such as to take overwhelming losses on other views for tiny gains on total utilitarian stances. In Superintelligence he specifically rejects an example extreme tradeoff of that magnitude (not reserving one galaxy's worth of resources out of millions for humanity/existing beings even if posthumans would derive more wellbeing from a given unit of resources).

I also wouldn't actually accept a 10 million year delay in tech progress (and the death of all existing beings who would otherwise have enjoyed extended lives from advanced tech, etc) for a 0.001% reduction in existential risk.

Help me find the crux between EA/XR and Progress Studies

By that token most particular scientific experiments or contributions to political efforts may be such: e.g. if there is a referendum to pass a pro-innovation regulatory reform and science funding package, a given donation or staffer in support of it is very unlikely to counterfactually tip it into passing, although the expected value and average returns could be high, and the collective effort has a large chance of success.

Help me find the crux between EA/XR and Progress Studies

Your 3 items cover good+top priority, good+not top priority, and bad+top priority, but not #4, bad+not top priority.

I think people concerned with x-risk generally think that progress studies as a program of intervention to expedite growth is going to have less expected impact (good or bad) on the history of the world per unit of effort, and if we condition on people thinking progress studies does more harm than good, then mostly they'll say it's not important enough to focus on arguing against at the current margin (as opposed to directly targeting urgent threats to the world). Only a small portion of generalized economic expansion will go to the most harmful activities (and damage there comes from expediting dangerous technologies in AI and bioweapons that we are improving in our ability to handle, so that delay would help) or to efforts to avert disaster, so there is much more leverage focusing narrowly on the most important areas. 

With respect to synthetic biology in particular, I think there is a good case for delay: right now the capacity to kill most of the world's population with bioweapons is not available in known technologies (although huge secret bioweapons programs like the old Soviet one may have developed dangerous things already), and if that capacity is delayed there is a chance it will be averted or much easier to defend against via AI, universal sequencing, and improvements in defenses and law enforcement. This is even moreso for those sub-areas that most expand bioweapon risk. That said, any attempt to discourage dangerous bioweapon-enabling research must compete against other interventions (improved lab safety, treaty support, law enforcement, countermeasure platforms, etc), and so would have to itself be narrowly targeted and leveraged. 

With respect to artificial intelligence, views on sign vary depending on whether one thinks the risk of an AI transition is getting better or worse over time (better because of developments in areas like AI alignment and transparency research, field-building, etc; or worse because of societal or geopolitical changes). Generally though people concerned with AI risk think it much more effective to fund efforts to find alignment solutions and improved policy responses (growing them from a very small base, so cost-effectiveness is relatively high) than a diffuse and ineffective effort to slow the technology (especially in a competitive world where the technology would be developed elsewhere, perhaps with higher transition risk).

For most other areas of technology and economic activity (e.g. energy, agriculture, most areas of medicine) x-risk/longtermist implications are comparatively small, suggesting a more neartermist evaluative lens (e.g. comparing more against things like GiveWell).

Long-lasting (centuries) stagnation is a risk worth taking seriously (and the slowdown of population growth that sustained superexponential growth through history until recently points to stagnation absent something like AI to ease the labor bottleneck), but seems a lot less likely than other x-risk. If you think AGI is likely this century then we will return to the superexponential track (but more explosively) and approach technological limits to exponential growth followed by polynomial expansion in space. Absent AGI or catastrophic risk (although stagnation with advanced WMD would increase such risk), permanent stagnation also looks unlikely based on the capacities of current technology given time for population to grow and reach frontier productivity.

I think the best case for progress studies being top priority would be strong focus on the current generation compared to all future generations combined, on rich country citizens vs the global poor, inhabit and on technological progress over the next few decades, rather than in 2121. But given my estimates of catastrophic risk and sense of the interventions, at the current margin I'd still think that reducing AI and biorisk do better for current people than the progress studies agenda per unit of effort.

I wouldn't support arbitrary huge sacrifices of the current generation to reduce tiny increments of x-risk, but at the current level of neglectedness and impact (for both current and future generations) averting AI and bio catastrophe  looks more impactful without extreme valuations. As such risk reduction efforts scale up marginal returns would fall and growth boosting interventions would become more competitive (with a big penalty for those couple of areas that disproportionately pose x-risk).

That said, understanding tech progress, returns to R&D, and similar issues also comes up in trying to model and influence the world in assorted ways (e.g. it's important in understanding AI risk, or building technological countermeasures to risks to long term development). I have done a fair amount of investigation that would fit into progress studies as an intellectual enterprise for such purposes.

I also lend my assistance to some neartermist EAresearch focused on growth, in areas that don't very disproportionately increase x-risk, and to development of technologies that make it more likely things will go better.

My attempt to think about AI timelines

Robin Hanson argues in Age of Em  that annualized  growth rates will reach over 400,000% as a result of automation of human labor with full substitutes (e.g. through brain emulations)! He's a weird citation for thinking the same technology can't manage 20% growth.

"I really don't have strong arguments here. I guess partly from experience working on an automated trading system (i.e. actually trying to automate something)"

This and the usual economist arguments against fast AGI growth  seem to be more about denying the premise of ever succeeding at AGI/automating human substitute minds (by extrapolation from a world where we have not yet built human substitutes to conclude they won't be produced in the future), rather than addressing the growth that can then be enabled by the resulting AI.

My attempt to think about AI timelines

I find that 57% very difficult to believe. 10% would be a stretch. 

Having intelligent labor that can be quickly produced in factories (by companies that have been able to increase output by  millions of times over decades), and do tasks including improving the efficiency of robots (already cheap relative to humans where we have the AI to direct them, and that before reaping economies of scale by producing billions) and solar panels (which already have energy payback times on the order of 1 year in sunny areas), along with still abundant untapped energy resources orders of magnitude greater than our current civilization taps on Earth (and a billionfold for the Solar System) makes it very difficult to make the AGI but no TAI world coherent.

Cyanobacteria can double in 6-12 hours under good conditions, mice can grow their population more than 10,000x in a year. So machinery can be made to replicate quickly, and trillions of von Neumann equivalent researcher-years (but with AI advantages) can move us further towards that from existing technology.
I predict that cashing out the given reasons into detailed descriptions will result in inconsistencies or very implausible requirements.

Why AI is Harder Than We Think - Melanie Mitchell

She does talk about century plus timelines here and there.

How do you compare human and animal suffering?

I suspect there are biases in the EA conversation where hedonistic-compatible arguments get discussed more than reasons that hedonistic utilitarians would be upset by, and intuitions coming from other areas may then lead to demand and supply subsidies for such arguments.

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