That sounds like a good plan, but I think a lot of the horses have already left the barn. For example, Coreweave is investing $1.6 billion dollars to create an AI datacenter in Plano, TX that is purported to to be 10 exaflops and that system goes live in 3 months. Google is spending a similar amount in Columbus, Ohio. Amazon, Facebook, and other tech companies are also pouring billions upon billions into purpose-built AI datacenters.
NVIDIA projects $1 trillion will be spent over the next 4 years on AI datacenter build out. That would be an unprecedented number not seen since the advent of the internet.
All of these companies have lobbyists that will make a short-term legislative fix difficult. And for this reason I think we should be considering a Plan B since there is a very good chance that we won’t have enough time for a quick legislative fix or the time needed to unravel alignment if we’re on a double exponential curve.
Again, if it’s a single exponential then there is plenty of time to chat with legislators and research alignment.
In light of this I think we need to have a comprehensive “shutdown plan” for these mammoth AI datacenters. The leaders of Inflection, Open-AI, and other tech companies all agree there is a risk and I think it would be wise to coordinate with them on a plan to turn everything off manually in the event of an emergency.
Source: $1.6 Billion Data Center Planned For Plano, Texas (localprofile.com)
Source: Nvidia Shocker: $1 Trillion to Be Spent on AI Data Centers in 4 Years (businessinsider.com)
Source: Google to invest another $1.7 billion into Ohio data centers (wlwt.com)
Source: Amazon Web Services to invest $7.8 billion in new Central Ohio data centers—Axios Columbus
A lot of the debate surrounding existential risks of AI is bounded by time. For example, if someone said a meteor is about to hit the Earth that would be alarming, but the next question should be, “How much time before impact?” The answer to that question effects everything else.
If they say, “30 seconds”. Well, there is no need to go online and debate ways to save ourselves. We can give everyone around us a hug and prepare for the hereafter. However, if the answer is “30 days” or “3 years” then those answers will generate very different responses.
The AI alignment question is extremely vague as it relates to time constraints. If anyone is investing a lot energy in “buying us time” they must have a time constraint in their head otherwise they wouldn’t be focused on extending the timeline. And yet—I don’t see much data on bounded timelines within which to act. It’s just assumed that we’re all in agreement.
It’s also hard to motivate people to action if they don’t have a timeline.
So what is the timeline? If AI is on a double exponential curve we can do some simple math projections to get a rough idea of when AI intelligence is likely to exceed human intelligence. Presumably, superhuman intelligence could present issues or at the very least be extremely difficult to align.
Suppose we assume that GPT-4 follows a single exponential curve with an initial IQ of 124 and a growth factor of 1.05 per year. This means that its IQ increases by 5% every year. Then we can calculate its IQ for the next 7 years using the formula.
y = 124 * 1.05^x
where x is the number of years since 2023. The results are shown in Table 1.
Table 1: IQ of GPT-4 following a single exponential curve.
Now suppose we assume that GPT-4 follows a double exponential curve with an initial IQ of 124 and growth constants of b = c = 1.05 per year. This means that its IQ doubles every time it increases by 5%. Then we can calculate its IQ for the next 7 years using the formula
y = 124 * (1.05)((1.05)x)
where x is the number of years since 2023. The results are shown in Table 2.
Table 2: IQ of GPT-4 following a double exponential curve.
Clearly whether we’re on a single or double exponential curve dramatically effects the timeline. If we’re on a single exponential curve we might have 7-10 years. If we’re on a double exponential curve then we likely have 3 years. Sometime around 2026 − 2027 we’ll see systems smarter than any human.
Many people believe AI is on a double exponential curve. If that’s the case then efforts to generate movement in Congress will likely fail due to time constraints. The is amplified by the fact that many in Congress are older and not computer savvy. Does anyone believe Joe Biden or Donald Trump are going to spearhead regulations to control AI before it reaches superhuman levels on a double exponential curve? In my opinion, those odds are super low.
I feel like Connor’s effort make perfect sense on a single exponential timeline. However, if we’re on a double exponential timeline then we’re going to need alternative ideas since we likely won’t have enough time to push anything through Congress in time for it to matter.
On a double exponential timeline I would be asking question like, “Can superhuman AI self-align?” Human tribal groups figure out ways to interact and they’re not always perfectly aligned. Russia, China, and North Korea are good examples. If we assume there are multiple superhuman AIs in the 2026⁄27 timeframe then what steps can we take to assist them in self-aligning?
I’m not expert in this field, but the questions I would be asking programmers are:
What kind of training data would increase positive outcomes for superhuman AIs interacting with each other?
What are more drastic steps that can be taken in an emergency scenario where no legislative solution is in place? (e.g., location of datacenters, policies and protocols for shutting down the tier 3 & 4 datacenters, etc.)
These systems will not be running on laptops so tier 3 & tier 4 data center safety protocols for emergency shutdown seem like a much, much faster path than Congressional action. We already have standardized fire protocols, adding a runaway AI protocol seems like it could be straightforward.
Interested parties might want to investigate the effects of the shutdown of large numbers of tier 3 and tier 4 datacenters. A first step is a map of all of their locations. If we don’t know where they’re located it will be really hard to shut them down.
These AIs will also require a large amount of power and a far less attractive option is power shutdown at these various locations. Local data center controls are preferable since an electrical grid intervention could result in the loss of power for citizens.
I’m curious to hear your thoughts.