RSI capabilities could be charted, and are likely to be AI-complete.
What does RSI stand for?
Lately I've been listening to audiobooks (at 2x speed) in my down time, especially ones that seem likely to have passages relevant to the question of how well policy-makers will deal with AGI, basically continuing this project but only doing the "collection" stage, not the "analysis" stage.
I'll post quotes from the audiobooks I listen to as replies to this comment.
More (#3) from Better Angels of Our Nature:
...let’s have a look at political discourse, which most people believe has been getting dumb and dumber. There’s no such thing as the IQ of a speech, but Tetlock and other political psychologists have identified a variable called integrative complexity that captures a sense of intellectual balance, nuance, and sophistication. A passage that is low in integrative complexity stakes out an opinion and relentlessly hammers it home, without nuance or qualification. Its minimal complexity can be quantified by counting words like absolutely, always, certainly, definitively, entirely, forever, indisputable, irrefutable, undoubtedly, and unquestionably. A passage gets credit for some degree of integrative complexity if it shows a touch of subtlety with words like usually, almost, but, however, and maybe. It is rated higher if it acknowledges two points of view, higher still if it discusses connections, tradeoffs, or compromises between them, and highest of all if it explains these relationships by reference to a higher principle or system. The integrative complexity of a passage is not the same as the intelligence of the person who wrote it, but the
Okay. In this comment I'll keep an updated list of audiobooks I've heard since Sept. 2013, for those who are interested. All audiobooks are available via iTunes/Audible unless otherwise noted.
Outstanding:
Worthwhile if you care about the subject matter:
A process for turning ebooks into audiobooks for personal use, at least on Mac:
Personal and tribal selfishness align with AI risk-reduction in a way they may not align on climate change.
This seems obviously false. Local expenditures - of money, pride, possibility of not being the first to publish, etc. - are still local, global penalties are still global. Incentives are misaligned in exactly the same way as for climate change.
RSI capabilities could be charted, and are likely to be AI-complete.
This is to be taken as an arguendo, not as the author's opinion, right? See IEM on the minimal conditions for takeoff. Albeit if &q...
(I don't have answers to your specific questions, but here are some thoughts about the general problem.)
I agree with most of you said. I also assign significant probability mass to most parts of the argument for hope (but haven't thought about this enough to put numbers on this), though I too am not comforted on these parts because I also assign non-small chance to them going wrong. E.g., I have hope for "if AI is visible [and, I add, AI risk is understood] then authorities/elites will be taking safety measures".
That said, there are some steps in...
I personally am optimistic about the world's elites navigating AI risk as well as possible subject to inherent human limitations that I would expect everybody to have, and the inherent risk. Some points:
I've been surprised by people's ability to avert bad outcomes. Only two nuclear weapons have been used since nuclear weapons were developed, despite the fact that there are 10,000+ nuclear weapons around the world. Political leaders are assassinated very infrequently relative to how often one might expect a priori.
AI risk is a Global Catastrophic Risk i
The argument from hope or towards hope or anything but despair and grit is misplaced when dealing with risks of this magnitude.
Don't trust God (or semi-competent world leaders) to make everything magically turn out all right. The temptation to do so is either a rationalization of wanting to do nothing, or based on a profoundly miscalibrated optimism for how the world works.
/doom
I think there's a >15% chance AI will not be preceded by visible signals.
Aren't we seeing "visible signals" already? Machines are better than humans at lots of intelligence-related tasks today.
Which historical events are analogous to AI risk in some important ways? Possibilities include: nuclear weapons, climate change, recombinant DNA, nanotechnology, chloroflourocarbons, asteroids, cyberterrorism, Spanish flu, the 2008 financial crisis, and large wars.
Cryptography and cryptanalysis are obvious precursors of supposedly-dangerous tech within IT.
Looking at their story, we can plausibly expect governments to attempt to delay the development of "weaponizable" technology by others.
These days, cryptography facilitates international trade. It seems like a mostly-positive force overall.
One question is whether AI is like CFCs, or like CO2, or like hacking.
With CFCs, the solution was simple: ban CFCs. The cost was relatively low, and the benefit relatively high.
With CO2, the solution is equally simple: cap and trade. It's just not politically palatable, because the problem is slower-moving, and the cost would be much, much greater (perhaps great enough to really mess up the world economy). So, we're left with the second-best solution: do nothing. People will die, but the economy will keep growing, which might balance that out, because ...
Here are my reasons for pessimism:
There are likely to be effective methods of controlling AIs that are of subhuman or even roughly human-level intelligence which do not scale up to superhuman intelligence. These include for example reinforcement by reward/punishment, mutually beneficial trading, legal institutions. Controlling superhuman intelligence will likely require qualitatively different methods, such as having the superintelligence share our values. Unfortunately the existence of effective but unscalable methods of AI control will probably lull el
Congress' non-responsiveness to risks to critical infrastructure from geomagnetic storms, despite scientific consensus on the issue, is also worrying.
Even if one organization navigates the creation of friendly AI successfully, won't we still have to worry about preventing anyone from ever creating an unsafe AI?
Unlike nuclear weapons, a single AI might have world ending consequences, and an AI requires no special resources. Theoretically a seed AI could be uploaded to Pirate Bay, from where anyone could download and compile it.
The use of early AIs to solve AI safety problems creates an attractor for "safe, powerful AI."
What kind of "AI safety problems" are we talking about here? If they are like the "FAI Open Problems" that Eliezer has been posting, they would require philosophers of the highest (perhaps even super-human) caliber to solve. How could "early AIs" be of much help?
If "AI safety problems" here do not refer to FAI problems, then how do those problems get solved, according to this argument?
@Lukeprog, can you
(1) update us on your working answers the posed questions in brief? (2) your current confidence (and if you would like to, by proxy, MIRI's as an organisation's confidence in each of the 3:
Elites often fail to take effective action despite plenty of warning.
I think there's a >10% chance AI will not be preceded by visible signals.
I think the elites' safety measures will likely be insufficient.
Thank you for your diligence.
There's another reason for hope in this above global warming: The idea of a dangerous AI is already common in the public eye as "things we need to be careful about." A big problem the global warming movement had, and is still having, is convincing the public that it's a threat in the first place.
Who do you mean by "elites". Keep in mind that major disruptive technical progress of the type likely to precede the creation of a full AGI tends to cause the type of social change that shakes up the social hierarchy.
Combining the beginning and the end of your questions reveals an answer.
Can we trust the world's elite decision-makers (hereafter "elites") to navigate the creation of [nuclear weapons, climate change, recombinant DNA, nanotechnology, chloroflourocarbons, asteroids, cyberterrorism, Spanish flu, the 2008 financial crisis, and large wars] just fine?
Answer how just fine any of these are any you have analogous answers.
You might also clarify whether you are interested in what is just fine for everyone, or just fine for the elites, or just fine for the AI in question. The answer will change accordingly.
More (#5) from Wired for War:
The challenge for the United States is that stories like that of the Blues and Predator, where smart, innovative systems are designed at low costs, are all too rare. The U.S. military is by far the biggest designer and purchaser of weapons in the world. But it is also the most inefficient. As David Walker, the head of the Government Accountability Office (GAO), puts it, “We’re number 1 in the world in military capabilities. But on the business side, the Defense Department gets a D-minus, giving them the benefit of the doubt. If they were a business, they wouldn’t be in business.”
The Department of Justice once found that as much as 5 percent of the government’s annual budget is lost to old-fashioned fraud and theft, most of it in the defense realm. This is not helped by the fact that the Pentagon’s own rules and laws for how it should buy weapons are “routinely broken,” as one report in Defense News put it. One 2007 study of 131 Pentagon purchases found that 117 did not meet federal regulation standards. The Pentagon’s own inspector general also reported that not one person had been fired or otherwise held accountable for these violations.
...Whenever any new weapon is contemplated, the military often adds wave after wave of new requirements, gradually creeping the original concept outward. It builds in new design mandates, asks for various improvements and additions, forgetting that each new addition means another delay in delivery (and for robots, at least, forgetting that the systems were meant to be expendable). In turn, the makers are often only too happy to go along with what transforms into a process of gold-plating, as adding more bells, more whistles, and more design time means more money. These sorts of problems are rife in U.S. military robotics today. The MDARS (Mobile Detection Assessment Response System) is a golf-cart-sized robot that was planned as a cheap sentry at Pentagon warehouses and bases. It is now fifty times more expensive than originally projected. The air force’s unmanned bomber design is already projecting out at more than $2 billion a plane, roughly three times the original $737 million cost of the B-2 bomber it is to replace.
These costs weigh not just in dollars and cents. The more expensive the systems are, the fewer can be bought. The U.S. military becomes more heavily invested in those limited numbers of systems, and becomes less likely to change course and develop or buy alternative systems, even if they turn out to be better. The costs also change what doctrines can be used in battle, as the smaller number makes the military less likely to endanger systems in risky operations. Many worry this is defeating the whole purpose of unmanned systems. “We become prisoners of our very expensive purchases,” explains Ralph Peters. He worries that the United States might potentially lose some future war because of what he calls “quantitative incompetence.” Norm Augustine even jokes, all too seriously, that if the present trend continues, “In the year 2054, the entire defense budget will purchase just one tactical aircraft. This aircraft will have to be shared by the Air Force and Navy, three and one half days per week, except for the leap year, when it will be made available to the Marines for the extra day.”
One open question in AI risk strategy is: Can we trust the world's elite decision-makers (hereafter "elites") to navigate the creation of human-level AI (and beyond) just fine, without the kinds of special efforts that e.g. Bostrom and Yudkowsky think are needed?
Some reasons for concern include:
But if you were trying to argue for hope, you might argue along these lines (presented for the sake of argument; I don't actually endorse this argument):
The basic structure of this 'argument for hope' is due to Carl Shulman, though he doesn't necessarily endorse the details. (Also, it's just a rough argument, and as stated is not deductively valid.)
Personally, I am not very comforted by this argument because:
Obviously, there's a lot more for me to spell out here, and some of it may be unclear. The reason I'm posting these thoughts in such a rough state is so that MIRI can get some help on our research into this question.
In particular, I'd like to know: