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 (#1) from The Undercover Economist Strikes Back:
In The Wealth of Nations, [Smith] wrote: “A linen shirt, for example, is, strictly speaking, not a necessity of life. The Greeks and Romans lived, I suppose, very comfortably though they had no linen. But in the present times, through the greater part of Europe, a creditable day-laborer would be ashamed to appear in public without a linen shirt. . . .”
Smith’s point is not that poverty is relative, but that it is a social condition. People don’t become poor just because the median citizen receives a pay raise, whatever Eurostat may say. But they may become poor if something they cannot afford—such as a television—becomes viewed as a social essential. A person can lack the money necessary to participate in society, and that, in an important sense, is poverty.
For me, the poverty lines that make the most sense are absolute poverty lines, adjusted over time to reflect social change. Appropriately enough, one of the attempts to do such work is made by a foundation established by Seebohm Rowntree’s father, Joseph. The Joseph Rowntree Foundation uses focus groups to establish what things people feel it’s now necessary to have in order to take part in society—the list includes a vacation, a no-frills mobile phone and enough money to buy a cheap suit every two or three years. Of course, this is all subjective, but so is poverty. I’m not sure we will get anywhere if we believe that some expert, somewhere—even an expert as thoughtful as Mollie Orshansky or Seebohm Rowntree—is going to be able to nail down, permanently and precisely, what it means to be poor.
Even if we accept the simpler idea of a nutrition-based absolute poverty line, there will always be complications. One obvious one is the cost of living: lower in, say, Alabama than in New York. In principle, absolute poverty lines could and should take account of the cost of living, but the U.S. poverty line does not. A second issue is how to deal with short-term loss of income. A middle manager who loses her job and is unemployed for three months before finding another well-paid position might temporarily fall below the poverty line as far as her income is concerned, but with good prospects, a credit card and savings in the bank, she won’t need to live like a poor person—and she is likely to maintain much of her pre-poverty spending pattern. For this reason, some economists prefer to measure poverty not by what a household earns in a given week, month or year—but by how much money that household spends.
And:
According to the official United States government definition, 15 percent of the U.S. population was poor in 2011. That was the highest percentage since the early 1990s, up from 12.3 percent in 2006, just before the recession began. For all its faults, you can see one of the appeals of an absolute poverty line: if poverty goes up during recessions, you are probably measuring something sensible.
The European Union doesn’t use a comparable poverty line, but in the year 2000, researchers at the University of York tried to work out what EU poverty rates would be as measured against U.S. standards. They estimated poverty rates as high as 48 percent in Portugal and as low as 6 percent in Denmark, with France at 12 percent, Germany at 15 percent and the UK at 18 percent. Clearly, national income is a big influence on absolute poverty (Portugal is a fair bit poorer than Denmark), but so, too, is the distribution of income (France and the UK have similar average incomes, but France is more egalitarian).
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: