• Develop advanced nanotechnology already!  In particular, develop a self-replicating machine technology at the molecular scale. This could be done by using any or many of the approaches outlined in the Roadmap or by a direct approach I call the Feynman Path which I will be writing more about in detail in the coming weeks. But the bottom line is simple, and can be stated: “Just do it.” There isn’t any major, well-funded effort to do this, by whatever pathway.  There should be, and at best, all the possibilities should be explored in parallel.
• Decide what the Earth’s climate ought to be.  It strains the bounds of credibility to imagine that the optimal climate is just what we happened to have in 1950 (or any other particular year). This includes how much natural variability we want to allow: In the absence of any human influence, climate ranges to the steaming jungles of the dinosaur age 100 million years ago to the ice ages of 100 thousand. Do we want to freeze any possible dinosaurs out of our future?  Do we want to preclude any ice ages?

  
  (note that the apparent levelling off of temperature is due to the logarithmic scaling of the time axis — the 10,000 year holocene is the same width as the peaks in the Pleistocene or the squiggles in the Pliocene, and wouldn’t show up at all on the left side of the chart.)

• Decide how much CO₂ we want in the atmosphere. This is essentially independent of the question of temperature: CO₂ is a relatively minor greenhouse gas, the major one being of course H₂O. Greenhouses are typically kept at 1000 ppm for good plant
  growth (think agricultural productivity) and OSHA limits for humans allow up to 5000 ppm. Set the CO₂ level to whatever we want by choking or amplifying the natural flows to and from sources and sinks:
  
  (Probably the easiest flow to interdict is rotting vegetation; nanoengineer a way to make plastic from cornstalks, hay, etc.)
• If the temperature we want is higher than the equilibrium one for the level of CO₂ we want, add additional greenhouse gases to the air. We are actually doing that in a fairly major way by irrigation, raising the humidity of the air in large areas (e.g. California) where it would naturally be dry. However, there are other gasses such as methane which are quite potent and could be used.
• If we want it colder, we either remove some water from the air, or construct a negative GHG using nanotech — that is, a molecule or nanoballoon which reflects near-IR and is transparent to thermal IR — and administer whatever amount is necessary.
• If all else fails, build a Weather Machine. Be careful, though: while natural climate variability is not an existential risk — we do fine in steaming jungles and have lived through ice ages — a Weather Machine run by the same people who ran our financial system recently could be a very dangerous toy.

The paper is part of an edited book collection, available for purchase from Amazon, on bio-inspired nanoscale computing that was published about a week ago by Wiley.

Freitas’ contribution to the book is the following chapter:

Robert A. Freitas Jr., “Chapter 15. Computational Tasks in Medical Nanorobotics,” in M.M. Eshaghian-Wilner, ed., Bio-inspired and Nano-scale Integrated Computing, John Wiley & Sons, New York, 2009, pp. 391-428.

The chapter is about 5.2 MB in size and a draft preprint version may be downloaded from Freitas’ nanomedicine website. From the abstract:

Nanomedicine is the application of nanotechnology to medicine: the preservation
and improvement of human health, using molecular tools and molecular knowl-
edge of the human body. Medical nanorobotics is the most powerful form of
future nanomedicine technology. Nanorobots may be constructed of diamondoid
nanometer-scale parts and mechanical subsystems including onboard sensors,
motors, manipulators, power plants, and molecular computers. The presence of
onboard nanocomputers would allow in vivo medical nanorobots to perform
numerous complex behaviors which must be conditionally executed on at least a
semiautonomous basis, guided by receipt of local sensor data and constrained by
preprogrammed settings, activity scripts, and event clocking, and further limited
by a variety of simultaneously executing real-time control protocols. …
[W]e introduce the concept of nanorobot control
protocols which are required to ensure that each nanorobot fully completes its
intended mission accurately, safely, and in a timely manner according to plan. Six
major classes of nanorobot control protocols have been identified and include
operational, biocompatibility, theater, safety, security, and group protocols. Six
important subclasses of theater protocols include locational, functional, situa-
tional, phenotypic, temporal, and identity control protocols.

The nanomedicine books remain freely available online here, with links to MNT-based medical nanorobot designs here.

Here’s the abstract:

Technocrats from many developed countries, especially Japan and South Korea, are preparing for the human-robot co-existence society that they believe will emerge by 2030. Regulators are assuming that within the next two decades, robots will be capable of adapting to complex, unstructured environments and interacting with humans to assist with the performance of daily life tasks. Unlike heavily regulated industrial robots that toil in isolated settings, Next Generation Robots will have relative autonomy, which raises a number of safety issues that are the focus of this article. Our purpose is to describe a framework for a legal system focused on Next Generation Robots safety issues, including a Safety Intelligence concept that addresses robot Open-Texture Risk. We express doubt that a model based on Isaac Asimov’s Three Laws of Robotics can ever be a suitable foundation for creating an artificial moral agency ensuring robot safety. Finally, we make predictions about the most significant Next Generation Robots safety issues that will arise as the human-robot co-existence society emerges.

Now frankly, as I mentioned last week, the major thing we have to worry about with future technology for quite a while yet will simply be whether it works as intended. One very important part of making this happen is to make the systems, whatever they are, as simple as possible (but not simpler, as Einstein said).

However, Weng does address one point that I haven’t seen anywhere else besides my own book Beyond AI — the “open texture” of the law. Well before AI and robotics folks realized that it was impossible to specify actions in the real world precisely, lawyers did, and the legal notion of the open texture is the result. It’s a kind of deontic uncertainty principle — what in Beyond AI I called “formalist float”. Here’s the example I give in the book:

Two men sit down at a lunch counter and order cups of coffee. The first man finishes, gets up, and leaves a dime on the counter where he was sitting. He pays at the register and leaves.

The second man gets up. He places his fingertip on the dime and slides it over to his spot on the counter. Then he, too, pays and leaves.

What, if anything, has been stolen? The dime, intended by the first man for the waitress, still goes to the waitress. The second man never picked it up or possessed it. He was not legally obligated to leave a tip. Yet we are morally certain that he stole something.

What this means for robotics, AI, and indeed any formal system, is that there has to be some common-sense way to fill in the fabric of flesh in the gaps between the bones of the rigid, formal specifications.

But that’s the hard problem of AI itself, not just roboethics. If we can solve it for housecleaning robots, it may give us a leg up on solving it for the law itself, and all the other mechanisms of our rapidly-formalizing world.

Current-day magnetic memory is already “nanotechnology” under the loose definition, involving 5-nanometer particles of cobalt (having about 50,000 atoms). The authors have shown that a single molecule consisting of a cobalt dimer sitting on top of a benzene ring would have a high enough magnetic anisotropy to store a bit magnetically.

(surprisingly enough, the cobalts prefer to stack up rather than so lie down flat on the carbon ring.)

Don’t expect this in your computer any time soon; the authors write:

Technological use would require to solve at least three additional
problems: fabrication of large regular arrays; protection against oxidation without reducing
the anisotropy; new read/write technologies. Let us finally discuss a possible method to
solve the latter problem. Conventional write technology makes use of magnetic fields B in
the order of 1 T, Ref. 2. It would fail in the present situation, where a field B = MAE/µs of
several hundred tesla would be needed.

But they then go on to show that the bit could be written (reading is relatively easy) by a scanning-probe like tip which briefly ionized the upper cobalt. The mechanisms to do that would of course still have to be designed and built; but this is exploratory engineering in atomically-precise mechanisms, and we’d like to see more of it.

Research areas considered relevant to MNT (e.g., productive nanosystems and molecular machine systems) include but are not limited to:

• artificial molecular machines
• atomically-precise construction
• biomolecular machinery
• computational chemistry and molecular modeling
• mechanosynthesis
• nanomechanical engineering
• nanomanipulation
• natural molecular machines
• scanning probes and nanometrology
• self-assembly
• self-replicating machines
• supramolecular chemistry
• ultra-precision machining

Special consideration will be given to submissions clearly leading toward the construction of productive nanosystems.

After all, the skill, ingenuity, and technological base was available in 1900 to build steam-powered robots of human size, range of motion, and other physical characteristics (think of watchmakers and the rapidly-burgeoning capability of industrial machinery of the day). What was lacking was sensing and control.

I got mixed signals at WG. On the one hand, it was clear that the real bottleneck today is software: “We don’t sit down to have discussions about whether we should hire another person or put a bigger computer on the robot,” one person told me. The value added is clearly with the increased talent at analyzing, programming, or whatever.

On the other hand, I also heard a description of a vision/ranging module where implementations on (the current) standard processor versus a GPGPU version were compared: 13 seconds per frame versus 60 frames per second. The fast version wasn’t better in the sense of getting more detail or recognizing more objects — but it was faster, and in a regime that bumped it from much worse than, to somewhat better than, human real-time performance.

My personal take on this is that in many fields, the advances due to algorithms have matched those due to raw processing power, and that robotics is in a position to take advantage of both. WG’s open-source strategy is great for leveraging their resources in this area while benefitting the field as a whole.

Over the course of the 2010s, as robots get better able to cope with domestic environments and are more widely used there, the pressure for them to be more robust and adaptive, to learn and exhibit common sense, will increase. The big breakthrough in robust 2-D navigation came from Hans Moravec’s Bayesian grids, which changed the whole style of navigation from efficient symbolic — but brittle — algorithms to robust but computationally brute force ones. My intuition is that a similar revolution awaits in virtually everything the robot does and thinks about, and Moore’s Law will make it feasible.

Investigators looking into the deadly crash of two Metro transit trains focused Tuesday on why a computerized system failed to halt an oncoming train, and why the train failed to stop even though the emergency brake was pressed.

The post is just a news clipping, and offers no interpretive comment, but I think some is perhaps appropriate.

Train crashes have been happening regularly for over a century. They are not something new that has anything at all to do with AI or machine ethics or any similar concern. They are, however, a reminder that there is something very important that is often overlooked in the popular concern about the increase in technological impact on our lives. And that is that technology already has a huge impact on our lives, and has done since the industrial revolution — and the first, most important concern we must have is to make sure that the technology we have works properly, as intended.

Unless I am completely mistaken and deluded, there was and is nobody associated with the DC train system who wanted the crash to happen. It’s not a question of morality at the level of bad intentions, either of people or machines.

It was, in simple terms, a case of incompetence. It may have been of design, or of management, or of implementation, or maintenance. It may have been software or hardware. Most likely it was some combination. But the bottom line is simple: things didn’t work the way they were supposed to.

The modern world is full of movements that are overly concerned with motivations, and it is passe to worry about whether whatever cause you’re espousing will actually accomplish the grand goals that are claimed for it. Bluntly put, people are too concerned with other peoples’ wishes, which are none of their business, and not enough concerned with other peoples’ competence, which is very much a legitimate concern.

You’ll find that for things that really matter — like not having train wrecks — people pretty much all want the right thing already.

Willow Garage is a research robotics company in Silicon Valley which has a unique mission for a start-up. They are oriented to making an impact on the field of robotics rather than making an immediate profit. Cousins explained it in these terms: the average robotics PhD student spends 90% of his time building a robot and the remaining 10% extending the state of the art. If Willow Garage succeeds, those numbers will be reversed.

Thus the WG design is very general and very robust, designed to be very hard to break and also fairly safe in the hands of an experimental, buggy, program. It’s a gorgeous piece of hardware. In a move that resonates strongly with Foresight, their software is open source.

Wearing my futurist hat, I asked several researchers at WG how strongly near-term improvements in processing power, a la Moore’s Law, would affect the performance of their robot. By and large they didn’t seem to think it was critical. The present bottleneck appears to be software — ideas, algorithms, integration, and experience.

The OSS community may be able to make a significant contribution here. And because it’s open source, anything you add would redound to the world at large and not just the company.

Rosie the robot maid by 2020? I wouldn’t bet against it.

This would be, frankly, an insane classification on which to base regulations of whatever technology you had in mind. We regulate hair from appearing in our food in restaurants; we regulate cell phones from operating on the wrong frequency; we don’t legally regulate golf balls but the USGA does. Regulating hair and 2-inch steel plate the same because they were both “millitechnology” would be nuts.

Similarly, the ridiculously broad term “nanotechnology” is a monumentally silly basis for regulating things. Nano-powders and particulates are substances — regulate them according to their toxicity, residence time in the atmosphere, biodegradability. Something real.

As reported in the online version of the Journal of Nanoparticle Research today (June 19), Scheufele and Corley found that the public tends to focus on the benefits — rather than potential environmental and health risks — when making decisions about nanotechnology regulation, whereas scientists mainly focus on potential risks and economic values.
“We think that nanoscientists view regulations as protections for the public, and that’s part of the reason why they focus on the potential risks,” says Corley, the Lincoln Professor of Public Policy, Ethics and Emerging Technologies in ASU’s School of Public Affairs. “On the other hand, the public seems to think of nanotechnology regulations as restricting their access to new products and other beneficial aspects of nanotechnology.”
According to the study, leading U.S. nanoscientists believe regulations are most urgently needed in the areas of surveillance and privacy, human enhancement, medicine and the environment. At the same time, this group feels that other areas, including machines and computers, have little need for further regulation.

Confounding the study, of course, or any study like this, would be the fact that what the researchers are calling “nanotechnology” and what the public thinks it is are two different things. And of course anyone writing in the Journal of Nanoparticle Research is likely to be about as far from a notion of nanomachines, even nanoelectronics with no moving parts, as anyone in the field.

To my mind, this is just another piece of evidence that the word nanotechnology has broadened to the point where it is more a hindrance than a help in understanding what’s really going on and how the future of technology may develop.