Deen Abiola - 16 Jul 2013
For a long time I was a skeptic about the possibility of a singularity - the notion that day to day living assumes large beyond human levels of intelligence (any child from 1800 will have no problem adapting to life today but not so post singularity), rapid change and that it would happen in the timespan of about a century or less.
But after reading an article by Vernor Vinge from around 1990 I switched gears. I'll point out though, that singularity people also often espouse bonus packages which I do not think of as likely: post-scarcity, post suffering and immortality. I will admit better economics, more energy, more equity and longer healthier lives however.
Often the assumption is that one of AI, mind uploading or nanotech will exist and have some exponential path. I can't know but I am highly skeptical of such developments in my lifetime. The methods of genetic engineering might lead to modest boosts but really, it's not even in the running.
The place we're heading by all signs is one of Intelligence Amplification. The amazing bit is that Vinge predicted it 20 years ago! Every one of the indications of being along an amplification path has occured. Quoting:
When people speak of creating superhumanly intelligent beings, they are usually imagining an AI project. But as I noted at the beginning of this paper, there are other paths to superhumanity. Computer networks and human-computer interfaces seem more mundane than AI, and yet they could lead to the Singularity. I call this contrasting approach Intelligence Amplification (IA). IA is something that is proceeding very naturally, in most cases not even recognized by its developers for what it is. But every time our ability to access information and to communicate it to others is improved, in some sense we have achieved an increase over natural intelligence. Even now, the team of a PhD human and good computer workstation (even an off-net workstation!) could probably max any written intelligence test in existence.
Here are the predictions with my commentary and examples in italics:
Human/computer team automation: Take problems that are normally considered for purely machine solution (like hill-climbing problems), and design programs and interfaces that take a advantage of humans' intuition and available computer hardware. Stuff like eyewire, foldit, mechanical turk, clickworker and crowdflower are examples of this
Develop human/computer symbiosis in art: Combine the graphic generation capability of modern machines and the esthetic sensibility of humans. As he writes it, this is still underdeveloped. Bret Victor recently gave a demo showing how much so http://blog.andreaskoller.com/2013/05/bret-victor-prototypes-interactive-dynamic-drawing/.
Allow human/computer teams at chess tournaments. We already have programs that can play better than almost all humans. But how much work has been done on how this power could be used by a human, to get something even better? If such teams were allowed in at least some chess tournaments, it could have the positive effect on IA research that allowing computers in tournaments had for the corresponding niche in AI. This one was incredibly spot on, both the sport and research aid, see Advanced Chess.
Develop interfaces that allow computer and network access without requiring the human to be tied to one spot, sitting in front of a computer. (This is an aspect of IA that fits so well with known economic advantages that lots of effort is already being spent on it.) It's hard to imagine a time before Smartphones and tablets. Soon we will have watches and glasses to boot. And those are all just the beginning.
Develop more symmetrical decision support systems. A popular research/product area in recent years has been decision support systems. This is a form of IA, but may be too focussed on systems that are oracular. As much as the program giving the user information, there must be the idea of the user giving the program guidance. This one is close but we are still missing out on the symbiotic aspect. Where rather than just expect an answer, the human also aids in forming the correct answer. Palantir is the nearest. This is my personal area of focus
Use local area nets to make human teams that really work (ie, are more effective than their component members). This is generally the area of "groupware", already a very popular commercial pursuit. The change in viewpoint here would be to regard the group activity as a combination organism. ... And of course shared data bases could be used much more conveniently than in conventional committee operations. This one is a hard problem and probably the one we're furthest from in his list. If we can nail effective collaboration (both digital and non) I do believe it would create such efficiency, an incredible chain reaction in progress would be unleashed
Exploit the worldwide Internet as a combination human/machine tool. Of all the items on the list, progress in this is proceeding the fastest and may run us into the Singularity before anything else. The power and influence of even the present-day Internet is vastly underestimated. wikipedia and stackoverflow are prominent examples
The very anarchy of the worldwide net development is evidence of its potential. As connectivity and bandwidth and archive size and computer speed all increase, we are seeing something like Lynn Margulis'  vision of the biosphere as data processor recapitulated, but at a million times greater speed and with millions of humanly intelligent agents (ourselves). Note that I am not proposing that AI research be ignored or less funded. What goes on with AI will often have applications in IA, and vice versa. I am suggesting that we recognize that in network and interface research there is something as profound (and potential wild) as Artificial Intelligence. With that insight, we may see projects that are not as directly applicable as conventional interface and network design work, but which serve to advance us toward the Singularity along the IA path.
Note that I am not proposing that AI research be ignored or less funded. What goes on with AI will often have applications in IA, and vice versa. I am suggesting that we recognize that in network and interface research there is something as profound (and potential wild) as Artificial Intelligence. With that insight, we may see projects that are not as directly applicable as conventional interface and network design work, but which serve to advance us toward the Singularity along the IA path.
Other prescient statements, stuff that have only really made the news in the past couple of years:
Limb prosthetics is a topic of direct commercial applicability. Nerve to silicon transducers can be made . This is an exciting, near-term step toward direct communication. [http://www.media.mit.edu/people/hherr, Todd Kuiken: A prosthetic arm that "feels", http://www.independent.co.uk/life-style/gadgets-and-tech/news/a-sensational-breakthrough-the-first-bionic-hand-that-can-feel-8498622.html]
Direct links into brains seem feasible, if the bit rate is low: given human learning flexibility, the actual brain neuron targets might not have to be precisely selected. Even 100 bits per second would be of great use to stroke victims who would otherwise be confined to menu-driven interfaces. [http://news.cnet.com/8301-17938_105-57559675-1/brain-implants-let-paralyzed-woman-move-robot-arm/]
Plugging in to the optic trunk has the potential for bandwidths of 1 Mbit/second or so. But for this, we need to know the fine-scale architecture of vision, and we need to place an enormous web of electrodes with exquisite precision. [http://www.guardian.co.uk/world/2013/jun/07/bionic-eye-vision-for-blind, http://www.nytimes.com/2013/02/15/health/fda-approves-technology-to-give-limited-vision-to-blind-people.html?_r=0]
And the final bit which we are nowhere near:
If we want our high bandwidth connection to be in addition to what paths are already present in the brain, the problem becomes vastly more intractable. Just sticking a grid of high-bandwidth receivers into a brain certainly won't do it. But suppose that the high-bandwidth grid were present while the brain structure was actually setting up, as the embryo develops. That suggests: Animal embryo experiments. I wouldn't expect any IA success in the first years of such research, but giving developing brains access to complex simulated neural structures might be very interesting to the people who study how the embryonic brain develops. In the long run, such experiments might produce animals with additional sense paths and interesting intellectual abilities.
He finishes with a warning:
We humans have millions of years of evolutionary baggage that makes us regard competition in a deadly light. Much of that deadliness may not be necessary in today's world, one where losers take on the winners' tricks and are coopted into the winners' enterprises. A creature that was built de novo might possibly be a much more benign entity than one with a kernel based on fang and talon. And even the egalitarian view of an Internet that wakes up along with all mankind can be viewed as a nightmare