Intelligence Augmentation

Intelligence Augmentation

A transcript of the above talk

Hi, I'm Tim Tyler, and this is a video about augmenting human intelligence.


Intelligence augmentation is the practice of making humans smarter with technology.

While the field also covers smart drugs, nutrition and education, this video will be concerned with the practice of making humans smarter using machines.

So far, most intelligence augmentation has consisted of interfacing brains to additional computing hardware, which has properties that complement the human brain.

Computers sit on many desktops, and they are carried around - in the form of laptops, PDAs and mobile phones. They are connected together in an enormous, worldwide network.

These computer excel at rapid, serial deterministic operations - and those are areas where the human brain is weak. They also effectively supplement human memory.

In contrast with "pure" machine intelligence strategies, intelligence augmentation builds on the human brain - rather than starting again from scratch. That means that systems start out with human level intelligence, and go forwards from there. On the other hand, these systems have to interface with a human - and that is often a clumsy and slow bottleneck in the resulting system.

Despite the problems, intelligence augmentation has had an enormous impact on the world so far - arguably much greater than machine intelligence strategies that omit humans.

This video will look briefly at the current state, and then consider the future prospects of the field.

Augmented intelligence

Some of the original cybernetic pioneers who originally conceived of the idea of intelligence augmentation envisaged it as an alternative to the pure machine intelligence projects of the time.

However, from the point of view of the machines, intelligence augmentation looks more like a way to make use of existing human brains as stepping stones, rather than competing directly with them. I'll illustrate the issue with some diagrams.

Here's a cybernetic diagram of the nervous system of an unmodifed human:

You can see that the sensory system is in green, and the motor system is in blue.

Next, here's the corresponding cybernetic diagram of a pure-machine intelligence:

Considering a human brain augmented with some machine sensors produces a diagram that looks like this:

The machine sensors preprocess part of the human's sensory data, and post-process the human's motor output.

The machine sensors do not need to passively process the data. They may themselves be intelligent. Just as the human retina highlights motion and edges, so machine sensors can highlight correct answers and potential risks.

Similarly with the motor outputs - they too can benefit from being intelligent - so they can identify incorrect actions and correct them.

Now consider this cybernetic diagram of an augmented human intelligence.

As time passes, we can expect the machine intelligence component to grow and grow - gradually replacing the functions of the human brain one domain at a time - until the original brain is redundant and can be discarded.

For the most part, intelligence augmentation looks like a route to pure-machine intelligence - rather than an alternative to it.

However, the relationship between pure-machine intelligence projects and ones which seek to augment human intelligence is not entirely benign. For one thing, the former has a greater need for parallelism. The sorry state of commercial computing hardware in this respect is - in part - a reflection of the fact that augmentation projects already have the resource of a huge parallel machine to draw on.

Sensors and actuators

One of the problems with augmented intelligence projects is that they require a specialised range of sensors and actuators devoted to the task of interfacing with humans.

Computer input devices are the biggest problem. Humans have terrible output bandwidth. Some of the most important input devices so far have been the computer keyboard and mouse. Cameras, scanners and microphones are becoming increasingly important.

Computer output devices generally face fewer problems. Computer monitors, computer printers and loud speakers have been some of the most significant output devices so far.

Future prospects

Looking to the future, input devices can be improved by getting speech recognition into a more usable state, and by training a camera on the user to track their head and eye movements - and to respond to gestures. There's also quite a lot which can be done with additional buttons, toggles and wheels - as my own set-up demonstrates.

Output devices can also be improved. In the short term, monitors will grow, and people will increasingly tile monitors, to produce monitor walls. On a longer timeline, the advent of 3D printing, programmable matter, and robots will result in more output channels.

Cost and portability are other areas with considerable scope for improvement. As costs come down, and portability improves, computers will become increasingly ubiquitous in wealthy countries - and will increase their penetration in less affluent ones.

Head-mounted systems will analyse the environment, whisper advice into our ears, and use lasers to project meta-information onto the external world.


Finally, we come to the issue of finance and rewards.

Pure-machine intelligence projects typically start off facing a funding gap - since considerable work needs to be done initially before the resulting products can be competitive with human labour.

There is no such gap for intelligence augmentation projects. They start out being competitive with humans - since a human is the base component - and every step forwards from there brings immediate rewards.

As a result, intelligence augmentation projects often enjoy better funding, since they bring quicker returns. This in turn raises the bar which pure-machine intelligence projects must rise above in order to be viable.

So, in summary, intelligence augmentation is an extremely important area. Those wishing to contribute to the progress of science, technology, or civilisation in general should consider this field closely - efforts in this area seems to have a history of paying off on a large scale.


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