summing up is a recurring series on topics & insights that compose a large part of my thinking and work. drop your email in the box below to get it – and much more – straight in your inbox.

Measuring Collective IQ, by Doug Engelbart

We have the opportunity to change our thinking and basic assumptions about the development of computing technologies. The emphasis on enhancing security and protecting turf often impedes our ability to solve problems collectively. If we can re-examine those assumptions and chart a different course, we can harness all the wonderful capability of the systems that we have today.

People often ask me how I would improve the current systems, but my response is that we first need to look at our underlying paradigms—because we need to co-evolve the new systems, and that requires new ways of thinking. It’s not just a matter of “doing things differently,” but thinking differently about how to approach the complexity of problem-solving today.

in a world where we've grown multiple orders of magnitude in our computing capacity, where we spend millions of dollars on newer, faster tools and technology, we put little emphasis on how we can augment human thinking and problem solving. and as doug says, it is not about thinking differently about these problems, it is thinking differently about our ability to to solve these problems.

The Seven Deadly Sins of Predicting the Future of AI, by Rodney Brooks

Suppose a person tells us that a particular photo is of people playing Frisbee in the park, then we naturally assume that they can answer questions like “what is the shape of a Frisbee?”, “roughly how far can a person throw a Frisbee?”, “can a person eat a Frisbee?”, “roughly how many people play Frisbee at once?”, “can a 3 month old person play Frisbee?”, “is today’s weather suitable for playing Frisbee?”. Today’s image labelling systems that routinely give correct labels, like “people playing Frisbee in a park” to online photos, have no chance of answering those questions. Besides the fact that all they can do is label more images and can not answer questions at all, they have no idea what a person is, that parks are usually outside, that people have ages, that weather is anything more than how it makes a photo look, etc., etc.

Here is what goes wrong. People hear that some robot or some AI system has performed some task. They then take the generalization from that performance to a general competence that a person performing that same task could be expected to have. And they apply that generalization to the robot or AI system.

Today’s robots and AI systems are incredibly narrow in what they can do. Human style generalizations just do not apply. People who do make these generalizations get things very, very wrong.

we are surrounded my hysteria about artificial intelligence, mistaken extrapolations, limited imagination any many more mistakes that distract us from thinking productively about the future. whether or not ai succeeds in the long term, it will nevertheless be developed and used with uncompromising efforts – regardless of any consequences.

Using Artificial Intelligence to Augment Human Intelligence, by Shan Carter and Michael Nielsen

Unfortunately, many in the AI community greatly underestimate the depth of interface design, often regarding it as a simple problem, mostly about making things pretty or easy-to-use. In this view, interface design is a problem to be handed off to others, while the hard work is to train some machine learning system.

This view is incorrect. At its deepest, interface design means developing the fundamental primitives human beings think and create with. This is a problem whose intellectual genesis goes back to the inventors of the alphabet, of cartography, and of musical notation, as well as modern giants such as Descartes, Playfair, Feynman, Engelbart, and Kay. It is one of the hardest, most important and most fundamental problems humanity grapples with.

the speed, performance or productivity of computers are mostly red herrings. the main problem is how we can leverage the computer as a tool. in different words, how can we use the computer to augment ourselves to do things that were previously impossible?