Data Mining: Text Mining, Visualization and Social Media

The Economist gets in on the AI Fluff

The Economist leads with an editorial and an article on The Dawn of Artificial Intelligence.

The editorial starts of with:

“THE development of full artificial intelligence could spell the end of the human race,” Stephen Hawking warns. Elon Musk fears that the development of artificial intelligence, or AI, may be the biggest existential threat humanity faces. Bill Gates urges people to beware of it.

Dread that the abominations people create will become their masters, or their executioners, is hardly new. But voiced by a renowned cosmologist, a Silicon Valley entrepreneur and the founder of Microsoft—hardly Luddites—and set against the vast investment in AI by big firms like Google and Microsoft, such fears have taken on new weight. With supercomputers in every pocket and robots looking down on every battlefield, just dismissing them as science fiction seems like self-deception. The question is how to worry wisely.

To my knowledge, while the three titans mentioned here of undeniable intellect, it is not clear why two of them are relevant at all. I consider myself reasonably smart, but should I be quoted on my opinion of current treatments of toxoplasmosis? The argument "a smart person says X, therefore we should attend" is known as the appeal to false authority (i.e. a fallacious argument). Such arguments introduce another argumentative crime: the exclusion of actual authority. Eric Horvitz comes to mind:

The head of Microsoft’s main research lab has dismissed fears that artificial intelligence could pose a threat to the survival of the human race.

Eric Horvitz believed that humans would not “lose control of certain kinds of intelligences”, adding: “In the end we’ll be able to get incredible benefits from machine intelligence in all realms of life, from science to education to economics to daily life.”

The article then stumbles along confusing advances in machine perception and machine learning with intelligence. Predictably, the Kasparov vs Deep Blue achievement is trundled out:

Yet AI is already powerful enough to make a dramatic difference to human life. It can already enhance human endeavour by complementing what people can do. Think of chess, which computers now play better than any person.

Suggesting that any computer can now beat all humans. Deep Blue was a singular machine which was dismantled after the match. And how does chess playing make a dramatic difference to human life?

A well informed article - and one that is actually interesting to read - should lead with a concrete set of definitions regarding the components of artificial intelligence (perception, reasoning, etc.) and discuss the discrete advances in those areas. Such an article should discuss the challenges of bringing those things together in anything other than the most rudimentary ways they are combined currently. An interesting article on AI would discuss the economics that drive investments and how they dictate what areas are worked on and which aren't.

In all these articles, there is a vague notion of inevitability, as if the machines themselves were selectively investing in research areas, or as if we could stand back and do nothing and this scary version of AI would emerge. It's as if the article were suggesting that landing on the moon was inevitable. The fact that humans did this and then never returned indicates that it was an incredibly intentional endeavor.

 

AI, Artificial Birds and Aeroplanes

The Turing Test for artificial intelligence is a reasonably well understood idea: if, through a written form of communication, a machine can convince a human that it too is a human, then it passes the test. The elegance of this approach (which I believe is its primary attraction) is that it avoids any troublesome definition of intelligence and appeals to an innate ability in humans to detect entities which are not 'one of us'.

This form of AI is the one that is generally presented in entertainment (films, novels, etc.).

However, to an engineer, there are some problems with this as the accepted popular idea of artificial intelligence.

I believe that software engineering can be evaluated in a simple measure of productivity. We either create things that make the impossible possible - going from 0 to 1, or we create things that amplify some value, generally a human's ability to do something, - going from X to nX. In other words, we enable a new thing, or we multiple our ability to do something.

Turing AI, while clearly an interesting intellectual concept, is like building an artificial bird instead of building an aeroplane:

• A Turing AI can converse in natural language, but humans can't speak charts or holograms as a means to explain something.
• A Turing AI can read a book and appear to understand it, but it can't read a thousand research articles on cancer and find a connection between discoveries that results in a breakthrough.
• A Turing AI doesn't have to even be particularly intelligence (though it probably ought to at least appear self aware, reflective, etc) and so would be potentially like making a very poor hire for your team.

I believe that if we consider opportunities for applying 'AI methods' to the vast corpus of data (both in natural language and in various structured forms) on the web, we will realize that there is an economic motivation (i.e. build value for users that can build a user base) that will require all the generally accepted facets of an AI (reasoning, perception, communication with humans, theory of mind, etc.) but will be nothing like a Turing AI.

Rather than think of search engines - the fundamental agents that mediate the web corpus - as mechanisms to help humans find the 'right' document - I believe it is time to change our intentions to:optimize the value of the data on the internet for all mankind.

When we achieve this, we will have built an AI, but it won't be a Turing AI and it may not even pass the Turing Test.

How to Understand Computers in Film

When we see an act of programming, screeds of code or other interactions with computers in movies, software engineers are likely to roll their eyes.

• When Chappie's coder has to write 'terabytes of code'
• When Ford's computer guy has to 'write a special program' to crack a password in one of the Jack Ryan movies
• etc.

I rolled my eyes at these.

But I also realize that these interactions are just symbols. They are place holders for 'someone doing some coding'. If we actually saw someone doing some coding, I think we'd roll our eyes for another reason.

This model probably works for any exposure of any technical area in a movie from coding to cooking to sailing to farming. Rather than criticizing the creators of the movie for lack of research, it is so much easier to recognize these moments as symbolic fillers with a dramatic twist.

How the Tech Media Keeps Artificial Intelligence at a Distance

In sympathy with yesterday's post about AI as presented in films, consider this recent article from the Wall Street Journal: Artificial Intelligence Experts are in High Demand. A list of mostly machine learning experts is produced as evidence for the topic of the article. There is an unfortunate trend being presented to the public in this space in which the term 'artificial intelligence' is being used to draw readers with stories of real technical achievements in the space of machine learning and machine perception (recognizing a cat in a image is not an act of artificial intelligence), movies are being produced that romanticize a form of unobtainable AI, and the two are being tied together with stories of impending doom (Musk, Hawking).

All this is done with little or no investment in helping us establish what we really mean - and need - in an artificial intelligence.

If artificial intelligence experts were in high demand, then linguistics, philosophers, sociologists, etc. should be very happy - not just ML peeps.

How Hollywood Keeps Artificial Intelligence at a Distance

When something doesn't exist (like artificial intelligence) it's easy to think that there is some missing piece of magic required to bring it in to existence. There has been a growing interest in movie depictions of AI of late, and these all seem to require some sort of non-linear step to realize this technology.

• Ex Machina (which I really enjoyed) required a new sort of hard/software in the form of a jelly like substance.
• Chappie (which I also liked, though I generally prefer cheese and ham combined in a sandwich) required 'terabytes of coding' and a good amount of luck to produce its AI.
• Age of Ultron (a film about one liners and explosions) required a magic jewel from Loki's staff no less to create its AI.
• Transcendence (Kurzweil summarized) gives up on AI and simply loads a human brain into the ether.

The message in all of these movies is - the reason we don't have AI is that we haven't taken some non-linear step.

Artificial Intelligence and Economics

There are lots of articles online of the form - humanity has built some amazing things, so why haven't we produced an artificial intelligence? These articles (here's an example) often include some discussion of a task that even a very young human can perform - e.g. look at an image and describe what objects are in it (though personally I don't believe this is an indication of intelligence).

I believe that one of the key reasons that we can produce algorithms that can design super efficient jet engines, but not systems with the rudimentary common sense reasoning capabilities of a 3 year old is the economic context that drives innovation. The airline industry has an annual revenue of 700 billion dollars. No one has (yet) articulated the revenue potential of a technology that can look at a photograph and tell you what is in it.

The most important (and possibly last) step in the development of artificial intelligence is to create the economic engine that will require and motivate it.