French Researchers Want HAL To Write Fatwas

from the God-of-the-machine dept

The Arabic Daily Asharq Al-Awsat reports that a team of French researchers are hoping to create an "Electronic Mufti" -- an artificial intelligence capable of processing the opinions of historical clerics and generating a fatwa, or religious edict, that answers novel problems as the human template would have. The goal is supposedly to generate "more accurate" opinions, not subject to... human... error.

This has the whiff of a prank about it, but if it's for real, it seems to raise intriguing theological no less than technological questions. Islam tends to frown on pictorial representations of Allah's handiwork, and in particular -- as the Danish Cartoon Fiasco reminded us -- of the Prophet Muhammad, a likely candidate for simulation. Would a simulacrum of the Prophet's thought processes run afoul of the prohibition on representation? One member of the French team, Dr. Anas Fawzi, assures us that Islamic scholars have declared that his project is not "haram," or unlawful. But something tells me controversy is inevitable. Either way, I find I can't help but think of the confessional CyberJesus from the George Lucas classic THX 1138.

Julian Sanchez is an expert at the Insight Community. To get insight and analysis from Julian Sanchez and other experts on challenges your company faces, click here.

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Fooling Computers With Optical Illusions Is A Step In The Right Direction

from the maybe-my-laptop-will-appreciate-escher-soon dept

Just a few weeks ago, computers were learning to understand knock knock jokes. Now, computers take another step towards being human; they are fooled by optical illusions, just like us. By creating a computer program that learns how to comprehend different shades of gray similar to the way that an infant learns, the computer also falls prey to White's Illusion, an illusion in which bands of gray appear different even though they are the same shade. This is an important step in computer vision since this illusion is not a physiological one, where optical sensors send the brain the wrong image, but rather, a cognitive one, where perception of an image is misinterpreted. As we get closer to true artificial intelligence, what other kinds of human faults will computers be able to emulate? And, considering that computers are already better than us at certain tasks, will those faults be amplified? After all, "to err is human, to really screw up you need a computer."

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Can You Teach Computers To Understand Knock-Knock Jokes?

from the knock-knock dept

We were just discussing how difficult it is for computers to handle certain types of tasks, that are often much better suited for human intelligence. However, that won't stop some from trying to program computers to do all sorts of things, with the latest such effort focused on teaching a computer to understand knock-knock jokes. Knock-knock jokes, of course, are usually based on puns, that involve recognizing how a word is being misused for the sake of humor. It's easy (if groan-inducing) for humans, but extremely difficult for computers. The idea, it seems, is that figuring out how to teach computers to understand humor could go a long way in figuring out ways to program stronger artificial intelligence. At least that's the theory. Of course, this isn't the first time we've talked about computers and their senses of humor. Back in 2001, when some researchers set up a program to pull a Monty Python and find the world's funniest joke -- for a long time, the leading entry was written by a computer (though, eventually the computer-written joke was eclipsed by a human-written joke).

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Artificial Artificial Intelligence Tries To Track Down Steve Fossett

from the finding-a-needle-in-a-haystack dept

As the best thinkers are discussing the future of AI at the Singularity Summit, perhaps we shouldn't just be looking at ways to create better computer artificial intelligence, but at ways to more efficiently make use of human intelligence that's available all the time. For example, take a look at the technologies being used to harness human cognitive abilities to help in the search for Steve Fossett's plane in the vast desert of Nevada. Searchers are leveraging Amazon's Mechanical Turk community to quickly scan through Google Earth satellite imagery to flag areas where the plane might have crashed or eliminate barren areas where rescue pilots shouldn't focus on. At the time of this post, there are still over 100,000 blocks to be looked over with each block representing a 278x278 sq ft. area. At what appears to be a scanning rate of about 10-20 square grids/sec by the Turk community, the entire area of interest could theoretically be searched in less than 5 hours -- assuming that the system isn't showing the same photo to multiple people (as appears to be the case). Contrast that to the (super)computing resources required to process an equivalent image of more than 8 billion pixels (img dimension(256x256) x (numOfImgs)100k), on top of the difficult task of defining the object-of-interest to a computer (what does a plane wreck look like to a computer?).

In this instance, using simple coordination mechanisms, human intelligence becomes an economic way to solve a hard problem -- which is exactly the rationale behind Amazon's Mechanical Turk. We have seen projects using other hooks and mechanisms to leverage human intelligence, like Recaptcha for OCRing books, and the ESP game for tagging images -- and even the Techdirt Insight Community, which is bringing you this post. On a grander scale, Amazon's Mechanical Turk is trying to be a platform for "artificial artificial intelligence", though so far the success stories for MTurk have been minor. Even in this case, it's not entirely clear how useful it is (or how they got the latest satellite imagery ready to go for this task). In fact, while there are fairly stunning reports that, in searching for Fossett, the remains of eight other plane crashes have been discovered -- it doesn't sound like any of them were found via Mechanical Turk and Google Earth. Still, with all this talk about mashing up web services and better artificial intelligence, perhaps it's time we start thinking about more effective and efficient ways of leveraging human intelligence?

Teck Chia is an expert at the Insight Community. To get insight and analysis from Teck Chia and other experts on challenges your company faces, click here.

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