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Can we unlock the Deep Learning black box?

Troy Sadkowsky - Wednesday, June 28, 2017

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Times; color: #000000; -webkit-text-stroke: #000000} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Times; color: #000000; -webkit-text-stroke: #000000; min-height: 14.0px} span.s1 {font-kerning: none} span.s2 {text-decoration: underline ; font-kerning: none; color: #0000ff; -webkit-text-stroke: 0px #0000ff}

Can we unlock the Deep Learning black box?

Artificial intelligence has experienced a boom in recent years due to the increasing automation and generation of big data. Due to deep learning and artificial neural networks, machines are acquiring new perceptual abilities, such as recognizing images, speech, or reading handwriting, paving the way for an infinite number of new applications in human lives. However, this leap forward in AI processing comes at a cost – the reasoning behind the choices that deep learning networks make has become inscrutable to the engineers that built them.

Progress in automated vision greatly benefits from deep learning because general visual processing is far too complex to code by hand. A program that can learn by observing human example or through complicated training sets, and can generate its own algorithms through an interconnected network of a dozen to several hundred layers of simulated neurons, positions us that much closer to a self-driving car, or other AI programs capable of sophisticated automated decision-making. But if we cannot understand a program’s individual decisions – why it chose to drive into a tree, why a patient’s medications should be changed, why one individual was hired for the job and another flagged as a terrorist – what ethical and moral boundaries are we crossing? And if an artificial intelligence program is not 100% accurate, as they rarely are, what are the dangers of putting ourselves at the mercy of a machine’s mistakes?

According to an article in MIT Technology Review (https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/), trust will be a key factor in future applications of deep learning. Once machines can explain their reasoning to humans, we will better be able to learn from and act on their insights. Research is underway to develop tools for machine learning programs to be able to explain themselves. Regina Barzilay, at MIT, is developing a system that can collaborate with doctors by extracting snippets of text that represent patterns it has discover, and Carlos Guestrin’s system, from the University of Washington, highlights significant keywords or parts of an image to support a particular decision.

However, interpretable deep learning is far off, and even then, explanations offered by machines will always be simplified to a degree, which will always make trusting machine learning programs controversial. As a consequence, the European Union might soon pass legislation to make explanations for automated decisions a fundamental legal right, required of the companies that implement AI machine programs.

Jeff Clune, an investigator at the University of Wyoming testing deep neural networks, offers that, just as with human intelligence and decision-making, it is perhaps “the nature of intelligence that only part of it is exposed to rational explanation. Some of it is just instinctual, or subconscious, or inscrutable”. As deep learning offers more appealing possibilities in medicine, technology and other industries, when and should, society take the deep learning leap of faith?

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Can we unlock the Deep Learning black box?

Troy Sadkowsky - Wednesday, June 28, 2017

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Times; color: #000000; -webkit-text-stroke: #000000} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Times; color: #000000; -webkit-text-stroke: #000000; min-height: 14.0px} span.s1 {font-kerning: none} span.s2 {text-decoration: underline ; font-kerning: none; color: #0000ff; -webkit-text-stroke: 0px #0000ff}

Can we unlock the Deep Learning black box?

Artificial intelligence has experienced a boom in recent years due to the increasing automation and generation of big data. Due to deep learning and artificial neural networks, machines are acquiring new perceptual abilities, such as recognizing images, speech, or reading handwriting, paving the way for an infinite number of new applications in human lives. However, this leap forward in AI processing comes at a cost – the reasoning behind the choices that deep learning networks make has become inscrutable to the engineers that built them.

Progress in automated vision greatly benefits from deep learning because general visual processing is far too complex to code by hand. A program that can learn by observing human example or through complicated training sets, and can generate its own algorithms through an interconnected network of a dozen to several hundred layers of simulated neurons, positions us that much closer to a self-driving car, or other AI programs capable of sophisticated automated decision-making. But if we cannot understand a program’s individual decisions – why it chose to drive into a tree, why a patient’s medications should be changed, why one individual was hired for the job and another flagged as a terrorist – what ethical and moral boundaries are we crossing? And if an artificial intelligence program is not 100% accurate, as they rarely are, what are the dangers of putting ourselves at the mercy of a machine’s mistakes?

According to an article in MIT Technology Review (https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/), trust will be a key factor in future applications of deep learning. Once machines can explain their reasoning to humans, we will better be able to learn from and act on their insights. Research is underway to develop tools for machine learning programs to be able to explain themselves. Regina Barzilay, at MIT, is developing a system that can collaborate with doctors by extracting snippets of text that represent patterns it has discover, and Carlos Guestrin’s system, from the University of Washington, highlights significant keywords or parts of an image to support a particular decision.

However, interpretable deep learning is far off, and even then, explanations offered by machines will always be simplified to a degree, which will always make trusting machine learning programs controversial. As a consequence, the European Union might soon pass legislation to make explanations for automated decisions a fundamental legal right, required of the companies that implement AI machine programs.

Jeff Clune, an investigator at the University of Wyoming testing deep neural networks, offers that, just as with human intelligence and decision-making, it is perhaps “the nature of intelligence that only part of it is exposed to rational explanation. Some of it is just instinctual, or subconscious, or inscrutable”. As deep learning offers more appealing possibilities in medicine, technology and other industries, when and should, society take the deep learning leap of faith?

Comments
astanainform.kz commented on 14-Sep-2017 03:19 AM
Spot on with this write-up, I actually feel this site needs a lot more attention. I'll probably be back again to read through more, thanks for the information!
هكر ولف تيم 2017 commented on 15-Sep-2017 09:19 AM
Ha, here from yahoo, this is what i was looking for.
Jual beli online terpercaya commented on 16-Sep-2017 08:50 AM
Hey there just wanted to give you a brief heads up and let you know a few of the pictures aren't loading correctly.

I'm not sure why but I think its a linking issue.
I've tried it in two different browsers and both show
the same results.
backlink pbn commented on 16-Sep-2017 04:34 PM
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I'm undoubtedly enjoying your blog and look forward to new
updates.
tooled-leather-look commented on 17-Sep-2017 09:58 AM
hey there and thank you for your info – I've certainly picked up anything new
from right here. I did however expertise several technical points using this
website, as I experienced to reload the web site many times previous to I could
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Casey commented on 23-Sep-2017 02:14 PM
Superb blog! Do you have any hints for aspiring writers?
I'm hoping to start my own site soon but I'm a little lost on everything. Would you advise starting with a free platform like Wordpress or go for a paid option? There are so many choices out there that I'm completely overwhelmed .. Any suggestions? Many thanks!


My blog postweb based business
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tooled-leather-look commented on 03-Oct-2017 07:53 PM
Way cool! Some extremely valid points! I appreciate you penning this article and
the rest of the site is really good.
Salvatore commented on 04-Oct-2017 08:08 AM
I was curious if you ever considered changing the structure of your blog?
Its very well written; I love what youve got to say. But maybe you could a little more in the way of content so people could connect with it better. Youve got an awful lot of text for only having one or two images. Maybe you could space it out better?

my blog postbetter Ebay seller
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seo服务 commented on 07-Oct-2017 08:09 PM
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department, they focus more on pure research, and most
research results are hard to be commercialized.
faux-leather commented on 08-Oct-2017 04:05 AM
Hello just wanted to give you a brief heads
up and let you know a few of the pictures aren't loading correctly.
I'm not sure why but I think its a linking issue. I've tried it in two different internet browsers and both show the same outcome.
Son commented on 09-Oct-2017 01:10 AM
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Hi, just wanted to share with you that we had a great time at Marina de Bolnuevo in June of this year. We flew into Alicante and hired a car from the airport for the short drive to Bolnuevo. The beaches are clean, most of them awarded the Blue Flag. The cafes were great, with paella on the beach a must and managed a trip to the nudist beach there. Very liberating. We also visited the Big Guns, The Roman Mines and the Sand sculptures. Will be returning there again next year. Thanks for reading Alicia.
market research commented on 10-Oct-2017 03:31 PM
But no serious talks have taken place in the last couple of years.
Costumes commented on 11-Oct-2017 05:48 PM
Howdy, i read your blog from time to time and i own a similar one
and i was just wondering if you get a lot of spam feedback?
If so how do you protect against it, any plugin or anything you can recommend?
I get so much lately it's driving me crazy so any help
is very much appreciated.
Brittney commented on 12-Oct-2017 10:30 AM
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Post a Comment




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