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Can we unlock the Deep Learning black box?

Troy Sadkowsky - Wednesday, June 28, 2017

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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
battery operated coffee makers commented on 12-Sep-2019 05:06 AM
As I website possessor I believe the content matter here is rattling fantastic , appreciate it for your efforts. You should keep it up forever! Good Luck.
battery powered coffee maker commented on 12-Sep-2019 05:12 AM
You have brought up a very excellent points , appreciate it for the post.
battery powered coffee makers commented on 12-Sep-2019 05:16 AM
I together with my buddies were actually reviewing the nice procedures found on the website while quickly got a horrible feeling I had not expressed respect to the website owner for those strategies. My people are actually as a result very interested to see all of them and have now surely been using those things. Appreciation for turning out to be quite accommodating as well as for pick out this form of ideal issues millions of individuals are really desperate to understand about. My personal sincere regret for not saying thanks to earlier.
battery coffee maker commented on 12-Sep-2019 05:16 AM
Some genuinely prime content on this website , bookmarked .
buy generic viagra commented on 12-Sep-2019 05:21 AM
Hello to all, how is everything, I think every
one is getting more from this website, and your views are good
designed for new visitors.
pengeluaran togel sgp hari ini live commented on 12-Sep-2019 05:22 AM
Great post. I was checking continuously this blog
and I am impressed! Very helpful info specially the last part :) I care for such information much.
I was looking for this certain information for a long time.
Thank you and best of luck.
12-volt coffee maker commented on 12-Sep-2019 05:26 AM
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battery powered coffee makers commented on 12-Sep-2019 05:29 AM
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battery operated coffee makers commented on 12-Sep-2019 05:38 AM
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http://www.thinkisolutions.com/ commented on 12-Sep-2019 05:39 AM
It shouldn't and they'll be sending the wrong signal if
they require money. You'll likely learn a large amount
about your partner's country, language, preferences and strategy for life.
A narrow-minded person might be boring on an internet dating and indeed ruin all the
fun.
battery powered coffee maker commented on 12-Sep-2019 05:43 AM
Thanks for any other informative web site. Where else could I am getting that kind of information written in such an ideal way? I have a project that I am simply now running on, and I have been on the look out for such information.
jagonyabandarq.blogspot.com commented on 12-Sep-2019 05:48 AM
You could certainly see your skills within the article you write.
The arena hopes for more passionate writers such as you who are not afraid to mention how they believe.
At all times go after your heart.
bocoran-trik-judi-online-62.webself.net commented on 12-Sep-2019 05:58 AM
Its like you read my mind! You appear to know a lot about this, like you
wrote the book in it or something. I think that you could do with some pics to drive the message home a bit, but instead of that, this is
fantastic blog. A great read. I'll certainly be back.
current time and date commented on 12-Sep-2019 06:58 AM
I consider something genuinely special in this web site.
battery operated coffee pot commented on 12-Sep-2019 07:04 AM
I don’t even know how I ended up here, but I thought this post was good. I do not know who you are but certainly you're going to a famous blogger if you are not already ;) Cheers!

Post a Comment




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