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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?

Comments
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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
Bonnie commented on 12-Jun-2019 10:21 PM
The game starts off humbly no less when you are an aspiring young wizard who would like to figure out how to use magic.
When there are capital ships around the tactical display, it will always be better for your Bismarck include them as her primary target. Before beginning the overall game, you have to setup 3 different kind of decks.

Here is my homepage ...Fortnite CHEAT Free Downloa
Замена замков во входной двери нашим мастером обойдется
Вам недорого. Подвал 5м2, во дворе металлический гараж.
Например, если вам нужны входные пластиковые двери,
то это будут двери из профиля Rеhau толщиной 70 мм,
двухкамерный стеклопакет и фурнитурная обвязка по контуру с нажимной гарнитурой.
Если вам надо срочно поставить дверное
полотно в новостройке, врезать замок, сделать переустановку коробки, изучите объявления на сайте Юду
или создайте индивидуальное задание.

Сейчас уже недостаточно просто
врезать замок, его нужно врезать качественно и высокоточно.
home business commented on 13-Jun-2019 02:01 AM
continuously i used to read smaller content that also
clear their motive, and that is also happening with this post which I
am reading at this place.
www.immigrationattorneycalifornia.us commented on 13-Jun-2019 02:37 AM
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However, what about the conclusion? Are you certain in regards to the supply?
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nails breda commented on 13-Jun-2019 10:49 AM
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during lunch break. I enjoy the info you present here and
can't wait to take a look when I get home. I'm amazed at how quick your blog loaded on my cell phone ..

I'm not even using WIFI, just 3G .. Anyways,
wonderful site!
ezreal commented on 13-Jun-2019 11:27 AM
Just wanna input on few general things, The website layout is perfect, the articles is very superb : D.
ایمپلنت commented on 13-Jun-2019 11:58 AM
If yyou share your ایمپلنت targets - and how much you are exercising every day -
you're feeling more accountable.
L1 Visa Lawyer San Jose commented on 13-Jun-2019 02:05 PM
Hello would you mind stating which blog platform you're working with?

I'm going to start my own blog soon but I'm having a tough time selecting between BlogEngine/Wordpress/B2evolution and Drupal.
The reason I ask is because your design and style seems different then most blogs and
I'm looking for something unique. P.S Sorry for being off-topic
but I had to ask!
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