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  <title><![CDATA[Ethics Highlight 'Day of Machine Learning Discussion']]></title>
  <body><![CDATA[<p>Machine learning at Georgia Tech was in the spotlight recently&nbsp;as <a href="http://ml.gatech.edu/">The Center for Machine Learning at Georgia Tech</a> (ML@GT) hosted its spring seminar on Feb. 22 in the Klaus Advanced Computing Building.</p>

<p>Billed as a &ldquo;day of discussions around machine learning,&rdquo; more than 200 students and faculty from across campus registered for the daylong event.</p>

<p>&ldquo;AI is like going to the moon. Data science is the rocket, but machine learning is the fuel that is propelling us forward,&rdquo; said ML@GT Director <strong>Irfan Essa</strong>.</p>

<p>&ldquo;The field crosses a wide variety of disciplines so Georgia Tech is an ideal setting to build a home for thought leaders and train the next generation in machine learning.&rdquo;</p>

<h3><strong>Algorithms and bias</strong></h3>

<p>The day began with an informal discussion over breakfast with Essa and <strong>Charles Isbell</strong>, executive associate dean and professor in the College of Computing.</p>

<p>&ldquo;Developers tend to walk around feeling objective because it&rsquo;s the algorithm that is determining the answer,&rdquo; Isbell said in response to a question relating to the ethical aspects of machine learning.</p>

<p>&ldquo;However, they need to ensure no bias is being introduced. The algorithms they create need to be &lsquo;inspectable&rsquo; and must be able to explain their answers.&rdquo;</p>

<h3><strong>Featured presentations</strong></h3>

<p>Following an update from the ML@GT leadership team about current research projects, recent achievements, and plans for the coming year, attendees were treated to lunch and a presentation from Princeton University&rsquo;s <strong>Sanjeev Arora</strong>.</p>

<p>Arora, the Charles C. Fitzmorris Professor of Computer Science at Princeton, explored the mysteries of deep learning as he shared his thoughts on <a href="https://arxiv.org/pdf/1706.08224.pdf">generative adversarial nets (GANs)</a> and their efficacy in learning from relatively small data sets. Associate Professor Joelle Pineau from McGill University followed Arora. Her remarks circled back to <a href="https://arxiv.org/pdf/1711.09050.pdf">ethical issues raised by artificial intelligence agents</a>, such as chatbots.</p>

<p>ML@GT&rsquo;s day of discussion wrapped up with another informal chat session and a reception in the Klaus Atrium.</p>

<p>ML@GT is an interdisciplinary research center launched in July 2016. A machine learning Ph.D. program was approved in June 2017. <a href="http://www.ml.gatech.edu/hg/item/592707">An inaugural class of approximately 15 students</a> is scheduled to convene for the Fall 2017 semester.</p>
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      <value>2018-03-02T00:00:00-05:00</value>
      <timezone><![CDATA[America/New_York]]></timezone>
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      <value><![CDATA[Informal chat sessions and invited guest presentations were highlights of the event hosted by the Center for Machine Learning at Georgia Tech.]]></value>
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            <title><![CDATA[Machine Learning at GT event]]></title>
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                  <filename><![CDATA[MLatGT event_1_feb2018.jpg]]></filename>
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                  <image_alt><![CDATA[Academic presentation about machine learning at Georgia Tech]]></image_alt>
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      <email><![CDATA[albert.snedeker@cc.gatech.edu]]></email>
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      <value><![CDATA[<p>Albert Snedeker, Communications Manager</p>

<p><a href="mailto:albert.snedeker@cc.gatech.edu?subject=ML%40GT%20event">albert.snedeker@cc.gatech.edu</a></p>
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