<html xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<meta name="Generator" content="Microsoft Word 15 (filtered medium)">
<style><!--
/* Font Definitions */
@font-face
{font-family:"Cambria Math";
panose-1:2 4 5 3 5 4 6 3 2 4;}
@font-face
{font-family:Calibri;
panose-1:2 15 5 2 2 2 4 3 2 4;}
/* Style Definitions */
p.MsoNormal, li.MsoNormal, div.MsoNormal
{margin:0in;
margin-bottom:.0001pt;
font-size:12.0pt;
font-family:"Calibri",sans-serif;}
a:link, span.MsoHyperlink
{mso-style-priority:99;
color:#0563C1;
text-decoration:underline;}
a:visited, span.MsoHyperlinkFollowed
{mso-style-priority:99;
color:#954F72;
text-decoration:underline;}
span.EmailStyle17
{mso-style-type:personal-compose;
font-family:"Calibri",sans-serif;
color:windowtext;}
span.apple-converted-space
{mso-style-name:apple-converted-space;}
.MsoChpDefault
{mso-style-type:export-only;}
@page WordSection1
{size:8.5in 11.0in;
margin:1.0in 1.0in 1.0in 1.0in;}
div.WordSection1
{page:WordSection1;}
/* List Definitions */
@list l0
{mso-list-id:638845393;
mso-list-template-ids:-1725264118;}
@list l0:level1
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level2
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:1.0in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level3
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:1.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level4
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:2.0in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level5
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:2.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level6
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:3.0in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level7
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:3.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level8
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:4.0in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l0:level9
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:4.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1
{mso-list-id:1655984276;
mso-list-template-ids:-78985376;}
@list l1:level1
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1:level2
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:1.0in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1:level3
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:1.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1:level4
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:2.0in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1:level5
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:2.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1:level6
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:3.0in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1:level7
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:3.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1:level8
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:4.0in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
@list l1:level9
{mso-level-number-format:bullet;
mso-level-text:;
mso-level-tab-stop:4.5in;
mso-level-number-position:left;
text-indent:-.25in;
mso-ansi-font-size:10.0pt;
font-family:Symbol;}
ol
{margin-bottom:0in;}
ul
{margin-bottom:0in;}
--></style>
</head>
<body lang="EN-US" link="#0563C1" vlink="#954F72">
<div class="WordSection1">
<p class="MsoNormal"><span style="font-size:11.0pt">TriPython:<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt">Please see below about a webinar of interest to TriPython given by one of our members. Earlier in the year I saw Chris Lam give a presentation on AI design bias at the Research Triangle Analysts Analytics
Forward unconference. I was so impressed that I made a bunch of noise about it at RENCI until National Consortium for Data Science agreed to invite Chris to present it again as part of their DataBytes webinar series. It was so well received that MCDS are having
Chris back for another webinar on the technologies backing his previous presentation. I highly recommend this to you and hope you will find the time to attend remotely this coming Tuesday.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman",serif">-- <o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman",serif">Sincerely,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman",serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman",serif">Chris Calloway<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman",serif">Applications Analyst<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman",serif">University of North Carolina<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman",serif">Renaissance Computing Institute<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Times New Roman",serif">(919) 599-3530<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span style="color:black">In early 2023, the National Consortium for Data Science rebooted DataBytes, a webinar series, with the intention of providing a platform to connect academia with emerging data science talent in industry. </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"> </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black">In June, we hosted Christopher Lam, Founder and CEO of<span class="apple-converted-space"> </span><a href="https://www.epistam.ai/"><span style="color:#0563C1">Epistamai</span></a>. Chris presented “AI Ethics Through the Lens of Causality:
A Theory of Fairness” (<a href="https://youtu.be/eWHQ_mZCKQc?si=WASDuhoMAgyUdDdX"><span style="color:#0563C1">watch the YouTube recording here</span></a>). In that session, Chris showed how to model a principal cause of algorithmic bias and directly map it
to the two fundamental laws of causal inference. Additionally, he showed how to bridge the field of causal inference to machine learning, providing us with a novel way to visualize the different ways that a supervised machine learning model can discriminate.
These causal models may help policymakers on both sides of the aisle to modernize AI regulations so that they are aligned to society’s values.</span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"> </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black">We’re delighted for Chris to return next week to present, “<a href="https://datascienceconsortium.org/upskilling/databytes/"><span style="color:#0563C1">Causal AI: The Key to High-Stakes Decision Making</span></a>”.<span class="apple-converted-space"> </span><b>There
has been tremendous attention to the generative AI wave and its enormous potential to transform industries. But there is a hidden wave developing right behind it called causal AI. Whereas generative AI is optimized for low-stakes decisions like chatbots and
image generation, it is not designed to address issues like ethics or trustworthiness that are essential for using AI in high-stakes decisions like credit and hiring decisions. This is where causal AI fits into the picture.</b></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"> </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black">In this presentation, Lam will discuss how to use causal AI to build AI systems that society can trust for high-stakes decision making. </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<ul style="margin-top:0in;caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px" type="disc">
<li class="MsoNormal" style="color:black;mso-list:l1 level1 lfo1">He’ll show how causal AI can help bridge the gap between symbolic AI and machine learning, demonstrating the value of integrating human knowledge and reasoning about the world to improve how
data is analyzed. <span style="font-size:10.0pt"><o:p></o:p></span></li><li class="MsoNormal" style="color:black;mso-list:l1 level1 lfo1">Through a use case, he’ll demonstrate how this more human-centric approach to AI can be used to build fairer and more equitable AI systems that are aligned with society's democratic values. <span style="font-size:10.0pt"><o:p></o:p></span></li><li class="MsoNormal" style="color:black;mso-list:l1 level1 lfo1">Finally, he will describe a new causal hierarchy, one that integrates machine learning with causal inference and system dynamics.<span style="font-size:10.0pt"><o:p></o:p></span></li></ul>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"> </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"><a href="https://renci.zoom.us/webinar/register/WN_TIiTZ24JRlqLZqkoc9WiOA#/registration"><b><span style="color:#0563C1">Register now</span></b></a><span class="apple-converted-space"><b> </b></span><b>for this hour-long Zoom webinar
from 4pm-5pm ET on Tuesday, December 5th. </b></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"> </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black">Here are a few points to keep in mind about this event: </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<ul style="margin-top:0in;caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px" type="disc">
<li class="MsoNormal" style="color:black;mso-list:l0 level1 lfo2">The presentation will last the full hour. <span style="font-size:10.0pt"><o:p></o:p></span></li><li class="MsoNormal" style="color:black;mso-list:l0 level1 lfo2">Chris will remain on the webinar for a brief Q&A session following the event. <span style="font-size:10.0pt"><o:p></o:p></span></li><li class="MsoNormal" style="color:black;mso-list:l0 level1 lfo2">A recording of the event will be available on our website the week of December 18. <span style="font-size:10.0pt"><o:p></o:p></span></li><li class="MsoNormal" style="color:black;mso-list:l0 level1 lfo2">Although it is not required, please consider watching the June DataBytes webinar on<span class="apple-converted-space"> </span><a href="https://youtu.be/eWHQ_mZCKQc?si=WASDuhoMAgyUdDdX"><span style="color:#0563C1">Causal
AI here</span></a>.<span style="font-size:10.0pt"><o:p></o:p></span></li></ul>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"> </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black">We encourage you to invite friends and colleagues to join us, this webinar is free and open to the public. Please direct all questions via email to NCDS Associate Director Amanda Miller (<a href="mailto:amiller@renci.org"><span style="color:#0563C1">amiller@renci.org</span></a>).<span class="apple-converted-space"> </span></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"> </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"> </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">-- </span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">Amanda C. Miller<span class="apple-converted-space"> </span></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">Associate Director</span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><a href="https://datascienceconsortium.org/"><span style="color:#0563C1">National Consortium for Data Science</span></a></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><a href="https://renci.org/"><span style="color:#0563C1">RENCI</span></a></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">University of North Carolina at Chapel Hill<span class="apple-converted-space"> </span></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">100 Europa Drive<span class="apple-converted-space"> </span></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">Chapel Hill, NC 27517-7583</span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black">Mobile: 917-548-1591<span class="apple-converted-space"> </span></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
<p class="MsoNormal" style="caret-color: rgb(0, 0, 0);font-variant-caps: normal;orphans: auto;text-align:start;widows: auto;-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;word-spacing:0px">
<span style="color:black"><a href="mailto:amiller@renci.org"><span style="color:#0563C1">amiller@renci.org</span></a></span><span style="font-size:10.0pt;color:black"><o:p></o:p></span></p>
</div>
</body>
</html>