update of intro with apple's credit card bias

doc/pub/Introduction/html/Introduction.html

@@ -73,7 +73,7 @@ end of tocinfo -->
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>Aug 13, 2019</h4></center> <!-- date -->
+<center><h4>Nov 19, 2019</h4></center> <!-- date -->
 <br>
 
 <h2 id="___sec0">Introduction </h2>
@@ -387,19 +387,21 @@ the likelihood of surving a collision with our future citizens, is
 much higher.
 
 <p>
-This leads to serious ethical aspects. Why should we
-opt for such an option? Who decides and who is entitled to make such
-choices? Keep in mind that many of the algorithms you will encounter in
-this series of lectures or hear about later, are indeed based on
-simple programming instructions. And you are very likely to be one of
-the people who may end up writing such a code. Thus, developing a
-sound ethical attitude to what we do, an approach well beyond the
-simple mechanistic one of making our science available and
-reproducible, is much needed. The example of the self-driving cars is
-just one of infinitely many cases where we have to make choices. When
-you analyze data on economic inequalities, who guarantees that you are
-not weighting some data in a particular way, perhaps because you dearly want a
-specific conclusion which may support your political views?
+This leads to serious ethical aspects. Why should we opt for such an
+option? Who decides and who is entitled to make such choices? Keep in
+mind that many of the algorithms you will encounter in this series of
+lectures or hear about later, are indeed based on simple programming
+instructions. And you are very likely to be one of the people who may
+end up writing such a code. Thus, developing a sound ethical attitude
+to what we do, an approach well beyond the simple mechanistic one of
+making our science available and reproducible, is much needed. The
+example of the self-driving cars is just one of infinitely many cases
+where we have to make choices. When you analyze data on economic
+inequalities, who guarantees that you are not weighting some data in a
+particular way, perhaps because you dearly want a specific conclusion
+which may support your political views? Or what about the recent
+claims that a famous IT company like Apple has a sexist bias on the
+their recently <a href="https://qz.com/1748321/the-role-of-goldman-sachs-algorithms-in-the-apple-credit-card-scandal/" target="_blank">launched credit card</a>?
 
 <p>
 We do not have the answers here, nor will we venture into a deeper