BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Pacific/Honolulu
BEGIN:STANDARD
DTSTART:19470608T023000
TZOFFSETFROM:-1130
TZOFFSETTO:-1000
TZNAME:HST
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BEGIN:VEVENT
DTSTAMP:20250131T203430Z
UID:83CA12C4-B160-4ED3-98C0-D24513323454
DTSTART;TZID=Pacific/Honolulu:20250131T090000
DTEND;TZID=Pacific/Honolulu:20250131T100000
DESCRIPTION:Humans make decisions and solve problems using heuristics (“t
 hinking fast”) or abstract approaches such as modeling (“thinking slow
 ”). Artificial intelligence approaches can similarly use either heuristi
 cs that are related to correlation and categorization\, or use models that
  are related to causation. Predictive Engineering\, which melds engineerin
 g modeling with probabilistic thinking\, aligns closely with causation and
  an aspect of artificial intelligence called Causal Learning. Issues with 
 some artificial intelligence approaches will be explored\, with real (and 
 sometimes controversial and provocative) examples\, and promising approach
 es encompassing causation /predictive engineering will be discussed.\n\n[]
 \n\nSpeaker(s): Eric Maass\n\nVirtual: https://events.vtools.ieee.org/m/44
 5270
LOCATION:Virtual: https://events.vtools.ieee.org/m/445270
ORGANIZER:brianne.tengan@ieee.org
SEQUENCE:14
SUMMARY:Predictive Engineering and Artificial Intelligence 
URL;VALUE=URI:https://events.vtools.ieee.org/m/445270
X-ALT-DESC:Description: <br /><p>Humans make decisions and solve problems u
 sing heuristics (&ldquo\;thinking fast&rdquo\;) or abstract approaches suc
 h as modeling (&ldquo\;thinking slow&rdquo\;). Artificial intelligence app
 roaches can similarly use either heuristics that are related to correlatio
 n and categorization\, or use models that are related to causation. Predic
 tive Engineering\, which melds engineering modeling with probabilistic thi
 nking\, aligns closely with causation and an aspect of artificial intellig
 ence called Causal Learning. Issues with some artificial intelligence appr
 oaches will be explored\, with real (and sometimes controversial and provo
 cative) examples\, and promising approaches encompassing causation /predic
 tive engineering will be discussed.</p>\n<p><img style="display: block\; m
 argin-left: auto\; margin-right: auto\;" src="https://events.vtools.ieee.o
 rg/vtools_ui/media/display/4f13137b-9762-4ce0-b076-1b0dff281ff6" alt="" wi
 dth="692" height="692"></p>
END:VEVENT
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