BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
DTSTART:20250309T030000
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:PDT
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20251102T010000
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:PST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260318T161131Z
UID:C2701640-61E4-4D4A-B947-D7172B258781
DTSTART;TZID=America/Los_Angeles:20251027T100000
DTEND;TZID=America/Los_Angeles:20251027T104000
DESCRIPTION:As intelligent systems play a larger role in safety-critical do
 mains\, they must move beyond acting as “black boxes” and become capab
 le teammates to humans. In aviation\, pilots are trained on Crew Resource 
 Management (CRM) skills to collaborate effectively as teammates and reduce
  risk. By giving intelligent systems similar skills\, Human-AI Teaming (HA
 T) can provide similar effectiveness and safety. In this talk\, I will pre
 sent aerospace case studies of pilot support and spacesuit assistant syste
 ms where HAT features such as operator-directed management and two-way com
 munication informed design and evaluation. These HAT features led to reduc
 ed workload while maintaining safety\, and point the way to safer\, more c
 ollaborative AI systems. Like aviation\, the energy sector also can requir
 e rapid human-AI coordination under high-stakes conditions. I will conclud
 e with a guided discussion on how these HAT features can be applied to res
 ults from a PNNL human-AI team study using the IEEE 118 Bus System.\n\nSpe
 aker(s): Uknown\n\nVirtual: https://events.vtools.ieee.org/m/506971
LOCATION:Virtual: https://events.vtools.ieee.org/m/506971
ORGANIZER:riley.maltos@pnnl.gov
SEQUENCE:24
SUMMARY:Human-AI Teaming for Safety: Lessons from Aviation and Energy Case 
 Studies
URL;VALUE=URI:https://events.vtools.ieee.org/m/506971
X-ALT-DESC:Description: <br /><p class="MsoNormal" style="mso-margin-top-al
 t: auto\; mso-margin-bottom-alt: auto\;">As intelligent systems play a lar
 ger role in safety-critical domains\, they must move beyond acting as &ldq
 uo\;black boxes&rdquo\; and become capable teammates to humans. In aviatio
 n\, pilots are trained on Crew Resource Management (CRM) skills to collabo
 rate effectively as teammates and reduce risk. By giving intelligent syste
 ms similar skills\, Human-AI Teaming (HAT) can provide similar effectivene
 ss and safety. In this talk\, I will present aerospace case studies of pil
 ot support and spacesuit assistant systems where HAT features such as oper
 ator-directed management and two-way communication informed design and eva
 luation. These HAT features led to reduced workload while maintaining safe
 ty\, and point the way to safer\, more collaborative AI systems. Like avia
 tion\, the energy sector also can require rapid human-AI coordination unde
 r high-stakes conditions. I will conclude with a guided discussion on how 
 these HAT features can be applied to results from a PNNL human-AI team stu
 dy using the IEEE 118 Bus System.</p>
END:VEVENT
END:VCALENDAR