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LOCATION:HG D 1.2
DTSTART;TZID=Europe/Stockholm:20240605T100000
DTEND;TZID=Europe/Stockholm:20240605T103000
UID:submissions.pasc-conference.org_PASC24_sess164_msa233@linklings.com
SUMMARY:Scientific Computing in Context of Applications, Technology, Infra
 structure, Energy, and Geography
DESCRIPTION:Minisymposium\n\nJakob Luettgau (INRIA)\n\nScientific computin
 g and high-performance computing (HPC) increasingly directly impact societ
 y. This can be observed by the growing number of disciplines and domain sc
 iences relying on access to large-scale computing and data facilities to c
 onduct their research. In particular machine learning technologies augment
  the capabilities to automate and scale decision making to unprecedented s
 cales. As a result ethical considerations surface at the level of applicat
 ions both in their implementation and deployment. Most prominently the imp
 act of machine learning approaches on society and the growing energy footp
 rint of large-scale data centers gained public attention but they are not 
 limited to machine learning and artificial intelligence (AI).\nAs practiti
 oners enabling the use of these technologies, we need to be prepared and e
 ducated on ethical principles but also the context of applications with re
 spect to, for example, infrastructure and energy. This work presents vario
 us such perspectives aiming to look beyond the spotlight and offer differe
 nt contextual and an evolution of different applications and technologies 
 and their characteristics and distribution. The work critically discusses 
 also the limitations of the perspectives and highlights current blindspots
  that need to be addressed to better back up ethical considerations in HPC
  and scientific computing with data.\n\nDomain: Applied Social Sciences an
 d Humanities\n\nSession Chair: Jay Lofstead (Sandia National Laboratories,
  University of New Mexico)
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