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JNU holds global symposium on artificial intelligence in governance and disaster management

The Special Centre for Disaster Research, JNU, New Delhi in collaboration with NITI Aayog, NDMA, NIDM, ICSSR, Skymet Weather and Springer Nature is organising a three day Global Symposium on Artificial Intelligence in Governance and Disaster Management at Convention Centre, JNU from March 11-13, 2019.

Updated on: Mar 11, 2019 07:48 PM IST
Hindustan Times, New Delhi | By
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The Special Centre for Disaster Research, JNU, New Delhi in collaboration with NITI Aayog, NDMA, NIDM, ICSSR, Skymet Weather and Springer Nature is organising a three day Global Symposium on Artificial Intelligence in Governance and Disaster Management at Convention Centre, JNU from March 11-13, 2019.

The Special Centre for Disaster Research, JNU, New Delhi in collaboration with NITI Aayog, NDMA, NIDM, ICSSR, Skymet Weather and Springer Nature is organising a three day Global Symposium on Artificial Intelligence in Governance and Disaster Management at Convention Centre, JNU from March 11-13, 2019. (Handout image)
The Special Centre for Disaster Research, JNU, New Delhi in collaboration with NITI Aayog, NDMA, NIDM, ICSSR, Skymet Weather and Springer Nature is organising a three day Global Symposium on Artificial Intelligence in Governance and Disaster Management at Convention Centre, JNU from March 11-13, 2019. (Handout image)

The symposium reflects on intensive preparedness required to address the problem of recurrent disasters, which have grown in frequency as well as their uncertain destructive ability. It is now beyond human capacity to assure safety and protection from the wide range and varieties of disasters. The use of AI, Machine Learning and Robots can help tremendously in disaster preparedness and community resilience building, which would lead to greater safety of public life and institutions.

AI in a preliminary understanding speeds up mapping, geographical and human vulnerabilities and can send directives and instructions to the relevant offices to take preemptive action. Most disasters and even the best of Early Warning Systems do not give adequate timely warnings for preemptive action. The use of AI would address delays, unwillingness, lack of accountability, fuzzy coordination and biased or deficit of understandings of decision makers.

 
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