Human Inspired Artificial Intelligence

Title: Human Inspired Artificial Intelligence
Date: Wednesday, October 6, 2021 11:00 AM ET/8:00 AM PT
Duration: 1 Hr

Manish Gupta, Director of Google Research, India; ACM Fellow


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GUNTER HESSLER: I am interested in the new dimensions of bias under AI.

Given the following scenario:
A) An IBM Watson cognitive system is becoming very easy to deploy: a licence, a decent desktop computer, and a decent internet connection to a server, and these systems are becoming very prevalent in hospital settings.
B) A middle-aged thrice-divorced nurse has had diabetes for many years. She has grown up in a world of Jane Austen, with anguish seen the rise of the world of George Orwell in her grandparent’s and parent’s lives, has explored future worlds through the novels of Doris Lessing and views the modern world of computers with distaste. She has announced to her children and close friends that after the children have ‘flown the nest’ and established themselves in their own lives she wishes to end her life. This patient has been a decades-long user of Gmail. Three of the four children have long ago started their own careers and live in different cities, and now the youngest has shipped out to go and start a family on a kibbutz in Israel. Now the nurse needs serious medical treatment for an organ dysfunction of the digestive system. She goes for diagnosis.
Her overworked surgeon consults all her pre-tests including cross-correlations from the hospital’s Watson databases.


  1. What is the likelihood that the hospital’s Watson databases search has already picked up on this patient’s ‘death-wish’?
  2. What checks and balances can be put in place so that the surgeon, in view of his heavy case load, does not neglect to do his best for this patient?