AI Will Make Us More 'Human', Says Affectiva's Rana el Kaliouby

Humanizing AI in healthtech will redefine what care delivery and patient-physician engagement look like.

Oliver Wyman Health

5 min read

Over 90 percent of how we communicate is non-verbal. Only 10 percent is in the actual choice of words. Emotions matter. They drive our decision-making, and they’re at the core of how we care for one another. As artificial intelligence (AI) becomes an integral part of the healthcare workforce, how can healthcare leaders ensure we don’t further erode the emotional side of health, alienate consumers, and exacerbate inequality? 

It's these ideas and more Rana el Kaliouby, Co-founder and CEO, Affectiva, discussed at the 2020 Oliver Wyman Health Innovation Summit. Artificial intelligence, she said, has great potential to make humans even more human. Healthcare leaders have an opportunity to quantity empathy like they've never done before.

Below, Rana outlines five ways humanizing AI in healthtech will improve patient outcomes, strengthen patient rapport with caregivers, and reimagine how diseases are diagnosed.

Watch the Conversation from the Health Innovation Summit

Memorable Moments

  • A doctor doesn't typically ask a patient what their temperature or blood pressure is. They just measure it. But, when it comes to mental health, the gold standard of how you acquire medical information about a patient is still in a survey format. (For example, On a scale of 1 to 10, how depressed are you?)
  • Collaborative robots will augment human clinicians and nurses. Nurse avatars and social robots are already proving their abilities to enhance patient-centered healthcare. 
  • Robots can serve the role of frontline “workers” especially in times of crisis. Here, robots can augment human frontline workers and increase safety. 
  • AI-based virtual assistants are evolving quickly, and now, increasingly more effort and resources are being put toward making them emotionally intelligent. Robots are now able to pick up on subtle cues in speech, inflection, or gesture and expression to assess a person’s health and wellbeing.
  • When designing and deploying algorithms, it is critical we avoid data and algorithmic bias.
Author
  • Oliver Wyman Health