Ai in Healthcare: Perspective
Nikhil Bhojwani
Managing Partner @ Recon Strategy | Healthcare Consulting | AI in Health | Visiting professor | Keynote speaker | Alum of Wharton, BCG, St. Stephen's College
If intelligence is understood to mean traits that enable humans to independently perceive, contextualize, interpret, and learn from information in a way that can be applied towards adaptive behaviors resulting in actions or communication, then Artificial Intelligence (AI) is simply one or more of these traits manifest in a machine in order to achieve a given goal.
That goal may be to:
- replicate what a human could otherwise do but in a way that is preferable for reasons such as improved productivity, quality, or safety
- surpass humans in tasks that humans cannot feasibly do such as to make optimal decisions with information that is too complex for humans to be able to absorb, interpret, or act on under real world conditions
- augment human intelligence to produce a capability that is superior to either the machine or the human alone
Machine Learning (ML) is often used interchangeably with AI but more accurately it is a form of AI that relates to the capability of a machine to improve its performance on a task by iteratively repeating the task, assessing its own performance relative to a desired outcome, and making adjustments as needed. It is a subset of AI, albeit an important one. Other possible attributes of AI include natural language processing, spatial navigation, machine vision, logical reasoning, and pattern recognition. Of course many of these are used in combination with each other and ML is a common component of many AI systems.
Scope of AI
There is a paradox in AI that once a machine achieves a form of intelligence, that capability is then no longer considered by many to be a form of AI. This idea was pithily captured in Tesler’s Theorem.
Optical Character Recognition (OCR) for example demonstrates one of the hallmarks of intelligence, namely perception. But as OCR has improved and become embedded in our machines, it is now thought of as software feature and not as AI.
Avoiding this paradox, the scope of the definition of AI at the Forum is broad and includes not just cutting edge innovations but also existing AI capabilities as they relate to healthcare.
“Intelligence is whatever machines haven’t done yet.”
LARRY TESLER, 1970
AI in Healthcare
AI in healthcare is being driven by three trends.
First there has been an exponential growth in useful health related data including from EHRs, personal monitoring devices, genomic information, social information, diagnostic information, and more. The diversity and complexity of these data necessitates the use of AI.
Second, continue reading here
By Nikhil Bhojwani and Marc Herant, Recon Strategy