How can investors spot AI BS?

Transcript

1. AI “washing” allows entrepreneurs and
   investors to cover up investment thesis
   flaws with hype and “BS”.
   How can investors spot
   AI BS?
   @ShahidNShah Publisher, www.Medigy.com
   

   View Slide

2. The simplest answer is:
   Can the innovator describe the
   outcome of their novelty
   without saying “ML” or “AI”?
   

   View Slide

3. Why?
   AI is not a product you can buy, it’s an experimentation
   technique which allows for rapidly poking and prodding at
   huge volumes of previously untapped data to discover
   facts and relationships about the complexity of our
   world.
   Rather than poking and prodding at genes, cells or
   molecules to see how they interact in labs, “data
   scientists” use ML and AI to more rapidly discover
   relationships that would be difficult for humans to “see”.
   

   View Slide

4. How to Spot AI BS
   An entrepreneur that says, "we use AI for drug discovery”
   is just as silly as one who says, “we experiment with
   molecules for drug discovery.” It does not mean anything.
   If someone said “you should invest in my company
   because we know how to culture bacteria" you'd look at
   them like they were delusional.
   The same should be done with entrepreneurs who use
   “AI” and “ML” as if they are the ends, rather than the
   means to the ends.
   

   View Slide

5. Technology has digitized our experiences
   Last and past decades
   Digitize
   mathematics &
   engineering
   Digitize maps,
   literature, news
   Digitize
   purchasing,
   social networks
   Predict crowd
   behavior
   This and future decades
   Digitize
   biology
   Digitize
   chemistry
   Digitize
   physics
   Predict human
   behavior
   Gigabytes and petabytes, all sharable Petabytes and exabytes, not shareable
   

   View Slide

6. AI must usher in the Scientific Method 3.0 .
   1.0
   Identify
   phenomenon
   Think about
   nature
   Fit to known
   patterns
   Guess at
   answers
   3.0
   Identify
   data
   Generate
   questions
   Mine data
   Answer
   questions
   2.0
   Identify
   problem
   Ask
   questions
   Collect
   data
   Answer
   questions
   

   View Slide

7. How will we know if we’ve reached 3.0 ?
   

   View Slide

8. 15-year-old student discovers cure for rare disease
   while gaming
   Computer creates treatment for prostate cancer
   

   View Slide

9. Machine Learning and AI in healthcare will be slowed by intermediated business
   models, misunderstood regulations such as HIPAA / FDA QSR and protective
   regulations such as licensure and credentialing.
   

   View Slide

10. Where ML and AI are applicable
    Therapies
    Therapeutic
    Tools
    Diagnostics
    Diagnostic
    Tools
    Patient
    Administration
    Payer Admin
    Clinical
    Professional
    Education
    Public Health
    Education
    Patient
    Education
    Most Regulation
    Least Regulation
    Cohort specific
    Personalized
    Risk Data Sharing
    

    View Slide

11. Where ML and AI are applicable
    Therapies
    Therapeutic
    Tools
    Diagnostics
    Diagnostic
    Tools
    Patient
    Administration
    Payer Admin
    Clinical
    Professional
    Education
    Public Health
    Education
    Patient
    Education
    Most Regulation
    Least Regulation
    Auto Literature Review
    Specialty-specific Content
    

    View Slide

12. Where ML and AI are applicable
    Therapies
    Therapeutic
    Tools
    Diagnostics
    Diagnostic
    Tools
    Patient
    Administration
    Payer Admin
    Clinical
    Professional
    Education
    Public Health
    Education
    Patient
    Education
    Most Regulation
    Least Regulation
    Auto Adjudication
    Fraud Detection
    Quality Compliance
    Contract Adherence
    

    View Slide

13. Where ML and AI are applicable
    Therapies
    Therapeutic
    Tools
    Diagnostics
    Diagnostic
    Tools
    Patient
    Administration
    Payer Admin
    Clinical
    Professional
    Education
    Public Health
    Education
    Patient
    Education
    Most Regulation
    Least Regulation
    Patient Self Diagnostics
    Unlicensed Pro Diagnostics
    Digitally and Heuristically Guided Diagnostics
    Images (self, guided, consulted)
    Labs and Chemistry (self, guided, consulted)
    Multi-omics (self, guided, consulted)
    Molecular Biology
    

    View Slide

14. Where ML and AI are applicable
    Therapies
    Therapeutic
    Tools
    Diagnostics
    Diagnostic
    Tools
    Patient
    Administration
    Payer Admin
    Clinical
    Professional
    Education
    Public Health
    Education
    Patient
    Education
    Most Regulation
    Least Regulation
    Auto Triage for Low-risk
    Augmented Triage for Higher risk
    Infection control / Anti-microbial Stewardship
    Consulted Tele Diagnostics
    Med Device Continuous Diagnostics
    

    View Slide

15. Where ML and AI are applicable
    Therapies
    Therapeutic
    Tools
    Diagnostics
    Diagnostic
    Tools
    Patient
    Administration
    Payer Admin
    Clinical
    Professional
    Education
    Public Health
    Education
    Patient
    Education
    Most Regulation
    Least Regulation
    Physical
    Mental (chat, VR, etc.)
    Digital (nutritional, etc.)
    Clinical Research ( “systematic review automation”)
    Drug Development
    Clinical Discovery (unattended and digital)
    

    View Slide

16. Where ML and AI are applicable
    Proteomics
    Genomics
    Biochemical
    Imaging
    Behavioral
    Phenotypics
    Admin
    Economics
    Connectivity Integration Transformation Comprehension Enrichment Insights Cognition
    No ML or AI possible without these
    

    View Slide

17. The State of AI in Life Sciences
    Find what might
    work
    Validate in silicon
    without clinical
    trials
    Validate
    effectiveness in
    the real world
    Commercialization
    Distribute safely
    and at scale
    Manufacture
    safely and at scale
    Monitor Patients
    Post Market
    Improve Safety
    Post Market
    Science 3.0 (drug
    discovery)
    VERY FAR AWAY AND
    SPECULATIVE
    

    View Slide

18. The State of AI in Life Sciences
    Find what might
    work
    Validate in silicon
    without clinical
    trials
    Validate
    effectiveness in
    the real world
    Commercialization
    Distribute safely
    and at scale
    Manufacture
    safely and at scale
    Monitor Patients
    Post Market
    Improve Safety
    Post Market
    Biology simulation
    VERY FAR AWAY BUT
    HAS SIGNIFICANT
    PROMISE, WORTH
    INVESTING
    

    View Slide

19. The State of AI in Life Sciences
    Find what might
    work
    Validate in silicon
    without clinical
    trials
    Validate
    effectiveness in
    the real world
    Commercialization
    Distribute safely
    and at scale
    Manufacture
    safely and at scale
    Monitor Patients
    Post Market
    Improve Safety
    Post Market
    Automating
    clinical trials,
    detecting fraud
    TODAY,
    ACCELERATING,
    WORTH INVESTING
    

    View Slide

20. The State of AI in Life Sciences
    Find what might
    work
    Validate in silicon
    without clinical
    trials
    Validate
    effectiveness in
    the real world
    Commercialization
    Distribute safely
    and at scale
    Manufacture
    safely and at scale
    Monitor
    Patients Post
    Market
    Improve Safety
    Post Market
    Biggest opportunity to learn
    from other industries
    TODAY, ACCELERATING,
    WORTH INVESTING
    

    View Slide

21. The State of AI in Life Sciences
    Find what might
    work
    Validate in silicon
    without clinical
    trials
    Validate
    effectiveness in
    the real world
    Commercialization
    Distribute safely
    and at scale
    Manufacture
    safely and at scale
    Monitor Patients
    Post Market
    Improve
    Safety Post
    Market
    Biggest opportunity to learn
    from other industries
    TODAY, ACCELERATING,
    WORTH INVESTING
    

    View Slide

22. The State of AI in Life Sciences
    Find what might
    work
    Validate in silicon
    without clinical
    trials
    Validate
    effectiveness in
    the real world
    Commercialization
    Distribute safely
    and at scale
    Manufacture
    safely and at scale
    Monitor Patients
    Post Market
    Improve Safety
    Post Market
    The most potential for immediate
    use (great investment thesis)
    TODAY, ACCELERATING
    

    View Slide

23. The State of AI in Life Sciences
    Find what might
    work
    Validate in silicon
    without clinical
    trials
    Validate
    effectiveness in
    the real world
    Commercialization
    Distribute safely
    and at scale
    Manufacture
    safely and at scale
    Monitor Patients
    Post Market
    Improve Safety
    Post Market
    Many opportunities
    in “real word
    evidence”
    TODAY, ACCELERATING
    

    View Slide

24. The State of AI in Life Sciences
    Find what might
    work
    Validate in silicon
    without clinical
    trials
    Validate
    effectiveness in
    the real world
    Commercialization
    Distribute safely
    and at scale
    Manufacture
    safely and at scale
    Monitor Patients
    Post Market
    Improve Safety
    Post Market
    Once we have lots of
    data from real-world
    evidence efforts
    SOON
    

    View Slide

25. What AI is worth investing in?
    Ask innovators hard questions, like:
    • Which monumental tasks is their novel AI eliminating?
    • Which significant roles in life sciences or healthcare
    are no longer necessary because of their novel AI?
    • Can their AI speed the delivery of patient-facing
    innovations, improve post-market quality, or speed up
    regulatory approvals?
    If you think of AI as a gold rush, pick-axes and shovels are worth investing in
    if they can be shown to add to the considerable work being done by open
    source software produced by Microsoft, Google, and others.
    

    View Slide

26. How should machines go through medical training?
    Which medical school will have the first machine
    learning algorithm training department?
    

    View Slide

27. Thank You. Join the Innovation
    Evaluation Revolution at
    www.Medigy.com
    Find this and many other of my decks at
    http://www.SpeakerDeck.com/shah
    How can investors spot AI BS?
    @ShahidNShah
    shahid@shah.org
    

    View Slide