Explainability, trust and layers of clinical decision making in pre and current AI LLM era:
EBM layer: This layer is the one our clinical decision making lab is largely engaged in although the other two layers are no less important.
We have already shared something around those in our previous demos particularly our two video links shared above.
Human layer: This is the most important layer where clinical decision making actually happens at multiple human stakeholder levels:
Below are recent examples of the limits of scientific explainability and it's effect on human trust.
This was human forwarded through WhatsApp and possibly AI generated. So should we call it human generated with AI in the loop or AI generated with human in the loop?
Well as mentioned before here : https://medicinedepartment.blogspot.com/2025/11/visual-4-what-is-intelligence-gim.html?m=0 all human intelligence is AI!
How much Trust building can one achieve through Human clinical decision making with AI in the loop?
Human mistrust due to persistent uncertainty due to scientifically limited explainability ?
Images of subclinical hypothyroidism patient data:
Human full trust inspite of persistent uncertainty due to scientifically limited explainability
Can AI act as a guard rail for human mistrust due to lack of communication and explainability?
All the real patient individual demonstrations above take a closer look at individual patient events producing their unique event data trajectories that are perhaps simpler in terms of explainability and interpretability than what may have happened if we tried to inter connect many more individuals with common attributes to predict individual trajectories based on past similar individual trajectories!
Using the language of what we have labeled as "machine layer":
"While random forests often achieve higher accuracy than a single decision tree, they sacrifice the intrinsic interpretability of decision trees. Decision trees are among a fairly small family of machine learning models that are easily interpretable along with linear models, rule-based models, and attention-based models. This interpretability is one of the main advantages of decision trees. It allows developers to confirm that the model has learned realistic information from the data and allows end-users to have trust and confidence in the decisions made by the model.[39][3] For example, following the path that a decision tree takes to make its decision is quite trivial, but following the paths of tens or hundreds of trees is much harder."
Unquoted from: https://en.wikipedia.org/wiki/Random_forest
Summary of current clinical decision making workflow:
So What? SWOT
S
trengths: Human centred management, Creativity
W
eaknesses : User Interface: Asynchronous, academic flatlands
O
pportunities : Prelude to the symphony of Singularity
T
hreats: TLDR, DPDP
Now what?
[27/01, 04:10] AyeAI ∴ AyeAM AC: The above messages form an outline of what could be called "a prelude to AI embodiments"
So that would leave folks without FOMO (Fear of missing out!) but the state of mind would be closer to the closing scene of Finding Nemo (see the pic)
[27/01, 04:16] AyeAI ∴ AyeAM AC: Now what?
Well next steps would be akin to a sci-fi novel I've been working on for quite some time (over a decade of writer's block)
Dr Particles... While our simple robots beat the Avatar movie model (these robots don't drop dead on log off - which was a serious patent mishap we faced and is now public domain)
Nano robotics... Smart dust... Wavefront shaping
[27/01, 04:27] AyeAI ∴ AyeAM AC: Dr Particles is the story of a nano swarm that explores human agency in the philosophy of Synthematic Pragmatic Realism! Hopefully in theatres sometime soon 🥹
Now that we've landed in 2126 (100 years from now)... Let's get back to our basic 2WD little "champy-bot" ... humble build that connects India and Bharat, and can still give MITs and Stanfords a run for their money :)
And our mantra... Festina Lente
Explore!
[27/01, 06:33] AyeAI ∴ AyeAM AC: We need a four wheel legged robot kit that's low cost and easy to build. Let's see what our genZ entrepreneurs are building further
We're not planning drones yet. ESC simply cannot be real low cost and risks are involved.
Minimal entry level for flying drones will be college students (18+) or possibly high school under strict parental control
[27/01, 06:47] AyeAI ∴ AyeAM AC: Remaining "form factors"
1. Uniwheel
2. Underwater
Hazard options... To people, property and robots.
Say someone wants to do an agricultural robot, IP66 grade embodiment are needed exponentially increasing the costs
A little introduction to industrial automation... Conveyers, rapid prototyping, casting, forming, shaping etc.
[27/01, 06:48] AyeAI ∴ AyeAM AC: Finally, all these need to be aligned with school syllabus... Across boards - ICSE CBSE NIOS State board etc
While accounting for global Ivy league admissions, Olympiads etc... IGCSE, IB, Advanced Placement etc
....
Some trivia. California schools allow online admissions. Do explore those for 11th 12th if you're targeting US
We will keep you posted on open calls for age appropriate competitions etc.
[27/01, 06:53] AyeAI ∴ AyeAM AC: A system/ a syllabus that doesn't overwhelm! (Most important for our post colonial reality as I have started to understand). Designing for Bharat without lived experience in villages is difficult (😀 that's also planned. Mana is the perfect spot. Last Indian village before Tibet - will make for a wonderful conference venue)
At the same time... Resource constraints should not mean compromise (as already described in the comparison of iCanSee Hindawi ILM with OLPC)
Now to get some CSR folks and NGO interested! Let's see
[27/01, 07:00] AyeAI ∴ AyeAM AC: Buy Unitree Go2 Air at Robu.in https://share.google/QqxPlRuz2JlWjNnpF
[27/01, 07:01] AyeAI ∴ AyeAM AC: 4 lakhs+ 🥹 our target 4000 INR... Let's see
[27/01, 07:13] AyeAI ∴ AyeAM AC: Apologies for the volume of messages.
Kindly read through these. We'll come forth with a structured prospectus!
Thank you for your support and cooperation
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