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People+ai Theses

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How to Read:

Start by reading the Theory of Change by

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Read Domain specific thesis by

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Leave your thoughts/feedback by

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Focus area rationale:

Population scale domains are evergreen with problems. Everyone is constantly trying to solve it. Our hypothesis is that the existing problems can be significantly solved by AI.

We want to demonstrate this capability.

Our belief in-

Working with public, in public,

Open sourcing the solutions developed, and

Capacity to build and foster domain specific communities

-puts us in a good position to build and demonstrate use cases and infrastructure for development areas.

[

domain specific rationale can be found in linked thesis below in the document⁠

]

[TOC] Logframe:

Summary

Indicators

Verification

Risks/

Assumptions

Goals

[vision is to reach population scale through market players/start-ups]

Solutions/Prototypes are taken to market and tested

Community picks up relevant use cases in domains and works on it

[no reinventing the wheel]

# no of market players test and adopt our solutions

# no of orgs/individuals working on use cases

Project Impact Report (format to be designed at M&E stage)

Market buy-in is seamless

It adds value to market players

AI can solve population scale problems effectively

Outcomes

- Prototypes for use cases are built and tested with partners/community

# no of prototypes built and tested with partners

Working Group Artefacts

Project Impact Assessment Data

Partners are willing to build/test prototypes and see value in solutions developed

Outputs

- Problem statement and solution is better fleshed out and worked upon

- Learnings from community events lead to evolved TOCs

- Domain Dashboard is populated (use-cases/Infrastructure ideas + learnings from projects)

# no of use cases are converted to seedlings/working groups

# no of times TOCs is updated

4x Domain dashboard updated

Coda Dashboard

Thesis document

Video/Blog posts

Our hypothesis developed is reflective of ground reality

Inputs/

Activities

- Experts mentoring and guiding Project anchors - Use cases/Infrastructure is explored - Community event is conducted

# no of Experts/mentors are onboarded into CRM/community

# no of use cases/infrastructure solution is updated

4x no of community events conducted/quarter

CRM data

Community event attendance

Ideas on Coda

Track thesis document

Videos

Attendance records

Events will take place on committed time frame

There are no rows in this table

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Pre-conditions:

Secondary/Primary research is conducted to populate use case/infrastructure ideas.

Thesis/Hypothesis for each domain is in place.

Meaningful networking track onboards experts/mentors on CRM.

What Domain areas we will be focusing on:

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`Health & Accessibility Thesis`⁠
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Current projects and ideas:

Discover

Use-Case Garden

All

Demonstrate

City AI Engine

Smart Cities & Infrastructure

Sunva ai

Public Health & Accessibility

Project Sukoon

Public Health & Accessibility

Interoperability for Legal Access

Legal & Justice

Sthaan

Smart Cities & Infrastructure

JKB

All

GreenTrack

Environment, Energy & Sustainability

ConsumeWise

Environment, Energy & Sustainability

Digiform

All

Disseminate

Adbhut India

All

There are no rows in this table

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Prioritisation for the next 1 year:

Area of Work

Time Frame

Community meetups are conducted per domain area -

1/6 weeks

Theory of Change is evolved based on learnings from Community engagement

August - October

# no of Project ideas in each domain is initiated and taken to working group stage and prototyped

#no of Projects undertaken by community partners to work on

October onwards

1 Domain Dashboard published with learnings from Use-Case/Infrastructure projects undertaken + new use cases

August onwards

Monitoring and Evaluation Framework and Tracking

(designed by track owner)

August - Framework Design September onwards - Tracking

There are no rows in this table

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I wish there was a thesis on AI powered Financial Advice/Planning for the masses. Everyone needs quality financial advice, but only a lucky few get access to the same. This is so because, qood/qualified financial planners are few (1 registered registered financial advisor per ~1 million indians) and the population that is in need of their advice is large and comes from diverse financial backgrounds. This is a high touch profession that involves investor education, trust building, exchange of information/money, frequent check ins and long term client servicing. Naturally, the best advisors tend to focus on the top of the pyramid and ignore the tail/masses. AI could potentially change this game. Imagine a farmer in a village in India, calling an AI Agent via telephone, asking the agent advice on how he can plan for a secure future for his kids and the AI guides him through various options available to him starting from Signing Up for Pradhanmantri Jeevan Jyoti Bima Yojna (Basic affordable insurance cover for exigencies) , Signing up the family for Ayushman Bharat (basic health cover for exigencies), Maybe Starting a Sachet SIP, RD or an LIC child scheme for kids that mature at at different life stages - School, College, marriage etc. What’s more the AI agent could possibly sign him up for relevant schemes there and then itself without any paper work. Once signed up, the AI agent would regularly follow up with the farmer on service updates, status of investments etc and could act as single service point for all plans. The same AI could also interact with a Senior Corporate Executive in a Metro city looking to diversify his/her PMS and MF portfolio. I am still debating with myself whether this is a use case or a thesis theme. Would love some feedback.