# AI Personas: Interview Approach

## Current approach

## The Voting Test


### Persona Generation


#### 1. Meta Persona: The Big Picture

Using general data, like census or population statistics.
- Sexual
- Age

#### 2. Tabular Personas: The Profile

Adding specific details

- **Objective**: Income, education, and job.
- **Subjective**: Political views and hobits.

#### 3. Descriptive Personas: The AI Sketch

Letting the AI do the simulation to persona's "life story" based on the data above.

### Election Day

#### 2024 Election

#### 2020 Election

#### 2016 Election

### Findings

#### Postive tendency

#### The "Iceberg" Problem
- **Above the water (Surface)**: AI is good at copying how we talk and what opinions we have.
- **Below the water (Deep Thinking)**: AI doesn't actually understand why humans believe what they do. It just creates "stereotypes" instead of real, diverse people.

## The Goal: Making AI "Think" Like a Human


#### Fidelity: Realism
Does the AI follow a human path to a decision, or is it just a "black box" that spits out an answer?

#### Individuality: Uniqueness
- Illusion of Consensus: AI dont like mistakes, they don't be evil
- In the real world, people disagree and have unique quirks.

### Human Reasoning

#### Causal: Cause and Effect
Understanding that one thing leads to another.
> 👩‍: "Someone is grabbing an ice cream, there must be an ice cream truck nearby."

#### Compositional: Building Blocks
Taking old experiences and using them in new situations.
> 👩‍: "The ice cream car is surrounded by many people, there must be a line of customers"

### Revisable: Correct Yourself
Learning from mistakes and updating beliefs.
> 👩‍: "If I saw Conan next time, there must be something bad just happened..."

## The GenMinds Solution

#### Step 1: Structured Thought Capture - Interviewing Humans
Let AI interview real users:

> 🤖: How "Transparency" leads to "Public Safety"?
👦: It can reduce crime by aiding investigations with more transparency, which increases public safety.

**Transparency → Crime rate → Public safety**
> 🤖: Does transparency have an effect on support for surveillance?
👩‍🦰: “People will have less privacy concern if they know how data is used…

**Privacy Concern ← Transparency → Crime rate**

#### Step 2: Causal Belief Network - Mapping Beliefs
It builds a "web" of how that specific person thinks.

#### Step 3: Inference via Intervention - Testing Changes
> 👦: "If the government ensures that the data is used for legitimate purposes and provides explanations of those purposes, how will this specific person's opinion change?"

## References
- [Skill.md](https://github.com/search?q=repo%3Amattpocock%2Fskills%20interview&type=code)
- [LLM Generated Persona is a Promise with a Catch](https://arxiv.org/html/2503.16527v1)
- [Simulating Society Requires Simulating Thought](https://arxiv.org/html/2506.06958v3)