# AI Ethics

## Introduction

* AI Ethics is a branch of applied philosophy. It deals with the moral principles and values that guide the development and deployment of AI. It answers the question: **"Just because we&#x20;*****can*****&#x20;build this AI,&#x20;*****should*****&#x20;we? And if so, according to what values?"**

## **Core Principles**

### **Privacy**

* To ensure each individuals can **control over personal information** and how it is used
* For data collection, it is required **user approval for the collection of data**
* During data preprocessing, some **sensitive data may need to be filtered or masked**

### Transparency

* To **resolve "Black Box" problem**. Users should understand how an AI arrived at a decision, especially in high-stakes areas like healthcare or criminal justice.
* **How the data is collected and used**. **How the model be trained / fine-tuned  and answered**
* To draft the benchmark and scope, **which question can be answered**, **what is the confidence score and limitation**

### **Accountability**

* AI accountability is not just about assigning blame; it is about **taking responsibility for the entire lifecycle of the system**
* Organizations must explicitly define **who owns the risk&#x20;*****before*****&#x20;the AI is deployed**.&#x20;
  * **The Developers:** Responsible for testing the model for bugs and bias.
  * **The Product Owners:** Accountable for the decision to deploy the model in the real world.
* Does the process follow the **legal compliance**?&#x20;
* How **government law secure the safety** of using AI?

### Fairness

* AI fairness is to **treat everyone equally**, avoiding discrimination and bias
* During data collection, **is the data variety high enough**?&#x20;
* Is the **model be fine-tuned by updated data**?
* Does the model run the **fairness check across different scenarios**?

## AI Governance

* [Artificial intelligence (AI)](https://www.ibm.com/think/topics/artificial-intelligence) governance refers to **the processes, standards and guardrails that help ensure AI systems and tools are safe and ethical**.
* AI governance is essential for **reaching a state of compliance,** [**trust**](https://research.ibm.com/topics/trustworthy-ai) **and efficiency** in developing and applying AI technologies.
* Effective AI governance includes oversight mechanisms that address risks such as [bias](https://www.ibm.com/think/topics/ai-bias), privacy infringement and misuse while fostering innovation and building trust.&#x20;
