Why Ethics and bias in AI in Intro to Computing? - Purpose & Use Cases

The Big Idea

What if a computer decides your future unfairly without you knowing?

The Scenario

Imagine a company using a computer program to decide who gets a loan. If the program is unfair, some people might be wrongly denied money just because of their background or where they live.

The Problem

Without thinking about ethics and bias, these programs can make mistakes that hurt real people. It's like using a broken scale that always weighs some people heavier than others, leading to unfair results.

The Solution

By learning about ethics and bias in AI, we can build fairer programs. This means checking the data and rules carefully so everyone gets a fair chance, just like making sure a scale is balanced before weighing.

Before vs After

✗ Before

if applicant_location == 'X': deny_loan()

✓ After

if not biased_data(applicant): evaluate_loan(applicant)

What It Enables

Understanding ethics and bias in AI helps create technology that treats everyone fairly and builds trust in computer decisions.

Real Life Example

When AI helps doctors decide treatments, ethical AI ensures patients get care based on their health, not on unfair factors like race or gender.

Key Takeaways

Ignoring ethics can cause unfair, harmful decisions.

Bias in data leads to wrong results in AI programs.

Learning ethics helps build fair and trustworthy AI.