Computer Science

when something is unfair towards or against something or someone

dealing with various issues that are commonly found in raw data sets, such as missing data, duplicated records and outliers

Data driven models

Introduction to AI

Machine learning

Predictive vs generative AI

Social and ethical issues of AI systems

Approaches to training machine learning models

Classification

Machine learning engines

This unit introduces pupils to the emerging field of data science. They will explore what AI systems are and the different categories of AI. The concept of machine learning and how models are driven by data will be explored. They will also consider the ethical and wider implications of AI systems.

Data science: AI and machine learning

data that is representative, high quality, and ethically sourced

any data you can find, regardless of quality or source

data that is biased towards one group so the model learns faster

When choosing data to train an AI system, what should you look for?

A team is preparing raw data to train an AI model. They notice some missing entries, repeated rows, and strange values that don’t fit the pattern. What process should they carry out?

dealing with various issues that are commonly found in raw data sets

a data point that's significantly different from others in the dataset

storing data in a secure, encrypted format

Which of the following is NOT a common cause of duplicated records in a dataset?

Data points that are significantly different from other data points in the data set are called:

The model will identify all cats equally well.

The model may fail to identify all cats correctly because of data bias.

The model may fail to identify black cats.

A student builds a machine learning model to recognise cats. They train it mostly with pictures of black cats and very few brown or white cats. What problem might occur?

Which of the following is a potential risk associated with the introduction of AI systems?

It protects personal information from misuse.

Why is privacy an important issue in the context of AI?

What is the term for when an AI system produces results that are unfair towards certain groups or individuals?

Arrange these steps in order to help make AI systems fairer:

to allow users to understand and question decisions

Why is it important for AI systems to be transparent?

AI systems can actually increase inequality of access to technology.

AI systems guarantee equal access to digital tools for everyone.

Only wealthy individuals benefit from AI systems.

AI systems are free for all users worldwide.

Which statement about AI systems and access to technology is correct?

Data driven models

Lesson outcome