Course Aim

The aim of this course is to give you the technical tools to ensure that your AI systems are unbiased, i.e., their decision-making process is ethical and fair against all potential societal groups.

We aim to give you knowledge of the main technical concepts of ISO/IEC 24027:2021, by exploring measurement techniques and methods that can be used to assess bias, with the ultimate objective of mitigating bias-related vulnerabilities. It's important to note that all phases of the AI system lifecycle, including data collection, training, continual learning, design, testing, evaluation, and monitor, are within the scope of this standard.

The course helps reinforce the importance of identifying various sources of bias and understanding what impact these can have on the development and deployment of AI systems

We aim to give you knowledge of the different contexts in which bias concerns can arise, by providing examples of bias concerns and give possible strategies for how to detect (and possibly address) such issues.

Course Description

Bias in AI systems can take on many different forms. For example, when an AI system learns patterns from data, it may unintentionally adopt existing societal biases against certain group. Here at BSI,  we have developed a comprehensive course that delves into the critical topics of bias and fairness in AI system, based on the ISO/IEC 24027:2021 standard. The course explores the importance of the ethical and fair development in AI Technologies.  

On-demand - training that’s even more flexible

BSI’s on-demand courses are market-leading and available 24/7. Developed by top subject matter experts, they contain the same high-quality content you will find in our tutor-led training, but with the added benefit of being able to learn at your own pace and at any time.

How will I benefit?

This course will help you:

• Build a toolset of methods that can help identifying bias and fairness issues,
• Identify potential sources of unwanted bias and terms to specify the nature of potential bias,
• Assessing bias and fairness through metrics,
• Addressing unwanted bias through treatment strategies.

What will I learn?

Upon completion of this course, you will be able to:

• Recognise and detect unwanted Bias in AI system
• Apply measurement techniques and methods to assess bias and fairness,
• Mitigate bias-related vulnerabilities
• Control and treat of unwanted bias throughout an AI system life cycle (Design, and Development, Verification and Validating, Deployment

Who should attend?

• Data Scientists
• Data Analysts
• Data Engineers
• Machine Learning Engineers
• AI architects

How will I learn?

This is an online, interactive on-demand course. Courses are available 24/7 and you can learn at any time and from any place that suits you – you just need an internet connection. You can learn as fast or as slowly as you want to. You can also take breaks at any time in the course and pick up where you left off when you are ready to continue. During the access period, you can go back and repeat parts or all the course to refresh and reinforce what you have learned. The course content is both detailed and engaging, with explanations, activities, and knowledge checks to enhance your learning.

What will I gain?

On completion, you’ll be awarded an internationally recognized BSI training course certificate.

Prerequisites

The course assumes that delegates know the basic concepts of AI and understand what a neural network is.

We recommend attending the: ‘Bias in AI systems and AI aided decision-making Awareness On-demand Training Course’

Modules

• Bias in AI aided decision making: Module 1