Trusted AI: A guide to building fair and unbiased AI systems
How to tackle AI bias and more


Provided by
The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data. These risks undermine the underlying trust in AI and affect your organisation’s ability to deliver successful AI projects, unhindered by potential ethical and reputational consequences.
Are you ready to deliver fair, unbiased, and trustworthy AI?
Download this guide to find out:
- How to build an end-to-end process of identifying, investigating, and mitigating bias in AI
- How to choose the appropriate fairness and bias metrics to prioritise for your machine learning models
- How to successfully navigate the bias versus accuracy trade-off for final model selection and much more
Sign up today and you will receive a free copy of our Future Focus 2025 report - the leading guidance on AI, cybersecurity and other IT challenges as per 700+ senior executives
ITPro is a global business technology website providing the latest news, analysis, and business insight for IT decision-makers. Whether it's cyber security, cloud computing, IT infrastructure, or business strategy, we aim to equip leaders with the data they need to make informed IT investments.
For regular updates delivered to your inbox and social feeds, be sure to sign up to our daily newsletter and follow on us LinkedIn and Twitter.
-
Lenovo IdeaPad Slim 3x review
Reviews The Qualcomm Snapdragon X-powered laptop packs a punch for the price
-
The Builder.ai collapse should be a turning point in the age of AI hype
News Builder.ai was among one of the most promising startups capitalizing on the generative AI boom – until it all came crashing down