AI Literacy Is No Longer Optional Under the EU AI Act, UK and US Regulations.

Why AI Literacy for Users?

According to the EU AI ACT Article 4 on AI Literacy:

Providers and deployers of AI systems shall take measures to ensure, to their best extent, a sufficient level of AI literacy of their staff and other persons dealing with the operation and use of AI systems on their behalf, taking into account their technical knowledge, experience, education and training and the context the AI systems are to be used in, and considering the persons or groups of persons on whom the AI systems are to be used. 

We Create Custom Videos to Help Users Understand How Your AI Systems Work, Their Risks, and Limitations.

Enhanced User Trust and Confidence

Ensure Regulatory Compliance with the EU AI ACT, UK and US

Empowered and Informed Users

Get Started Today and Be Ready to Meet Compliance in 48 Hours

Achieving AI literacy compliance doesn’t have to be complicated or time-consuming. With our tailored video solutions, you can get your team up to speed quickly and meet regulatory requirements in as little as 48 hours. Here’s how we make it happen in three simple step:

1. Conduct Initial Assessment


We begin by understanding your organization's needs, and dive deep into your AI systems. This helps us create a customised training plan for your users.

2. Customised AI Literacy Videos

Our experts design and produce custom videos that gives an introduction to AI and explains how your AI systems work, along with their risks and limitations.

3. Download Videos


Once your videos are ready, you can download them and integrate them into your onboarding process.

Medical And Healthcare Services

Fintech, Banking, and Finance

Government And Public Sector

InsurTech and Insurance

Industries we work - AI Training

With our customised service we help you to improve user trust and ensure compliance.

What People Say About Esdha

Client Testimonials

Aramco

First National Bank

Department Of Education

NHS

Articles and Resources

Esdha's - Responsible AI Toolkit

Counterfactual Fairness in Machine Learning

Fairness in machine learning has been predominantly studied through global metrics like Demographic Parity and Equalized Odds. These approaches aim to ensure equity between groups

Predictive Rate Parity in Machine Learning

Fairness in healthcare machine learning is highly context-dependent. Different use cases, populations, and risks require tailored approaches to fairness, making it essential to align fairness