Seclea Blogs

All Explainable AI, responsible AI, regulatory compliance and AI Governance, Risk and Compliance (GRC) blogs in one place. 

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Product Info

Quick reference material for different features of the Seclea Platform


Free tutorials to learn and practice explainable and responsible AI development. 


Blogs on topics ranging from explainable AI, responsible AI to AI GRC.

White papers

White papers related to use cases and case studies about responsible AI practices.


What do we need explainable AI?
Why We Need Explainable AI?

Explore the rationale of having Explainable AI as a core solution to ensure AI trust and acceptance.

AI Bias can put women at risk
AI Bias Can Put Women at Risk!

AI bias targets the under-representative segments, and if unchecked, it can put women at higher risk.

ML Risk Management and Regulatory Compliance
ML Risk & Regulatory Compliance

Setting up and managing AI GRC for any organisation is a unique challenge.

dangers of AI and responsible Ai
Dangers of AI and How Responsible AI Can Help?

Responsible AI is the key to reaping the benefits of AI and limiting its negative impact on individuals and societies.

gender equality and AI
Why Does Gender Equality Matter in Artificial Intelligence?

AI bias can significantly impact gender equality in modern societies, whether fair access to credit, healthcare, education or job.

AI Bias Risk
AI Bias is a Significant Risk for Organisations

AI pose a significant risk to an organisation – primarily legal, brand and customer trust. So how you should manage the AI risk?

dangers of AI and responsible Ai
Explainable AI in the Financial Services

How to use Explainable AI in de-risking AI for highly regulated applications in the financial services sector.

gender equality and AI
Why do we need AI Fairness?

AI Fairness helps organisations achieve regulatory compliance and is the moral thing to do.

AI Bias Risk
Explainable AI for all stakeholders

To ensure AI projects successful move from prototype to production, we need to involve all AI stakeholders early on.

dangers of AI and responsible Ai
Who is Liable for AI applications?

Tracking and identifying the root cause of an AI issue is critical to ascertaining liability and ensures AI accountability.

gender equality and AI
Limitations of Explainable AI

Explainable AI is a crucial tool; it is not the solution to all AI problems; we need to understand its benefits and limitations.

AI Bias Risk
Principles of Responsible AI

Organisations can implement seven basic principles to ensure they follow Responsible AI practices.

Ai in Healthcare
AI in Healthcare

AI in healthcare challenges ranges from fairness and explainability to accountability and solutions requiring collective effort.

Ethical AI, why do we need it?

By preventing unfair and biased AI solutions, ethical AI can improve the credibility and performance of AI software.

AI Bias Risk
Top five responsible AI challenges

Managing these five challenges enhances AI credibility and ensures Responsible AI practices.