securitywing

Artificial Intelligence

AI Without the Risk: How to Build Simple, Smart Guardrails for Your Team

Artificial Intelligence (AI) tools are landing on everyone’s desk faster than almost any technology in history. Employees are using AI to write emails, draft code, summarize long documents, and analyze data.

While AI opens up massive opportunities, it also brings brand-new risks: confidential company data getting leaked, AI making confident mistakes (“hallucinations”), or unfair biases slipping into key business decisions. [Read more…] about AI Without the Risk: How to Build Simple, Smart Guardrails for Your Team

From Vectors to Context: How Transformers Learn Through Attention and Self-Supervision

When I first started learing about transformer I found a couple of concepts were the key to understand the transformer model properly and those are wordembedding or vectorization of text, attechteion mechanism, multi head attention, self-supervised learning. In this post I have tried to explain how they are linked together and how they form the build blocks of the transfomer model.

These ideas are linked because they form the core of how a Transformer language model learns from text and uses context.

Here is the big picture:

Text > tokens  >vectors > multi-head attention > contextual representations ? predictions

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AI Ethics and Security: What You Need to Know

This post explores the interplay between artificial intelligence (AI), ethics, and information security. As AI becomes increasingly pervasive and processes vast amounts of personal data, strong security controls are essential to prevent misuse and to uphold ethical boundaries.

Before implementing any AI initiative within an organization, it is important to highlight historical concerns around AI ethics, the significant overlap between ethical and security responsibilities, and the need for clearly defined roles and close collaboration among stakeholders. These elements are critical for addressing risks such as privacy violations, data leakage, and unauthorized access.AI Ethics and Security-What You Need to Know [Read more…] about AI Ethics and Security: What You Need to Know

The Evolving Impact of AI on the IT Risk Landscape

This post explores how artificial intelligence (AI) is transforming industries while introducing significant new risks that extend beyond traditional IT risk management. Here we will foucus on AI’s “black box” nature, rapid adoption, and unique challenges (e.g., bias, privacy issues, and emergent behaviors) require organizations to adopt enhanced risk management strategies, including AI-specific controls, governance structures, and legal compliance measures. Relying solely on acceptable use policies is insufficient; instead, a “reasonable care” approach, informed by legal standards like the business judgment rule, is essential to mitigate liabilities and ensure ethical deployment. The piece emphasizes the need for ongoing inventories, risk assessments, and tailored life cycles for AI systems, concluding that organizations must evolve their practices to handle AI’s systemic impacts responsibly.The Evolving Impact of AI on the IT Risk Landscape [Read more…] about The Evolving Impact of AI on the IT Risk Landscape