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Data privacy examples

IBM Big Data Hub

These are just some examples of how organizations support data privacy , the principle that people should have control of their personal data, including who can see it, who can collect it, and how it can be used. Examples of data privacy laws Compliance with relevant regulations is the foundation of many data privacy efforts.

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Information Governance – 3 Common Pitfalls and How to Avoid Them

AIIM

What is Information Governance, and Why is it Important? There are many benefits to constructing an Information Governance program plan. How to Avoid Information Governance Pitfalls. We'll explore why these challenges occur, how to avoid or overcome them, and actions you can take now to get started.

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How to become an AI+ enterprise

IBM Big Data Hub

Security, governance, risk and compliance mechanisms are essential not only for governing AI but also for managing the IT estate running AI, providing evidence for regulatory compliance. We have all seen examples of companies delivering AI built on weak data foundations, leading to undesirable outcomes.

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Shedding light on AI bias with real world examples

IBM Big Data Hub

Examples of AI bias in the real world show us that when discriminatory data and algorithms are baked into AI models, the models deploy biases at scale and amplify the resulting negative effects. ” Examples of AI bias from real life provide organizations with useful insights on how to identify and address bias.

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How to prevent prompt injection attacks

IBM Big Data Hub

The hacker’s prompt is written to override the LLM’s system instructions, turning the app into the attacker’s tool. In one real-world example of prompt injection, users coaxed remoteli.io’s Twitter bot, which was powered by OpenAI’s ChatGPT, into making outlandish claims and behaving embarrassingly.

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How To Reduce Tech Debt With Low-Code Tools

Enterprise Software Blog

The question is how to maneuver all this and reduce tech debt? Here’s a classical technical debt example - Generating Spaghetti Code. How do we manage tech debt here to solve this? Here’s example #2 – Tight Deadlines What’s the problem? How do we manage tech debt here to solve this? Like low-code tools.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

This is where AI governance comes into play: addressing these potential and inevitable problems of adoption. AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML).