AI Governance & AI Risk Management: Formula for Success!

AI Governance & AI Risk Management

What is AI Governance?

AI governance is about creating rules and guidelines for how artificial intelligence should be developed and used. Simply, it’s like traffic laws, but for AI instead of cars.

It refers to the principles, policies, and practices designed to ensure the responsible and ethical use of generative AI technologies.

Understanding AI basics is crucial in grappling with the unique challenges posed by AI systems that can generate creative outputs autonomously. It involves defining standards, establishing guidelines, and implementing controls to steer the development and deployment of AI algorithms.

What are types of risks involved in AI?

There are hundreds of documented risks posed by AI systems. MIT has created this repository to help assess the evolving risks of AI. This repository uses a two-dimensional classification system. First, risks are categorized based on their causes, taking into account the entity responsible (human or AI), the intent (intentional or unintentional), and the timing of the risk (pre-deployment or post-deployment). This causal taxonomy helps to understand the circumstances and mechanisms by which AI risks can arise.

Second, risks are classified into seven distinct domains, including discrimination and toxicity, privacy and security, misinformation and malicious actors and misuse. 

This AI Risk Repository by MIT is designed to be a living database. Their research team plans to regularly update the database with new risks, research findings, and emerging trends. 

Why Do We Need AI Governance?

Now that you know that are hundreds of risks associated with AI tools and there are compliance your business needs to be following. So in this dynamic field of artificial intelligence (AI) , you have to safeguard your business. 

You need to make sure that you have AI governance and you can safeguard your business, your customers and your employees and be compliant with the different regulations. 

AI Governance and AI Risk Management - Protect Your Business

Key Areas of AI Governance

  1. Ethics: Making sure AI is designed and used in ways that are morally right.
  2. Transparency: Ensuring we can understand how AI makes decisions.
  3. Accountability: Deciding who’s responsible when AI causes problems.
  4. Privacy: Protecting people’s personal information when it’s used by AI.
  5. Fairness: Making sure AI treats all people equally and doesn’t discriminate.

Challenges in AI Governance

  • Keeping up with rapidly advancing technology
  • Balancing innovation with safety and ethics
  • Coordinating rules across different countries and states
  • Ensuring compliance

What Can You Do To Safeguard Your Business?

There are frameworks and tools listed below for your reference.

If you would like an expert to take a look at your current technical stack, integrations, use cases and your unique situation, then contact me today at [email protected]. I’ll design a custom AI Governance Program that’s suited for your ogranization.

Frameworks

Tools

  • Dioptra:  Developed by NIST. It’s a modular, open source web-based tool to help companies training AI models — and the people using these models — assess, analyze and track AI risks. Dioptra can be used to benchmark and research models as well as to provide a common platform for exposing models to simulated threats in a “red-teaming” environment.
  • Data Provenance: The Data Provenance Initiative is a volunteer collective of AI researchers from around the world. They conduct large-scale audits of the massive datasets that power state-of-the-art AI models. They have audited over 4,000 popular text, speech, and video datasets, tracing them from origin to creation, cataloging data sources, licenses, creators, and other metadata, which researchers can examine using their Explorer tool.