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Generative AI governance: A tale of two models

As the public becomes more aware of generative AI models, thanks in part to tools like OpenAI's ChatGPT, there has been a surge of fear and concern regarding AI regulation and governance. In this article, we put that fear into context and offer actionable steps toward governance, drawing from historical lessons.

3 things we learned about the modeling mindset

What’s your mindset when building an AI model? Christoph Molnar, a statistician and machine learning expert, explains that our approach to factors such as interpretability and uncertainty is what takes our models beyond mere performance.

Data management's role in ML and AI model systems

What is data management's role in machine learning and AI model systems? We illustrate the importance and process of establishing data controls and data quality prior to building these systems.

AI regulation can miss the big picture of modeling best practices

The increasing concerns about AI and the need for regulations are prevalent. However, focusing on regulations specific to LLMs can miss the bigger picture of best practices.

AI ethics and innovation for product development

Learn more about product development and design to make ethical AI considerations an enabler of innovative products your customers will trust and love.

The real risks of OpenAI's GPT-4

While many were marveling at the release of OpenAI's GPT-4, Monitaur analyzed the accompanying papers that examined the risks and technical design of its latest engine through the lens of proper governance, responsible use, and ethical AI.

Responsible AI doesn’t exist without governance

AI governance is a business enabler. Without proper governance practices, deploying AI is like asking your models to keep silent about the reasons they're making decisions that affect your business.

Top bias metrics and how they work

How to measure for bias can be a moving target. In this blog post, we will examine the common methods to evaluate for bias, how they conflict and our recommended approaches.

3 ways to drive innovation while achieving compliance

Compliance and risk management are often seen as the enemy to innovation. This has become more and more of a challenge as companies today have to move fast in order to react to market changes. Given the speed at which the world is changing, innovation can’t continue to be bogged down (by compliance or other internal processes) in order for companies to survive.