Module 6 - AI Deployment and Ethics Archives

AI Regulations and Governance

What is a regulation in artificial intelligence? The landscape of artificial intelligence (AI) is as dynamic as it is revolutionary, weaving into the very fabric of our daily lives and reshaping the boundaries of what’s possible. Yet, with great power comes the undeniable need for regulation and governance. This necessity is not born out of a desire to stifle innovation but to ensure that the development and deployment of AI technologies occur within a framework that protects, empowers, and respects all stakeholders involved. National and International regulations At the heart of AI governance lies a complex

AI and Society

How does AI affect the society? Artificial intelligence (AI) has woven its threads through the fabric of society, subtly altering the canvas upon which our lives are painted. Its influence extends far beyond mere technological advancement, shaping the very structure of our job market, societal norms, and ethical responsibilities. Impact of AI on employment The advent of AI has sparked a transformation in employment, a metamorphosis that is both promising and challenging. On one hand, AI automates mundane tasks, liberates human intellect for more creative pursuits, and pioneers new professions. Imagine a world where the tedium

Interpretability and Explainability

In the realm of artificial intelligence (AI), two terms frequently surface, often used interchangeably yet distinct in their nuances: interpretability and explainability. These concepts serve as the bridge connecting human comprehension and machine decision-making, ensuring that AI’s logic isn’t locked away in an impenetrable black box. What is Interpretability? Imagine you’re a detective, and each AI model is a suspect with an alibi. Interpretability is the clarity of that alibi. It’s about how easily one can comprehend why the model made a particular decision. This does not necessarily mean knowing the exact mathematical operations (though that

Model Deployment

Deploying AI Models in Production Deploying an AI model into production is the process of transitioning the model from a development or testing phase to a live environment where it can start providing value by making predictions or decisions based on new data. This step is crucial for realizing the practical benefits of the model’s capabilities. Key Considerations for Successful Deployment Successful deployment hinges on meticulous planning and execution. Some crucial things to keep in mind are as follows: Integration with Existing Systems Integrating an AI model with existing systems can be seen as a bridge-building

Category: Module 6 – AI Deployment and Ethics

AI Regulations and Governance

AI and Society

Interpretability and Explainability

Model Deployment

AI JetTech