Getting People to Trust Your AI System

One of the biggest issues with AI is whether people will be able to trust it or not. That is what makes AI governance such a big deal. Trust in AI is a major deal because it will start to influence a significant part of our daily lives. A machine learning model will be in charge of whether someone can buy a home or not.

The big thing about AI systems is that they will become more prevalent as time goes on. Trust has to be built, and there are many dimensions that will need to see trust in AI. The Important thing when it comes to AI algorithms is being able to build that trust in the dimensions required. In terms of these dimensions, you have the ethics side, operations, and performance sides. No matter what, there’s always a way to improve your AI model to make people trust it more. Building that trust is something that companies will need to figure out when deciding to go all-in on AI systems.

Trust in Performance

One of the biggest problems with AI systems is knowing whether they perform well or not. How accurate is your machine learning model? Was your AI model built with good data? These are the questions you need to ask to ensure you have a system that performs extremely well. If your system doesn’t perform well, it means you will have trouble convincing people that they should base their entire livelihoods on what it puts out.

You also want your machine learning model to perform well and be stable. All of these things count, and you never know when a simple bug can cause disruption to millions of people. Engineers often think about performance from a technical standpoint, but they need to also start thinking about how AI systems impact the people using them.

The Operations Side of the Equation

When it comes to running AI systems, there are also other issues you need to worry about. An AI model doesn’t get put into production with no other work needed. You need to run everything and provide monitoring and maintenance. A major part of the operations side is dealing with legal compliance and other issues that are not technical.

You need to think about how your AI model is working based on what the business needs. Trust in AI will be based on how you can keep it operating well to provide both the business and users with benefits. Your machine learning model will need to be constantly checked and monitored to ensure that it doesn’t drift or start providing bad results.

Does Your AI Do Ethical Things?

The final dimension is how your AI model works in the ethics department. Eliminating bias and ensuring good AI governance is a major undertaking in the industry. For example, is your machine learning model biased against a certain group of people? How about privacy concerns? These might not seem like major problems, but there will become crucial in how trust in AI works in the future of this industry.