Regulation is coming to AI. That is one of the many reasons model monitoring and trusted AI are two concepts that developers will need to understand. These two concepts can be the difference in ensuring that your AI models can withstand future oversight and regulations that might come to the industry. AI algorithms are now a crucial component of many modern activities. Because of this, companies need to have a good handle on ensuring that fairness is maintained at every step of the process.
Modern AI algorithms operate like black boxes. That means that they don’t show how they get to the results they put out. This can be a huge problem in societies where fairness is a major cultural phenomenon. After all, you can’t have AI algorithms preferring one racial group over another when making decisions. These things make AI governance key.
International groups have developed a system for classifying what constitutes a fair AI system.
What Is AI Bias
Artificial intelligence algorithms are often built from data sources that are trained to turn into good models. AI bias is anything that makes that model benefit one group arbitrarily over another. For example, you wouldn’t want to have a system that was trained on only one racial group. It would be better at identifying that racial group over others. Simple things like this can have massive impacts on our society.
Because of the black-box nature of AI algorithms, there has to be AI explainability to help normal people understand what goes on inside an algorithm. MLOps governance is also going to be a crucial component of the process. Companies will need new ways of mitigating bias to be successful in the future.
How It Manifests Itself
Bias can manifest itself in many ways. For example, banks might find that certain racial groups are prioritized for loans based on the AI algorithm being implemented. This obviously has a massive effect on the community and the trust they have in the bank. Maintaining transparency can be the difference between trust being lost or not. Model monitoring is also another thing that companies can do to ensure that bias never creeps in.
How Proper Governance Can Fix Things
Proper governance can form the foundation to have trusted AI that works to the benefit of everyone.
AI audits will become a foundation of proper governance. Another solution will be AI explainability. That explainability is key to ensuring that the average person will trust what’s inside your algorithm. It will also help you avoid increased scrutiny that can come from governments all around the world. MLOps has processes built in to help you detect and eliminate bias.
When everything is combined, you have an increased chance of avoiding all of the problems that will come your way. Proper governance will be an issue. Machine learning models will become an increasingly important piece of our society. Having a system to detect and prevent bias is going to be more crucial going forward.