Responsible AI is a small portion of AI governance. It focuses on ethics and democratization. That means that it provides a framework through which companies can create AI models that are both ethical and understandable by the average person. We need this ethical AI to be the norm, as there are no governing bodies currently for artificial intelligence algorithms.
Right now, the current paradigm is leading to AI algorithms that are biased and are essentially black boxes. Explainable AI would solve that problem, as it would mean the average person would have a good understanding of what the AI algorithm is doing. This AI governance framework is something that companies will have to come together and invent as an industry.
What Exactly Is Responsible AI
Responsible AI is a way for the industry to regulate itself without waiting for governments to step in. It is about finding the right balance of technology and ethics. You can think of it in the same way you think of the three laws of robotics by Isaac Asimov. In that paradigm, AI regulations need to be applied, or the models need to be robust enough to work well in every situation.
It also needs to be explainable, meaning you have to be able to put it into simple words for the end-user. Finally, responsible AI also has the initiative of being ethical. There should not be any bias in your AI models.
A common example of bias in AI modeling can be seen when certain models are trained with a specific race of people. For example, if you try to train a model with Europeans, it will have many problems identifying people of African heritage. Having ethical AI means good governance in these realms.
Making Responsible AI a Practical Reality
There are many different ways that companies can make responsible AI a practical reality. The right AI regulations can make a big difference, which is what responsible AI aims to do. A good AI governance framework can also provide the solution that companies are looking for.
It will take ongoing effort to ensure that there is an AI governance framework in place to deal with possible AI regulations. One of the first things organizations need to do to make practical Responsible AI reality is to focus on bias testing. Every single phase of the AI model building process needs to root out bias. Your AI algorithm should also be explainable to the general population.
Responsible AI Best Practices
It will take a companywide effort to ensure you have the best AI best practices in place for AI governance.
- One of the first things you can do is to give everyone a voice in talking about what is ethical in your implementation.
- Multiple people should review every design to ensure that it is also bias-free and ethical.
- Finally, fairness is also another issue that companies need to look into.
Realize that it is not a one-and-done process. Responsible AI is something that organizations will need to continually review and improve as time goes on.