4 Ways Experts are Trying to Keep Bias Out of Conversational AI

Conversational AI powers the voice and text conversations that happen between computers and humans. You might have used conversational AI while choosing the perfect flowers to ship to your grandma or having Alexa create a playlist for your breakup. 

Although conversational AI is immensely useful to streamline customer experiences, every machine has its kinks. Sometimes, unintended bias can happen in the middle of these human-like interactions. Because of misrepresentation in data, not enough data, or a lack of diversity, there have been incidents where chatbots based on machine learning have used hate speech or simply recreated implicit bias. 

Bias in conversational AI can’t be removed completely any more easily than bias in life more generally, but there are plenty of ways to proactively prevent discrimination and make user experiences better. Here are four ways experts are working to keep bias out of conversational AI.

1. Keep humans Included

AI works better when human brainpower is involved. No matter how well machines work, human involvement always helps them run more smoothly.

In a way, AI chatbots are similar to children. Like parents spoon-feed their children, chatbots learn information straight from humans. Conversational AI chatbots are the product of the data they receive. So, if the team that developed the system has a bias, the chatbot will have a bias too. 

When knowledgeable humans are involved, they can assess for bias and make sure the methods work for their users. Humans can also look deeper into each case to make sure the AI is in line with ethical procedures.

2. Introduce diverse viewpoints

It’s important to hire diverse teams and test algorithms on different groups of people. If not, it will only lead to more prejudice in conversational AI. Creating a team with different races, genders, ages, cultures, disabilities, and experiences helps build a more unbiased conversational AI. These people will ask different questions and offer suggestions that aren’t one-sided. They’ll also be better equipped if there ever is a case of bias. 

3. Build case-specific chatbots

Conversational chatbots should have enough context to be ethical and specific to its users. Giving a chatbot a wider range of topics to cover can create unwanted bias in the chat, or simply more opportunities for a serious error to slip through. When chatbots are made for more detailed cases, they’ll only be used for those related tasks, and bias can be prevented. 

4. Gather better data and be open to feedback 

As you work to prevent bias in conversational AI, make sure the data you receive is interpreted carefully before your AI processes it. As you evaluate that same data, rate it for fairness and equal opportunity.

Being open to feedback is important too. Find out how conversational AI applies in the real world by getting input from a diverse group of people. Be open to the discussion along with that feedback to make sure your conversational AI is headed in the right direction. 

Once you’ve got what you need, you can create a solid plan to move forward with the valuable feedback you just received. 

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