AI algorithm

In the digital world, everything is powered by big data and machine learning. We are using some kind of technology in day-to-day operations routinely. Even business organizations are heavily relying on artificial intelligence to streamline growth. On the other hand, despite modernization, we are still combating an age-old issue called bias. As technology’s dominance intensifies, there are high chances of biased AI algorithms invading our digital space. Therefore, some organizations are coming up with counteractions to mitigate inequality. Companies working to reduce bias in AI algorithms are anticipated to pave the way for a better future.

Why is now the right time to address AI bias? Because we are already ripe in terms of technology adoption and are moving to a future where autonomous systems could rule the world. Stepping ahead, machine learning systems will start functioning on autonomous mode, making it especially important for AI algorithms to follow an unbiased format. However, machine learning models are trained with real-world data, which means the human actions and hatred will reflect on the datasets. If there are inherent biases in the data used to feed AI algorithms, the outcome could unleash untrustworthy and potentially harmful models. Fortunately, on the other hand, some AI models are designed specifically to detect bias and expose irrational circumstances. Therefore, many organizations are using such systems to fish out biased AI algorithm. Companies working to reduce bias in AI algorithms are expecting to unleash an equal circumstance in the digital sphere. Some of the companies are listed as follows.

Top Companies Working to Reduce Bias in AI Algorithm

AiCure

AiCure is a pharmaceutical company that moderates patients on their medication during clinical trials. The company keeps an eye on patients through their smartphones and reassures that any untaken dose of medicine is not added to the clinical trial data. 

Founded in 2011, AiCure faced an issue when it realized that its facial recognition algorithm doesn’t identify darker-skinned people. It was because of the dataset they used to train their AI algorithm. Focused mainly on fair-skinned people, the AI algorithm was failing to do its job on darker-skinned patients. Fortunately, after taking notice of the situation, the company rebuilt its AI algorithm by introducing new black faces to its visual system. With their fair initiative, AiCure was able to mitigate its bias issues. Today, with more than one million dosing interactions recorded, the company’s AI algorithm works with patients of all skin tones.

SymphonyRM

Based in Palo Alto, California, SymphonyRM found that an algorithm developed by its data science team to identify patients in need of a heart consultation was not performing accurately on Black and Asian patients. The company immediately organized and framed new ways to adjust the threshold of its model to increase outreach to those groups and planned to conduct a follow-up study to examine outcomes. 

Further, SymphonyRM developed and debated many approaches to ensure responsible and unbiased AI algorithm. They even sought external help to destroy the biased nature from the root.

Vertione

Founded by Chad Steelberg, Vertione’s signature product aiWARE is an operating system for AI. The solution helps people directly communicate with computers by transcribing the audio clips instead of adding them as an input in software and then transitioning it to hardware. 

The company is taking precautionary measures to not introduce biased AI algorithm in its functionality. To do so, Vertione is adopting a couple of simple methods. One is to train the algorithm with narrow use cases. The company believes that exposing the algorithm to a limited amount of clean data, it will keep away bias issues. Another thing is that Vertione never ignores small subsets of training data. The company thinks that it can achieve a higher degree of accuracy overall while performing horribly on certain queries.