Imagine that your company’s HR director is able to analyze an AI’s model outcome that shows patterns on employee social media preferences, and not only that, but is also able to identify groups of people being left out because of race, sexual preference or any type of social diversity? Great, right? 

Instead of making this blog post negative, I want to shift your mindset to find solutions for current issues, and not complaining. I want to help individuals make use of technology for good, when everything else seems to be failing.  

So with that in mind, let’s dig in. Here are a few ways AI can help control racism.

Models to identify inclusivity

By using data from email and social media messaging within a company, departments can identify behavioral patterns, as well as audience clusters. By doing this, companies are able to pin point clusters of people who may be subject to discrimination among specific groups, and statistically measure if race is the reason behind it. 

This statistical level of measure is more accurate than human-made reports due to the fact that its accuracy is based on real data, while self-made reports carry biased accounts of information. Why? Because humans typically describe themselves as non racial people, even though they are. And when they are, they think they are not showing it, which explains why statically, the number of people who answer “no” to the question “are you a racist?”, is far higher than the number of actual racists.

Monitor bullying with insights

If these were different times, we would have to assign someone to go over every single email, chat and social media post to identify words used to bully others. Thankfully, running a simple data pipeline in minutes can do just that. By monitoring employee language and running a model with this data, organizations can find discriminatory or disrespectful words being used by them. This granular data provides insights into a company’s health in terms of inclusivity and it can serve as a powerful tool to create resources and initiatives to help build a diversified culture.

Rating humans?

Imagine if we could use a prospective employee’s online history or rating, made up entirely from their actions online. A set of algorithms can be trained to identify people’s digital history into a numerical estimate of for example, their willingness to interact with others, tolerance, leadership, empathy, etc. Sometimes people are just racist and apathetic, leaving the need to even perform these types of tests out of the question. The same way we have standards when meeting someone new, we instantly turn to that person’s social media profiles to see a historical story of who they are, leaving us with the necessary information to determine if he/she is someone who shares our same values, morals, empathy, etc. Today, hiring managers have to follow their gut when hiring a prospective employee. And even though they may try to leave out preconceived notions, subjectivity or bias in their decision making process, an AI algorithm can most likely do it better. This doesn’t mean AI would replace their job, but it can enhance it, by providing quantitative averages of a person’s behavior through time, thanks to a collection of their comments on social media, Amazon purchase ratings, tv preferences, etc. Hell this could even be the end of social media trolls, being that their modus operandi is behind a screen, until they have to face the real-world where they make sure kindness is written on their forehead. 

So, the outcome from a hiring process aided by AI, can assess a person’s digital history, with a quantitative rating, predicting whether that person is a good fit, how often they can display a specific behavior and a predictive analysis of his/her performance.

So what are companies waiting for? Like we have said before, AI will not replace humans, it will augment their capabilities. So if humans decide they want to do good in the world, AI will only help augment that. It may sound as a cliche, but change starts from within, and companies can start by setting an example from the bottom all the way up, by promoting equality, inclusivity and ethics.