Artificial Intelligence Must Be Built On Human Diversity

Last updated: 05-24-2019

Read original article here

Artificial Intelligence Must Be Built On Human Diversity

One of the most important yet overlooked aspects of artificial intelligence (AI) is that it’s not intended to replace human brain power. In fact, current and future AI is best conceptualized as augmented intelligence. In this sense, the most successful AI supplements human intellect in a marriage of art and science, wherein the science component leverages current computing technology to facilitate the art of human decision making.

An easy way to imagine this concept is to consider the art and science of cooking. In this analogy, AI would be used to quickly retrieve, accurately measure and uniformly prepare ingredients, freeing the chef to focus on creating and executing their own artful recipe. Very few – if any – people would want to eat a dish entirely devised by a computer. Flavor is too nuanced and inextricable from human experience to imagine technology usurping the role of a fine chef in the foreseeable future.

If AI relies on human ability, then, just like the most popular restaurant will appeal to the most diners, successful applications must work for the overwhelming majority of people around the world. In this vein, employing diversity in AI and the tech industry as a whole isn’t just a virtue signal or a sociopolitical nicety; it’s an essential data-driven method for building the most viable product in an ever-growing sea of competitors.

An individual company’s most important measure of diversity depends on its particular product and target market. Often, these crucial diversity markers are hard to detect. So the process of diversifying should begin from the ground up; the more varied input you receive, the better you’ll be able to create the most consumable user experience with the highest quality results.

Diversity Goes Beyond Gender And Ethnicity

When YouTube released an early version of its video uploading app for iOS,it was surprisedto see that up to 10% of its videos were uploaded upside-down. The whole design team scratched their heads and wondered what could have gone so wrong with their product. Eventually, they realized that the percentage of upside-down videos correlated with the percentage of people in the general population who are left-handed and tend to hold their phones 180 degrees differently than people who are right-handed.

YouTube’s mistake was assembling almost entirely right-handed teams to develop and test its app. The lesson to learn from this case is that, while women and ethnic minorities are most substantially underrepresented in tech – even for industry giants likeFacebookandGoogle– it can be even easier to overlook other points of diversity that are less obvious but just as, if not more, important to the functionality of your product.   

A great litmus test for determining whether or not a technology is accessible to the broadest user base is to ask yourself whether or not your parents could use it. By streamlining your product so that it’s flexible and adaptable to a wider audience, you’re improving its efficiency for all of your users. Because of this principle, it’s important not to limit design input and decision making to your design team. Your sales and marketing teams may be less tech savvy, but their design feedback is just as important. If a particular feature is too confusing or not incentivizing enough for the general user, it might be time to go back to the drawing board.

The goal with technology – especially AI  – is to create a fast and seamless user experience. If you can accomplish a function in two clicks, why would you design a system that requires three clicks? Your inexperienced testers are some of your most valuable assets when it comes to developing a product people will come to know as well as the backs of their hands.

Assume You Don’t Know Your Own Biases

It can be difficult to face the fact that none of us fully understands our own biases, despite our best intentions. But biases are a part of the human experience and are so deeply ingrained in each of us that we usually need outside input just to identify our own limiting thought patterns. Leaders in tech and AI are often educated and trained in such homogeneous environments that they can’t fully imagine what a truly diverse work environment might look like on their own.

It’s impossible to understand what is not being heard. Diversifying your workforce requires a huge push to seek those unheard voices and go out of your way to understand as many pain points from as many perspectives as possible, with the underlying assumption that you don’t know anything about someone else’s experience until you ask.

Diversifying your company’s culture must be a continuous collaborative effort. To create a flourishing work ecosystem, leaders should focus less on hiring culture “fits” and more on hiring culture “contributors.” True diversity runs deeper than creating mainstream technology; your customers also care about every aspect of your company culture, from marketing to customer service. When every member of your team is valued as their own unique cultural ambassador, diversity will begin to run through the blood of your organization.

Technology has a long way to go before achieving a measurable level of diversity. We’ll know we’ve achieved equitable representation when we’ve stopped talking about it. Until then, we need to talk about diversity – at every possible opportunity.

One of the most important yet overlooked aspects of artificial intelligence (AI) is that it’s not intended to replace human brain power. In fact, current and future AI is best conceptualized as augmented intelligence. In this sense, the most successful AI supplements human intellect in a marriage of art and science, wherein the science component leverages current computing technology to facilitate the art of human decision making.

An easy way to imagine this concept is to consider the art and science of cooking. In this analogy, AI would be used to quickly retrieve, accurately measure and uniformly prepare ingredients, freeing the chef to focus on creating and executing their own artful recipe. Very few – if any – people would want to eat a dish entirely devised by a computer. Flavor is too nuanced and inextricable from human experience to imagine technology usurping the role of a fine chef in the foreseeable future.

If AI relies on human ability, then, just like the most popular restaurant will appeal to the most diners, successful applications must work for the overwhelming majority of people around the world. In this vein, employing diversity in AI and the tech industry as a whole isn’t just a virtue signal or a sociopolitical nicety; it’s an essential data-driven method for building the most viable product in an ever-growing sea of competitors.

An individual company’s most important measure of diversity depends on its particular product and target market. Often, these crucial diversity markers are hard to detect. So the process of diversifying should begin from the ground up; the more varied input you receive, the better you’ll be able to create the most consumable user experience with the highest quality results.

Diversity Goes Beyond Gender And Ethnicity

When YouTube released an early version of its video uploading app for iOS,it was surprisedto see that up to 10% of its videos were uploaded upside-down. The whole design team scratched their heads and wondered what could have gone so wrong with their product. Eventually, they realized that the percentage of upside-down videos correlated with the percentage of people in the general population who are left-handed and tend to hold their phones 180 degrees differently than people who are right-handed.

YouTube’s mistake was assembling almost entirely right-handed teams to develop and test its app. The lesson to learn from this case is that, while women and ethnic minorities are most substantially underrepresented in tech – even for industry giants likeFacebookandGoogle– it can be even easier to overlook other points of diversity that are less obvious but just as, if not more, important to the functionality of your product.   

A great litmus test for determining whether or not a technology is accessible to the broadest user base is to ask yourself whether or not your parents could use it. By streamlining your product so that it’s flexible and adaptable to a wider audience, you’re improving its efficiency for all of your users. Because of this principle, it’s important not to limit design input and decision making to your design team. Your sales and marketing teams may be less tech savvy, but their design feedback is just as important. If a particular feature is too confusing or not incentivizing enough for the general user, it might be time to go back to the drawing board.

The goal with technology – especially AI  – is to create a fast and seamless user experience. If you can accomplish a function in two clicks, why would you design a system that requires three clicks? Your inexperienced testers are some of your most valuable assets when it comes to developing a product people will come to know as well as the backs of their hands.

Assume You Don’t Know Your Own Biases

It can be difficult to face the fact that none of us fully understands our own biases, despite our best intentions. But biases are a part of the human experience and are so deeply ingrained in each of us that we usually need outside input just to identify our own limiting thought patterns. Leaders in tech and AI are often educated and trained in such homogeneous environments that they can’t fully imagine what a truly diverse work environment might look like on their own.

It’s impossible to understand what is not being heard. Diversifying your workforce requires a huge push to seek those unheard voices and go out of your way to understand as many pain points from as many perspectives as possible, with the underlying assumption that you don’t know anything about someone else’s experience until you ask.

Diversifying your company’s culture must be a continuous collaborative effort. To create a flourishing work ecosystem, leaders should focus less on hiring culture “fits” and more on hiring culture “contributors.” True diversity runs deeper than creating mainstream technology; your customers also care about every aspect of your company culture, from marketing to customer service. When every member of your team is valued as their own unique cultural ambassador, diversity will begin to run through the blood of your organization.

Technology has a long way to go before achieving a measurable level of diversity. We’ll know we’ve achieved equitable representation when we’ve stopped talking about it. Until then, we need to talk about diversity – at every possible opportunity.


Read the rest of this article here