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Imagine trying to use Alexa when you can’t hear her voice. 或者得知有人走了 ahead of you for care at the hospital because of an algorithm, when your health is worse and your skin color is different.
作为一个行业, the possibilities of artificial intelligence (AI) often make us so eager to create new 应用程序 that we sometimes forget to consider all the people who will benefit from them. Or those who will be excluded when we don’t factor the principles of diversity, equality and 包容 (DEI) within the data we use to build the 应用程序.
AI is only as good as the data you input. Recently a study showed that facial recognition could identify a white male with 99% accuracy, 但对于有色人种女性来说, 下降到35%. 为什么? Because that population was left out of the test cases during the design phase.
And in Oakland, software was piloted to predict high crime areas. But it turns out the algorithm was actually tracking areas that had a high population of minorities — regardless of crime rate.
These are examples of injustice, plain and simple, amplified by technology.
在人工智能和软件设计方面, it is absolutely critical that we think about everyone as we’re innovating. 否则, we’re guilty of perpetuating and accelerating damaging stereotypes, even if we are doing it unconsciously. The result is that we are missing out on additional benefits that AI can bring to our lives and holding back the true potential of this technology.
At 微米, we think a lot about this issue. Last year, 微米给 announced our 推进好奇号计划 to provide $1 million to leading university re搜索 groups and nonprofit organizations dedicated to social good through AI.
Sharawn康纳斯, 多元化副总裁, Equality and Inclusion (left) onstage at Techonomy 19 speaking about the importance of diversity in the workplace.
This commitment includes supporting a UCLA project that aims to identify and combat bias in AI and promoting transparency in machine learning by developing computationally rigorous methods to help identify bias. To promote stronger diversity within the AI field, we also support AI4All 和它的营地, which focus on generating interest in these fields, particularly among underrepresented groups.
And it goes beyond race and gender; we must look at all dimensions of diversity. Almost all AI assistants are voice-based, a functionality that all but eliminates the hard of hearing or deaf from using these tools. The 推进好奇号计划 is working with Rochester Institute of Technology to develop alternative AI-assisted technology that is engaging hard-of-hearing users throughout the design loop. This engagement ensures the solution really works for the people who use it.
你看到, to get quality data inputs for AI, it’s crucial that the mix of people and organizations developing these projects reflect the world we all live in. 如果我们看到美国.S. population with 7% of people with disabilities, that percentage should be mirrored in the workplace. 这就是你如何获得有价值的AI, through the diversity and 包容 of people who contribute to the design and development of the 应用程序 themselves.
But you also have to think about diversity of 认为. It’s equally important to have an inclusive environment where everyone feels comfortable sharing ideas. If you have diversity but people don’t contribute, you’re not getting the value of that diversity.
Today, we are at a tipping point, with massive AI datasets being built all around us. It is imperative that we think about our data and whether it fully represents those we want to serve and help. 要做到这一点, we must create workplaces where the best solution, 最好的创新, the best idea rises to the top — no matter where it comes from.
I’m excited to be a part of a team that is committed to building a workforce that is diverse, 平等包容. 我们绝不是完美的, but I believe the will and momentum are here, and we recognize the value that DEI provides to our culture, to our innovation and to our competitiveness. 了解更多 about diversity, equality and 包容 efforts at 微米 and read our latest DEI report.