No wonder, Artificial Intelligence is the future. We've seen its application in possibly every field now. The problem isn't with the technology, it is with the biasness that goes in, says Timnit Gebru. She goes on to add that it is built in a manner that replicates the white work force that's mostly men-dominated making it. Right from her first lecture in Spain which is by far the world's most important conference on AI till date, she has seen a vast difference in the number of men and women, obviously men being dominant in number.

Facial recognition systems from large tech companies often incorrectly classify black women as male -- including the likes of Michelle Obama, Serena Williams and Sojourner Truth. That's according to Joy Buolamwini, whose research caught wide attention in 2018 with "AI, Ain't I a Woman?" a spoken-word piece based on her findings at MIT Media Lab. The video, along with the accompanying research paper written with Timnit Gebru of Microsoft Research, prompted many tech companies to reassess their facial recognition data sets and algorithms for darker and more female-looking faces. "Coded Bias," a documentary directed by Shalini Kantayya which premiered at the Sundance Film Festival in late January, interweaves Buolamwini's journey of creating the Algorithmic Justice League, an advocacy organization, with other examples of facial recognition software being rolled out around the world -- on the streets of London, in housing projects in Brooklyn and broadly across China. Jennifer 8. Lee, a journalist and documentary producer, caught up with Joy Buolamwini and Shalini Kantayya in Park City, Utah after the premiere of Coded Bias.

Artificial intelligence has already started to shape our lives in ubiquitous and occasionally invisible ways. In its new documentary, In The Age of AI, FRONTLINE examines the promise and peril this technology. AI systems are being deployed by hiring managers, courts, law enforcement, and hospitals -- sometimes without the knowledge of the people being screened. And while these systems were initially lauded for being more objective than humans, it's fast becoming clear that the algorithms harbor bias, too. It's an issue Joy Buolamwini, a graduate researcher at the Massachusetts Institute of Technology, knows about firsthand. She founded the Algorithmic Justice League to draw attention to the issue, and earlier this year she testified at a congressional hearing on the impact of facial recognition technology on civil rights. "One of the major issues with algorithmic bias is you may not know it's happening," Buolamwini told FRONTLINE.

I experienced this firsthand, when I was a graduate student at MIT in 2015 and discovered that some facial analysis software couldn't detect my dark-skinned face until I put on a white mask. These systems are often trained on images of predominantly light-skinned men. And so, I decided to share my experience of the coded gaze, the bias in artificial intelligence that can lead to discriminatory or exclusionary practices. Altering myself to fit the norm--in this case better represented by a white mask than my actual face--led me to realize the impact of the exclusion overhead, a term I coined to describe the cost of systems that don't take into account the diversity of humanity. How much does a person have to change themselves to function with technological systems that increasingly govern our lives? We often assume machines are neutral, but they aren't.

Joy Buolamwini is a poet of code on a mission to show compassion through computation. As a graduate researcher at the MIT Media Lab, she leads the Algorithmic Justice League to fight coded bias. Her research explores the intersection of social impact technology and inclusion. In support of this work, Buolamwini was awarded a grant as the Grand Prize winner of a national contest inspired by the critically acclaimed film Hidden Figures, based on the book by Margot Lee Shetterly. As a technologist, I have always been hopeful about the potential of artificial intelligence to improve the lives of individuals around world.

There is growing concern that many of the algorithms that make decisions about our lives - from what we see on the internet to how likely we are to become victims or instigators of crime - are trained on data sets that do not include a diverse range of people. The result can be that the decision-making becomes inherently biased, albeit accidentally. Try searching online for an image of "hands" or "babies" using any of the big search engines and you are likely to find largely white results. In 2015, graphic designer Johanna Burai created the World White Web project after searching for an image of human hands and finding exclusively white hands in the top image results on Google. Her website offers "alternative" hand pictures that can be used by content creators online to redress the balance and thus be picked up by the search engine.