Founded by Patricia Scanlon in 2013, Dublin edtech SoapBox Labs uses AI and deep learning to develop voice recognition tech for kids.
SoapBox Labs, the Dublin-based company that makes voice technology for children, has been recognised for its work in identifying and mitigating racial bias.
It is the first edtech company to receive the Prioritizing Racial Equity in AI Design product certification.
This independent certification was provided by nonprofit Digital Promise, which was established by the US Congress in 2011 to develop research, practice and technologies that drive education equity and give all children a level playing field in learning.
The Edtech Equity Project, another US-based undertaking that aims to combat racial bias in education technologies, was the co-provider of the certification.
Founded in 2013 by former Bell Labs researcher Dr Patricia Scanlon, SoapBox Labs creates, builds and innovates around children’s speech, designing algorithms and using deep learning to develop accurate and safe voice technology for kids as young as three.
“There is so much potential for voice-enabled learning to help educators and young students, but to unlock that potential the voice-enabled products we use in the classroom must be accurate and treat all kids’ voices equally, regardless of accent, age, race or socioeconomic background,” said Dr Martyn Farrows, who took over from Scanlon as CEO last year.
Vic Vuchic, chief strategy officer at Digital Promise, said that the certification aims to help educators and learners find products that are committed to implementing best practices and focused on making sure AI works for learners from different backgrounds.
“AI has tremendous promise to impact learning, especially for supporting teachers and learners who are furthest from opportunity,” he added. “That said, AI can have bias that impacts certain populations disproportionately.”
Earlier this year, Scanlon – who currently serves as chair at SoapBox Labs – was appointed by the Government as Ireland’s first AI ambassador.
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