It's pronounced Diane. I do data architecture, operations, and backend development. In my spare time I maintain Massive.js, a data mapper for Node.js and PostgreSQL.
As far as I understand it facial recognition technology is roughly at the party-trick level, able to guess not quite as well as humans can, and we ourselves are hardly infallible. Algorithms so far have also tended to display training bias and are worse at categorizing women and people of color, to say nothing of trans and gender-nonconforming people. It's completely unacceptable for something this important, but to my point elsewhere no automated general-purpose solution is acceptable for what fundamentally isn't a technical problem.
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As far as I understand it facial recognition technology is roughly at the party-trick level, able to guess not quite as well as humans can, and we ourselves are hardly infallible. Algorithms so far have also tended to display training bias and are worse at categorizing women and people of color, to say nothing of trans and gender-nonconforming people. It's completely unacceptable for something this important, but to my point elsewhere no automated general-purpose solution is acceptable for what fundamentally isn't a technical problem.