On April 1, UT Austin's Machine Learning Lab held its inaugural public lecture, "AI For Accurate and Fair Imaging" with Alex Dimakis. The talk covered recent research into bias in AI imaging algorithms. In 2020, a deep learning generative model with groundbreaking performance was posted on the web. The model could turn low-resolution images to high-quality photos. A user uploaded a low-resolution image of President Obama and obtained an image that is now referred to as'White Obama'.

Researchers at the University of Texas at Austin are leading the way when it comes to fine-tuning the accuracy of artificial intelligence. UT's Machine Learning Lab held a public lecture Friday titled, "AI for Accurate and Fair Imaging." Researchers with the lab's Institute for Foundations of Machine Learning (IFML) have been working to improve the algorithm that in 2020 produced an internet-famous image of former President Barack Obama, dubbed "White Obama." AI that was meant to enhance a pixelated, low-resolution photo of the 44th president instead transformed him into a white man. "Even though it looked like a good image, a high resolution, realistic image of a person, it had a bias," said Alex Dimakis, IFML co-director.

UT's Machine Learning Lab held a public lecture Friday titled, "AI for Accurate and Fair Imaging."

Researchers with the lab's Institute for Foundations of Machine Learning (IFML) have been working to improve the algorithm that in 2020 produced …