AI systems are deployed all the time, but it can take months or even years until it becomes clear whether, and how, they’re biased. The stakes are often sky-high: unfair AI systems can cause innocent people to be arrested, and they can deny people housing, jobs, and basic services. Today a group of AI and…
Posted by Manoj Kumar, Research Engineer, and Ekin Dogus Cubuk, Research Scientist, Google Research The task of determining the similarity between images is an open problem in computer vision and is crucial for evaluating the realism of machine-generated images. Though there are a number of straightforward methods of estimating image similarity (e.g., low-level metrics that…
“I am quitting because I’m tired,” Alex Hanna wrote on February 2, her last day on Google’s Ethical AI team. She felt that the company, and the tech industry as a whole, did little to promote diversity or mitigate the harms its products had caused to marginalized people. “In a word, tech has a whiteness…
Posted by Avi Singh, Research Scientist, and Laura Graesser, Research Engineer, Robotics at Google Robot learning has been applied to a wide range of challenging real world tasks, including dexterous manipulation, legged locomotion, and grasping. It is less common to see robot learning applied to dynamic, high-acceleration tasks requiring tight-loop human-robot interactions, such as table…
A recently passed law in New York City requires audits for bias in AI-based hiring systems. And for good reason. AI systems fail frequently, and bias is often to blame. A recent sampling of headlines features sociological bias in generated images, a chatbot, and a virtual rapper. These examples of denigration and stereotyping are troubling…
In the 1990s, if you suggested that the corner three-pointer was the best shot in basketball, you might have been laughed out of the gym. The game was still dominated largely by a fleet of seven-foot centers, most of whom couldn’t shoot from more than a few feet out from the basket. Even the game’s…
To receive The Algorithm in your inbox every Monday, sign up here. Welcome to The Algorithm! Let me introduce you to Philip Nitschke, also known as “Dr. Death” or “the Elon Musk of assisted suicide.” Nitschke has a curious goal: He wants to “demedicalize” death and make assisted suicide as unassisted as possible through technology. As…
Posted by Yi Tay and Mostafa Dehghani, Research Scientists, Google Research, Brain Team Building models that understand and generate natural language well is one the grand goals of machine learning (ML) research and has a direct impact on building smart systems for everyday applications. Improving the quality of language models is a key target for…
Posted by Ashish Thapliyal, Software Engineer, and Jordi Pont-Tuset, Research Scientist, Google Research Image captioning is the machine learning task of automatically generating a fluent natural language description for a given image. This task is important for improving accessibility for visually impaired users and is a core task in multimodal research encompassing both vision and…
In a workshop in Rotterdam in the Netherlands, Philip Nitschke—“Dr. Death” or “the Elon Musk of assisted suicide” to some—is overseeing the last few rounds of testing on his new Sarco machine before shipping it to Switzerland, where he says its first user is waiting. This is the third prototype that Nitschke’s nonprofit, Exit International, has…