This week in AI and Machine Learning: Plainsight shares insights at Google Cloud Next, AI powers diagnoses through speech patterns, and more.
Author’s Note
This week, Plainsight’s Co-Founder and CEO, Carlos Anchia, joined a panel of Google Cloud Partners and Product Managers at Google Cloud Next 2022 to discuss the future of computer vision applications.
Whether you attended Google Cloud Next or you’re just registering now, you can check out the full breakout session below.
And check out my playlist of must-see sessions.
Artificial Intelligence News
AI for Diagnosing Illnesses Through Speech
There are plenty of ways to diagnose an illness: Doctors might take a patient’s temperature, analyze a mucus or saliva sample, or even survey the patient on the type and severity of their symptoms. A new project funded by the National Institutes of Health (NIH) hopes to use AI to assess vocal recordings. Dr. Yael Bonsoussan, one of the project’s lead researchers, suggests everything from subtle nuances in breathing patterns to vocal cord vibrations can help doctors get to the bottom of medical trouble.
Vocal patterns are already useful for diagnosing conditions like Parksinson’s disease and researchers are hopeful their efforts could lead to vocal diagnoses for depression, cancer, and more. Research subjects are being organized in five distinct groups: mood disorders, neurological disorders, pediatric disorders, and respiratory problems. The largest ever project of its kind hopes to amass data on 30,000 patients over the next several years. Check out a summary of NIH’s ongoing research and listen to vocal samples of patients with several conditions.
Applying AI for Talent Management
A new study published in Philosophy & Technology finds that AI tools designed to reduce bias in the recruiting and hiring processes often fail to accomplish their goals. The authors conclude with a number of recommendations for making more effective use for AI-powered solutions for sourcing talent.
First, they suggest, organizations should shift their focus from individual instances of bias to the broader forces that produce inequality and biases in hiring. They also encourage HR professionals to more deeply immerse themselves in AI to ensure they fully understand the solutions they invest in. Consulting dedicated AI ethicists and policymakers can help too.
Writing for The Harvard Business Review, Jessica Kim-Schmid and Roshni Reveendhran address many of the same drawbacks to AI in talent management and offer recommendations of their own. They note that AI can be especially useful for creating attractive job listings, identifying pain points in real time, and assessing employee engagement. Getting the most out of solutions, however, will mean committing to transparency, conducting thorough research, and taking a proactive approach to managing risk.
A New Technique for Detecting Distinct Humans
Singapore’s Hyundai Motor Group Innovation Center has published a new paper outlining an object detection approach capable of distinguishing between human subjects in close proximity. Traditional approaches sometimes struggle to accurately detect distinct people who are hugging, standing in front of one another, or otherwise overlapping within an image. As a result, they mistakenly identify multiple subjects as a single object. New text-to-image solutions can also cause problems, often causing people to “melt” together.
The researchers call their approach Occlusion Copy & Paste. OC&P outperformed existing frameworks and, even better, can easily be applied to existing frameworks alongside other model-centric improvements. Read a detailed summary of the paper.
Join our Community
See you next week! Until then, keep the conversation going on Plainsight’s AI Slack Channel.
About the Author & Plainsight
Bennett Glace is a B2B technology content writer and cinephile from Philadelphia. He helps Plainsight in its mission to make vision AI accessible to entire enterprise teams.
Plainsight’s vision AI platform streamlines and optimizes the full computer vision lifecycle. From project strategy, through model deployment, and ongoing monitoring, Plainsight helps customers successfully create and operationalize vision AI applications to solve highly diverse business challenges.
