Is it fair for a computer alone to accept or reject your job application? Welcome to the fast-growing world of AI recruitment.
A growing number of firms are using artificial intelligence to pass or fail jobseekers.
Category: robotics/AI – Page 1,753
“The world of COVID-19 is going to need more and more automation to keep people safe,” Hanson Robotics founder David Hanson said.
Hanson Robotics says more automation is needed during the pandemic. It has now started mass production of its humanoid robot, Sophia.
Circa 2020
AI can read your emotional response to advertising and your facial expressions in a job interview. But if it can already do all this, what happens next? In part two of a series on emotion AI, Jennifer Strong and the team at MIT Technology Review explore the implications of how it’s used and where it’s heading in the future. This episode was reported and produced by Jennifer Strong, Karen Hao, Tate Ryan-Mosley, and Emma Cillekens. We had help from Benji Rosen. We’re edited by Michael Reilly and Gideon Lichfield.
Systems designed to detect deepfakes—videos that manipulate real-life footage via artificial intelligence—can be deceived, computer scientists showed for the first time at the WACV 2021 conference which took place online Jan. 5 to 92021.
Additive manufacturing has proven an ideal solution for certain tasks, but the technology still lacks more traditional methods in a number of categories. One of the biggest is the requirement for post-printing assembly. 3D printers can create extremely complex components, but an outside party (be it human or machine) is required to put them together.
MIT’s CSAIL department this week showcased “LaserFactory,” a new project that attempts to develop robotics, drones and other machines than can be fabricated as part of a “one-stop shop.” The system is comprised of a software kit and hardware platform designed to create structures and assemble circuitry and sensors for the machine.
A more fully realized version of the project will be showcased at an event in May, but the team is pulling back the curtain a bit to show what the concept looks like in practice. Here’s a breakdown from CSAIL’s page:
Human-Autonomy Interaction, Collaboration and Trust — Dr. Julie Marble, JHU Applied Physics Laboratory (APL)
Dr. Julie Marble is a senior scientist at the Johns Hopkins University Applied Physics Laboratory (JHUAPL) leading research in human-autonomy interaction, collaboration and trust.
Dr. Marble earned her PhD in Human Factors/Cognitive Psychology from Purdue University. After graduating from Purdue University, she joined the Idaho National Laboratory (INL), one of the national laboratories of the United States Department of Energy involved in nuclear research, first in the Human Factors group and then the Human and Robotic Systems group.
Following INL, she joined Sentient Corporation, where as CEO she led a DARPA Broad Agency Announcement BAA on Neuro-Technology for Intelligence Analysts and led research on to develop an intelligent decision aid to perform just-in-time maintenance on Navy helicopters.
Dr. Marble then worked as a Senior Scientist at the US Nuclear Regulatory Commission leading international and US studies on Human-Reliability Analysis methods in this vital domain and related to this, she is internationally recognized for her work, and is co-author of the SPAR-H method (Standardized Plant Analysis Risk Human Reliability Analysis), the most commonly used method of human reliability analysis in the US. She is also co-developer of the Cultural Affective Model, which integrates cultural impacts into human reliability in order to predict operator behavior.
In the past few years, researchers have turned increasingly to data science techniques to aid problem-solving in organic synthesis.
DARPA’s Robotic Autonomy in Complex Environments with Resiliency — Simulation (RACER-Sim) project is seeking innovations in technologies that bridge the gap from simulation to the real world and significantly reduce the cost of off-road autonomy development. DARPA invites proposals for promising solutions that support these goals.
DARPA’s TRAnsformative DESign (TRADES) program, which began in 2017, set out to develop foundational design tools needed to explore the vast space opened by new materials and additive manufacturing processes commonly called 3D printing. The program recently concluded having successfully developed new mathematics and computational techniques, including artificial intelligence and machine learning, that will allow future designers to create previously unimaginable shapes and structures of interest to defense and commercial manufacturing.
DARPA has executed contract options to continue the Manta Ray project that began in 2020. The effort seeks to demonstrate innovative technologies allowing payload-capable unmanned underwater vehicles (UUVs) to operate on long-duration, long-range missions in ocean environments. The three prime contractors will be Northrop Grumman Systems Corporation, Martin Defense Group, LLC (formerly Navatek, LLC), and Metron, Inc.