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MIT Technology Review


Podcast: Beating the AI hiring machines

MIT Technology Review

When it comes to hiring, it's increasingly becoming an AI's world--we're just working in it. In this, the final episode of Season 2 of our AI podcast "In Machines We Trust" and the conclusion of our series on AI and hiring, we take a look at how AI-based systems are increasingly playing gatekeeper in the hiring process--screening out applicants by the millions, based on little more than what they see in your résumé. In fact, an increasing number of people and services are designed to help you play by--and in some cases bend--their rules to give you an edge. This is NOT Jennifer Strong. To wrap up our hiring series, the two of us took turns doing the same job interview, because she was curious if the automated interviewer would notice. So, human Jennifer beat me as a better match for the job posting, but just by a little bit. It got better personality scores. Because, according to this hiring software, this fake voice is more spontaneous. It also got ranked as more innovative and strategic, while Jennifer is more passionate, and she's better at working with others. Jennifer: Artificial intelligence is increasingly used in the hiring process. And these days algorithms decide whether a resume gets seen by a human, gauge personalities based on how people talk or play video games, and might even interview you. In a world where you no longer prepare for those interviews by putting your best foot forward--what does it mean to present your best digital self? Sot: Youtube clips montage: Vlogger 1: Want to know three easy hacks to significantly improve your performance on video interviews like HireVue, Spark Hire, or VidCruiter? Vlogger 2: Please do make sure you watch this from beginning to end, because I want to help you to pass your interview.


The voices of women in tech are still being erased

MIT Technology Review

And it is still the case that when we hear a woman's voice as part of a tech product, we might not know who she is, whether she is even real, and if so, whether she consented to have her voice used in that way. Many TikTok users assumed that the text-to-speech voice they heard on the app wasn't a real person. But it was: it belonged to a Canadian voice actor named Bev Standing, and Standing had never given ByteDance, the company that owns TikTok, permission to use it. Standing sued the company in May, alleging that the ways her voice was being used--particularly the way users could make it say anything, including profanity--were injuring her brand and her ability to make a living. Her voice becoming known as "that voice on TikTok" that you could make say whatever you liked brought recognition without remuneration and, she alleged, hurt her ability to get voice work.


An endlessly changing playground teaches AIs how to multitask

MIT Technology Review

They advance to more complex multiplayer games like hide and seek or capture the flag, where teams compete to be the first to find and grab their opponent's flag. The playground manager has no specific goal but aims to improve the general capability of the players over time. AIs like DeepMind's AlphaZero have beaten the world's best human players at chess and Go. But they can only learn one game at a time. As DeepMind cofounder Shane Legg put it when I spoke to him last year, it's like having to swap out your chess brain for your Go brain each time you want to switch games.


Podcast: Playing the job market

MIT Technology Review

Increasingly, job seekers need to pass a series of tests in the form of artificial-intelligence games just to be seen by a hiring manager. In this third of a four-part miniseries on AI and hiring, we speak to someone who helped create these tests, and we ask who might get left behind in the process and why there isn't more policy in place. We also try out some of these tools ourselves. This miniseries on hiring was reported by Hilke Schellmann and produced by Jennifer Strong, Emma Cillekens, Anthony Green, and Karen Hao. Jennifer: Often in life … you have to "play the metaphorical game"… to get the win you might be chasing. It's just a complicated game.. Gh - ah.. Game.." Jennifer: But what if that game… was literal? And what if winning at it could mean the difference between landing a job you've been dreaming of… or not. Increasingly job seekers need to pass a series of "tests" in the form of artificial-intelligence games… just to be seen by a hiring manager. Anonymous job seeker: For me, being a military veteran being able to take tests and quizzes or being under pressure is nothing for me, but I don't know why the cognitive tests gave me anxiety, but I think it's because I knew that it had nothing to do with software engineering that's what really got me. She asked us to call her Sally because she's criticizing the hiring methods of potential employers and she's concerned about publishing her real name. She has a graduate degree in information from Rutgers University in New Jersey, with specialties in data science and interaction design. And Sally fails to see how solving a timed puzzle... or playing video games like Tetris... have any real bearing on her potential to succeed in her field. So companies want to do diversity and inclusion, but you're not doing diversity and inclusion when it comes to thinking, not everyone thinks the same. So how are you inputting that diversity and inclusion when you're only selecting the people that can figure out a puzzle within 60 seconds.


AI voice actors sound more human than ever--and they're ready to hire

MIT Technology Review

A new wave of startups are using deep learning to build synthetic voice actors for digital assistants, video-game characters, and corporate videos.


Bats' brains predict their next move during flight

MIT Technology Review

More than a thousand species use echolocation, but after billions of years of evolution, bats' brains are especially well optimized for navigation. A new paper released today in Science suggests that as bats fly, special neurons known as place cells--located in their hippocampus, a part of the brain that controls memory--helps them process key navigational information about their position not only in the moment but in the past and future as well. "The finding is kind of intuitive, because we, at least as humans--we have the capability of thinking about where we're going to be or where we've been," says Nicholas Dotson, a project scientist at the Salk Institute and the lead author of the study. Using a combination of wireless neural data loggers and a motion-tracking system made of 16 cameras, Dotson and his coauthor Michael Yartsev, a professor of neurobiology and engineering at UC Berkeley, observed six Egyptian fruit bats in two experiments meant to record bursts of neural activity. While some of the bats randomly explored a room covered in black foam to minimize acoustic reverberations, others were given a foraging task that involved indoor feeders, and one lucky critter was even tested in both environments.


We tested AI interview tools. Here's what we found.

MIT Technology Review

After more than a year of the covid-19 pandemic, millions of people are searching for employment in the United States. AI-powered interview software claims to help employers sift through applications to find the best people for the job. Companies specializing in this technology reported a surge in business during the pandemic. But as the demand for these technologies increases, so do questions about their accuracy and reliability. In the latest episode of MIT Technology Review's podcast "In Machines We Trust," we tested software from two firms specializing in AI job interviews, MyInterview and Curious Thing. And we found variations in the predictions and job-matching scores that raise concerns about what exactly these algorithms are evaluating.


Are computers ready to solve this notoriously unwieldy math problem?

MIT Technology Review

The computer scientist Marijn Heule is always on the lookout for a good mathematical challenge. An associate professor at Carnegie Mellon University, Heule has an impressive reputation for solving intractable math problems with computational tools. His 2016 result with the "Boolean Pythagorean triples problem" was an enormous headline-grabbing proof: "Two hundred terabyte maths proof is largest ever." Now he's deploying an automated approach to attack the beguilingly simple Collatz conjecture. First proposed (according to some accounts) in the 1930s by the German mathematician Lothar Collatz, this number theory problem provides a recipe, or algorithm, for generating a numerical sequence: Start with any positive integer.


Mapping the way to climate resilience

MIT Technology Review

"We just know it's the right thing to do for our customers and--I say this from years of doing risk management-- it's good, basic risk management," says Shannon Carroll, director of global environmental sustainability at AT&T. "If all indications are that something is going to happen in the future, it's our responsibility to be prepared for that." Globally, leaders from government, business, and academia see the urgency. When citing risks with the highest impact, those surveyed listed climate action failure and other environmental risks second only to infectious diseases. AT&T is taking action with its Climate Resilience Project, using spatial data analysis and location information to tackle the complex problem of how increasingly powerful storms could affect infrastructure such as cell towers and the telecom's ability to deliver service to its customers. "Spatial analysis is this way of going beyond what we visually see," explains Lauren Bennett, head of spatial analysis and data science at Esri, a geographic information systems (GIS) company.


The future starts with Industrial AI

MIT Technology Review

Today's industrial organizations, and especially those in capital-intensive industries, stand at a crossroads for opportunity. They recognize the need to reinforce their industrial operations and complex value chains with greater resiliency, flexibility, and agility to respond to shifting market conditions. At the same time, they're investing in autonomous and semi-autonomous artificial intelligence (AI) capabilities to realize their vision of the digital plant of the future--the "Self-Optimizing Plant." Generational shifts in the workforce are creating a loss of operational expertise. Veteran workers with years of institutional knowledge are retiring, replaced by younger employees fresh out of school, taught on technologies and concepts that don't match the reality of many organizations' workflows and systems.