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"Shapiro said that using ChatGPT can be "great" in helping applicants "brainstorm verbs" and reframe language that can "bring a level of polish to their applications." At the same time, she said that submitting AI-generated materials along with job applications can backfire if applicants don't review them for accuracy. Shapiro said Jasper recruiters have interviewed candidates and discovered skills on their résumés that applicants said shouldn't be there or characterizations they weren't familiar with. Checking the AI-generated materials to ensure they accurately reflect an applicant's capabilities, she said, is critical if they're using ChatGPT - especially if the applicant gets hired."

"Perkins' report offers a dizzying list of data the TikTok app can access while it's running, including the device location, calendar, contacts, other running applications, wi-fi networks, phone number and even the SIM card serial number. He concludes: For the TikTok application to function properly, most of the access and device data collection is not required. This leads us to believe that the only reason this information has been gathered is for data harvesting. It is also notable that the device only needs to ask the user for permission to perform each of these actions once and then follow the user's preferences. The application however has a culture of persistent access or continuously asking for a decision reversal by the user. The hourly checking of location is also unnecessary. Finally, device mapping, external storage access, contacts and third-party applications data collection allows TikTok the ability to reimage the phone in the likeness of the original device."

"If you've been job hunting recently, chances are you've interacted with a resume robot, a nickname for an Applicant Tracking System, or ATS. In its most basic form, an ATS acts like an online assistant, helping hiring managers write job descriptions, scan resumes and schedule interviews. As artificial intelligence advances, employers are increasingly relying on a combination of predictive analytics, machine learning and complex algorithms to sort through candidates, evaluate their skills and estimate their performance. Today, it's not uncommon for applicants to be rejected by a robot before they're connected with an actual human in human resources. The job market is ripe for the explosion of AI recruitment tools. Hiring managers are coping with deflated HR budgets while confronting growing pools of applicants, a result of both the economic downturn and the post-pandemic expansion of remote work. As automated software makes pivotal decisions about our employment, usually without any oversight, it's posing fundamental questions about privacy, accountability and transparency."

"Some unemployment applicants have said that ID.me's facial recognition models fail to properly identify them (generally speaking, facial recognition technology is notoriously less accurate for women and people of color). And after their applications were put on hold because their identity couldn't be verified, many should-be beneficiaries have had to wait days or weeks to reach an ID.me "trusted referee" who could confirm what the technology couldn't."

"Admission algorithms can make or break your academic plans. A Washington Post investigation found 44 schools use prediction software to give applicants a score out of 100 for its admissions process. The score considers different aspects of a student's application from test scores, home address, transcripts, and even what websites they've visited. That's all calculated to rate how strong of a match a student is for a school."

"The first paper turns the tables on the trend for job applicants to be screened by algorithms. The researchers assigned some applicants "algorithmic writing assistance" with their CVs or covering letters to see if it influenced employers' decisions. But obviously those of us who do lots of recruiting would never be affected by such small changes… would we? I'm afraid so. Jobseekers who had the tech help were 8% more likely to get hired. Sigh."

"We submitted the grant on time. The next day, while speaking to a friend, I told him, "This week, I wrote my first ChatGPT grant." He replied that he had been doing it for months and that many other scientists are doing the same. A 2023 Nature survey of 1,600 researchers found that more than 25% use AI to help them write manuscripts and that more than 15% use the technology to help them write grant proposals. Some people might see the use of ChatGPT in writing grant proposals as cheating, but it actually highlights a much bigger problem: what is the point of asking scientists to write documents that can be easily created with AI? What value are we adding? Perhaps it is time for funding bodies to rethink their application processes."

""After cutting me off, the AI would respond, 'Great! Sounds good! Perfect!' and move on to the next question," Ty said. "After the third or fourth question, the AI just stopped after a short pause and told me that the interview was completed and someone from the team would reach out later." (Ty asked that their last name not be used because their current employer doesn't know they're looking for a job.) A survey from Resume Builder released last summer found that by 2024, four in 10 companies would use AI to "talk with" candidates in interviews. Of those companies, 15% said hiring decisions would be made with no input from a human at all."

"Toyota's Lexus rolled out an update for some of its cars, including RX350, which broke the vehicles' navigation and entertainment systems leaving them stuck in a boot loop. Lexus confirmed that the software updates are routinely pushed out via satellite to cars and that a faulty application may be to blame."

"There's an increasingly popular solution to this problem: why not let an intelligent algorithm make hiring decisions for you? Surely, the thinking goes, a computer is more able to be impartial than a person, and can simply look at the relevant data vectors to select the most qualified people from a heap of applications, removing human bias and making the process more efficient to boot."

"Security Analysis of Emerging Smart Home Applications demonstrates how Samsung's SmartThings platform may be especially vulnerable to hackers. "

"Such powerful software is still several years away from being fully developed, if at all, and raises all sorts of ethical questions. But the potential applications-such as masterfully translating foreign languages, identifying objects in photos and directing self-driving cars through busy intersections-are so compelling that technology giants like Facebook and Google Inc. are investing heavily in artificial intelligence"

"A smartphone application called Peek, Portable Eye Examination Kit, utilizes the phone's camera and can conduct visual and color field tests, lens imaging for cataracts, and retinal imaging, among other tests to detect sight impairments and diseases."

"But Lodge admits that the BYOD trend does have a number of flaws. His biggest concern? It encourages students to use technology during teaching time: "The major downside of BYOD is the potential for distraction. Students' own devices are likely to include all the applications they use on a regular basis. This cannot be controlled like it can be with computers provided by the institution.""

"Upcoming cell phone chips from Qualcomm will use artificial intelligence to block malware before it infects your phone. The chip company said on Monday that the next-generation Snapdragon 820 processor used in a variety of Android smartphones will be the first chip that uses machine learning to detect threats and privacy issues thanks to an application called Snapdragon Smart Protect." Qualcomm is trying to use artificial intelligence in a chip for smart phones. The chip will learn to detect any privacy or security issues that would usually be hard to detect.

"An Israeli company is trying to prove that augmented reality is not only the premise of video games, it can also save lives. iOnRoad is a new mobile application, developed by Picitup, that is "helping smartphone users make smarter driving decisions" by using a phone's camera and GPS."

"Unskilled manual laborers have felt the pressure of automation for a long time - but, increasingly, they're not alone. The last few years have been a bonanza of advances in artificial intelligence. As our software gets smarter, it can tackle harder problems, which means white-collar and pink-collar workers are at risk as well. Here are eight jobs expected to be automated (partially or entirely) in the coming decades. Call Center Employees call-center Telemarketing used to happen in a crowded call center, with a group of representatives cold-calling hundreds of prospects every day. Of those, maybe a few dozen could be persuaded to buy the product in question. Today, the idea is largely the same, but the methods are far more efficient. Many of today's telemarketers are not human. In some cases, as you've probably experienced, there's nothing but a recording on the other end of the line. It may prompt you to "press '1' for more information," but nothing you say has any impact on the call - and, usually, that's clear to you. But in other cases, you may get a sales call and have no idea that you're actually speaking to a computer. Everything you say gets an appropriate response - the voice may even laugh. How is that possible? Well, in some cases, there is a human being on the other side, and they're just pressing buttons on a keyboard to walk you through a pre-recorded but highly interactive marketing pitch. It's a more practical version of those funny soundboards that used to be all the rage for prank calls. Using soundboard-assisted calling - regardless of what it says about the state of human interaction - has the potential to make individual call center employees far more productive: in some cases, a single worker will run two or even three calls at the same time. In the not too distant future, computers will be able to man the phones by themselves. At the intersection of big data, artificial intelligence, and advanced

"O'Neill recounts an exercise to improve service to homeless families in New York City, in which data-analysis was used to identify risk-factors for long-term homelessness. The problem, O'Neill describes, was that many of the factors in the existing data on homelessness were entangled with things like race (and its proxies, like ZIP codes, which map extensively to race in heavily segregated cities like New York). Using data that reflects racism in the system to train a machine-learning algorithm whose conclusions can't be readily understood runs the risk of embedding that racism in a new set of policies, these ones scrubbed clean of the appearance of bias with the application of objective-seeming mathematics. "