Latest news with #HRprofessionals
Independent Singapore
2 days ago
- Business
- Independent Singapore
‘Just seeing her gives me cold sweat' — Accountant wants to quit her job after just one year because her supervisor blames her for everything that goes wrong
SINGAPORE: A 25-year-old accountant is thinking about leaving her job after just one year due to ongoing issues with her supervisor. Posting on r/askSingapore, she shared that although the job itself isn't terrible and comes with generous benefits like 20 days of annual leave, the daily interactions with her only direct supervisor have taken a toll on her mental well-being. 'My only and direct supervisor has been really hard to work with,' she wrote. 'An example being how she loves to accuse that it MUST be me messing up the printer settings when I don't receive it in my mail.' In another incident, the accountant said she was blamed for misplacing a client's cheque book, only for it to be found later on her supervisor's cluttered desk. The accountant added that, despite desperately wanting to quit, she's afraid that leaving her job so soon might affect her reputation when applying for new roles. She wrote, 'I'm worried that it will look bad in my CV that I'm changing jobs even though I stayed for a year. A friend told me that for my age group, it is very common to be job-hopping, and I shouldn't worry too much. But I would still like to get insights from HR/job recruiters if it will affect the rate of my being hired?' She ended the post by seeking advice from HR professionals and recruiters, asking if staying only a year in her current role would reduce her chances of getting hired elsewhere. 'I appreciate any feedback. I would love to take the step forward because just seeing my supervisor causes me enormous stress that I'd get cold sweat by her calling my name.' 'Better things are out there; no harm in just giving it a try!' In the comments, many assured the accountant that leaving her job after a year is not unusual, especially given the circumstances. Several users, including those who work in human resources or recruitment, explained that staying in a role for at least a year is generally seen as acceptable. One recruiter commented, 'One year is fine; your reason for leaving to be shared with your next prospective employer could simply be looking for better opportunities.' Another shared, 'HR here. If it's the start of your career or if this is the only instance, it's perfectly fine. My suggestion, however, is to start looking. And if the company you are interviewing at asks why you're leaving, say there are no active push factors, but the pull factor that attracted me to your company is (insert some random stuff).' Others shared their own experiences of quitting jobs within a year and still managing to secure better opportunities afterwards. One said, 'My peers and I have changed jobs even with less than one year tenure. Also, there are places with more than 20 days of AL. Better things are out there; no harm in just giving it a try!' In other news, a nursing student took to Reddit to express her frustration over the negative perceptions people have of her chosen career. In her post titled 'Why are nurses so poorly regarded in society despite how hard they work?', the student shared that whenever she tells someone she is studying nursing in a polytechnic, she often receives a 'judgy look.' Some even go so far as to ask whether nursing was her 'first choice.' Read more: 'Why is nursing looked down on?' Student in Singapore pushes back against tired stereotypes Featured image by Depositphotos (for illustration purposes only)
The Guardian
13-05-2025
- Business
- The Guardian
People interviewed by AI for jobs face discrimination risks, Australian study warns
Job candidates having to conduct interviews with AI recruiters risk being discriminated against if they have non-American accents or are living with a disability, a new study has warned. This month, videos of job candidates interacting with at-times faulty AI video interviewers as part of the recruitment process have been widely shared on TikTok. This article includes content provided by TikTok. We ask for your permission before anything is loaded, as they may be using cookies and other technologies. To view this content, click 'Allow and continue'. The use of AI video recruitment has grown in recent years. HireVue, an AI recruitment software company used by many employers, reported in February that, among 4,000 employers surveyed worldwide, AI use in hiring had risen from 58% in 2024 to 72% in 2025. Sign up for Guardian Australia's breaking news email Australian research published this month estimates the use is significantly lower – about 30% in Australian organisations – but expected to grow in the next five years. However, the paper, by Dr Natalie Sheard, a University of Melbourne law school researcher, warns the use of AI hiring systems to screen and shortlist candidates risks discriminating against applicants, due to biases introduced by the limited datasets the AI models were trained on. In her research, Sheard interviewed 23 human resources professionals in Australia on their use of AI in recruitment. Of these, 13 had used AI recruitment systems in their companies, with the most common tool being CV analysis systems, followed by video interviewing systems. Datasets based on limited information that often favours American data over international data presents a risk of bias in those AI systems, Sheard said. One AI systems company featured in Sheard's research, for example, has said only 6% of its job applicant training data came from Australia or New Zealand, and 33% of the job applicants in the training data were white. The same company has said, according to the paper, that its word error rate for transcription of English-language speakers in the US is less than 10% on average. However, when testing non-native English speakers with accents from other countries, that error rate increases to between 12 and 22%. The latter error rate is for non-native English speakers from China. This article includes content provided by TikTok. We ask for your permission before anything is loaded, as they may be using cookies and other technologies. To view this content, click 'Allow and continue'. 'The training data will come from the country where they're built – a lot of them are built in the US, so they don't reflect the demographic groups we have in Australia,' Sheard said. Research participants told Sheard that non-native English speakers or those with a disability affecting their speech could find their words not being transcribed correctly, and would then not be rated highly by the recruitment algorithm. This prompted two of the participants to seek reassurance from their software vendor that it did not disadvantage candidates with accents. Sheard said they were given reassurances that the AI was 'really good at understanding accents' but no evidence was provided to support this. Sign up to Afternoon Update Our Australian afternoon update breaks down the key stories of the day, telling you what's happening and why it matters after newsletter promotion Sheard said there was little to no transparency around the AI interview systems used, for potential recruits, the recruiter, or the employer. 'This is the problem. In a human process, you can go back to the recruiter and ask for feedback, but what I found is recruiters don't even know why the decisions have been made, so they can't give feedback,' she said. 'That's a problem for job seekers … It's really hard to pick where liability lies, but absolutely vendors and employers are legally liable for any discrimination by these systems.' There had yet to be a case of AI discrimination that reached the courts in Australia yet, Sheard said, with any discrimination issues needing to go to the Australian Human Rights Commission first. In 2022, the federal merit protection commissioner revealed 11 promotion decisions in Services Australia in the previous year had been overturned, after the agency outsourced the process to a recruitment specialist which used AI automated selection techniques including psychometric testing, questionnaires and self-recorded video responses. It was found that the selection process 'did not always meet the key objective of selecting the most meritorious candidates'. Sheard said the returned Albanese Labor government should look to a specific AI act to regulate the use of AI, and potentially strengthen existing discrimination laws to guard against AI-based discrimination.
Fast Company
08-05-2025
- Business
- Fast Company
The deskless workforce will benefit from digital training
There is a nationwide talent war for frontline, skilled workers, and unfortunately, too many companies are losing. Turnover among deskless workers, who account for about 80% of the workforce globally, is high, and they are notoriously difficult to train through traditional training programs. Corporate training solutions that work for someone sitting behind a desk rarely work for someone on a job site or factory floor. HR professionals cited employee engagement, retention, and recruitment as the top management challenges within the deskless workforce, according to a Society for Human Resource Management study. Unlike office workers with predictable schedules and easy access to digital tools, deskless employees are mobile and harder to reach. As a result, 79% of HR leaders cite learning and development as the biggest talent challenge for deskless teams, followed by retention and onboarding cited by 75%. Training can address each of those issues, but even when available, it's often disconnected from actual business outcomes and lacks measurable value. Why? Because training frontline workers is fundamentally different from training office-based employees. Training and onboarding in-the-field workers is complicated and complex, so many companies are slower to invest in it. Recruit, Ramp, and Retain And yet, the frontline workforce is a business-critical system. Executives love to say, 'People are our most important asset.' However, when asked what systems they use to recruit, ramp, and retain employees, most stumble, which tells you everything. The workforce isn't always treated like the strategic system it is. To connect training to business value, we need to view the entire employee journey—recruit, ramp, retain—as an integrated pipeline. Of those three stages, ramp is the most important. It's the anchor. Companies that invest heavily in ramping programs find it easier to recruit and are more successful at retaining. When you invest in frontline workers early, they stay longer. This is especially true for skilled and industrial workers. Studies show that the majority of employees say training programs positively affect their engagement, and 94% say training encourages them to stay at a company longer. In contrast, lack of career progression is one of the top reasons employees leave. So what does ramp look like for most frontline workers today? Most often it is job shadowing. There's value in that, especially when mentorship is involved, but the challenge is that it doesn't scale. Not every employee is a good trainer. As experienced workers retire, mentorship will become harder to deliver consistently, especially in industries facing labor and skills gaps. Digital Training Allows For Customization The goal, then, is to build a digital training system that can act as a mentor but can scale. Simulations have already been proven in aviation, medicine, and the military. They offer the closest thing to hands-on training and will become even more accessible as spending on technology for deskless workers increases. When digital learning is done well, it mimics great teachers by not just showing people how to do their jobs but also challenging them to understand why it's done that way. It also provides assessments, which is critical in ramping programs. A strong system meets new workers where they are, quickly understanding their current capabilities and tailoring training accordingly. Digital training also supports personalized learning plans, delivering key lessons in short, targeted bursts that can teach what's needed to improve job performance and support career advancement. Too often, training is treated as a one-size-fits-all solution without alignment to the business strategy. AI will bring even more customization to learning, making it more relevant. But to tie it back to business outcomes, companies must use data to track progress and impact and then align it to company goals. Retain Frontline Talent Companies that see real results are those that define success, design training programs that build the skills to get there, and actively measure how training improves operations. We're already seeing this investment mindset emerge in places like private equity-backed roll-ups of skilled trades companies. These firms are building standardized, scalable training systems across dozens of operating companies to drive profitability. In doing so, they're setting a model that others can follow. Winning the war for frontline talent requires a shift in thinking. Leaders need to ask themselves: Do we treat workforce development like other critical business systems? Can the knowledge gained translate to measurable business outcomes? Do we have a learning and development foundation that is connected to the business? Can our existing training system leverage the power of AI to deliver personalized, engaging training that derives even more value for employees and the company? Those who can answer yes to these questions are creating a system that recruits faster, ramps better, and retains longer, all of which help transform workforce development from a cost center into a competitive advantage.
