Did Women Really Ruin the Workplace? On Thursday, November 6, the New York published an op-ed video criticizing the effects of feminism on institutions and warning of the dangers of "toxic femininity." It briefly ran with the title "Did Women Ruin the Workplace?" I can answer that question: yes. Specifically, me--I'm the woman who ruined the workplace.

A degree in computer science used to promise a cozy career in tech. Now, students' ambitions are shaped by AI, in fields that blend computing with analysis, interpretation, and data. In the early 2010s, nearly every STEM -savvy college-bound kid heard the same advice: Learn to code . Python was the new Latin. Computer science was the ticket to a stable, well-paid, future-proof life.

Discrete choice models (DCMs) have long been used to analyze workplace location decisions, but they face challenges in accurately mirroring individual decision-making processes. This paper presents a deep neural network (DNN) method for modeling workplace location choices, which aims to better understand complex decision patterns and provides better results than traditional discrete choice models (DCMs). The study demonstrates that DNNs show significant potential as a robust alternative to DCMs in this domain. While both models effectively replicate the impact of job opportunities on workplace location choices, the DNN outperforms the DCM in certain aspects. However, the DCM better aligns with data when assessing the influence of individual attributes on workplace distance. Notably, DCMs excel at shorter distances, while DNNs perform comparably to both data and DCMs for longer distances. These findings underscore the importance of selecting the appropriate model based on specific application requirements in workplace location choice analysis.

There's Never Been a Worse Time to Be Authentic at Work Workers have been told to bring themselves to work, only to be disappointed time and time again, argues author Jodi-Ann Burey in her new book. Jodi-Ann Burey was only two weeks into her new role as an inclusion marketing manager for an outdoor retail company when she was accused of having a "race agenda." Burey, who is Black, was no stranger to workplace hypocrisy; as she sees it, the office is a petri dish where the knotty dynamics of society are concentrated. At the time of the accusation in February 2020, however, all she could do was laugh. "I was like, you knew who I was before you poached me. This is exactly what you wanted me to do," she says over Zoom.

'AI already appears to be squeezing the number of entry-level jobs in white-collar occupations.' 'AI already appears to be squeezing the number of entry-level jobs in white-collar occupations.' I n The Making of the English Working Class, the leftwing historian EP Thompson made a point of challenging the condescension of history towards luddism, the original anti-tech movement. The early 19th-century croppers and weavers who rebelled against new technologies should not be written off as "blindly resisting machinery", wrote Thompson in his classic history . They were opposing a laissez-faire logic that dismissed its disastrous impact on their lives. Photographers, coders and writers, for example, would sympathise with the powerlessness felt by working people who saw customary protections swept away in a search for enhanced productivity and profit.

This paper presents a comparative analysis of community unionism (CU) in two distinct historical and organizational contexts: the National Boot and Shoe Union (B\&S) in the 1920s and Unite Community in the 2010s--2020s. Using BERTopic for thematic modeling and cTF-IDF weighting, alongside word frequency analysis, the study examines the extent to which each union's discourse aligns with key features of CU -- such as coalition-building, grassroots engagement, and action beyond the workplace. The results reveal significant differences in thematic focus and discursive coherence. While Unite Community demonstrates stronger alignment with outward-facing, social justice-oriented themes, the B\&S corpus emphasizes internal administration, industrial relations, and member services -- reflecting a more traditional, servicing-oriented union model. The analysis also highlights methodological insights, demonstrating how modern NLP techniques can enhance the study of historical labor archives. Ultimately, the findings suggest that while both unions engage with community-related themes, their underlying models of engagement diverge significantly, challenging assumptions about the continuity and universality of community unionism across time and sector.

Digital clones--AI models that replicate a specific person--package together a few technologies that have been around for a while now: hyperrealistic video models to match your appearance, lifelike voices based on just a couple of minutes of speech recordings, and conversational chatbots increasingly capable of holding our attention. But they're also offering something the ChatGPTs of the world cannot: an AI that's not smart in the general sense, but that'thinks' like you do. Could well-crafted clones serve as our stand-ins? I certainly feel stretched thin at work sometimes, wishing I could be in two places at once, and I bet you do too. To find out, I tried making a clone of myself.

Australia must "lean in hard" to the benefits of artificial intelligence or else risk ending up "on the end of somebody else's supply chain", according to the new industry and science minister, Tim Ayres, with the Labor government planning to further regulate the rapidly evolving technology. Ayres, a former official with the manufacturing union, acknowledged Australians remained sceptical about AI and stressed that employers and employees needed to have discussions about how automation could affect workplaces. The minister said Australia had "no alternative" but to embrace the new technology and seek to become a world leader in regulating and using AI. "It's the government's job to lean into the opportunity to outline that for businesses and for workers, but also to make sure that they are confident that we've got the capability to deal with the potential pitfalls," Ayres told Guardian Australia. "I think the Australian answer has got to be leaning in hard and focusing on strategy and regulation that is in the interest of Australians."

The integration of collaborative robots (cobots) in industrial settings raises concerns about worker well-being, particularly due to reduced social interactions. Avatars - designed to facilitate worker interactions and engagement - are promising solutions to enhance the human-robot collaboration (HRC) experience. However, real-world perspectives on avatar-supported HRC remain unexplored. To address this gap, we conducted a focus group study with employees from a German manufacturing company that uses cobots. Before the discussion, participants engaged with a scripted, industry-like HRC demo in a lab setting. This qualitative approach provided valuable insights into the avatar's potential roles, improvements to its behavior, and practical considerations for deploying them in industrial workcells. Our findings also emphasize the importance of personalized communication and task assistance. Although our study's limitations restrict its generalizability, it serves as an initial step in recognizing the potential of adaptive, context-aware avatar interactions in real-world industrial environments.

This work presents a novel course titled The World of AI designed for first-year undergraduate engineering students with little to no prior exposure to AI. The central problem addressed by this course is that engineering students often lack foundational knowledge of AI and its broader societal implications at the outset of their academic journeys. We believe the way to address this gap is to design and deliver an interdisciplinary course that can a) be accessed by first-year undergraduate engineering students across any domain, b) enable them to understand the basic workings of AI systems sans mathematics, and c) make them appreciate AI's far-reaching implications on our lives. The course was divided into three modules co-delivered by faculty from both engineering and humanities. The planetary module explored AI's dual role as both a catalyst for sustainability and a contributor to environmental challenges. The societal impact module focused on AI biases and concerns around privacy and fairness. Lastly, the workplace module highlighted AI-driven job displacement, emphasizing the importance of adaptation. The novelty of this course lies in its interdisciplinary curriculum design and pedagogical approach, which combines technical instruction with societal discourse. Results revealed that students' comprehension of AI challenges improved across diverse metrics like (a) increased awareness of AI's environmental impact, and (b) efficient corrective solutions for AI fairness. Furthermore, it also indicated the evolution in students' perception of AI's transformative impact on our lives.