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Tech News
Diogo Machado of consultancy Technopolis tested OpenAI's GPT-4o on 139 real grant proposals submitted to Austria's Science Fund in 2021, asking it to pick the better of each pair. The model matched human reviewers' funding decisions 60% of the time, but was notably less likely than humans to back proposals rated high for novelty, according to the study published in Scientometrics.
An analysis examines how artificial intelligence is reshaping exhaustion and satisfaction at work differently for women than for men, citing occupational segregation, differing task assignments within organizations, and unequal evaluation of similar work. The piece identifies five positive effects and eight negative effects of AI specifically on women's work experiences.
The article describes a cognitive bias known as 'the curse of knowledge,' in which deep expertise and strong conviction about an issue actually make someone worse at persuading others. This happens because experts struggle to imagine what it's like not to know what they know, distorting how they communicate with less-informed audiences. The piece draws on findings from behavioral economics and neuroscience to explain the phenomenon and offers an alternative approach to persuasion.
New research cited in the report finds that women perceived as highly intelligent tend to face worse treatment at work, while men with similar cognitive ability do not experience the same penalty. The findings point to an unconscious bias affecting how competence is perceived and rewarded differently by gender. The report illustrates this with the experience of sales veteran Sara Winslow, who said conditions grew uncomfortable after nearly 20 years in her field.
Researchers at the University of Limerick had 189 participants interact with male and female-presenting AI assistants in a virtual reality office, dividing real money as payment for completed tasks. The female-presenting agent, "Johanna," received 10.25 percent less pay than the identical male-presenting agent, "Johan," and was also rated as less human-like, according to the study published in Proceedings of the ACM on Human-Computer Interaction.
A technical explainer breaks down a widely used pattern in which a random 64-bit integer is reduced via the modulo operator to select among a fixed number of choices. It shows mathematically that when the number of choices does not evenly divide the range of the random number generator, some choices end up more likely than others, breaking the assumption of equal probability.
Three attendees died at the 2026 Burning Man festival, the highest number recorded in the event's history. A statistical review comparing this figure to age-adjusted US mortality rates found that roughly five deaths would be expected among a similarly sized, similarly aged population, meaning three deaths falls within normal statistical variation.
Researchers Liu, Lee and Bai ran a large between-subjects experiment where participants wrote hiring evaluations of resumes from a 'male' and 'female' applicant using an LLM autocomplete tool. When suggestions countered gender stereotypes, the female candidate's perceived competence and salary offers rose to match the male candidate's, but she was rated less likable, and the male candidate remained the overall favorite. Participants largely didn't notice the stereotype manipulation, focusing instead on the writing tool's usefulness.
A longtime WIRED writer and editor published a personal essay recounting a 17-year career marked by repeated instances of sexism, including being paid less than a male predecessor, having her parenting fitness questioned by bosses, and working at a publication where men appeared on 70 covers versus four for women. She traces her discomfort with some men in the industry back to her early days interning at WIRED in 2009, when the newsroom lacked female editors and reinforced narratives crediting men as the primary innovators in tech.
An Entrepreneur commentary argues that the backlash over Google's Gemini AI producing biased outputs was wrongly dismissed as a mere technical glitch. The author contends that because AI models learn from human-generated data, they inherit the assumptions and blind spots of that data, and scaling such systems only amplifies those flaws. The piece stresses that any business deploying AI tools—regardless of whether it built the model—inherits this bias risk.
A leadership commentary argues that the popular advice to treat all team members identically is misguided, even though it stems from good intentions around avoiding bias and favoritism. Instead, it suggests leaders should adapt their approach based on each person's unique circumstances, skills, and needs.
Commentary highlights a common pattern in success stories: high achievers frequently emphasize the hardships and risks they overcame while leaving out the financial cushions, connections, or circumstances that made those risks survivable in the first place. Audiences consume these narratives through books, articles, and social media hoping to extract a replicable formula for success.