EverythingScience

AI 'workslop' is creating unnecessary extra work. Here's how we can stop it Have you ever used artificial intelligence (AI) in your job without double-checking the quality or accuracy of its output? If so, you wouldn't be the only one. Our global research shows a staggering two-thirds (66%) of employees who use AI at work have relied on AI output without evaluating it. This can create a lot of extra work for others in identifying and correcting errors, not to mention reputational hits. Just this week, consulting firm Deloitte Australia formally apologized after a A$440,000 report prepared for the federal government had been found to contain multiple AI-generated errors. Against this backdrop, the term "workslop" has entered the conversation. Popularized in a recent Harvard Business Review article, it refers to AI-generated content that looks good but "lacks the substance to meaningfully advance a given task." Beyond wasting time, workslop also corrodes collaboration and trust. But AI use doesn't have to be this way. When applied to the right tasks, with appropriate human collaboration and oversight, AI can enhance performance. We all have a role to play in getting this right. The rise of AI-generated 'workslop' According to a recent survey reported in the Harvard Business Review article, 40% of US workers have received workslop from their peers in the past month. The survey's research team from BetterUp Labs and Stanford Social Media Lab found on average, each instance took recipients almost two hours to resolve, which they estimated would result in US$9 million (about A$13.8 million) per year in lost productivity for a 10,000-person firm. Those who had received workslop reported annoyance and confusion, with many perceiving the person who had sent it to them as less reliable, creative, and trustworthy. This mirrors prior findings that there can be trust penalties to using AI. Invisible AI, visible costs These findings align with our own recent research on AI use at work. In a representative survey of 32,352 workers across 47 countries, we found complacent over-reliance on AI and covert use of the technology are common. While many employees in our study reported improvements in efficiency or innovation, more than a quarter said AI had increased workload, pressure, and time on mundane tasks. Half said they use AI instead of collaborating with colleagues, raising concerns that collaboration will suffer. Making matters worse, many employees hide their AI use; 61% avoided revealing when they had used AI and 55% passed off AI-generated material as their own. This lack of transparency makes it challenging to identify and correct AI-driven errors. What you can do to reduce workslop Without guidance, AI can generate low-value, error-prone work that creates busywork for others. So, how can we curb workslop to better realize AI's benefits? If you're an employee, three simple steps can help. 1. Start by asking, "Is AI the best way to do this task?" Our research suggests this is a question many users skip. If you can't explain or defend the output, don't use it 2. If you proceed, verify and work with AI output like an editor; check facts, test code, and tailor output to the context and audience 3. When the stakes are high, be transparent about how you used AI and what you checked to signal rigor and avoid being perceived as incompetent or untrustworthy. Source:Phys.org @EverythingScience

Exploring the power of plants to make drugs out of sunlight Source:Phys.org @EverythingScience

'This moves the timeline forward significantly': Quantum computing breakthrough could slash pesky errors by up to 100 times Researchers have discovered a way to speed up quantum error correction (QEC) by a factor of up to 100 — a leap that could significantly shorten the time it takes quantum computers to solve complex problems. The technique, called algorithmic fault tolerance (AFT), restructures quantum algorithms so they can detect and correct errors on the fly, rather than pausing to run checks at fixed intervals. In simulations, AFT reduced the time and computational effort spent on error correction by up to 100 times while still maintaining accuracy, according to scientists at QuEra. The results, published Sept. 24 in the journal Nature, were based on tests run on a simulated neutral-atom quantum computer. Source:Live Science @EverythingScience

Identical Twins Can Have Significant IQ Differences, Study Reveals Identical twins who were raised apart may have IQ differences similar to those of total strangers, according to new research. The findings suggest that variations in IQ may be less about genetics and more about schooling. The heartbreaking separation of twin siblings is a rare occurrence, and only nine large group studies have been published to date. In the past, researchers have concluded that identical twins raised apart have many matching traits, including similar IQs, suggesting that IQ (a sign of intelligence) is largely determined by nature, not nurture. Not so fast, argue cognitive neuroscientist Jared Horvath and developmental researcher Katie Fabricant. These two have crunched the numbers again, and this time, they've included a key overlooked factor: schooling. When the researchers divided 87 twin-pairs into groups based on similar and dissimilar schooling backgrounds, they found IQ differences across the spectrum. The gaps in IQ scores grew in tandem with educational differences, the authors say, "enough to transcend specific teachers or peer groups." Twins that were raised apart and who went to significantly different schools showed IQ patterns more similar to strangers (a roughly 15-point difference). There were only 10 twin-pairs in the study with school experiences that met suitable criteria, making for a small sample size that places limits on the study's conclusions. Source:ScienceAlert @EverythingScience

Horses became gentle and easy to ride thanks to two gene mutations Horses had a huge impact on the success of many human societies. Now, scientists have found two key gene variants that helped paved the way for that equine role in human history. The pair made horses tamer and more rideable, researchers now report. Ancient horse DNA suggests modern domesticated horses came from southwestern Russia more than 4,200 years ago. This research, published in 2021, revealed where and when humans had domesticated the animals. Ludovic Orlando led that study. A molecular archaeologist, he works at the Centre for Anthropobiology and Genomics. That’s in Toulouse, France. What that work hadn’t shown was precisely what genetic changes in horses — mutations — might have led to these new traits. Orlando and a team of scientists from China and Switzerland have now done that. They analyzed horse genomes, the full set of genetic instructions making up their DNA. In all, they compared the genomes of 71 horses from a range of breeds and time periods. The team focused on 266 places in the genomes. From these, nine genes showed strong signatures of have been selected, or altered. That suggests the traits these genes produced in the horses may have been targeted by human breeders. Two of these genes appear to have been heavily selected very early in horse taming. Source:SN Explores @EverythingScience

Experimental Nanoparticle “Super-Vaccines” Stop Breast, Pancreatic, And Skin Cancers In Their Tracks A nanoparticle vaccine has shown great promise in preventing three types of cancer in mice, as well as stopping tumors from spreading when they were exposed to cancerous cells. Cancer vaccines have moved from the sci-fi dream realm into actual scientific possibility within just a few short decades. We’re not just talking about the HPV vaccine, incredible though its success has been at preventing cases of cervical cancer. A vaccine against a virus, albeit one that causes cancer, is easier to conceptualize – we get vaccinated against tons of other viruses, after all. But vaccinating against a non-infectious disease like cancer, with all its complex causes and different presentations, is much harder to wrap your head around – making this latest study perhaps even more impressive. Researchers led by a team at the University of Massachusetts Amherst have developed a nanoparticle-based vaccine that has previously been shown to shrink and clear cancerous tumors in mice. Now, they’ve demonstrated it can also work to prevent three types of cancer: pancreatic cancer, melanoma, and triple-negative breast cancer. Source:IFLScience @EverythingScience