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TikTok has been abuzz with the workplace trend task-maskingthat is, making yourself look busy so that your boss thinks youre hard at work. Cue behaviors like pounding hard on the keyboard, always keeping your status to active, or walking around the office with your laptop and looking like you have somewhere to be when you dont. Its all show. Its all performance, one TikTok user posted. They could be typing a thousand words a minute, but really be typing nothing, posted another. Some argue that its backlash against return-to-office policies: Many of these employees, especially Gen Z, feel like their presence doesnt equal productivity, a TikTok user said. And crucially, its not just about laziness, wrote another, arguing the pressure to look busy could actually be a sign of overwhelm. The term has come to be associated with Gen Z on social media, but in reality, the act (and art) of looking busy has been around for decades. Task-masking is the digital equivalent of shuffling papers, says employee coach and attorney Theresa DAndrea, known as That Work Girl, whos also discussed the trend on TikTok. Its an employer’s market right now to get a job, so people feel like they have to be busier than usual in order to keep their jobs. Nearly half (48%) of managers are concerned about employees who fake their productivity on the joband not without reason. That’s because 37% of managers and 32% of non-managers themselves admit to such fauxductivity, or trying to appear busy even when theyre not, according to a 2024 survey of 3,000 full-time employees in the U.S., U.K., and Ireland by Workhuman, an HR software company. Thats not good for employeesor companies. Such pressure to look busy can lead to burnout and inefficiencies, DAndrea says. Rampant task-masking may be a sign of workflow or cultural issues that management needs to address. And it may be an act of defiance for some, but a scrambling to prove worth for others. If youre feeling the pressure to look busy to show your boss how important you are, try these tactics instead of pretending to answer emails during the next all-hands meeting. Get clear about whats important, and prioritize ZipRecruiter career expert Sam DeMase says that in order for employees to truly add value, they need to understand the metrics used for success by both their supervisors and the company. You just need to focus on doing work that actually moves the needle, she says. DeMase suggests asking your boss questions to get clarity: How is success defined for this project? How does this project serve the companys goals for 2025? Know your core strengths and communicate those. DAndrea agrees. Instead of responding to every text, email, and communication platform notification immediately in an attempt to look busy, focus on what matters. Thats especially true after youve gotten a sense of what your boss and the organization value. Maybe even help your boss put together a KPI [key performance indicators] dashboard to track the performance of the team if your boss doesn’t already have something like that, says Korn Ferry senior client partner Maria Amato. I would be delighted if someone on my team did that. Keep learning Instead of tackling a task just for the sake of crossing it off the to-do list, keep learning where you can, says workplace culture expert Marissa Andrada. Work on understanding more about the company and its culture and values. If you get the context of how the work that you’re doing fits in [to the team and values]why it’s importantthen you can show, Here’s what I think about it, she says. Not only does this give you a better perspective on the work youre doing, but it can also help frame your work as more essential to your team (and boss). Its making your manager be successful by delivering on time and on point, she adds. It replaces the performative busywork of task-masking with strategic thinking that demonstrates real value. Taking on stretch roles or additional projects can help you keep learning, too. However, Amato cautions that its important to understand the culture of your company and the nature of your supervisor: Dont make it seem like you are trying to get away or are not interested in what you’re currently doingnot wanting to pay your dues, for example, in your current role. Document your wins DeMase suggests keeping a weekly log of your progress and wins, such as meaningful contributions to meetings, goal completion, positive feedback, project milestones, and processes you improve along the way. She adds that documenting your successes can also keep you motivated in your job. Amato says what you do with that information depends, again, on the culture of your organization and team. You might tell your supervisor that youve collected some data on your performance, and ask whether they would like you to share the information with them. Your boss may say, Oh, I would love to see that as it comes in. Just send it to me each and every time. But if they haven’t actually asked for [the info], it could be sort of like spamming your boss, she adds. We need to move away from busyness bringing value, DAndrea says. By getting more clarity about your role, reconnecting with your works meaning, and documenting your wins, you can add value and get more satisfaction. Those are payoffs that marching around the office with an open laptop simply cant deliver.
Category:
E-Commerce
Halloween candy shoppers who bought Reese’s pumpkin-shaped candy said they felt tricked when the picture on the outside packaging didn’t exactly match the treat inside. They were so upset, in fact, that they filed a lawsuit in late 2023 seeking $5 million in damages. Now a judge has dismissed their claims. At issue is Reese’s Peanut Butter Pumpkins, whose wrappers show an image of a pumpkin-shaped candy with a jack-o’-lantern face carved into the chocolate outer layer. In reality, the chocolate inside is faceless. In a class-action suit filed in the U.S. District Court in the Southern District of Florida, plaintiffs claimed Reese’s candy wrappers were deceptive. According to court documents, plaintiffs thought “the product contained a cute looking carving of a pumpkin’s mouth and eyes as pictured on the product packaging” and said they would not have made the purchase had they known the chocolates would not actually feature those decorative details. [Images: USDC/Middle District of Florida] Reese’s maker the Hershey Co. didn’t buy it. The confectioner noted the Halloween-themed packaging also included images of uncarved pumpkin chocolates and a disclaimer reading “decorating suggestion” to indicate the carvings were an idea to try yourself. The class-action suit claimed the “decorating suggestion” disclaimer was printed in tiny letters on the back and thus inadequate, but a judge didn’t agree and wrote that these consumers ultimately got what they were after: edible candy. “Plaintiffs paid for a consumable good, and in return, they received a delicious, edible Reese’s product,” Judge Melissa Damian wrote in her order granting a motion to dismiss on September 26. “Plaintiffs have failed to allege facts demonstrating a concrete injury.” It’s common for packaged foods to include disclaimers like “enlarged to show texture” and “product may not appear exactly as shown” for exactly this reason. No, your Cheerios aren’t actually that big, and no, your Reese’s pumpkin-shaped peanut butter cup doesn’t come pre-carved. For Hershey, which accounts for some 36% of the U.S. chocolate market, according to PitchBook data, these disclaimers are a way to guard against frivolous lawsuits when the company wants to use something other than ultrarealistic product images on its packaging. Like a box of cake mix that shows a picture of a finished cake on the outside, the Reese’s wrapper wasn’t showing what the candy looked like upon opening it, but what it could look like after some DIY carving. For those who can’t bear to eat a pumpkin Reeses without a jack-o-lantern grin, the message here is clear: You’re better off with a toothpick and some creativity than a multimillion-dollar lawsuit.
Category:
E-Commerce
Thinking forward is an automatic process. Cause, then effect. Input, then output. A to B. It feels logicaland normal to start with a conclusion, then find justification around it.But we can always take our thinking a step further. Sometimes, the best way to get the answers you want is to think backwards. Its called mental inversion. Turn the whole thinking process upside down. As the great algebraist Carl Jacobi said, Invert, always invert. Put another way, What would guarantee I fail at X?” is a better question than How do I achieve X? Most people focus on the obvious process because the brain doesnt like to think through ugly pitfalls. Starting from B to A helps you avoid the results you dont want. Its one of the most powerful tools I use to think clearly. To turn your decision-making process upside down, start from the back. Thinking backwards works because it forces you to reflect on what may be missing. The human brain is wired to save energy. It wants quick answers. Slowing down to see the full picture helps you cover all the basics of your decision-making process. Inversion helps you ask better questions. It can improve your clarity. Psychology research backs this up. A study in Cognitive Science showed that framing problems in reverse helps people make fewer errors in judgment. It works because it breaks default thinking patterns. It slows you down just enough to think more deliberately. The antidote to mental fog Clarity disappears in abstraction. If I try to think through every possible positive outcome, I get overwhelmed. But if I ask, Whats the dumbest mistake I could make here? I suddenly see the risk clearly. When I want to be productive, I dont just make a to-do list. I make a not-to-do list. Thats mental inversion. It opens up a whole perspective Im missing. Taoist philosopher Lao Tzu has said, To attain knowledge, add things every day. To attain wisdom, remove things every day. When I write, I dont just think about everything I should include. I also look for what to cut. What confuses the reader? What slows them down? I try to remove what makes the post unreadable. And try to get rid of that. Inversion works because subtraction is often more effective than addition. It applies to almost every area of life.In his book, The Bed of Procrustes, author Nassim Taleb writes, Knowledge is subtractive, not additivewhat we subtract (reduction by what does not work, what not to do), not what we add (what to do). Think like a contrarian Reversing your thinking also trains you to be mentally independent, assuming the opposite of what you believe and testing it. It reveals hidden assumptions. Dont just look for whats true. Look for what could be false. You dont always need a new good idea. Sometimes you just need to clear out the bad ones. Look at opposites. Always invert. Indeed, many problems can’t be solved forward, says philanthropist and investor Charlie Munger. By exploring the worst, you can unlock the best. When in doubt, reverse. Dont just pursue outcomes. Find the blind spots people normally ignore. Sometimes the fastest way forward is to look backward first. How to apply inversion in life If you are stuck on big, knotty questions, invert. How do I find happiness? is vague. Instead, ask, What are the specific, proven actions that make me miserable every single time? For me, its skipping quality sleep, isolating myself, and overthinking. If life satisfaction is what you want, dont just ask, How do I live a happy life?” The more helpful question is, What makes my life miserable? List those things, and get rid of them first. Is it a specific experience in your relationship? Poor health or lack of purpose? Be specific. Detail the things that make you unhappy. Now try avoiding them. Its a precise way to eliminate everything draining your soul. For good health, avoid everything that makes your body worse off over the long term. Bad sleep, ultra-processed food, no exercise, sedentary lifestyle. Think through how people ruin their health. Dont start with what should I do? Start with what habits destroy health? Get rid of those first. Subtraction before addition. To improve your social relationships, spend less time with your connections who drain you. Career benefits If you want to apply inversion to your career, think about what people do that hinders their careers. Complacency. Refusal to adapt or learn new skills. Over-promising and under-delivering. Avoid those traps. You dont need complex systems. You need fewer blind spots. Inversion applies everywhere. In business, you can focus on what would make your new project an absolute failure in record time. The answers will be clear. Ignore your customers. Spend money you dont have on things you need. Assume youre the smartest person in the room. Dont validate your idea. Be inconsistent. Start with your anti-checklist. Your actual plan becomes the inverse of that list. Listen obsessively. Be ruthlessly frugal. Test everything. Be more consistent on what moves the needle. Seek smarter advisors. The path forward becomes clear from the list of things to avoid. Inversion gets rid of mental traps, shows you what matters, and stops you from making the same thinking errors. If you want to think clearly, start thinking backwards.
Category:
E-Commerce
A new business infrastructure is emerging with enormous potential impact but almost no conscious design. In this new world, algorithms negotiate with algorithms, making decisions that shape markets, determine the course of careers, and decide whether companies succeed or fail. Humans, meanwhile, risk being left to watch from the sidelines. On LinkedIn, posts written by AI models are liked by bots and commented on by AI assistants. In recruiting, candidates use AI to draft résumés while companies use AI to evaluate them. In procurement, some organizations are already using AI to draft requests for proposals, or RFPsdetailed documents that invite vendors to bid on supplying goods or serviceswhile vendors are turning to AI to generate the proposals they have been invited to submit. The efficiency gains that AI can deliver are very realautomation can save time, cut costs, and improve consistency. But this does not mean we should ignore the dangers that those gains obscure. If we want to avoid slipping into a world in which humans are increasingly irrelevant, we need to be both alert to the risks and intentional about designing processes and tools to mitigate them. What Changes When Algorithms Interact In order to navigate this new reality, business leaders must first understand it more precisely. Here there are four important features of our algorithmically abstracted world: The Audience Changes New technologies often transform business, but whats happening now is different. The new technology isnt just providing new tools, but a new audience. This isnt an entirely new phenomenon. Humans have been tuning content for algorithms in some areas for years, as in the case of search engine optimization for websites. But not only is the scale now changing, but the algorithmic audience is taking over both sides of the conversation. When algorithms speak to other algorithms, language changes from a medium for human understanding into code for machine processing. For a job seeker writing an application today, the best path forward is not always to try to tell their professional story in a way that will be compelling to a human audience. Instead, it will often be better for them to encode keywords and phrases to maximize their score in the applicant tracking system (ATS scores). And, ironically, the best tools for creating this kind of optimized application are often algorithmic themselves: generative AI models. This does not mean that communication has stopped. It has not. Rather, it has changed. In addition to, and sometimes in place of, human meaning, a different kind of meaning is becoming increasingly important, one that is measured in match scores, engagement rates, and ranking positions. Humans are still involved in the loop, but only at certain points, and much of the process goes on without human intervention. Metrics Are Replacing Reality In 1975, the British economist Charles Goodhart came up with what is now known as Goodharts Lawthe idea that when a measure becomes the target for action, it ceases to be a good measure. The idea is that once people make decisions with the goal of meeting certain metrics, the underlying behavior that the metric was meant to measure is changed as people shift from focusing on the real, underlying goal to trying to optimize their score. Briefly put, once we understand there is a system, we always try to game it. Goodharts Law becomes increasingly relevant as we move toward autonomous algorithmic interactions. For example, ATS systems score candidates based on keyword matches, years of experience, and educational credentials. Candidates respond by using AI tools to optimize for exactly these metrics. But high scores in the assessment system then lose their intended meaning: Where a high score once meant that a candidate was probably a good fit for the job, now it may just mean that the candidate has access to tools that are good at gaming the scoring system. Tacit Knowledge Erodes Teachers and sports coaches have long known that much of the most important learning for their students or athletes happens in the process of doing the work rather than in a flash of insight when an explanation is given. When managers write performance reviews, they arent just documenting performance; they are also developing their ability to observe, evaluate, and articulate feedback. When teams craft project proposals, in addition to bidding for work, they are clarifying their thinking, discovering gaps in logic, and building shared understanding. This tacit knowledgethe skills and insights that emerge from doing rather than consuming informationerodes when AI takes over the process. Purpose Shifts Our current business functions evolved in a human-driven world. They contain processes designed by humans, for humans, to achieve some human goal. When these processes are outsourced to autonomous algorithmic interactions, often they stop serving the original purpose. In fact, the whole point of doing them can be lost. Take performance reviews. These originally had the clear goal of assessing employee capabilities to support actions aimed at increasing the effectiveness of the human worker. But if we end up with AI on both sides of the interaction, the whole process becomes performative. For instance, if a knowledge worker uses AI to write his reports, and his managers uses AI to generate the workers performance reviews, the original purpose of the review process is no longer being served. This doesnt mean that nothing valuable is taking place: an AI assessment of the quality of AI outputs can still tell us something useful. But it does mean that the reason for carrying out the reviews is now a pretenseimproving the effectiveness of the human worker has become irrelevant to the process that is actually being conducted. Four Strategic Responses As algorithms increasingly transact with algorithms, business now operates on two levels at once: an algorithmic layer where signals are exchanged between machines, and a human layer where meaning and value are created. Leaders must guide the interaction between these layers so that efficiency gains do not come at the expense of judgment, learning, or purpose. Here are four practical steps: Protect Human Judgment: Not every decision can or should be automated. Leaders must deliberately ring-fence certain domainsfinal hiring calls, creative development, setting organizational purposeand ensure that human judgment retains the final say in these areas. Generally, where values, creativity, and culture are at stake, a human should be the final decision maker. Translate Between Worlds: As business anguage splits into two distinct trackssignals for machines and meaning for humansleaders will need translators. These are people and processes that can interpret ATS scores, SEO rankings, or engagement metrics and reconnect them with human insight. A résumé may score well, but does the candidate bring originality? A post may perform, but did it actually persuade? Translation layers stop organizations from mistaking algorithmic proxies for real understanding. Design for Learning: Some activities are valuable not only for their output but also for the tacit knowledge they generate. Leaders must protect key processes as sites of practice, even if they are slower or less polished. Short-term efficiency gains should never come at the cost of eroding the capabilities on which long-term success depends. Protect the Purpose: When business activities shift into algorithmic exchanges, its easy for the form to survive while the function disappears. A performance review still gets written, but the developmental conversation never happens. A proposal gets generated, but the shared thinking never occurs. Leaders must continually bring activities back to their underlying purpose and ensure that the process still serves that purpose rather than becoming an empty performance. Algorithms are now part of the basic fabric of business. Resisting this shift is as pointless as commanding the tide not to come in. But while this change is inevitable, it must still be managed and steered by leaders who are aware of what is at stake. By protecting judgment, translation, learning, and purpose, organizations can ensure that automation delivers efficiency without erasing the human meaning that business depends on.
Category:
E-Commerce
If you’re in charge of an editorial team, you’re used to objections from the rank and file about using AI. “It gets things wrong.” “I don’t know what it’s doing with my data.” “Chatbots only say what you want to hear.” Those are all valid concerns, and I bring them up often in my introduction to AI classes. Each one opens a discussion about what you can do about them, and it turns out to be quite a bit. AI hallucinations require careful thought about where to apply fact-checking and “human in the loop.” Enterprise tools, APIs, and privacy settings can go a long way to protecting your data. And you can prompt the default sycophancy out of AI by telling it to give you critical feedback. There’s another objection to AI that’s been growing, however, and you can’t just prompt your way out of this one. There’s a growing reluctance among some knowledge workers to use AI because of how much energy it consumes and the consequential environmental impact. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}} It’s no secret that, as the number of people using AI grows, the colossal energy footprint of the AI industry increases. It’s true that chips powering AI continually become more efficient, but tools like deep research, thinking models, and agents ensure the demand for energy rises, too. It didn’t help that Sam Altman once said that saying “please” and “thank you” to ChatGPT was needlessly burning millions of extra dollars. Data center construction alone has soared by 40% year over year, raising concerns about not just energy needs but also water consumption. When guilt over AI use turns into pushback In the eyes of those concerned about the environment, these stories and statistics can weigh on a person. Using ChatGPT starts to feel like a betrayal, with every query producing both intelligence and a commensurate amount of guilt. If they feel their employer is pushing them to use these tools anyway, that guilt can bubble up into anger, and even resistance. We’re already starting to see serious objections. Civil servants in the U.K. voiced reluctance to use AI tools because of net zero emissions concerns, The Telegraph reported. Various officials charged with implementing AI-driven initiatives balked, fearing that doing so would conflict with Britains climate commitments. A similar dynamic is playing out at the municipal level in the U.S. Some city IT staff and policymakers in places like California have begun scrutinizing AI projects through a sustainability lens. Many media professionals are concerned too. A couple of weeks ago, I saw at least three journalists bring up the concernat separate eventswhile I was attending the Online News Association conference in New Orleans. And in a recent training I did with a large corporate comms team, I polled the audience: What is your chief concern about using AI, giving them five choices: hallucinations, bias, sycophancy, privacy, or energy use? A full 37% picked energy use. All the evidence points to AI’s energy use developing into a massive PR problemnot just for the industry, but for any business. It’s hard to be “AI forward” if your workers think using it is a huge step backward for climate change. To be clear, this isn’t to say the environmental concerns aren’t validit’s just that they’re simply not my area of expertise. But AI and managing teams are, and it’s clear this issue will be a growing challenge for AI leaders across industries, but especially media, since journalists are on the front lines of reporting AI’s environmental impact. Dos and donts for managing employee concerns So what can company leaders do to address this problem before it gets out of control? That will depend on a number of things: your AI policy, the tools you’re using, and the demographics of your workers. But here is some guidance, divided between dos and don’ts: Do listen carefully to their concerns. Are they objecting because of broad climate implications, or are their concerns more specific? Does it have to do with a specific tool? A local impact? The more detail you have on the issue, the more you will know what you can do about it. Don’t dismiss their concerns, or try to deflect them by pointing to other industries. Yes, cars spew carbon, and there are microplastics in the ocean. But there are also diesel engines and recycling programs. It’s fair to ask what the equivalent is for AI. Do research the problem. In August this year, Google became the first major lab to produce a detailed technical report on the energy, carbon, and water footprint of its AI services, which was an opportunity for the company to brag about its progress, reducing the energy consumed per prompt by 33 times from May 2024 to May 2025. This could be useful information for your team. Don’t encourage mitigating individual use. This might be controversial, but the worst thing an AI-forward worker can do is neglect to use AI to help solve a problem that it can really help with. And that goes for thinking, deep research, and GPT-5 Pro, too. Rather than mitigating individual use of tools, instead . . . Do transition workflows into dedicated tools. If a particular tool or workflow proves useful enough, you should develop it such that it uses the most efficient model possible, which will save on compute costs and the environment. Paying for your own compute is the ultimate incentivizer to throttling unnecessary use. Finally, don’t stop talking about the problem. When you give updates to your team, talk about what you’re doing, as an organization, to address the issue. Ambitious companies might even create an internally visible energy countersomething that would measure not just how much energy you’re using, but also how much compute you’re getting from it, showing how you’re improving efficiency over time. The risk when workers lose faith As AI advances, governed by mammoth trillion-dollar companies and world governments, it’s understandable that individuals may feel they have no agency in how it impacts society, and that includes the planet. It’s important for leaders to recognize that feeling of impotence and flip it into a quest for efficiency and open communication. Organizations that don’t might find that the workers using AI in unauthorized ways aren’t nearly as bad as the ones who refuse to use it at all. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}}
Category:
E-Commerce
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