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Picture a memory from childhood, one that feels real and nostalgic, but somehow just out of grasp: perhaps a family trip to the beach, or a moment mid-swing on the playset, or an afternoon spent hunting for four-leaf clovers. Now, imagine that you could bottle that golden moment into a fragrance. One scientist at MIT, Cyrus Clarke, is working to do just that. Alongside a team of fellow researchers, Clarke has developed a physical machine called the Anemoia Device, which uses a generative AI model to analyze an archival photograph, describe it in a short sentence, and, following the users own inputs, convert that description into a unique fragrance. The word anemoia was coined by author John Koenig and included in his 2021 book, The Dictionary of Obscure Sorrows. It refers to a specific feeling of nostalgia for a time or place that one never actually experienced themselvesand its exactly what Clarkes team hopes to capture with the Anemoia Device. According to a paper published by the team, the device explores the concept of extended memory, or the idea that, in the digital age, memory is increasingly stored and accessed through external media, like digital archives. Studies have already shown that memory can be formed vicariouslylike when a second-hand account, perhaps from a parent, shapes ones own memoriesbut the Anemoia Device is a delightfully physical, interactive experiment into how AI might allow users to experience a memory of a past they never actually lived. [Photo: Cyrus Clarke/courtesy MIT Media Lab] The Anemoia Device The Anemoia Device looks like something that one might find in the medical bay of a retro sci-fi spaceship. Its a slim, metal-and-plastic contraption accented with a singular neon green screen and a simple array of three physical dials. At the bottom, a glass beaker waits to catch the final fragrance. [Photo: Cyrus Clarke/courtesy MIT Media Lab] To start, a user inserts a photograph into the device. A built-in vision-language model (VLM) analyzes the image and generates an initial caption based on what it finds. For a picture of tourists in China, an example used in the paper, the device might write, A tourist in black shorts and a child pose in the doorway along the Great Wall of China, with the iconic stone steps and mountainous landscape stretching up toward the sky. [Photo: Cyrus Clarke/courtesy MIT Media Lab] Users can then adjust the parameters of the caption with the three dials: one to decide which person or object in the image should be the subject; a second to describe the age of the subject; and a third to describe the mood of the scene. [Photo: Cyrus Clarke/courtesy MIT Media Lab] “Im personally very interested in inventing new physical interfaces for generative AI,” Clarke says. “Generative AI usually starts with a blank prompt. The dials replace that with a physical, easy to understand grammar. Youre not trying to say the right thing to an algorithm, its more akin to tuning an instrument.” A language-learning model (LLM), built from ChatGPT-4o, aggregates the original caption and the user’s inputs into a short, poetic narrative. If one were to select the Great Wall of China itself as the subject of the aforementioned prompt, the result would be something like, For centuries, from the Warring States to the Ming, Ive joyfully observed times march and countless travelers along my path of stone, brick, and wood. Next comes the LLMs most impressive task: converting this written poe into a tangible scent. [Photo: Cyrus Clarke/courtesy MIT Media Lab] Smell as a memory portal The scent-development process relies not just on identifying the appropriate olfactory notes, but also on evoking the right emotions. Clarkes team trained the model to select from a scent library of 39 different fragrances (since expanded to a broader portfolio of 50 scents), ranging from old books to leather and dirt. Each fragrance was coded with a set of descriptors, labeling them with details like their primary notes, associated concepts, and strongest emotions. The LLM uses its training to select the right fragrances and determine how much of each should be used in the final concoction. All of that information is funneled to a custom olfactory display, which uses four pumps to draw the necessary liquid out of their vials and into the waiting beaker (the final formula for the Great Wall of China fragrance includes campfire, dirt, cedar, and bamboo). The Anemoia Device is capable of capturing an essentially infinite range of fragrances, from the smell of a sandy beach on a hot summer day in the 80s to the aroma of a couple enjoying a pear in a scenic garden. Ultimately, the study concludes, the device is a provocation that asks “what it means to remember when memory itself can be generated, what it means to feel when that feeling is co-authored with a machine, and what it means to be human when we can craft beautiful, fragrant fictions of pasts we have never lived.”
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Integrity, understood as a disposition to behave in prosocial, ethical, and principled ways rather than corrupt or self-serving ones, is among the strongest and most consistent predictors of job performance and leadership effectiveness. The reason is far from mysterious. Leadership, whatever its context, is a collective enterprise. No meaningful goal, from building empires to running companies, has ever been achieved alone. Across history, not just in humans but also other animals, cooperation has depended less on raw power than on trust. Ancient trading societies flourished precisely because reputation constrained behavior: merchants in Phoenician city-states, medieval guilds, and Silk Road networks relied on repeated interactions and informal enforcement mechanisms to ensure that partners honored their commitments. Those who cheated were excluded, not merely judged. Trust, in effect, functioned as an early mechanism for coordination and enforcement. The same logic applies in modern organizations. Teams perform better when members believe that leaders will act fairly, keep promises, and avoid exploiting asymmetries of information or power, or are so focused on their personal gain that they have little concern in harming the group. In line, research shows that leaders perceived as lacking integrity struggle to attract talent, elicit discretionary effort, or sustain collaboration over time. Conversely, leaders known for ethical consistency benefit from faster coordination, lower monitoring costs, and greater willingness among others to take risks on their behalf. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/tcp-photo-syndey-16X9.jpg","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/tcp-photo-syndey-1x1-2.jpg","eyebrow":"","headline":"Get more insights from Tomas Chamorro-Premuzic","dek":"Dr. Tomas Chamorro-Premuzic is a professor of organizational psychology at UCL and Columbia University, and the co-founder of DeeperSignals. He has authored 15 books and over 250 scientific articles on the psychology of talent, leadership, AI, and entrepreneurship. ","subhed":"","description":"","ctaText":"Learn More","ctaUrl":"https:\/\/drtomas.com\/intro\/","theme":{"bg":"#2b2d30","text":"#ffffff","eyebrow":"#9aa2aa","subhed":"#ffffff","buttonBg":"#3b3f46","buttonHoverBg":"#3b3f46","buttonText":"#ffffff"},"imageDesktopId":91424798,"imageMobileId":91424800,"shareable":false,"slug":""}} The cost of distrust Given a choice, people prefer to collaborate with those they trust not because they are nave, but because distrust is expensive. Working with unreliable or unethical partners increases the likelihood of failure, conflict, and reputational damage. In business, this may mean backing leaders who misrepresent performance or shift blame. In politics, it can mean empowering those who erode institutions for personal gain. In both cases, the costs are borne not only by the followers but by the system as a whole. This is why chronic corruption is one of the most reliable markers of institutional breakdown. As documented year after year by Transparency International in its Corruption Perceptions Index, countries that score lowest on integrity and trust tend to share familiar pathologies: weak rule of law, politicized institutions, capital flight, and persistent underinvestment, generally caused by parasitic governments and destructive leadership. By contrast, countries that consistently rank at the top of integrity and trust measures benefit from stronger institutions, more predictable governance, and higher levels of social and economic cooperation. To be sure, these societies are not free of self-interest or ambition; rather, they have succeeded in aligning incentives so that ethical behavior is rewarded and corruption is costly, censoring selfish short-term individual gains in favor of collective long-term benefits. Measuring integrity So, how can we tell whether a person has integrity, or gauge someones moral reliability? The question is especially consequential when applied to leaders, whose decisions shape the success, welfare, and future prospects of others. Fortunately, behavioral science offers several useful insights, even if it stops short of perfect certainty. First, integrity is not directly observable. Unlike physical attributes such as height or hair color, it cannot be seen or measured at a glance. Instead, it is inferred or deducted from patterns of behavior, consistency over time, and alignment between words and deeds. Integrity is therefore an attribution rather than a trait we can observe directly, which makes assessment inherently probabilistic rather than definitive. Second, short-term interactions are often misleading. Because appearing ethical brings clear benefits (trust, influence, reduced scrutiny, and access to resources) people are incentivized to signal integrity even when they lack it. This helps explain why superficially ethical environments can sometimes attract parasitic actors who exploit the goodwill and assumptions of others. In contrast, in persistently corrupt settings, distrust becomes the default, and even well-intentioned individuals are treated with suspicion. Context shapes both behavior and perception. A parallel and increasingly robust line of evidence comes from research on the so-called dark traits, narcissism, psychopathy, and Machiavellianism. Although conceptually distinct, these traits share a common core of low empathy, emotional coldness, and a tendency to instrumentalize others. From an integrity standpoint, this combination is toxic. Individuals high on these traits are less constrained by guilt or concern for others, more willing to bend or ignore rules, and more likely to justify unethical behavior as necessary, deserved, or clever rather than wrong. Psychopathy is most directly linked to callousness and fearlessness, reducing sensitivity to punishment and moral emotion. Machiavellianism predicts strategic deception, cynicism about human motives, and a belief that ends justify means. Narcissism, especially in its more grandiose forms, adds entitlement and moral exceptionalism, the belief that normal rules apply to others but not to oneself. Together, these traits reliably predict counterproductive work behaviors, ethical transgressions, and integrity failures, particularly in roles that confer power, discretion, and weak oversight. Crucially, this is not because such individuals lack intelligence or self-control, but because their motivational architecture is misaligned with prosocial norms. Where integrity depends on empathy, respect for authority, and an internalized concern for collective outcomes, dark traits tilt decison making toward self-interest, dominance, and short term gain, making them among the strongest dispositional red flags for integrity risk in organizational life. Third, while integrity cannot be measured perfectly, it can be assessed meaningfully. Research shows that peer ratings are among the most reliable indicators, precisely because integrity is reputational: it reveals itself in how people behave when others depend on them. Longitudinal data, such as 360-degree feedback, is especially informative. Personality traits like conscientiousness, altruism, and self-control (including the capacity to self-edit) also predict ethical conduct, as does past behavior. Self-reports are often dismissed, but well-designed measures still differentiate reliably between individuals with higher and lower integrity. Track records matter, even if they do not render anyone immune to temptation. As Warren Buffett famously observed, reputation takes a lifetime to build and a moment to destroy. Finally, the environment matters. Ethical failures are not only the result of bad apples, but also of rotten barrels. Weak governance, misaligned incentives, and tolerance for small transgressions can erode integrity even among otherwise decent individuals, while well-designed systems can reinforce ethical behavior by making misconduct costly and transparency unavoidable. Sapping growth Taken together, these points suggest that integrity is neither inscrutable nor guaranteed. Whether in governments, firms, or teams, integrity functions as an enabling condition for coordination and progress. When trust erodes, actors devote more effort to monitoring, hedging, and self-protection, leaving less energy for innovation or growth. In this sense, integrity is not merely a moral ideal, but a form of social infrastructure: largely invisible when it works, and painfully obvious when it does not. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/tcp-photo-syndey-16X9.jpg","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/tcp-photo-syndey-1x1-2.jpg","eyebrow":"","headline":"Get more insights from Tomas Chamorro-Premuzic","dek":"Dr. Tomas Chamorro-Premuzic is a professor of organizational psychology at UCL and Columbia University, and the co-founder of DeeperSignals. He has authored 15 books and over 250 scientific articles on the psychology of talent, leadership, AI, and entrepreneurship. ","subhed":"","description":"","ctaText":"Learn More","ctaUrl":"https:\/\/drtomas.com\/intro\/","theme":{"bg":"#2b2d30","text":"#ffffff","eyebrow":"#9aa2aa","subhed":"#ffffff","buttonBg":"#3b3f46","buttonHoverBg":"#3b3f46","buttonText":"#ffffff"},"imageDesktopId":91424798,"imageMobileId":91424800,"shareable":false,"slug":""}}
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AI inspired many employers to take a wait-and-see approach to hiring in 2025, but new data suggest theyll be returning to the market in search of certain skills in 2026. According to Upworks In-Demand Skills 2026 report, demand for AI-specific proficiencies have more than doubled on the freelancer platform over the last year. But at the same time, nearly half of employers also say theyre also putting a premium on human skills, like creativity, emotional intelligence, resilience and innovation. When we look at the fastest growing skills in terms of demand, AI is all over it. Thats not surprising, says Dr. Gabby Burlacu, licensed organizational psychologist and Upworks senior research manager. However: What is interesting is that this is not growing demand for AI generalists, or even necessarily people who can build AI tools, but rather its growing demand for AI applied within a context. In 2026, more employers want to inject AI into more business operations, and are seeking candidates that are not only able to utilize the technology, but also maximize its impact by leveraging their human skills and unique experience. Integrating, Not Building According to the Upwork study, demand for skills tied to AI is up 109% year-over-year. Skills related to AI video and content creation saw the biggest jump with a 329% increase, followed by AI integration (which helps inject the technology into existing business practices) at 178%. AI data annotation, which specializes in preparing and training content for the purpose of AI model training, ranked third with 154% demand growth. At the same time, the study found that employers are looking for what are traditionally labelled as soft skills or human skills, which are increasingly viewed as vital enablers of new tech tools. We are seeing enormous demand and recognition from business leaders of just how important nontechnical and uniquely human skill sets are, says Dr. Burlacu. They want human judgment, they want creativity, they want innovation, and when we asked business leaders what skills are becoming critical in an AI world, the ability to build or even engage with AI tools wasn’t at the top of that list; it was learning agility and adaptability. The study, and others like it, suggest AI isnt replacing human workers on a wide scale as initially feared. Instead, its changing the kinds of skills employers are looking for, putting a higher premium on traits that cant be automated. A Labor Market Bounce-back in 2026? Dr. Burlacu explains that each time a new disruptive AI tool or category of tools hits the market, employers tend to pull back on hiring in that domain as they figure out what exactly the technology is capable of, and where it falls short. This [research] suggests that the impact of AI is taking shape, and that it is much more about augmenting how existing domains and roles are done, versus completely replacing the need for human skills, says Dr. Burlacu. There’s a tremendous opportunity to use AI to do the work that you do and that you specialize in [today] differently. That is what business leaders are seeking. Dr. Burlacu adds that as employers gain a deeper understanding of how AI will impact their business, theyre gradually moving off the sidelines and pursuing the skills they need to best utilize the new technology. Towards an AI-Enabled Human Workforce The Upwork study is consistent with a recent McKinsey report titled Agents, robots, and us: Skill partnerships in the age of AI, which suggests the future of work will be defined by harnessing the best of both technology and humans. In that study, researchers examined 7,000 commonly sought-after skills from real job postings across industries and organized them based on those that could be fully automated today, those that will likely never be automated, and those that fell somewhere in between. They ultimately found roughly 70% of skills can be enhanced by technology, but still rely on human expertise. Another 12% remain entirely within the domain of humans while just 18% can be fully handed over to technology. The implication is that it’s going to be a world in which we upgrade that skill by using it in conjunction with AI, says the studys co-author and McKinsey Global Institute Partner Anu Madgavkar. If we can use AI as an assistant or a collaborator or a co-worker, then our own ability to use that skill and deploy it will be enhanced. Madgavkar explains that in our AI-enabled future, workers wont need the deep technical expertise required to build their own AI tools. Instead, they will be challenged to utilize the technology to enhance their own capabilities. People’s roles are going to change quite a lot and very fast, and you can imagine theres a degree of anxiety or uncertainty about that, says Madgavkar. It’s not just about adoption; it is indeed about reimagining how work gets done, not just at the level of an individual’s job or set of tasks, but really as a whole workflow. The Transition is Already Underway Whether it was the ability to use word processors, social media or cloud computing, candidates have long been encouraged to list proficiency with the hottest technology of the day on their resumes. What’s new is the pace and the level of acceleration, explains Aashna Kircher, the group general manager of CHRO products at Workday. The evolution of some of these tools is happening at a pace weve never seen, where every day there are new skills, new learnings, new understandings of what is and isnt possible. Fortunately, AI is itself making that education more attainable. According to a Workdays Elevating Human Potential: The AI Skills Revolution report, 83% of employees globally say AI has enhanced their ability to learn new skills. As the ability to leverage AI to work more efficiently becomes table stakes, Kircher says workers and candidates are quickly becoming valued for the things they can offer that the technology cant. You need to apply context, values, nuanced to AI outputs and systems, as well as ethical decision making, emotional intelligence, relationship building and connection conflict resolution, leadership skills, she says. It’s not that technical skills aren’t important. They certainly are, but some of these other skills are actually becoming outsized in importance relative to some of the technology skills.
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