 |
|
|
|||||
Since no one ever does anything worthwhile on their own, who you know is important. But what you know — and what you do with what you know — is crucial. Learning, memory, and cognitive skills are a competitive advantage. Here are five neuroscience-based ways to learn more quickly, and even more importantly, better retain what you learn. Best of all, each takes a couple of minutes at most, and one requires no effort at all. Say it out loud. We took the grandkids to surf lessons. They wanted to go back for another session, the instructor was great, so I asked him his name. Problem is, I’m terrible at remembering names. So I said it aloud three or four times. Why? A study published in the Journal of Experimental Psychology found that saying words out loud (or even just mouthing the words) makes them more memorable. While the underlying mechanism is unclear, neuroscientists theorize saying something out loud separates and distinguishes it from “mere” thoughts. (You didnt just think it. You also heard it.) That makes the information, idea, or plan you want to remember even more memorable. When you need to remember something, say it aloud, or mouth it to yourself. Your cerebral cortex will help you retain it longer. Then… Do a 40-second replay. Remembering a name is fairly simple. Remembering something more complex requires memory consolidation, the process of transforming temporary memories into more stable, long-lasting memories. Even though memory consolidation can be sped up, storing a memory in a lasting way takes time. A good way to increase the odds is to mentally replay whatever you want to remember for 40 seconds. A 2015 study published in Journal of Neuroscience found that a brief period of rehearsal — replaying an event in your mind, going over what someone said in a meeting, mentally mapping out a series of steps, etc. — makes it significantly more likely you will remember what you replayed. As the researchers write: A brief period of rehearsal has a huge effect on our ability to remember complex, lifelike events over periods of one to two weeks. We have also linked this rehearsal effect to processing in a particular part of the brain, the posterior cingulate. A week or two? That should be long enough for you to actually do something with whatever you wanted to remember. Then… Make a prediction. While it sounds odd, a study published in the Canadian Journal of Experimental Psychology shows the act of asking yourself whether you will remember something significantly improves the odds that you will remember, in some cases by as much as 50 percent. Thats especially true for prospective memories, or remembering to perform a planned action or intention at some point in the future. Following up with a customer. Checking on a vendor’s status. After you deal with a problem, determining the the root cause. Why playing the prediction game works is also somewhat unclear. Possibly the act of predicting is a little like testing yourself; as research shows, quizzing yourself is a highly effective way to speed up the learning process. What is clear is that the act of predicting helps your hippocampus better form and index those episodic memories for later access. Want to remember to do something in the future? Take a second and predict whether you will remember. That act alone makes it more likely you will. Then… Zone out for two minutes. According to a study published in Nature Reviews Psychology, “even a few minutes of rest with your eyes closed can improve memory, perhaps to the same degree as a full night of sleep.” Psychologists call it “offline waking rest.” In its purest form, offline waking rest can be closing your eyes and zoning out for a couple of minutes. But you can also daydream. Meditate. Clear your mind and think happy thoughts. While none of those sound productive — should you really be wasting time you could be learning? — intermittent lack of focus improves memory consolidation; in simple terms, constantly going from one thing to the next makes it hard for your brain to keep up. As the researchers write: Periods of reduced attention to the external world are a universal feature of human experience, which suggests that spending a portion of time disengaged from the sensory environment permit the reactivation of recently formed memory traces. This iterative reactivation of memory could strengthen and stabilize newly formed memories over time, contributing to early stages of memory consolidation during the first few minutes following encoding. The key is to be intentional about it. First, replay what you want to remember for 40 seconds or so. Then, predict whether you will remember it. Then, close your eyes, zone out, and engage in a minute or two of offline waking rest. As the researchers write, “Moments of unoccupied rest should be recognized as a critical contributor to human waking cognitive functions. And finally… Get a good night’s sleep. Here’s the effortless aspect of improving your memory. According to a study published in Psychological Science, peple who studied before bed, slept, and then did a quick review the next morning spent less time studying — and increased their long-term retention by 50 percent. The underlying mechanism is what psychologists call sleep-dependent memory consolidation: “Converging evidence, from the molecular to the phenomenological, leaves little doubt that offline memory reprocessing during sleep is an important component of how our memories are formed and ultimately shaped.” In simple terms, sleeping on it helps your brain file away what youve learned, and makes it easier to access when you need it. Thats also true where longer-term memory is concerned. Learning, then getting a good nights sleep, and then learning again is an extremely effective way to boost intelligence and skill. As the researchers write: We found that interleaving sleep between learning sessions not only reduced the amount of practice needed by half but also ensured much better long-term retention. Sleeping after learning is definitely a good strategy, but sleeping between two learning sessions is a better strategy. Say youre learning a new sales demo. After a practice session, say the main bullets of your presentation out loud. Then mentally replay key elements of your presentation. Then predict whether youll remember what youve learned. Then take a minute or two to zone out. Then get a good nights sleep, do a quick review the next day, and work on the next chunk of information. Rinse and repeat, and neuroscience says youll spend less time learning — and you’ll remember a lot more. Which means youll be able to do more. Because what you know is only as good as what you do with it. By Jeff Haden This article originally appeared on Fast Company’s sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.
Category:
E-Commerce
Weve spent decades building frameworks to help people lead teams: courses, certifications, coaching, culture decks. All aimed at shaping better managers of humans. But thats no longer enough. Because for many workers, their first report wont be a person. Itll be an agent. In June BNY Mellon onboarded 1,000 digital workers while JPMorgan Chase is building AI teams at scale. This isnt theoretical. The new direct reports are already clocked in and they dont need coffee, feedback, or PTO. The problem? Most organizations are still running on legacy management models built for human hierarchies and not set up to manage machines. Leading humans versus governing agents When you manage people, you guide behavior. You motivate, delegate, coach, and course correct. Its a loop built on trust and conversation. When you manage an AI, none of that applies. You dont coach a model. You govern it. You define inputs, monitor outputs, escalate issues, and answer for the consequences. And you do that in real time. In AI-led teams, leadership is less about motivation and more about judgment. The ability to assess, adjust, and act across decision chains is what separates performance from liability. Its knowing what good looks like. Its catching the drift, asking the right question before the system generates the wrong answer, and being accountable for outcomes, even when you didnt directly produce them. The HR model is out of sync HR isnt ready for this shift. Most performance frameworks still assume linear paths, human reports, and long-term role tenure. But digital agents break that logic. They dont climb ladders. They execute tasks. They can outperform junior staff one day and be outpaced by a new model the next. You dont manage their growth. You manage the conditions in which they operate. That shift puts pressure on organizational design itself. Hierarchies built for human oversight dont hold when decision loops involve systems acting faster than approvals can be processed. That means rethinking how we define productivity, collaboration, and leadership. It means building new metrics for how human employees interact with agents, not just what they produce on their own. Are they designing good prompts? Are they escalating ethical concerns? Are they reviewing outputs critically or rubber-stamping them? These are the new leadership signals. Most performance reviews arent built to detect them. Prompting is a leadership act Prompting isnt a technical skill; its a management one. The way you frame a prompt shapes what an agent does. Vague prompts lead to vague results. Biased prompts produce biased outcomes. And poor prompting isnt just inefficient. It can become a legal or reputational risk. Yet most companies treat prompting like its keyboard wizardry. Something for the engineers or the AI power users. Thats a mistake. Everyone managing agents, from interns to executives, needs to learn how to design clear, intentional instructions. Because prompts are decisions in disguise, shaped by where they sit in the organizational context and why theyre being made. The ethics chain is breaking In traditional teams, ethics and escalation follow a chain of command. Something goes wrong, someone flags it, and a manager gets involved. But with agents acting independently and often invisibly, the chain breaks. You cant escalate what you dont notice. And too often, companies havent defined what ethical escalation looks like when the actor is synthetic. Whos accountable when an AI produces a discriminatory recommendation? Or leaks sensitive information? Or makes a decision a human wouldnt? If your answer is the tech team, youre not ready. Governance cant sit in the back office. It needs to be built into team workflows. The best companies are training their people to pause, question and report, not just accept what the system spits out. Chain of thought and chain of reasoning arent just cognitive tricks. Theyre how human teams will spot drift, bias, and breakpoints in the AI value chain. And that skillset is only going to grow in importance. The bottom line AI wont replace all managers, but it will redefine what management means. Leading agents demands flexing a different muscle and most organizations havent trained for it. This isnt about replacing soft skills with hard skills, but rather its replacing passive management with active stewardship: less people-pleasing and more decision accountability, fewer status meetings and more escalation pathways. Managing machines still means leading people. But the people you lead need new tools, new rules, and a different playbook. The companies that get this right wont be the ones with the flashiest tech. Theyll be the ones that know how to change the game by managing what theyve built.
Category:
E-Commerce
Child care costs are growing. Access is declining. But small businesses aren’t too concerned about the impact on business. The National Federation of Independent Business recently released its quadrennial report on the most pressing problems for small-business owners in the U.S. For the first time, it asked about the “cost and availability of child care,” which owners ranked as their 66th most pressing concern of the 75 assessed. Moreover, only 7% of small-business owners considered the problem “critical,” and 40% didn’t consider it a problem at all. This might be surprising, considering that child care costs increased 32% for American households from 2019 to 2023, and the share of parents without access to child care grew from 17.7% at the end of 2023 to 22.2%in the early months of 2024. But as Holly Wade, executive director of the NFIB Research Center, says, the results suggest that the problem is relatively limited in scope right now, at least in the eyes of business owners: “For some employers, they’re able to work around child care issues fairly easily, accommodate scheduling conflicts — [so it doesn’t rise] to the level of issues, for instance, like the cost of health insurance.” Indeed, in the NFIB report, health insurance costs ranked at the top of small-business owners’ concerns, as it has since 1986. The costs of supplies and inventories, economic uncertainty, and federal taxes were among other top issues for owners this year. Plus, if businesses have a “younger demographic of employees or an industry that has higher turnover [or] seasonal employment,” child care issues might not be a pain point for them at all, Wade adds. Other recent reports, however, still indicate that these pressures are impacting workforces. 29% of job switchers identified a lack of child care benefits as their top motivation in looking for another job, according to a 2024 report from Care.com. Women’s labor force participation is now lagging compared to pre-pandemic levels — and taking care of “the home or family” is the primary reason mothers are not working, according to the Pew Research Center. And as Inc. previously reported, there are still small-business owners who already believe that a lack of child care is negatively impacting their business — even if it may not be their top concern. By Sarah Lynch This article originally appeared on Fast Company’s sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.
Category:
E-Commerce
All news |
||||||||||||||||||
|
||||||||||||||||||