5 Myths About Classroom Management in PBL

I want to make something clear before we dive into this topic. I made huge mistakes in classroom management as a teacher. I let certain disruptive behaviors go unchecked because I was tired and I didn’t want to put out another fire. I had moments when I shamed a student or yelled at a class.

I won’t even use the term “raise my voice” which sounds nicer. I yelled. Each time, I apologized and continued to grow. But the reality remains: I had tons of moments when I failed in this area. So, I feel a certain reticence when tackling the question, “How do I handle classroom management in a PBL unit?”

And yet, I also realize that my mistakes, as cringe-worthy as they may be, were also learning experiences. Teaching is an iterative process filled with experiments. I believe we can learn as much from the failures and mistakes as we can from the successes. So, with that in mind, I’d like to share what I learned about PBL and classroom management from my twelve years teaching middle school and my last three years working with new teachers who want to try out PBL but are nervous about the classroom management implications.

Why Classroom Management Matters

When I was new to project-based learning, people told me to “embrace the chaos.” I tried my hardest to embrace this mindset. Our class would be a vibrant space filled with noise and chaos and movement. I told students that during our project time, they could go wherever they wanted to go and talk whenever they wanted to talk.

This lasted three days.

I had students wandering around the classroom for the entire class period, socializing with friends and never actually working on their projects. The room became ear-splittingly loud. Meanwhile, I became edgy. The chaos felt off-task at best and unsafe at worst. At one point, another teacher walked into my classroom and said, “Why did you kick Alejandro out of class? He’s normally so quiet.” But the thing is, I hadn’t kicked Alejandro out. He had walked away because he felt anxious in the chaotic space.

Alejandro wasn’t alone. I printed up a quick survey (these were the pre- Google Forms days) to see how students felt about the classroom environment. Two-thirds described having a hard time concentrating on their work.

The next morning, I had coffee with my mentor and lamented, “I thought the project was authentic. I thought I could create a student-centered environment. I thought they would just know how to behave during a project like this. But, I don’t know, maybe I’m not able to create that kind of environment.”

He furrowed his eyebrows and said, “You ever work on a project when you’re at Starbucks?”

I nodded.

“Okay, watch the people in Starbucks. What trends do you see?”

I described people sitting at the tables and occasionally standing at a tall table. They moved to get coffee, to use the restroom, and to order items. However, they weren’t running around. Instead, it was relaxed.

Although the environment was noisy, it was mostly due to the work of grinding coffee and blending beverages. Most people were talking at a reasonable volume. They followed unspoken norms that allowed for communication and work. He then challenged me to think of all the spaces where I had done my best individual and collaborative projects. These were spaces designed for communication, deep thinking, and deep work. Some of these spaces were silent and others were loud. However, they were all spaces where I could focus.

I realized something critical at that moment. If we want students to engage in authentic projects, we need to design systems and structures that facilitate collaboration and creativity. For all the talk of “embracing chaos,” it turns out classroom management is a vital part of authentic PBL.

Myths About Classroom Management and PBL

The following are some of the common myths about classroom management and PBL.

Myth #1: Structure ruins creativity

This was the myth I bought into when I first embraced the PBL process. Like I mentioned before, I created a classroom environment free of constraint. Go where you need to go. Be as loud as you need to be. Take the John Mayer route and run through the halls of your high school and scream at the top of your lungs (yes, I just paraphrased John Mayer).

This came from a genuine recognition that school structures are often arbitrary and overly restrictive. However, I had gone to the opposite extreme of classroom management anarchy. I mistakenly believed in a false dichotomy between student ownership and classroom expectations.

Reality: Well-designed structures facilitate creativity

Architects often design spaces with two competing goals: craft spaces to reflect the way people will use them (starting with empathy) and create spaces that will create desired behaviors. Take Panera, for example. The physical layout reflects the need for both open and closed spaces with plenty of “breathing room.” They designed it to reflect the way people actually like to collaborate (the empathy-driven approach). However, they also have visual cues and physical structures that lead you toward specific locations the moment you walk in the door.

The same should be true of the structures in a PBL classroom. As educators, we can work like architects designing the structures that will facilitate creativity. We can start with the empathy-driven approach by asking “What would this be like to experience this as a student?”  It can help to imagine you are a student and spend some time thinking through what you might think and feel during an entire PBL Unit. You might even create student surveys to gauge what students need in order to thrive in a PBL environment.

From there, we can design systems that fit the needs of our students. For example, students need to move and they need to have the chance to stand up. However, they also need the opportunity to focus without distraction. So, we can create standing centers at the edges of the classroom. We can create physical pathways that allow for movement of materials.

However, we can also embrace the ideas of UX Design to guide students through the process. Students should be able to know where to find materials and where to go to get help. This goes beyond the physical structures. Students need to have pedagogical structures for things like brainstorming, ideating, research, and collaborative decision-making.

Myth #2: You need tons of transitions or students will be off-task

This was one of my biggest fears when starting out on my PBL journey. I had always transitioned every 15-20 minutes to prevent students from getting bored and checking out. I kept my lessons fast-paced with tight deadlines. So, when I switched to a project-based approach, I initially broke tasks down for students and kept the same tight time deadlines.

I didn’t realize it at the time, but I was creating a stop-and-go approach to projects. Although I wanted students to work quickly, they never truly hit a place of deep concentration because we were frantically moving from task to task, only to stop, wait for directions, and move on.

Reality: Students need to engage in deep work to hit a state of flow

Students actually accomplished more when we took out the transitions and focused on longer stretches of time to engage in the project work. This is a key idea behind what Cal Newport describes as “deep work” (I highly recommend the book), where people spend 1-3 hours without distractions. Here, they often hit a state of creative flow, where they attain hyper-concentration and fixate on their work. When this happens, they learn at a deeper level and they retain more of their knowledge.

But these moments of flow, whether they are in groups or individually, can also work as preventative classroom management. When students focus on their projects, they are less likely to disrupt the learning.

Myth #3: An engaging project means you won’t have discipline issues

When I look back at my worst moments as a teacher (those times when I shamed a student or yelled at a class), it was almost never during a project. A well-constructed project is one of the best preventative classroom management strategies. However, it’s a myth to think that you can focus on the pedagogy and ignore classroom management. Even in your best PBL units, you will have discipline issues you need to deal address.

Reality: You need clear expectations

When you first launch a PBL unit, you will likely have students who have never experienced project-based learning. They will need to know how it works and what they are expected to do. Because it’s so different (more collaborative work, more creativity, and often more hands-on learning) you will need to clarify the expectations.

You might need to generate a list of rules or norms together with your students. You will likely need to model and practice procedures with your students. The goal is to make it clear, visual, and memorable for students. Although this can feel less exciting than the actual project, it’s actually a vital part of the process.

Myth #4: PBL classrooms are noisy all the time

I get it. Some tasks are inherently noisy. It’s hard to have students doing physical prototyping in silence. The class is going to get noisy during the collaborative part of ideation. However, a project-based classroom doesn’t have to reach a deafening volume all the time.

Reality: The noise should never get in the way of the learning

It’s easy for one group to get louder and then other groups start talking louder until it slowly creeps to a level that prevents groups from working effectively. This is why it’s okay to have expectations of a general volume level during collaborative work. I’ve seen teachers use volume level charts (like a noise meter). When I taught middle school, I would do a thirty-second silent time-out when the noise got too loud. It worked like a reset button.

It also helps to create moments of strategic silence throughout a project. You might start the class period with a silent warm-up and end with a silent reflection. Or you might break up the project process to have students engage in silent thinking or quick writes to boost metacognition. You can also embed quiet individual tasks into the project process.

For example, students can engage in individual research to gain extra background knowledge. During the ideation process, students can brainstorm in isolation before meeting with their groups. They can also create their own SWOT assessments on their own before meeting with their groups to test and revise prototypes.

Myth #5: You need a system of punishments and rewards to keep group members accountable

We’ve all been there before. You do a group project and suddenly one member disappears. Another member has tons of opinions and ideas but doesn’t want to do any of the work. So, you end up doing the entire project by yourself. For this reason, it’s tempting to create rigid rules and consequences for group members in PBL units.

Reality: The best accountability is interdependence

There is a time and a place for external accountability. PBL expert Trevor Muir has students sign group accountability contracts at the start of each PBL unit. However, I’ve found that students are more accountable to one another when they have to work interdependently on their projects. Take, for example, this brainstorming strategy. Students actually benefit from listening to one another depending on each other for new ideas.

I often think of the LAUNCH Cycle as a roadmap for interdependent student ownership in creative projects. Here’s what this looks like:

  • Students tap into their own awareness and background knowledge during the Look, Listen, and Learn phase. Here, each member has the opportunity to share what they already know.
  • Students own the inquiry process as they ask specific questions in the Ask Tons of Questions phase. Each member can contribute their own questions to the entire group’s set of questions. Each member can add questions, regardless of their skill level or prior knowledge.
  • Students work interdependently to find specific facts in the research phase.
  • Students are generating their own ideas individually before engaging in the Navitage Ideas (group ideation) phase.
  • Each member of the group has a different role in the project management process and they all discuss progress collectively as a group
  • Every student has the opportunity to engage in assessment in the Highlight and Fix phase. I love the interdependence of the 20-minute peer feedback system here.
  • Being Proactive About Classroom Management
  1. Think about the procedures you will need to teach ahead of time.  What procedures and expectations will you need to teach ahead of time? How will students get materials? How will you handle noise? How will you handle movement? Are groups allowed to talk to one another? If so, what does that process look like? How will you handle students finishing at different rates? What kinds of “brain breaks” will you offer to students who need to walk away from their projects? How will you help students define these expectations together as a classroom community?
  2. Think about the space. How will you differentiate the space for different tasks? How will you design spaces for different types of learning? What will you do to encourage a free flow of movement? What visual cues will you create to help students navigate the space? What materials will you use? Where will you store these materials? Where will students put their physical products when they leave the class period (or move on to a new subject)? It helps hear to do an empathy exercise where you picture yourself as a student and ask what a student might be feeling or thinking.
  3. Think about the roles within the classroom. What types of group roles will you have?  How will your role change as a teacher? How will you spend your time when students are in the prototyping phase?
  4. Consider how you might communicate this shift to stakeholders. Are you comfortable having administrators and other leaders walking into your classroom during the prototyping phase? What kinds of fears might certain teachers face if they saw something that looked chaotic? What do you need to do to communicate the PBL process to parents/guardians, fellow staff members, and administrators?

Classroom management can actually be easier in a PBL classroom. With increased engagement and clear expectations, you often find yourself doing student-teacher conferences rather than redirecting behaviors. However, this requires an intentional, proactive classroom management plan. When this happens, all students are able to work collaboratively and creatively on the epic projects you have designed for them.

By: John Spencer

My goal is simple. I want to make something each day. Sometimes I make things. Sometimes I make a difference. On a good day, I get to do both.More about me

Source: 5 Myths About Classroom Management in PBL – John Spencer

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Ignore These Myths About Life Insurance

Photo: BalanceFormCreative (Shutterstock)

Many young, single people assume they don’t need life insurance. Unfortunately, this misconception is difficult to reconcile before it’s too late. After all, life insurance is one of those investments that you can’t exactly buy after you need it, and if you wait too long, it’s going to cost a lot more to get it.

The purpose of life insurance is to provide a safety net so your family or loved ones won’t struggle to pay bills or handle other financial responsibilities after you’re gone—but that doesn’t mean you don’t have to think about it until after you have a family. Here’s what you need to know about that and other myths about life insurance that are best ignored, and what facts to consider instead.

Life insurance only matters after you die

In fact, life insurance is for the living. It’s in the name, and sure, the central reason to get life insurance is to financially protect your loved ones in the event of your death. But many life insurance policies also have living benefits, which allow you to tap into your plan in the event you are diagnosed with a terminal or chronic illness.

Another way you can benefit from your life insurance your plan while you’re still alive is through its cash value. Depending on your plan type, you may be able to build tax-deferred wealth through your policy, with the ability to make withdrawals from or take out loans against the value during your lifetime.

All life insurance is too expensive

Life insurance costs will vary depending on your age, gender, health, and specific policy. Predictably, the younger and healthier you are, the less expensive life insurance will be. For example, a healthy 35-year-old can pay under $28 per month for a term life insurance policy with a $500,000 death benefit payout and a duration of 20 years, according to Policy Genius.

If you’re concerned about costs, Business Insider advises you to start small. Get as much life insurance as you can afford for now, and then reassess when you are able to increase your coverage down the line. For your first plan, term life insurance is one of the most popular and affordable options. It’s a straightforward policy that provides a large assured sum assured for a low premium over an extended term, typically 10 to 30 years.

If you have health issues, consider looking into policies that don’t require medical exams.

You don’t need life insurance if you’re single with no dependents

This might be the most prevalent myth about life insurance: If no one is depending on you, why create a financial security blanket? The reality is that if you have transferable debt, like student loans, you could render your parents or other family members responsible after you’re dead. Life insurance is not just for married couples.

And while many think of life insurance as replacing lost income, even a stay-at-home parent who doesn’t receive a salary should take out life insurance. Although they may not be the traditional “breadwinner,” the cost of replacing childcare or other household duties is worth considering, and preparing for.

You should just stick with your employer’s life insurance

While many company life insurance policies are a low-cost (or even free) perk, they likely aren’t sufficient to meet your financial needs, typically offering around a year of your usual salary. Investopedia explains: “If you have dependents who rely on your income, then you probably need coverage worth at least six times your annual salary…Some experts even recommend getting coverage worth 10 to 12 times your salary.” It’s wise to supplement employer-provided insurance benefits with policies that are tailored to your needs.

The bottom line: Life insurance is not one size fits all

Take advantage of the fact that life insurance is highly customizable. And compared to other forms of insurance, your life insurance needs will change drastically over time. Think about it: Children, marriage, divorce, remarriage, caring for elderly family members, and retirement…and that’s just your thirties. (Kidding.)

Even if you don’t think you need it now, you should start with what you can afford and build coverage as your circumstances change. Nerd Wallet provides a handy table that will help you compare quotes now, and companies like Policy Genius make it easy to shop around for a good rate. But rather than rely solely on online platforms, it’s also worth consulting a real life professional.

By: Meredith Dietz

Source: Ignore These Myths About Life Insurance

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Why The Myth of The Miserable Lottery Winner Just Won’t Die

On Friday night, Mega Millions held a drawing for a whopping $1.28 billion jackpot, the third largest in American history. Late in the evening, officials announced the winning numbers—13-36-45-57-67, with a Mega Ball of 14—and on Saturday morning, said that one jackpot-winning ticket had been sold, in Illinois.

One in eight American adults play the lottery at least once a week, and almost half buy at least one ticket a year. Unfortunately, even if you bought your annual ticket sometime in the last few days, that winner is probably not going to be you—unless you happen to be that lucky Illinoisan. Maybe that’s okay, you tell yourself. Don’t lottery winners end up broke and miserable? It would be great to be rich, but I don’t need $1.1 billion.

Except most lottery winners do not wind up broke, or miserable, or bankrupt. Stories about regretful lottery winners are trotted out whenever jackpots get big. But as much as jealous losing bettors might want to think that winners’ unfathomably good luck is balanced out by bad, most people who strike it rich this way settle into lives of quiet, comfortable anonymity.

And yet, the myth of the miserable lottery winner persists. The history of this myth reveals a longstanding national discomfort with gambling, and exposes deep-seated cultural beliefs about the connection between wealth, work, and merit.

In the United States, media coverage of lottery winners is nearly as old as lotteries themselves. The first American lotteries were held in the 17th century to raise funds for colonial infrastructure projects. Lotteries appealed to gamblers at the time for many of the same reasons they are popular today: they offered a chance to dream of instant affluence, and provided a rare opportunity for the poor to hit it big.

But starting in the colonial period, a specific genre of human-interest story became widespread: lottery winners who wound up broke, beleaguered, or worse. From the 18th through the 20th century, newspapers in the United States recounted the misfortunes of lottery winners from across the globe: A baker and his pregnant wife murdered for his winnings by an employee (Paris, France, 1765). A squandered jackpot invested in a failed shipping venture (Newburyport, Massachusetts, 1883). A winner dying of a heart attack immediately upon hearing news of his windfall (Bilbao, Spain, 1934).

These stories remained common as states began legalizing lotteries in the 1960s and 1970s. With so many lottery prizes being handed out—and so many winners’ stories to choose from—journalists began to frame miserable lottery winners not as unique curiosities, but as a trend. Jackpots at the time were small, and some winners reported being hounded for money from strangers and family members.

Partly due to the federal government’s semi-adversarial approach to state-run gambling, many also faced problems with the IRS. University of Buffalo sociologist H. Roy Kaplan interviewed around 100 early lottery winners in the mid-1970s and found most of them happy, despite these challenges. Nonetheless, a narrative was born. “Instant millionaires: Dream becomes nightmare for some,” one 1976 headline noted. “Million-dollar winners find reasons to cry in their champagne,” read another.

The myth has been with us ever since. With the rise of rollover jackpot games in the 1980s, prizes got a lot bigger, and the tragedies suffered by some winners became even more dramatic: Jack Whittaker, a West Virginia man, won $314.9 million in 2002. He was robbed multiple times and lost a granddaughter to a drug overdose, an event he blamed on the windfall. Abraham Shakespeare was killed by an acquaintance three years after winning $30 million in 2006.

William Post won $16.2 million in 1988 and spent lavishly. He quickly faced legal troubles, and his brother tried to hire someone to kill him and his sixth wife. Post died broke in 2006. A headline from the satirical website The Onion, the day after a record-breaking 2012 jackpot, captured the prevailing wisdom about lucky lottery players: “Powerball Winners Already Divorced, Bankrupt.”

But unlucky winners like Post, Whittaker, and Shakespeare are the exception, not the rule. Their stories are repeated so often not because they are representative but because they are some of only a few examples of regretful winners. The vast majority of jackpot recipients collect their novelty checks at press conferences and are never heard from again.

The non-miserableness of lottery winners is borne out by studies from across the globe. Research into winners in Germany, Singapore, and Britain found that winning the lottery does, in fact, make people happier, and a 2004 study found that 85.5 percent of winners in Ohio kept working, a sign of how many carried on with their normal, pre-jackpot lives. A commonly cited statistic about the percentage of lottery windfall recipients who wind up bankrupt—often attributed to the National Endowment for Financial Education—was refuted by the organization in 2018. Money, it seems, really can buy happiness.

And yet, the myth endures. Stories about the lottery winner “curse” are deployed whenever jackpots approach the billion-dollar mark. Though he won his jackpot 34 years ago, William Post’s story was retold in a Washington Post article just last week, under the headline “s Mega Millions hits $1 billion, winning doesn’t mean a happy ending.” Why, despite all the available evidence, does the myth persist? What does it mean that this narrative is believed so widely?

Gambling has long been an alternative form of upward mobility in the United States. For anyone who could not or would not climb the traditional class ladder—or who faced discrimination in the mainstream economy—lotteries offered a seemingly fair shot at the American Dream. Especially over the last forty years, as economic opportunity has dried up or became concentrated in certain pockets of the country, lotteries have served as an important means of trying for a new life.

But Americans’ enduring love of gambling has long been in conflict with an important element of the nation’s mythology: that the United State is a meritocracy founded on hard work, a place where the smart, the savvy, and the deserving rise to the top, no matter their background. The implication of this ethos is that hard work always yields a just reward. By design, the meritocracy leaves little room for chance.

In this context, the tale of the miserable winner is less a human-interest tabloid tale and more a moralizing lesson about wealth, merit, and class mobility.

All of these stories bear a single message: it is not healthy to win a windfall. The implication is that if someone won money through gambling, they had somehow violated the natural order of the universe and would inevitably suffer a comeuppance to restore things to their proper place.

The myth reinforces the supposed direct connection between work and merit. Because these winners lost it all, their stories suggest that if they had worked for their fortune, they would have truly deserved it. And anyone who deserves a fortune would know how to live with it, and such a fate would not befall them.

The tale of the regretful winner seems to confirm that a society built on luck is dangerous, even for the very lucky.

The myth, then, is not just an outdated and factually inaccurate narrative. It is a story that reinforces the idea that hard work always and automatically earns just rewards. And it disparages anyone who reasons that it is worth their while to search for an alternative route to the American Dream.

So lottery fans across the country can play with confidence, and can buy a lottery ticket (or five) when a jackpot like Friday night’s is in the offing, secure in the knowledge that a windfall is unlikely to invite a life of pain, suffering, and regret. The bad news, of course, is that they still face nearly impossible odds of winning. But American gamblers have faced long odds for centuries, and it should not be surprising that so many are so eager for a chance to test their luck.

Source: Why winners of jackpots like the Mega Millions are, contrary to popular belief, probably going to be just fine.

Related contents:

Winning lottery jackpot is lucky for some, tragic for others Belleville News-Democrat, Illinois

16:22
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23:09 Fri, 29 JulLas Vegas Nevada Policing

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Securing Your Digital Life The Finale Debunking Worthless Security Practices

Information security and privacy suffer from the same phenomenon we see in fighting COVID-19: “I’ve done my own research” syndrome. Many security and privacy practices are things learned second- or third-hand, based on ancient tomes or stuff we’ve seen on TV—or they are the result of learning the wrong lessons from a personal experience.

I call these things “cyber folk medicine.” And over the past few years, I’ve found myself trying to undo these habits in friends, family, and random members of the public. Some cyber folkways are harmless or may even provide a small amount of incidental protection. Others give you a false sense of protection while actively weakening your privacy and security. Yet some of these beliefs have become so widespread that they’ve actually become company policy.

I brought this question to some friends on InfoSec Twitter: “What’s the dumbest security advice you’ve ever heard?” Many of the replies were already on my substantial list of mythological countermeasures, but there were others that I had forgotten or not even considered. And apparently, some people (or companies… or even vendors!) have decided these bad ideas are canon.

If I’m repeating myself from previous articles, it’s only because I keep hearing these bad pieces of advice. This article won’t eradicate these practices, sadly—they’re so embedded in culture that they will continue to be passed down and practiced religiously until the technological weaknesses that allow them to exist have faded into antiquity. But together we can at least try to end the madness for those in our circles of influence.

Myth: Thou shalt change thy password every 30 days

Passwords have been part of computer security since 1960, when Fernando Corbató added passwords for personal files to MIT’s Compatible Time-Sharing System (CTSS). And almost immediately, they became, as Corbató himself admitted, “a nightmare.” Since then, all sorts of bad advice (and bad corporate policy) has been disseminated about how to use, manage, and change passwords.

Technology limits have in the past been the main thing dictating password policy—limits on the number and type of characters, for example. The low security of short passwords led to policies that required that passwords be frequently changed. But modern operating systems and security systems have made the whole short-password-versus-frequent-password-change dance obsolete, right?

Apparently not. Not only have these folkways continued to be used to log in to personal computers at work, but they’ve been integrated into consumer services on the web—some banking and e-commerce sites have hard maximum sizes for passwords. And—likely because of poor software design and fear of cross-site scripting or SQL injection attacks—some services also limit the types of characters that can be used in passwords. I guess that’s just in case someone wants to use the password “password’); DROP TABLE users;–” or something.

Regardless of whether we’re talking about a password or a PIN, policies that limit length or characters weaken complexity and security. Long passwords with characters such as spaces and punctuation marks are more memorable than arbitrary numbers or leetspeak morphs of words. Microsoft’s definition of a PIN is, essentially, a hardware-specific password that controls device access and login credentials based on Trusted Platform Module black magic; a four-digit PIN for device access is not more secure than one based on letters and numbers if someone has stolen your computer and is banging away on it at their leisure.

Pick a sufficiently long and complex password for a personal or work computer, and you should only have to change it if it’s been shared with or stolen by someone else. Changing passwords every 30 days only makes passwords harder to remember and can cause people to develop bad password-creation workarounds that result in weaker passwords—for example, by incrementing numbers at the end of them:

  • Pa55w0rd1
  • Pa55w0rd2
  • Pa55w0rd3
  • …you can see where this madness leads

So pick one complex but memorable password for your computer login or your phone, like XKCD suggests (though don’t use the one in the comic—maybe generate one with Diceware!). Don’t reuse it anywhere else. And don’t change it unless you have to.

Myth: Don’t write it down!

Many of us have seen the worst-case scenario in password management: passwords on Post-it notes stuck to monitors in cubicle-land, just waiting to be abused. This habit has led many a would-be security mentor to cry out, “Don’t write down your passwords!”

Except you probably should write them down—just not on a Post-it in your cubicle. Many two-factor authentication services actually promote printing and saving recovery codes in the event you lose access to your second-factor app or device, for example. And you can’t save device passwords in a password manager, can you?

Some people insist on writing passwords in a notebook (Hi, Mom!). Never tell these people they’re wrong, but do encourage them to do this only for passwords that can’t be stored in a password manager or might be needed to recover backups and services if a device is damaged or lost—for example, if you have an Apple ID. You want these high-value passwords to be complex and memorable, but they’re used infrequently, so they may be more easily forgotten. Go ahead, write them down. And then put the written passwords (and your 2FA recovery codes!) in a nonpublic, safe place you can access when things go awry.

There is something you should not do with passwords, however, and that is keeping them in a text file or other unencrypted format. In a recent intrusion incident I was reviewing, one of the first things the criminals managed to do was find a file called Password List.xlsx. You can imagine how things went from there. And apparently this happens on the regular at some companies:

Now, if these files were password-protected Office documents, there’d at least be some hope—since Office uses AES encryption and does some serious SHA-1 shuffling of passwords to generate the keys in more recent versions. In instances when you can’t keep passwords in a password manager but need to keep track of them, this is an acceptable level of security in most cases.

Myth: 2FA is 2 scary 4 me

I’m a major proponent of two-factor authentication (“2FA”) as a way to protect login credentials; it has saved me a few times from having accounts hacked after provider breaches revealed my passwords. (There was also the one time when I lost access to an email account because a domain-name provider decided not to auto-renew my personal domain and instead sold it to a scam blog operator. I’ll leave it to you to guess which registrar did me dirty that way.) But I frequently see people deciding not to use 2FA because they saw somewhere that 2FA via text message is less secure, but they didn’t see the other part about using an authenticator app or other method instead if possible. And then they erroneously reached the conclusion that foregoing 2FA is more secure than 2FA with SMS.

Let me be clear: any 2FA is better than no 2FA. And with the usual types of brute-force attempts attackers make against common cloud services, any 2FA will render about 90 percent of these attempts totally unsuccessful (and the other 10 percent of the time will just result in a potentially recoverable denial of service). You definitely want some form of 2FA on an Amazon account or anything that has any ties to your purchasing information, no matter what kind of 2FA it is.

But just having 2FA is not a guarantee that someone won’t succeed in getting what they want. Some phishing attacks are now managing to get around two-factor authentication by using 2FA “passthrough” attacks:

If you receive an email with a link that takes you to a website requesting your credentials, and you then get a 2FA alert for your login, that does not necessarily mean that the link was legitimate and that you should give the code or tap the “approve” button. This could be an attempt to simply have you assist the attacker. Take a hard look at that link. Then call your security team, maybe. (My current employer’s security team attempts to 2FA phish me two or three times a month these days.)

So use 2FA. But be mindful of your login requests, and don’t approve weird ones.

Myth: My VPN protects me!

A few weeks ago I mentioned that, for most normal Internet usage, virtual private networks are kind of pointless now. All they really do (when properly configured) is hide the Domain Name Service requests you make and the resulting IP addresses you visit from your Internet Service Provider. This (mostly) prevents your ISP from collecting data about your Internet habits—and instead passes that privilege on to the VPN provider you’re using.

VPNs are good for some situations:

  • If you’re working from home and you need to access resources on the corporate LAN, you probably need to use the corporate VPN
  • If you’re stealing BBC content from Great Britain by watching it in the US without paying TV tax—assuming the Beeb has not yet blocked your VPN provider
  • If you’re pretending to be in another country to fool Google or other sites into giving you localized results for that geographic location, or otherwise working around some form of geoblocking

That’s about it. Otherwise, VPNs aren’t much more effective in protecting your privacy than what you already get from visiting sites that use modern Secure HTTP (HTTPS).

This doesn’t prevent VPN providers from using scare-tactic advertising (or in some cases, actually using fake alerts and other sorts of manipulative and illegal “advertising”) to drive you toward downloading VPNs for your computer or phone. If a friend or relative tells you they got a notification saying they had 1,000 viruses on their iPhone and that they needed to install a VPN right away, make sure you walk them through how to remove that app immediately (and also how to report a fraudulent application to Apple, Google, and the Federal Trade Commission).

Now, if your goal in life is to make sure that Comcast, AT&T, Verizon, Spectrum, T-Mobile, and all the rest know as little about your Internetting as possible and you’ve done due diligence on your VPN provider’s privacy disclosure, then go right ahead and VPN. Just don’t freak out too much when you have to go through a thousand CAPTCHAs to visit a site because some denial of service bro has been using the same VPN exit point as you. (It’s also important to understand that, unless you can actually audit your VPN provider’s privacy policy yourself, you can’t do effective due diligence.)

Myth: You don’t need antivirus on that

Just like fear of 2FA, some people swear that antivirus software is unnecessary, because:

  • “I have a firewall that blocks all that stuff”
  • “I don’t visit porn sites”
  • “We don’t need antivirus on the servers, just the desktops”

… and variations of these.

Microsoft Defender, up to date on a properly configured Windows 10 or Windows 11 system, is pretty good for blocking known threats. Microsoft’s security team has done a lot to raise the bar of its malware protection. But the number of improperly configured, half-disabled, non-updated systems I have had the privilege to examine forensically does not indicate to me that the majority of computers connected to Internet-adjacent networks are “properly configured Windows” for any number of reasons.

If a piece of software tells you that you need to disable the antivirus software for a folder in order for it to work, my advice is to just not use that software. There have been plenty of examples of how bad not following this advice can turn out—I lost most of my Independence Day weekend thanks to one in particular.

Stopping the madness

If there’s one cyber folkway that drives me the most nuts, it’s the widely held belief that people can achieve security through obscurity. “Why would they hack me? I’m not anyone special” are famous last words before a ransomware attack.

True fact: I’m proud of my parents for remembering all the things I’ve told them about identifying digital scams, and I lose much less sleep since my parents started doing most of their Internetting on iPads. The less time they spend reading email or browsing the web on their desktops, the better, because using up-to-date iOS devices significantly reduces their attack surface (at least from malware). But all cell phones have some security risk associated with them, and it’s not just smartphones.

It may not be possible through your own singular efforts to get your company to change its password policy. But if enough people gently persuade others to stop following flawed advice (advice they’ve received from people who probably haven’t exactly done themselves any privacy or security favors), then maybe we can avoid a few million dollars’ worth of cybercrime. (And if you’re an IT decision-maker or you sit on your company’s IT steering committee, then it’s time to weigh in and do your part!)

If you’ve seen or heard any particularly flawed information security or privacy advice, please share it in the comments here. The only way we can stop these sorts of bad security memes from propagating further and end cyber quackery is by pointing out instances every time we hear or see them.

Sean Gallagher is a former IT editor and national security editor at Ars Technica. A University of Wisconsin grad, he wrote his first program in high school on a DEC PDP-10, and his first database app on a dual-floppy Apple II.

Source: Securing your digital life, the finale: Debunking worthless “security” practices | Ars Technica

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Digital Transformation Depends on Diversity

Across industries, businesses are now tech and data companies. The sooner they grasp and live that, the quicker they will meet their customer needs and expectations, create more business value and grow. It is increasingly important to re-imagine business and use digital technologies to create new business processes, cultures, customer experiences and opportunities.

One of the myths about digital transformation is that it’s all about harnessing technology. It’s not. To succeed, digital transformation inherently requires and relies on diversity. Artificial intelligence (AI) is the result of human intelligence, enabled by its vast talents and also susceptible to its limitations.

Therefore, it is imperative for organizations and teams to make diversity a priority and think about it beyond the traditional sense. For me, diversity centers around three key pillars.

People

People are the most important part of artificial intelligence; the fact is that humans create artificial intelligence. The diversity of people — the team of decision-makers in the creation of AI algorithms — must reflect the diversity of the general population.

This goes beyond ensuring opportunities for women in AI and technology roles. In addition, it includes the full dimensions of gender, race, ethnicity, skill set, experience, geography, education, perspectives, interests and more. Why? When you have diverse teams reviewing and analyzing data to make decisions, you mitigate the chances of their own individual and uniquely human experiences, privileges and limitations blinding them to the experiences of others.

One of the myths about digital transformation is that it’s all about harnessing technology. It’s not.

Collectively, we have an opportunity to apply AI and machine learning to propel the future and do good. That begins with diverse teams of people who reflect the full diversity and rich perspectives of our world.

Diversity of skills, perspectives, experiences and geographies has played a key role in our digital transformation. At Levi Strauss & Co., our growing strategy and AI team doesn’t include solely data and machine learning scientists and engineers. We recently tapped employees from across the organization around the world and deliberately set out to train people with no previous experience in coding or statistics.

We took people in retail operations, distribution centers and warehouses, and design and planning and put them through our first-ever machine learning bootcamp, building on their expert retail skills and supercharging them with coding and statistics.

We did not limit the required backgrounds; we simply looked for people who were curious problem solvers, analytical by nature and persistent to look for various ways of approaching business issues. The combination of existing expert retail skills and added machine learning knowledge meant employees who graduated from the program now have meaningful new perspectives on top of their business value. This first-of-its-kind initiative in the retail industry helped us develop a talented and diverse bench of team members.

Data

AI and machine learning capabilities are only as good as the data put into the system. We often limit ourselves to thinking of data in terms of structured tables — numbers and figures — but data is anything that can be digitized.

The digital images of the jeans and jackets our company has been producing for the past 168 years are data. The customer service conversations (recorded only with permissions) are data. The heatmaps from how people move in our stores are data. The reviews from our consumers are data. Today, everything that can be digitized becomes data. We need to broaden how we think of data and ensure we constantly feed all data into AI work.

Most predictive models use data from the past to predict the future. But because the apparel industry is still in the nascent stages of digital, data and AI adoption, having past data to reference is often a common problem. In fashion, we’re looking ahead to predict trends and demand for completely new products, which have no sales history. How do we do that?

We use more data than ever before, for example, both images of the new products and a database of our products from past seasons. We then apply computer vision algorithms to detect similarity between past and new fashion products, which helps us predict demand for those new products. These applications provide much more accurate estimates than experience or intuition do, supplementing previous practices with data- and AI-powered predictions.

At Levi Strauss & Co., we also use digital images and 3D assets to simulate how clothes feel and even create new fashion. For example, we train neural networks to understand the nuances around various jean styles like tapered legs, whisker patterns and distressed looks, and detect the physical properties of the components that affect the drapes, folds and creases. We’re then able to combine this with market data, where we can tailor our product collections to meet changing consumer needs and desires and focus on the inclusiveness of our brand across demographics.

Furthermore, we use AI to create new styles of apparel while always retaining the creativity and innovation of our world-class designers.

Tools and techniques

In addition to people and data, we need to ensure diversity in the tools and techniques we use in the creation and production of algorithms. Some AI systems and products use classification techniques, which can perpetuate gender or racial bias.

For example, classification techniques assume gender is binary and commonly assign people as “male” or “female” based on physical appearance and stereotypical assumptions, meaning all other forms of gender identity are erased. That’s a problem, and it’s upon all of us working in this space, in any company or industry, to prevent bias and advance techniques in order to capture all the nuances and ranges in people’s lives. For example, we can take race out of the data to try and render an algorithm race-blind while continuously safeguarding against bias.

We are committed to diversity in our AI products and systems and, in striving for that, we use open-source tools. Open-source tools and libraries by their nature are more diverse because they are available to everyone around the world and people from all backgrounds and fields work to enhance and advance them, enriching with their experiences and thus limiting bias.

An example of how we do this at Levi Strauss & Company is with our U.S. Red Tab loyalty program. As fans set up their profiles, we don’t ask them to pick a gender or allow the AI system to make assumptions. Instead, we ask them to pick their style preferences (Women, Men, Both or Don’t Know) in order to help our AI system build tailored shopping experiences and more personalized product recommendations.

Diversity of people, data, and techniques and tools is helping Levi Strauss & Co. revolutionize its business and our entire industry, transforming manual to automated, analog to digital, and intuitive to predictive. We are also building on the legacy of our company’s social values, which has stood for equality, democracy and inclusiveness for 168 years. Diversity in AI is one of the latest opportunities to continue this legacy and shape the future of fashion.

By: Katia Walsh

Source: Digital transformation depends on diversity | TechCrunch

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