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Employees who practice mindfulness meditation are less motivated, having realized the futility of their jobs

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In the NYT, a pair of behavioral scientists describe a forthcoming Organizational Behavior and Human Decision Processes article (Sci-Hub mirror) that studied the effect of mindfulness meditation (a trendy workplace moral-booster) on workers' motivation and performance. (more…)

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jafarim
1 day ago
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Remote work is here to stay. Be good at it.

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So, how’s remote work working for you?

I hear this question fairly often. Usually when we plan a collaboration meeting. Oh, I say - DockYard has been full-remote for some time. So we can meet anywhere – and we’re happy to come to your office to collaborate. Folks seem a bit surprised at first. Then, maybe considering how it might feel to work remotely full time themselves, everybody asks: how’s this remote work situation working out for you?

What I want to say in response is, remote working is like having a boat. Or a puppy. When it’s good, it’s good. It’s a responsibility. Time it well, and you’ve got tremendous freedom. It can make you happier.

Remote work is a thing, even if you’ve got an office

More and more teams work remotely now. The video calling technology has been getting better, and expectations have kept up. With reliable cell connections in the majority of the US, web based office tools and compact laptops – more businesses will schedule business-y things in transit, or outside the office. We may plan to do user interviews or meet with stakeholders remotely because they’re located far away, even if we on the DockYard team all call in from our office.

I believe we’ve reached a tipping point. Any professional is expected to have a base level of remote-work literacy. This does not mean working all the time, or pulling nights and weekends. It does mean that you’re expected to take responsibility and figure out what you need to connect remotely, and be reasonably good at it.

You can get better at this remote thing

To do design work, you might need time, space, privacy, collaboration with people, sketching tools, reference books, inspiration, a computer with a large display, a light portable laptop, a projector, and focus…. But not all of these things at once!

As a full-remote worker for almost a year, I’ve gotten better at scheduling different types of work, and understanding what I need when. With this, I can take advantage of the freedom remote work offers. Here are some specific tips.

Time your coffee shop visits

Coffee shops can be a great place to work, if you do it right. They can be loud, crowded, and have poor connection. I’ve learned to be OK with all these things potentially happening. I schedule my coffee-shop time for when I need to do work by myself, and can do so on a smaller screen. To stay connected, I check our company Slack at least every 20 minutes, and inform collaborators that I’ve scheduled some writing-time.

If you want to avoid crowds, just schedule your coffee-shop time to off-peak hours. I try to never occupy a table by myself between 11-2pm, when 6 different paying customers could have used it for lunch. When relying on coffee or restaurant spaces for wifi during travel, I plan 3-4 hour stretches at a time, with a walk in between. This way I switch locations, and clear my mind to stay concentrated.

Your calendar isn’t just for meetings

I often block off time on my calendar to mark when I’m doing what. If there’s travel time on a train with spotty wifi, it’s best that my colleagues know this. I get the focus-time when I can write or draw, and they know when I’m less available for video calls.

What’s in my remote-work bag

Maria’s remote working toolkit in a bag

This is my standard remote-working bag arrangement. Here’s why the things I have work for me:

A bag that sits flat on the floor, and is washable lets me be less precious with it, and just set it down next to me for easy access. When I commute regularly with a laptop and do long walks for exercise, I prefer a structured backpack, but it’s not nearly as convenient as this open horizontal bag. This feels like a file cabinet I can carry :)

Your work setting may require a more formal bag (and outfit), but I found that most tech / business environments allow for a reasonably casual look. One of my life goals is to perfect a “hike to the office” style & set of gear, so I can walk a few miles before on mixed terrain even before a meeting.

A pouch with business cards, drawing supplies, and a phone charger. The exact contents change once in a while, but these are the essentials right now. Having to carry these with me (as opposed to storing them in a desk drawer) means I only bring the stuff I actually use.

A notebook! I could, of course, take notes right on my laptop, but I prefer not to. If nothing else, the notebook gives me extra space in addition to what I see on the screen. I currently carry a Muji recycled paper plain notebook, and go through about one of them each month with mostly written notes.

The longer laptop charger cord. This one is important: I used to only bring the compact charger, but found that it reduces my options with power outlets. When I travel, I also carry a power cord with a splitter for situations with sparse outlets.

Two pairs of headphones (not shown) - they are such an essential, that I have a backup old pair in the pouch as well. I find that the Apple earbuds work acceptably well even in noisy environments, and their built-in microphone does a good job at isolating my voice from room noise.

Comfortable walking shoes! I do a lot of walking when I’m working outside the house or office, and being comfortable is key.

A scarf, in any season. You can never predict the temperature inside or out, and I prepare for strong AC even if it’s beautiful weather otherwise. Being comfortable helps me focus, so my scarf habit is non-negotiable.

What I do in the home office

A home office with a Mac computer Disclaimer: NOT my own home office. But a nice one!

Clear your desk between work and personal projects. If you don’t have a dedicated room and desk for work, you may see things related to personal projects in your work space. Or, you might be relaxing at home in the evening, and see a work note that snaps you back into the work mindset. I prefer to be focused on one thing at a time - and to do this, I do my best to clear the desk between uses.

Find meeting-spaces for meetings. Since we’ve become remote by default, we are more proactive about scheduling an in-person meeting. When we do, we get the most out of it by renting a dedicated space, often providing lunch, and in general - celebrating the chance to get together.

Take advantage of off-peak travel. Because I largely control when I can do specific work, I can often travel off-peak, and get a better experience. For example, I can work from home 8-10, then travel to a meeting in the late morning, come back sometime in the afternoon, and finish up working from home. Even though my day included commuting, the off-peak hours reduce the stress and length of the commute. However, I also learned that you can be too off-peak: traveling at 10am feels great, but buses and trains have longer wait times midday, or later in the evening.

Batch your work. Because I can plan my own work, I often have the flexibility to batch like kinds of work together. For example, if I need to get roughly 12 hours of writing or editing done in a week, I can easily batch some of those hours to happen on the same day, and schedule a work-from-coffee-shop time. To balance this out, I might have a very focused day working from home, surrounded with paper sketches, and taking full advantage of my large display for detailed visual design work. Some of my work days can involve focused reading and research. When the weather is nice, who is to say those days shouldn’t happen at the cape?

Take strategic walks out of the house! I can’t recommend walking enough. When you’re in an office, you’re forced to move between meeting-rooms, and to walk during the commute. Working from home can feel isolating specifically because you have the option to stay in the same few square feet of space all day if you choose to. I found that if when I actively offset my comfortable at-home situation with brisk walks, I am much more productive and focused. And, scheduling part of your workday to happen at a coffee shop can give you just the nudge you need to get up and walk somewhere.

tl;dr:

Remote work is here to stay. And just like owning a boat, if you take responsibility, and do it right – it’s a good thing. You will no doubt feel isolated and too remote at times. But I think I felt that way sometimes even sitting on the bus, uncomfortable and tired.

Automattic, the company behind WordPress, recently closed their San Francisco office space. It was lovely, and they had the money to keep it up – but the employees simply weren’t using the space.

I expect similar transitions to happen for many companies going forward. Some may keep an office, but expect workers to have the remote-work skills when needed. As a knowledge worker, it’s to my advantage to get good at remote work, and then choose whether and when an office makes sense.

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jafarim
24 days ago
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Facebook Deleted 583 Million Fake Accounts in the First Three Months of 2018

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Facebook said Tuesday that it had removed more than half a billion fake accounts and millions of pieces of other violent, hateful or obscene content over the first three months of 2018. From a report: In a blog post on Facebook, Guy Rosen, Facebook's vice president of product management, said the social network disabled about 583 million fake accounts during the first three months of this year -- the majority of which, it said, were blocked within minutes of registration. That's an average of over 6.5 million attempts to create a fake account every day from Jan. 1 to March 31. Facebook boasts 2.2 billion monthly active users, and if Facebook's AI tools didn't catch these fake accounts flooding the social network, its population would have swelled immensely in just 89 days.

Read more of this story at Slashdot.

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jafarim
35 days ago
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Class Action Suit Filed Against Apple Over the Keyboards in MacBook Pro and MacBook Laptops

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On Friday, Apple was hit with a class action lawsuit over the butterfly-switch keyboards, found on the current generation MacBook Pro and MacBook lineups, that have plagued its customers since they were released in 2015. The suit, filed in the Northern District Court of California, alleges that Apple "promoted and sold laptops it knew were defective in that they contain a keyboard that is substantially certain to fail prematurely," The Outline reports, and that selling these computers not only directly to its customers but also to third party retailers constitutes a violation of good faith. From the report: The Outline was the first outlet to substantially cover the magnitude of the issue, writing that Apple Geniuses responsible for diagnosing and repairing these Apple computers would benevolently attribute dead keys and double-spacing spacebars to a "piece of dust" stuck under the keyboard. Under Apple's warranty, Geniuses might offer to replace the entire top case of the computer, a process that takes about a week. Out of warranty, it costs about $700 to replace this part on a MacBook Pro. Apple has declined repeatedly to comment on the issue, but directs sufferers to a support page that instructs users how to tilt the computer at an angle, blow canned air under the malfunctioning keys, light candles arranged in the shape of a pentagram, and recite an incantation to Gaia in hopes of fixing their machines. Earlier this month, users kickstarted a petition on Change.org that calls on Apple to recall MacBook Pro units released since late 2016 over the defective keyboard. The petition has garnered about 20,000 signatures. Widely respected iOS developer and Apple commentator Marco Arment tweeted on the news, "We can't know for sure that Apple knew the 2016 keyboards were defective and sold them anyway. But it's hard to see how they couldn't have known. They were released 18 months earlier in the 12" MacBook, and those had the same problems with high failure rates from the start."

Read more of this story at Slashdot.

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jafarim
36 days ago
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Deep Learning for Electronic Health Records

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When patients get admitted to a hospital, they have many questions about what will happen next. When will I be able to go home? Will I get better? Will I have to come back to the hospital? Having precise answers to those questions helps doctors and nurses make care better, safer, and faster — if a patient’s health is deteriorating, doctors could be sent proactively to act before things get worse.

Predicting what will happen next is a natural application of machine learning. We wondered if the same types of machine learning that predict traffic during your commute or the next word in a translation from English to Spanish could be used for clinical predictions. For predictions to be useful in practice they should be, at least:
  1. Scalable: Predictions should be straightforward to create for any important outcome and for different hospital systems. Since healthcare data is very complicated and requires much data wrangling, this requirement is not straightforward to satisfy.
  2. Accurate: Predictions should alert clinicians to problems but not distract them with false alarms. With the widespread adoption of electronic health records, we set out to use that data to create more accurate prediction models.
Together with colleagues at UC San Francisco, Stanford Medicine, and The University of Chicago Medicine, we published “Scalable and Accurate Deep Learning with Electronic Health Records” in Nature Partner Journals: Digital Medicine, which contributes to these two aims.
We used deep learning models to make a broad set of predictions relevant to hospitalized patients using de-identified electronic health records. Importantly, we were able to use the data as-is, without the laborious manual effort typically required to extract, clean, harmonize, and transform relevant variables in those records. Our partners had removed sensitive individual information before we received it, and on our side, we protected the data using state-of-the-art security including logical separation, strict access controls, and encryption of data at rest and in transit.

Scalability
Electronic health records (EHRs) are tremendously complicated. Even a temperature measurement has a different meaning depending on if it’s taken under the tongue, through your eardrum, or on your forehead. And that's just a simple vital sign. Moreover, each health system customizes their EHR system, making the data collected at one hospital look different than data on a similar patient receiving similar care at another hospital. Before we could even apply machine learning, we needed a consistent way to represent patient records, which we built on top of the open Fast Healthcare Interoperability Resources (FHIR) standard as described in an earlier blog post.

Once in a consistent format, we did not have to manually select or harmonize the variables to use. Instead, for each prediction, a deep learning model reads all the data-points from earliest to most recent and then learns which data helps predict the outcome. Since there are thousands of data points involved, we had to develop some new types of deep learning modeling approaches based on recurrent neural networks (RNNs) and feedforward networks.
Data in a patient's record is represented as a timeline. For illustrative purposes, we display various types of clinical data (e.g. encounters, lab tests) by row. Each piece of data, indicated as a little grey dot, is stored in FHIR, an open data standard that can be used by any healthcare institution. A deep learning model analyzed a patient's chart by reading the timeline from left to right, from the beginning of a chart to the current hospitalization, and used this data to make different types of predictions.
Thus we engineered a computer system to render predictions without hand-crafting a new dataset for each task, in a scalable manner. But setting up the data is only one part of the work; the predictions also need to be accurate.

Prediction Accuracy
The most common way to assess accuracy is by a measure called the area-under-the-receiver-operator curve, which measures how well a model distinguishes between a patient who will have a particular future outcome compared to one who will not. In this metric, 1.00 is perfect, and 0.50 is no better than random chance, so higher numbers mean the model is more accurate. By this measure, the models we reported in the paper scored 0.86 in predicting if patients will stay long in the hospital (traditional logistic regression scored 0.76); they scored 0.95 in predicting inpatient mortality (traditional methods were 0.86), and they scored 0.77 in predicting unexpected readmissions after patients are discharged (traditional methods were 0.70). These gains were statistically significant.

We also used these models to identify the conditions for which the patients were being treated. For example, if a doctor prescribed ceftriaxone and doxycycline for a patient with an elevated temperature, fever and cough, the model could identify these as signals that the patient was being treated for pneumonia. We emphasize that the model is not diagnosing patients — it picks up signals about the patient, their treatments and notes written by their clinicians, so the model is more like a good listener than a master diagnostician.

An important focus of our work includes the interpretability of the deep learning models used. An “attention map” of each prediction shows the important data points considered by the models as they make that prediction. We show an example as a proof-of-concept and see this as an important part of what makes predictions useful for clinicians.
A deep learning model was used to render a prediction 24 hours after a patient was admitted to the hospital. The timeline (top of figure) contains months of historical data and the most recent data is shown enlarged in the middle. The model "attended" to information highlighted in red that was in the patient's chart to "explain" its prediction. In this case-study, the model highlighted pieces of information that make sense clinically. Figure from our paper.
What does this mean for patients and clinicians?
The results of this work are early and on retrospective data only. Indeed, this paper represents just the beginning of the work that is needed to test the hypothesis that machine learning can be used to make healthcare better. Doctors are already inundated with alerts and demands on their attention — could models help physicians with tedious, administrative tasks so they can better focus on the patient in front of them or ones that need extra attention? Can we help patients get high-quality care no matter where they seek it? We look forward to collaborating with doctors and patients to figure out the answers to these questions and more.
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jafarim
42 days ago
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Earth Temperature Timeline

15 Comments and 64 Shares
[After setting your car on fire] Listen, your car's temperature has changed before.
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popular
643 days ago
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jafarim
644 days ago
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14 public comments
tedder
638 days ago
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Keep arguing about parking spaces, XKCD edition.
Uranus
sjk
643 days ago
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Proof that painting, pottery, rope, and bows and arrows cause Global Warming. All we need to do, is revert our technology to those halcyon days and all will be right with the world.
Florida
srsly
644 days ago
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All these likes and shares, even Samuel can't pull this attention!
Atlanta, Georgia
tante
645 days ago
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XKCD's brilliant visualization of global warming.
Oldenburg/Germany
DerBonk
645 days ago
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Munroe is on the top of his game with this web comics essay. Very disturbing. Summer is coming.
Germany
gangsterofboats
645 days ago
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Fossil fuels will solve the problem.
MaryEllenCG
645 days ago
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Yeah, we're fucked, because too many people believe climate change is a hoax.
Greater Bostonia
kazriko
645 days ago
I'd say it's because of doctrinare belief that the only way to stop climate change is to stop emitting carbon. I believe you'd make far more headway if you said that instead of a carbon tax, you had to transfer money to those who design and maintain carbon sinks. That would give people more incentive to create the technology to remove CO2 from the air, and to not cut down forests, etc.
stefanetal
643 days ago
@kazriko Your proposal is about as sensible as letting everybody take your stuff and then hiring people to look for it after a week. It will create costs and employment for looking. But you won't end up with much stuff. Not using the 100x more expensive technology isn't doctrinaire.
kazriko
643 days ago
You're not going to make any headway with the idea that everyone must immediately stop all of the things that make them healthy, prosperous, and happy though. The technology is only expensive because nobody has put money into the research and development of it. Even the drastic step of stopping emissions does nothing whatsoever for the problem because you have to do something about what is already in the air. If you want to actually solve the problem, then funding this research is the only way to actually do it.
stefanetal
643 days ago
Ahm, it's a carbon tax, like a sales tax, it won't 'stop all of the things that make [people] healthy, prosperous, and happy' any more than current sales taxes do. You might as well suggest people not be allow to take all the stuff they see that makes them happy. It's only expensive since property is theft. And if people could take what makes them happy, companies would do research on how to make more cheaply. Maybe the gov should fund research on that instead of wasting it on police. On a less sarcastic note, your view just does't work if you try to write out any basic cost functions based on any input-output technologies. There may be an escape if we get really cheap non-carbon energy, but that's about it. Paying people to put carbon back in the ground if you don't tax others as least as much to take it back out is about as reasonable as say Venezuela buying gasoline on the open market to sell it to 'users' at 10 cents/gallon (who then sell it right back). It may be how the politics play out (see your first sentence), but it doesn't end well (or it needs to be sustained by rationing -- which is where any implementation of your proposal is going).
stefanetal
643 days ago
Also, on 2nd thought, If you want to discuss cost functions and physical constraints on them, I'd be happy to do so non-sarcastically. Writing a good and realistically model of this might help clarify why we disagree and who is right/wrong, under which kinds kinds of assumptions. For instance, sometimes other costs (transportation costs?) do function as the near equivalent of Pigouvian taxes, so things can work out at times for other reasons. I don't see that here.
stefanetal
643 days ago
Real issue is that the climate change 'cost' part is still pretty much all in the future, due to the very very high heat capacity of the ocean and the ocean's slow turnover. Lots of future warming is already fully baked in and many people aren't willing the see it as real yet. And I do expect that using taxes to control carbon emissions is going to look very gentle compared to methods that at least some groups are going to try 50 years from now (say, biological methods to control energy demand by reducing the customer base). So concern about taxes making people unhappy is going to look very pre-crisis quaint.
kazriko
642 days ago
That's quite the wall of text there. I'm not talking about the carbon tax. I'm talking about all of the environmentalists who say that the only solution is the complete ceasing of all emissions, and won't take "nuclear" for an answer. You know, the ones you're referring to as "some groups are going to try." You would be taxing others through this scheme, but you would be then shifting that money to putting carbon back in the ground, instead of shifting it to governments to do... whatever... with. I just don't trust anyone who says that taxes only are a viable answer because it will neither decrease emissions enough, nor will it actually decrease concentrations whatsoever. It alone is not a solution. It is only an intermediate step towards banning all emissions.
stefanetal
642 days ago
You write: "I'm not talking about the carbon tax." I was responding to your 2nd initial sentense: " I believe you'd make far more headway if you said that instead of a carbon tax". And your arguement that carbon can't be in the tax base since taxes are bad is...well, we already have a tax base, just a economically and ecology less good one. Can't follow your other claims, but they strike me as incoherent as articulated (i.e. using word with different coverage in different parts of the argument as if they referred to the same thing, that is 'carbon tax' = 'crazy enviromenatlist", so lets discuss "crazy enviromentalists". You've not shown that carbon taxes are crazy or associated only with crazy enviromentalists. ).
kazriko
642 days ago
The main thing I don't want is for how all of the current taxation schemes seem to be doing it. Emitters are grandfathered in to a certain amount, and if they cut emissions they can sell those credits to others. This basically entrenches all of the existing interests and makes it impossible for new companies to make any headway. Any solution shouldn't give exemptions to the entrenched, only allow those who find ways of mitigating the issue to sell exemptions to others.
kazriko
642 days ago
*sigh* Yes, that sentence doesn't parse the way I was intending. I was meaning instead of ONLY a carbon tax. I didn't also mean "crazy environmentalist" = "carbon tax" but "crazy environmentalist" = "100% end of all carbon emissions" As I said just before, the problem with the tax schemes are that they just go to do whatever, and don't solve the problem, just slightly discourage things rather than solving them. Only a carbon tax will lead to the 100% end of emissions because it won't work, and if it doesn't work, by your own admission people will be doing less gentle methods.
kazriko
642 days ago
You can see what I intended to say by the "transfer money to" thing in the same sentence. That meant transfer money from those who emit carbon to those who remove it.
stefanetal
642 days ago
Ah, mostly a misunderstanging then...:-). We still disagree, but I can dial back to a much more manageable debate...need to run now. I do take the technocratic basline view that Pigouvian taxes are a good starting point, but there are political issues that are serious and hard to model. More later...
Ferret
645 days ago
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:-|
darastar
645 days ago
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This is legit. And also scary?
alt_text_bot
645 days ago
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[After setting your car on fire] Listen, your car's temperature has changed before.
drchuck
645 days ago
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Stonehenge!
Long Island, NY
emdeesee
645 days ago
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Fun fact: If laser-etched onto a 2x4 we use to hit people who say "...but the climate has changed before" over the head, it would be almost seven feet long.
📌 Lincoln, NE ❤️️ Sherman, TX
joeythesaint
645 days ago
And since the most common sizes you find 2x4s in is 6' and 8' long and you wouldn't want to truncate the graph, that means you've got more than an extra foot to extrapolate the data further. Or wrap it with a shirt and tape so you don't get calluses.
jscartergilson
645 days ago
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bookmarked
smadin
645 days ago
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