- Walt Whitman
A good take on why Trumpkins don’t hear what the rest of us hear when President Trump spews incoherent word salad.
Also why I have limited interest in, or energy for, trying to persuade them through rational debate.
I have been baffled by this all along - I could not for the life of me imagine what his supporters were hearing when they listened to him babble incoherently. He’s like a political Rorschach’s test.
I feel like I’ve had the curtain drawn back.
I realized I do this to him too. I’m always trying to figure out WHAT THE FUCK HE MEANS. Only because I don’t like him and what he stands for, I’m actually trying to parse reality from it, so it strikes me as insane.
But if I was predisposed to him, my mind would decide on something that filled out my preconceived expectation.
Humans Brains are so fucking weak and wrong.
If you’ve paid attention to the way racist/generally bigoted white people have talked literally since the dawn of time, this wouldn’t be a surprise to you, but I like the way OT phrased it.
But really people often talk like this when they want to say horrible things about other human beings they know they shouldn’t be saying, it’s just with Trump it suddenly matters can’t he’s flushing our country down the toilet.
See: the way white people have always talked about the mysterious inner city and the infamous black on black crime. Or just black women in general. There are always unfinished sentences about black people/POC and ya’ll never have trouble completely them in your own heads.
It’s like their very own “auto-complete” for searches they know have already been done by their supporters time and time again.
By the way, Fox News has been doing a similar version of this for years. A local columnist pointed out that they often ask absolutely ridiculous questions, but because they ask it in question form, they get wiggle room.
“Does Obama want to kill your grandparents when they go to the doctor?”
Now, the question in itself is open ended, but obviously, you’re set up to believe that, yes, your grandparents will die because of Obama. The onus is on the station to disprove a question like this, but instead they throw a vague, twisted statement out and have two opposing people argue as if both sides of the conversation are equal in value and truth. The subject of the question then the non-clear rebuttal makes the answer seem obvious that Obama is killing your sweet granny and grandpa when they go for a flu shot.
I say all this because this network has been grooming their followers to fill in the blanks from vagueness this entire time. Trump just knows how to fill in just enough words to start the thought process down that way. He’s taken what Fox News started and perfected it.
Is ‘Trumpkins’ actually a term people are using? A little:
I wonder if we can get ‘trumpobabble’ to trend?
Whoever came up with the name “Human Resources” deserves a medal. Such a descriptive, helpful, and seemingly useful name. Why yes, I’m human and I sure could use some resources. Purely viewed by the name, Humans Resources or HR seems like such a great idea. These are the people who are responsible for looking after your people whether it’s their health, compensation, or career.
So, why do we freak out when HR is in the building? What’s with the hush whispers when you see your boss huddled with HR in her office? Layoffs? Reorg? Has anyone seen Ryan today? HR’s presence typically makes folks paranoid. I’ll repeat that: the folks whose job it is to be resources for humans collectively gives us the shakes. What happened?
It’s not HR; it’s your culture.
Disclaimer: I’ve never worked in HR, and all of my observations regarding HR have been made without what I assume is the daily toil of having a gig where the expectations are so high, but corporate support is traditionally low. However, both as manager and as a former employee of an HR-focused start-up, I know a bit.
Simplification: There are all sorts of different jobs inside of HR and depending on the size of your company, your HR team may have one or all of them. Benefits, recruiting, compensation, training, it’s a long list. For the purpose of this article, let’s consider HR to be the folks who are responsible for helping a team thrive. They have many other jobs, but that’s the one I’m thinking about in this piece.
HR is a tough gig. They have constraints which often leads to unique behavior that affects their reputation. Two examples:
- Lack of clear measures. Just like managers, HR folks have fuzzy measures of success. You write code, you fix bugs, you make it 27.5% faster, and everyone can point at that work and say, “You did something of measurable value.” While engineering managers can ride the coattails of this work by completing meta-goals like “Ship on time” or “Deliver the features the customers needs,” HR often has fewer obvious concrete deliverables that directly affect the production and selling of the product.
As a support team and a cost center, HR traditionally does not receive a lot of investment. How many folks is your manager responsible for? Ok, how many is your HR partner responsible for? My guess is your HR person has 10x the number of people for whom they are responsible. This under-resourcing has interesting consequences.
First, because of their limited numbers, they logically gravitate towards informed decision makers because these humans are an early warning system regarding what is and aren’t going well. This network helps keep them as to the state of the company.
Second, because of their allegedly human-related skills, they are called in when there are people-related problems. This means you only see them when something is going down. These infrequent appearances when the sky is falling contributes to their grim reaper reputation.
Finally, when they do arrive because the sky is falling, they are informed because of the carefully built information gathering network, but when they start talking, they don’t sound like you. They, like every group at your company, have a language all their own, which when accompanied with the penchant for showing up when the shit is going down makes their language the language of trouble.
All of these attributes contribute to the problematic reputation of HR. Yet, in two decades of work I’ve discovered that when the team is freaked out by HR, it’s not HR, it’s the culture. Something is rotting.
Culture == Values
Your company has values regardless of whether you’ve painted them on the wall or produced an employee handbook. They exist as a result of the Old Guard employees working together, making decisions, and successfully building the company.
Values exist as stories. Back in our first building, Christine once stayed up all night working on a single performance bug that ended up revealing fundamental flaws in our architecture. The implied value? Persistence or perhaps craftsmanship.
Values exist as people. When I watch Brad run a meeting, I realize how poorly I run my own. The implied value? Everyone’s time is valuable, efficiency, or maybe constant improvement.
Values are principles or standards of behavior, and in a group of humans, they are first defined by the founding employees and then evolved over time by the leadership team. Painting them on the walls or writing them down in an employee handbook makes them accessible and obvious, but it is how these values are consistently applied especially during times of crisis that gives values value.
When I hear, “I don’t trust HR,” I ask, “Why?” The answers vary, “They are political. They are risk mitigators. They protect the company… not the employees.” There are humans in HR who exhibit this behavior. However, it is equally likely there are humans at every level of leadership who exhibit this behavior, and all are allowed to behave in this way because of the values of the company.
Has Anyone Seen Ryan Today?
The rule is: in the absence of information, humans will make up a story to fill the vacuum. When this happens, listen to the story because not only do they usually find the worst case scenario, it’s a situation that reflects the perception of your company’s values.
Where is Ryan? Well, he left early on Friday and was out all day on Monday. I think he’s checked out and you know what we do to checked out people here? HR fires them without warning.
No, HR doesn’t fire people without warning. No, Ryan is not checked out. He’s just sick, and his manager forgot to send a message to the team. The issue here is that the team believes HR has nefarious unchecked power and in my experience they rarely do. They are capable, overworked, emotionally intelligent humans who I call when I need help.
Yes, they swarm around disasters. Yes, they have access to a lot of information. You should hold them to them a high bar. More importantly, you should understand how in the world your team comes to hold seemingly irrational beliefs because their existence is not a sign of their character of your team, it is a sign your culture is rotting.
In theory, collaboration seems simple enough—you just need to be open to ideas and solve problems as a team. Unfortunately, small complications can make collaborating far more cumbersome than you’d think. That’s why we’ve built features to help you avoid collaboration obstacles and get back to working together. Here are four ways Dropbox can help.
1. Your team keeps running out of space
It’s been a productive month: your team just cranked out five launch videos, each translated in a dozen different languages. Unfortunately, all those shared videos now sit in a bloated team folder, causing several employees to run out of local storage space. It’s the sort of problem that starts as a minor nuisance and only gets worse over time.
Instead of making your employees micro-manage their hard drive space, Smart Sync can do it for them. Smart Sync allows your team to place some files in online-only storage, but still lets them access everything right from their desktops. When they open a file stored online, Smart Sync will automatically download it to their computers. Let your team jump straight to sharing their work, rather than worrying how to make room for it.
2. Team conversations are scattered
You sent out details for your ad campaign, and two days later, a dozen co-workers have responded with feedback. Unfortunately, the comments are scattered across three emails, two meetings, a whiteboard, and a text message.
Next time, you can send your campaign plans with Paper. Paper keeps the conversation in one place, regardless of when and how your colleagues respond. Your collaborators can comment on text, photos, or videos; see each other’s feedback; and contribute their own ideas in a doc tracking real-time changes. As the doc owner, you can loop in new reviewers, control who has access, and decide what level of feedback you want, whether comments only or in-doc editing. It’s a shared workspace that keeps everyone engaged and informed.
3. Tracking down collaborators takes too much time
You’re ready for feedback, but it’s been over a week, and half your teammates haven’t said anything. Did they forget about you? Did they miss your message?
Dropbox Business teams can now keep track of collaborators with viewer info—a live-updating look at who’s opened a file and when they last viewed it. You can see who a file’s been shared with, and check who’s viewing now. Need to give someone a nudge? You can see who hasn’t viewed the file yet, and follow up with the right co-workers, all without interrupting the group at large.
4. You can’t control who sees your work
Sometimes you want private feedback from just one or two people. But the last time you sent an early design mock-up over email, your colleague wound up forwarding it to the whole marketing team, prompting an hour of distracting debate.
With Dropbox, you can share a file securely with just a few close colleagues. Dropbox will require your collaborators to sign in first, so only the people you trust can access the file. Once your design is truly ready for primetime, you can create a shared link. Anyone can view files sent with a shared link, even if they don’t have a Dropbox account.
When people spend less time worrying about how they collaborate, they spend more time actually working together. And when you can remove the collaboration snags, you’re much more likely to love the way you work.
From Josh Begley, this quickfire flip book shows every New York Times front page since 1852. Watch the shift from all words, to a handful of small pictures, to larger pictures, to color, and then more color pictures.
Attached is a photo essay inspired by the design stage of the Arbutus Greenway. Other places, it seems, have done things in the public realm that are vaguely similar. And it got me looking.
Here in Puerto Vallarta, Mexico, the city has transformed their seawall (the Malecon) with some major work. Total length is about 2 km. And the work was done in stages over decades. All to vastly improve the experience for locals and tourists alike.
Click a photo for larger versions in the form of a slide show with marvelously insightful captions.
Organizational Theory isn’t a science, though it would like to be. Unfortunately, building a scientific approach requires understanding from a number of fields that themselves are still only aspiring to be sciences. Because psychology, economics, and sociology are a mish-mash of rules of thumb and vague, non-predictive, and generally unfalsifiable “theories”, organizations are reduced to ad-hoc rules and guesswork: critical, but prescientific.
For now, to abuse the parable of the blind men and the elephant, organizational theorists are still groping at their respective elephants, unable to figure out that the trunk is next to the tusks, or even that they are part of the same animal. It’s not a science: if anything, it’s a field of engineering, albeit one without a grounding in physics or Asimovian psychohistory to draw from. Precisely because the field isn’t scientific, understanding the engineering rules of thumb that were developed over time is fantastically useful for a practitioner.
Henry Petroski’s excellent To Engineer is Human introduced me to the history of engineering. Failure is the watchword of that history. Even generations after Newton, science was simply incapable of answering basic engineering questions, like “what load will this beam support?” So engineers developed rules of thumb in different domains that assured safety, grounded in experience. This approach was almost scientific — the theory is that this structure will be stable, and if it’s untrue, it will be falsified all on its own. Organizational Structure is similar: we know a lot about what doesn’t work.
As with most fields, it’s easiest to dissect organisms once they are dead, so I’ll stick to ideas that are older than I am. Understanding the various theses and antitheses won’t lead to synthesis without the basic grounding to unify them, but the history of failed ideas can still give us a map of the pre-scientific minefield of organizational design. Once we’ve traced out the map, I’ll add some ideas about how we can navigate around the unknown dragons, and find useful insights into organizations without actually pretending to understand them.
Prehistory, History, and the Future
The textbooks all try to tell us that the earliest theory of management is F. W. Taylor’s Scientific Management (1911). Before this, according to scholars of the field, “Craftsmen owned their tools, [which] minimized the possibility of management’s establishing general measure of productivity and quality.” But this is a ludicrous contention: cost accounting was well established, and factories were common a century before Taylor developed his insights. When interchangability was discovered, there must have been some theory that preceded Taylor which allowed businesses to optimize their processes — and there was! Unfortunately, it is so basic, and still so prevalent, that people haven’t noticed it.
Intuitive Organizational Theory
Intuitive management is the grandfather of all management theories. Everyone has worked with others in some form or another, and management is just working with others. Some people are batter at this than others, and those best able to manage will be obvious, so there is no need for scientism. Instead, we admit we can’t formalize everything, and let people work it out. And it works!
Well, it works for a while. But at some point, things get a bit too complex, and people need to go corporate or go home. But, as I argued in that post, there is a tremendous advantage to having little structure, and hence little need for organizational theory. And as the world consolidates and bifurcates into lumbering mega-corporations and nimble scavengers and upstarts, the big guys need to realize why they aren’t able to replicate that agility — they are too large for intuition. Instead, they need theory.
Scientism, in the form of “Scientific Management”, reared its efficient head in the late nineteenth century, with clocks and measurements that found tremendous benefit from imposing order on the evidently previously unruly and disordered factory floor. Taylor observed and intervened — and he certainly found room for improvement, like allowing manual laborers rest breaks to increase their efficiency. Unfortunately he also managed to perpetuate the single most destructive management practice: the unthinking application of a paradigm to a complex problem. (This rigidity and oversimplification which replaces intuition is part of why models fail.)
One specific drawback of his approach is due to the Hawthorne effect, where measurement distorts the system it was trying to measure. Specifically, when you pay attention to someone, they get more efficient. It seems, like children, employees thrive on attention. But that means any attempt to improve efficiency by monitoring performance closely will be effective, spurring a proliferation of middle management supervisory roles, with additional costs that begin to offset this additional efficiency. Organizing many layers of management was difficult. Principles were needed to decide how to set them up — it would hardly be efficient and orderly without rules and procedures. And who better to institute strict rules then an authoritarian German sociologist?
Structure and Function
Max Weber’s theories demanded further orderliness in corporations. He took a term intended to critique French government, bureaucracy, and turned it into a principle. The so-called Bureaucratic Management Theory (~1920) was a way to try to ensure that everything in the system worked according to the rules. The successes of the approach are obvious in the increased industrialization of industry. He formalized things like the now nearly universal idea of listing and insisting on rigid job qualifications, and an explicit hierarchy with rigid roles to fill. Actual humans would be shuffled around these systems via systematic processes.
Weber was inspired and informed by Marx’s analyses of the role of capital, but unlike the more utopian Marx, he viewed the tension between owners and employees as unresolvable. At the same time, Weber was aware of the problems of bureaucracy that were being created by the layering of management, but thought that restructuring the system properly would be enough to allow humans to fit. Ironically, the proliferation of his theories and the effects of oppressing workers were a key reason for the later rise of the Marxist approach he disputed. The success of industrializing the workforce made workers just cog-like enough to be efficiently organized into unions. The rise of unions in the wake of scientific management was a counterbalancing force to bureaucratic organization. Of course, this led to a further proliferation of the structural dichotomy of workers and managers, following the Marxist vision. Weber lived to see the beginnings of the ultimately doomed collectivist approaches started in earnest in Russia, a few years before his death in 1920.
But when it’s time to fail because of insufficient appreciation of the problem, everyone fails. And so despite Weber’s opposition to Marxism, it failed to work for much the same reason his own models failed: humans don’t really work that way.
As most of us know, dealing with micromanagement sucks. Unfortunately, measurement and structure require it, to some extent, and the cumulative effects of this were not captured in Taylor’s original short-term studies. The increase in management structure only accelerated in response to the demand for unions, which fed the opposition, and cemented the structure in place. Management was dedicated to maximizing productivity in the face of union demands. This meant that management was precluded from doing anything other than managing work processes and structure, and the tension was resolved by limiting the tools available for managing a workforce, and the tools of scientific management were institutionalized. (Instead of being institutionalized.)
Span of Control and Magical Thinking
One particularly amusing construct in management that came out of Weberian approaches is the span of control. To lay the background for this fanciful notion, we pretend each manager has the same task, of monitoring and managing their reports — which means that all management is, in almost a parody of Weber’s approach, a single clearly defined role to be standardized. Bureaucracies are necessarily hierarchical, for deep reasons I discussed previously, so many people were led to an assumption that management is, or should be, fractal. Each manager has K people they manage, and they are managed by someone with K direct reports as well, going all the way up and down the K-ary tree. The puzzle induced by this simplification is finding the optimal value of K – and this is called “span of control.” Reams of paper have been filled with empirical and theoretical justifications for what the optimal span is, despite lack of conceptual clarity for why this single number is useful, or how it should be applied in the real world.
Several years ago, I had the privilege of hearing Francis Fukuyama speak to an audience of experts in policy and public organizations, and a few interested students like myself, at the RAND Corporation. (It must have been 2012 or early 2013, since he mentioned drafted chapters of his then-upcoming book.) As a side-bar to the discussion, he mentioned his critique of Span of Control in his essay, “Why There is No Science of Public Administration.” Part of the justification given for a span of control of seven, he pointed out, is Miller’s Law. The law states that the number of objects an average person can hold in working memory is about seven. The justification of this, Fukuyama amusingly noted, came from a paper suggestively titled “The Magic Number Seven,” where Miller suggested, tongue-in-cheek, that seven was somehow a universal value.
As Miller concluded: “What about the seven wonders of the world, the seven seas, the seven deadly sins, the seven daughters of Atlas in the Pleiades, the seven ages of man, the seven levels of hell, the seven primary colors, the seven notes of the musical scale, and the seven days of the week? What about the seven-point rating scale, the seven categories for absolute judgment, the seven objects in the span of attention, and the seven digits in the span of immediate memory? For the present I propose to withhold judgment. Perhaps there is something deep and profound behind all these sevens, something just calling out for us to discover it. But I suspect that it is only a pernicious, Pythagorean coincidence.”
Fukuyama pointed out that the adoption of seven for span of control was evidently an application of this magical thinking. In general, simplification to such rules is itself an example of magical thinking, something we see all over. And if this makes sense, you’ll agree that it’s not simply coincidence that the number seven also has deep numerological significance. According to one blog, which is evidently well-respected by Google’s Pagerank, “Number 7 also relates to the attributes of mental analysis, philosophy and philosophical, technicality, scientific research, science, alchemy… ahead of the times.” Perhaps there is something deep and profound about the fact that science and alchemy are grouped here. Perhaps my dismissal of the magical number seven is because I’m not “ahead of the times.” But blind application of similar generalizations in management led to quite a few pernicious management beliefs. So I suspect the magical thinking just mirrors people’s inability to accept that sometimes, simple connections are illusory, and things are complex.
Failing to Integrate Humanity into Management
Backing away from our foray into mysticism, and returning to the realm of scientism-istic “fact”, the rising star of psychology was soon adopted by management theorists. After World War 2, as psychology began to gain more widespread acceptance, the discipline of “Human Relations” was born, with the motivation to provide a human approach to management. Maslow’s work in the 1960s, on Eupsychian Management was an early push in that direction, promoting the primacy of worker actualization as the goal of management. The manager changed from a cog to a coach, creating character, instead of impersonally pushing profitability.
It turns out that this approach, and related ones, failed for almost exactly the opposite reason Taylorism did: it ignored business goals in favor of human factors.
Today, firms like Goldman Sachs proudly say that “our people are our greatest asset.” That may be true, but thankfully for investors, they don’t mean the welfare of their employees or their development as human beings; they mean that people are what allows them to create wealth. Human Relations is now an almost Orwellian euphemism for everything impersonal about business: screening interviews, harassment complaints, legal and liability issues, and of course, firing people.
As a personal aside, at the start of the great recession, I was working at an investment bank. As the most junior member of my group, I suspected I was first up at the chopping block, and eventually my team-lead clumsily made it obvious that I was on my way out. After a few painful days of clumsy excuses about cross-training on the tasks I managed and re-engineered, I was asked to meet with my manager. My manager sat there, uncomfortably. The HR person sitting in the corner (conspicuously failing to provide any of those vaunted eupsychian benefits to anyone involved) would occasionally prompt him. As he read through a literal script, with the obligatory lip-service to encouraging me to view being laid-off as an opportunity, I distinctly remember that the most uncomfortable part for me, having seen this coming for a week or so, was watching my manager forced through the charade.
The process was impersonal, insulting to everyone involved, and inefficiently redundant — which describes the result of these systems in general. Human Relations as originally envisioned as a discipline is a failure. Instead of convincing management to care about workers more than profits, it led to doublespeak, as the HR workers that wanted to be psychologists were forced to be cogs instead.
Systems Management and Premature Optimization
A more recent management model has been suggested is to understand organizations as complex systems. And they are complex systems. The approaches suggested, however, are usually somewhat more nuanced than throwing a copy of Gleick’s Chaos at managers and running away. But unless the question is “what buzzword is being used to obscure our lack of understanding?”, “Complexity” isn’t the answer. We don’t understand most complexity enough for it to be a useful predictive model in scientific fields, so applying it to organizational theory is a lost cause. As one paper puts it, “Organizational theory has shamelessly borrowed from the physical and biological sciences for its models and metaphors. These models and metaphors have been unsatisfactory in predicting the behavior of organizations, and to provide prescriptive designs for creating organizations that are more efficient and effective.”
That noted, there are approaches to complexity that have been useful in the sciences which have had some success in organizational theory as well. My introduction to management and organizational theory, in many ways, was The Fifth Discipline: The Art & Practice of The Learning Organization, (thanks to a fantastic recommendation by Todd Slingsby.) The primary insight of this theory was that there are many quantifiable factors in business, and their relationship can be understood quantitatively — and that then-recent tools in systems theory were the way to get there. Like other approaches, this was insightful, but limited by the lack of rigor in many of the underlying models.
What it got right, however, was that a model for how the components of an organization interact was helpful for lending insight. By simplifying organizations to the simple dynamics of factory physics, approaches like the Theory of Constraints, as explained clearly by Tiago Forte, were able to lend insight to where organizations, once understood, could be improved. This move back towards neo-Taylorism is more sophisticated, and more aware of the failures of the past, but it seems primed for a similar pushback against more globalized, efficient, and inhuman business, and a similar pattern of failure.
So it is useful back a bit to consider how the lack of scientific synthesis and the role of failure has been understood.
Multiple Failures and the Language of Synthesis
Herbert Simon’s 1946 The Proverbs of Administration notes that there are proverbs that are widely accepted, but exactly opposed to each other; “Look before you leap” and “He who hesitates is lost.” In organizational theory, he notes, different accepted aphorisms lead to similarly contradictory conclusions. This was a criticism of much of the pre-scientific wisdom, but it applies to the recommendations of many of the later theories as well.
A later wave of criticism went beyond this basic critique. In 1956, a decade after Herbert Simon’s critique, the journal Administrative Science Quarterly launched. Almost 60 years later, the journal’s editor wrote; “ASQ’s aim was not to provide practical advice to managers but to build an interdisciplinary science of administration that both drew on and contributed to the broader enterprise of social science.” And yet, even now, “it is difficult to point to many areas of settled science when it comes to organizations.” He argues, much to my approval, that the problem retarding progress is a misalignment of metrics, or as I termed this dynamic, underspecified goals. There has been progress, but the scientific elephant remains elusive.
The failure of the field as a science is a problem for researchers but practitioners need to move forward anyway. So how can we manage our understanding in a pre-scientific field? The trick is to exploit the failures of multiple models together.
Obviously the best method is to achieve the grand insights that would coalesce pre-scientific views into a coherent predictive model. Unfortunately, despite standing on the shoulders of giants, I’m much too short to see a way around the obstacles, but I do see ways to peek through to the other side. And the way I want to talk about it is inextricably tied to language. Here, the obvious shoulders on which to stand are those provided of Gareth Morgan, who surveys a set of eight different conceptual metaphors with which to view corporations in his classic Images of Organization. As Venkat notes the book is helpful both for understanding corporations, and understanding how people discuss and understand corporations, because as he notes, “these are not really 8 perspectives, but 8 languages.”
As the political scientist Philip Tetlock notes, using any single model is demonstrably worse than using many. But the problem is more complex than than foxes versus hedgehogs, because those aren’t the only options. As Venkat puts it, hedgehogs have strong views, but ideally are swayed by evidence – the views are weakly held. Strongly holding a single view is being what he calls a cactus. Systems that dictate decisions based on simplified metrics display exactly this failure mode, as I laid out exhaustively in my earlier posts. Of course, using an unchanging set of metaphors is the informal equivalent of this failure mode, and it’s appropriate to approach the topic of organizational dynamics using a different language that that of metrics and models.
As Martin Marty said about religion; “If you only know one religion, you don’t know any.” In a slightly different vein, as the old joke goes, “If a person speaks three languages, they are trilingual, if they speak two, they are bilingual, but what do you call someone who only speaks one language?” “American.” Strict adherents of most religions tend to find comparative religion blasphemous, and American insistence on English smacks of the same type of cultural puritanism. As another old American joke puts it, “There’s no need for foreign languages – if the English in the King James Bible was good enough for St. Paul, why learn any others?” But the reason these jokes exist speaks to a deeper point; lacking comparative understanding is perfectly okay if you possess the sole and complete truth.
This is the equivalent to the internal model principle I’ve discussed; if your model is exactly correct, you only need one. If your language is the only one anyone needs, foreign languages are a waste of time. And if your religion was ordained by god, any deviance or variation is not just worthless, but heresy. But if you think you have such a model of organizations, despite the deep reasons I have laid out for why one can’t exist, you should have better things to do with it than argue the point with me.
Jokes and organizations are like beliefs: if you’ve fully explain them, you’ve killed them. And while we can learn to be multilingual, humorless, and polytheistic, that doesn’t solve the problems with rigidly applying a single paradigm. And for an organization, rigid application of a single paradigm is deadly.
If an institution behaves exactly as incentives suggest it should, it is dying. Institutions are alive to the degree they are unpredictable.
— vgr (@vgr) December 22, 2016
Multilingual and Muddled, or Models and Mosquitoes
Understanding a system must occur on many levels, simultaneously. Speaking multiple languages can be helpful for untangling the umwelt of any particular oeuvre, or allow the speaker to grok the gestalt — rarely. Most of the time, it leads to a muddled mess. As you can see.
So how do we selectively apply the insights of our multiple incorrect models without devolving into a incoherent mess? A concrete example may help.
A mosquito is a component of an ecosystem, with behavior shaped by evolutionary and environmental pressures. At the same time, it is an organism with dietary needs dictated by its digestive system. Of course, it is also a physical system that obeys physical and chemical laws such as conservation of energy. A single aspect of the mosquito’s life, such as its diet, is not shaped by one factor or the other. Instead it is shaped by all of them in different ways.
The mental models we use, however, rarely combine these different classes and levels of understanding. The ecologist, biologist, and chemist read different journals, use different languages, and are only roughly familiar with the fields of the others. This works well when they are advancing their field individually, single-mindedly following their incentives to publish or perish, but it fails as soon as a cross-cutting question is asked.
The relationship between temperature, rainfall, ecology, and prevalence of a mosquito-borne disease can involve models at each of these three levels. Control of this sort of disease requires an understanding of many different aspects of the virus. Female mosquitoes bite people or animals in order to breed; after such a “blood-meal”, they can find a body of still water and lay their eggs. For Zika to spread, a (female) mosquito must first feed on a person with an infection for their blood meal, then, after the virus has time to multiply inside of it, feed on another person, re-transmitting the disease.
The hatching of different species of mosquitoes occurs when eggs previously laid near the water line are re-submerged. Different species lay them in different places, and then compete over resources. If frogs and fish live in the bodies of water, these predators may feed off of larvae after they hatch. If conditions are much more favorable for non-dengue mosquitoes, fewer disease carriers will exist. If temperatures are low, the mosquitoes mature slowly, and the females rarely live to have multiple blood-meals, meaning the disease cannot be spread.
A biologist might come to the conclusion that we need to control the breeding grounds, and advocate removing bromeliads that provide the locations for egg laying. A meteorologist instead focuses on where temperatures would lead to outbreaks. An ecologist could advocate introducing more predator or competitor species. A geneticist might advocate genetic engineering to stop the mosquitoes breeding. An entomologist could recommend potent insect poisons, or suggest when it is safe or unsafe to venture outside. A complete model of all of these factors is unlikely to be feasible, but all of the models can supply parts of a solution. And by considering and applying different approaches, you still don’t arrive at a perfect strategy, but with ongoing work from many angles, you can keep Zika out of Florida.
Diversity – Taking the Good with(out) the Bad
Given my insistence on switching languages and switching models, it should come as no surprise that I’m going to advocate diversity. But diversity isn’t monolithic, and it’s important to differentiate between what I’ll call inclusive diversity versus exclusive diversity. As an example of inclusive diversity, we want a variety of approaches when generating ideas. If we can eliminate insect breeding grounds by asking residents not to leave stagnant water in their yards, we don’t need genetic engineering or climate control. The gains from diversity are much more general than this single example, of course. In a software-oriented example, when a product is aimed exclusively towards people who are like the team building it, more inclusive diversity means a larger potential audience. Similarly, if there’s a way around an intractable coding problem via tweaking the UI, having the UI designer in the scrum can be critical. Being more inclusive creates gains in diversity, but it also has costs.
Exclusive diversity, on the other hand, is accompanied by privileged viewpoints and constraints, or adding additional goals and requirements. Needing to accommodate additional user types is a constraint, while being able to accommodate them is inclusive diversity. Contempt for others is exclusionary; it’s a constraint, and has real costs. So is ignorance.
Blind acceptance of diverse approaches isn’t useful either; we need to be selective about how we utilize diversity in our models. If we have many models providing constraints, showing different ways that a system can fail, we run the risk of eliminating possibilities and approaches instead of finding them.
Getting back to the point of synthesis of different incorrect approaches, balancing different models for organizational theory isn’t about trying to blindly apply multiple conflicting models, and being bound by the constraints of each. It’s about making sure all the approaches have a seat at the table. Esperanto was a disaster because it tried to synthesize instead of allowing for multiple maps. It created a new linguistic map of the world that didn’t particularly lend new insight, but mirrored the constraints of other languages.
Novices at a language frequently import the structure of their native tongue incorrectly into their speech. Once the new language is learned, however, it provides a new map of the world, one that can be integrated with the old one. Which is correct? Neither — all language is approximate, and maps are always only approximations.
Attempts to systematize organizational theory led to attempts to build single unified models, in bouts of physics envy. But this approach is backwards; before you can begin to build a single useful theory, a willingness to change your mind in the face of evidence is the most important thing a scientific mindset can provide. The fox doesn’t know which is the right model in each situation, but by evaluating them all, he can notice when predictions are shared, and when the models diverge, or are unclear. That doesn’t always make the fox’s predictions correct, but it can still keep him from holding on too tightly to the wrong answer.
As you may already know, last Friday – February 17th – we held a new Testday event, for Firefox 52 Beta 7.
Thank you all for helping us making Mozilla a better place – P.Avinash Sharma, Vuyisile Ndlovu, Athira Ananth, Ilse Macías and Iryna Thompson, Surentharan R.A., Subash.M, vinothini.k, R.krithika sowbarnika, Dhinesh Kumar, Fahima Zulfath A, Nagaraj.V, A.Kavipriya, Rajesh, varun tiwari, Pavithra.R, Vishnu Priya, Paarttipaabhalaji, Kavya, Sankararaman and Baranitharan.
From Bangladesh team: Nazir Ahmed Sabbir, Maruf Rahman, Md.Majedul islam, Md. Raihan Ali, Sabrina joadder silva, Afia Anjum Preety, Rezwana Islam Ria, Rayhan, Md. Mujtaba Asif, Anmona Mamun Monisha, Wasik Ahmed, Sajedul Islam, Forhad Hossain, Asif Mahmud Rony, Md Rakibul Islam.
– several test cases executed for the Graphics.
Again thanks for another successful testday
We hope to see you all in our next events, all the details will be posted on QMO!
Susan J. Fowler published a compelling blog post detailing continual sexual harassment — and HR malpractice — at her former employer, Uber. Uber CEO Travis Kalanick has promised an “urgent investigation.” I analyze why her account is so believable and powerful. Women claiming sexual harassment face nearly insurmountable challenges. Managers are more likely to be men. Management … Continued
The post Why the Susan J. Fowler sexual harassment story at Uber rings true appeared first on without bullshit.
Flickr Heroes Honorable Mentions:
If you want your photo to be considered for a Flickr Hero feature, submit it to the Flickr Heroes group pool by Monday morning next week!
Calls for Apple to buy Netflix are getting louder. Instead of evaluating whether Apple should buy Netflix, a more valuable question is whether or not Apple actually needs to buy Netflix to accomplish its goals. Upon closer examination, it becomes clear that calls to buy Netflix are misplaced as Apple is chasing after something entirely different in the video streaming space.
Music Streaming Lessons
One way to judge Apple's approach to video streaming is to look at how the company approached music streaming. In 2014, Apple had a growing problem on its hands. A music streaming startup called Spotify had amassed 40 million subscribers by positioning free music as a carrot for signing up to paid music streaming, for which there were 10 million paying subscribers. While Apple was still seeing increasing revenues from its paid music download empire, the company lacked a viable music streaming alternative. iTunes Radio wasn't an answer as it was chained to the paid download model.
With $147 billion of cash on the balance sheet at the end of 2013, Apple could have bought Spotify for $15 billion in 2014. Apple would have not only acquired an entirely new business model for content, but also solved its music streaming service problem overnight. Spotify would have had a difficult time turning down Apple's offer since $15 billion would be overvaluing the firm.
Instead of buying Spotify, Apple bought Beats for $3 billion in 2014. Three years later, many are still not sure what to make of the acquisition. Beats was a headphones company with a questionable balance sheet. The company also had a fledgling music streaming business via its MOG acquisition two years earlier. These items didn't position Beats as a traditional Apple acquisition target. If management wanted quick access to a successful music streaming service, the obvious path forward ran through Spotify, not Beats.
However, Apple wasn't looking to buy just a music streaming service. Instead, Tim Cook and Eddy Cue, Apple SVP of Internet Software and Services, were looking for a long-term vision as to how Apple should approach music content. Beats co-founder Jimmy Iovine was selling that vision. In fact, Iovine had tried to sell that vision to Apple more than a decade earlier as co-founder of Interscope Records. With Spotify gaining power and cracks beginning to appear at the edges of the iTunes empire, Apple decided it was time to buy into Iovine's vision in 2014. Instead of buying Spotify, Apple bought Jimmy Iovine.
Apple relies on a very particular M&A strategy. Management acquires companies in order to fill holes in product strategy. As a result, Apple uses M&A primarily to buy technology and teams of people behind a certain technology. In such a scenario, the product is placed above all else. In recent years, Apple has been an active acquirer, buying 15 to 20 smaller companies every year.
Apple looked at its music strategy and concluded that the product hole involved more than just streaming technology. If that were the case, Spotify would have done a great job at plugging up that hole for Apple. Instead, management saw weakness when it came to talent, ideas, and a broader vision for content. Apple wanted fresh connections and relationships with the music industry - items Spotify lacked. Management was searching for a vision as to how it could strengthen its relationship with Hollywood, push the music industry forward, and strengthen the iOS ecosystem. Jimmy Iovine and the Beats team, including former music industry executives such as Larry Jackson, had the relationships Apple was chasing.
By acquiring Beats, has Apple's streaming music plans worked out? Would Apple have done better by acquiring Spotify? As seen in the following chart, Apple Music has done well when looking at the number of paid subscribers. While some thought the product had little chance of gaining adoption out of the gate, Apple now has more than 20 million paying subscribers after just 17 months in the market. Apple management is likely pleased with that total. The service has obviously benefited from Apple's extensive marketing campaign as well as prominent placement within the iOS platform. The company has unofficially positioned its goal as surpassing 100 million paying subscribers.
When it comes to assessing Spotify's performance, the task becomes more complicated. On the surface, Spotify's paid subscriber growth rate appears to have remained steady following Apple Music's launch. The streaming service last disclosed 40 million paying subscribers. The problem is that Spotify has moved the goal posts when it comes to paid subscribers. The term has lost much of its meaning due to Spotify's heavy usage of promotions and bundling. In addition, Spotify's disclosures have become more sporadic when it comes to paid subscribers. Apple Music's disclosures have remained consistent to date.
There are also questions regarding Spotify's business model and sustainability. It's not clear when or how those questions will be answered. This has placed a shroud of mystery over the music streaming space.
In the meantime, Apple appears to be running fast with Apple Music as it positions "Planet of the Apps" and "CarPool Karaoke: The Series" as the first two original video shows for its streaming service. Apple's efforts with Apple Music don't appear to have been jeopardized by passing over Spotify as an acquisition target. It remains unclear if Spotify will serve as a ceiling to Apple Music's user growth. This is why Spotify's financial well-being is such a crucial topic to consider when thinking about Apple's long-term strategy to play in the music streaming space via Jimmy Iovine.
Why Acquire Netflix?
When it comes to the world of video streaming, Netflix is in an even stronger position than Spotify. With close to 90 million paying subscribers, Netflix has seen an incredible amount of success in getting people to pay for video content.
The crux of the argument for why Apple should buy Netflix centers around revenue growth. However, a few other reasons are often cited.
- Revenue growth. By owning Netflix, Apple management would be well on its way to reaching their goal of doubling the Services business in four years. A $12 billion per year stream of subscription revenue (100 million Netflix customers paying $10 per month) is approximately 40 percent of Apple's annual Services revenue.
- A different business model. Subscription revenue would help smooth the lumpiness found with Apple hardware sales and could eventually help the company make a push into a more encompassing subscription/service business model.
- Original content. Netflix would give Apple a shot in the arm when it comes to original content programming. Instead of spending years to build something from scratch, Apple would quickly be in a position of producing enough original video content to match ESPN.
Netflix Acquisition Lacks Rationale
Upon closer examination, calls that Apple should buy Netflix are misplaced as they do not take into account how Apple actually views the world. Many of the arguments assume Apple's current hardware-centric revenue model is in trouble. In addition, each of the three primary reasons cited for why Apple should buy Netflix contain significant gaps in logic and rationale.
- Revenue. Apple doesn't, and shouldn't, use M&A to directly acquire revenue streams. Apple didn't buy Beats for its revenue-generating headphone business. Instead, Apple bought Jimmy Iovine's music vision. A headphones business just happened to be attached to that vision. If M&A is used as a tool to grow revenue, Apple's effort to place the product above everything else is put into jeopardy. This logic explains why Apple doesn't acquire the large companies often paraded in the press as possible acquisition targets.
- A different business model. Apple has already shown the willingness to embrace change when it comes to selling product. This is a company that pivoted from a very successful paid music download model for iTunes to paid subscriptions with Apple Music. With more than 20 million paying subscribers for Apple Music after only 17 months, the streaming service is already 20 percent the size of Netflix - and this is with little to no video content.
- Original content. There is no evidence to suggest Apple wants to own large portfolios of video content. Instead, the company is still focused on being a content distributor with its iOS platform. In addition, rather than buying legacy content portfolios (Time Warner, Viacom, Disney, etc.) or original content initiatives found at tech companies masquerading as media companies (Netflix, Amazon), Apple is more interested in buying great ideas. This was very much on display with Apple's approach to music streaming.
Apple's Video Strategy
In essence, Netflix is like Spotify. Apple could acquire Netflix and instantly become the leader in paid video streaming. However, there is evidence that Apple is instead looking for something different. Apple is searching for another "Jimmy Iovine," new connections and relationships with Hollywood.
Apple's content goals have a better chance of being reached by working with smaller Hollywood production companies than by acquiring Netflix. This explains Apple's reported interest in Imagine Entertainment. According to The Financial Times, Tim Cook and Eddy Cue discussed a range of possibilities with Imagine Entertainment, founded by Ron Howard and Grazer, including a possible acquisition. The takeaway from those talks doesn't revolve around Apple getting its hands on an existing content portfolio. Rather it focuses on bringing people on board to come up with new ideas.
Another scenario that would likely interest Apple would be sitting down with a well-known entertainer and producer, such as Oprah, to discuss the possibility of working together on a few big ideas. Such an opportunity would let Apple stand out from the pack in the video streaming space instead of competing head-to-head with Netflix or Amazon Video. Such actions may seem trivial compared to Netflix doing 1,000 hours of original content programming. However, Apple would be looking to compete on different terms.
The preceding Apple strategy is the cornerstone of my Apple Studios theory. Apple would build a Hollywood arm tasked with coming up with original video (and music) content. Instead of viewing this as a Netflix 2.0, Apple Studios would be more of an incubator for trying out new entertainment ideas. Apple Studios would sit uniquely within Apple's organizational structure in order to have the independency needed to prosper yet not be completely cut out of Apple.
Eddy Cue and Jimmy Iovine like to say they are positioning Apple Music to be all about culture. When Apple says "culture," the company is actually referring to relevancy. Apple wants to remain relevant in the entertainment space. They want people to talk about what is going on in Apple Music. Eddy Cue recently compared Apple Music to MTV. While the juxtaposition may not be the most flattering thing for Apple Music these days considering MTV's weakened influence, Cue likely meant the MTV of yesterday. The cable channel was a cultural force for decades.
Apple is more interested in acquiring select ideas that have the potential to extend beyond just video or music content than it is in using a portion of its $230 billion of cash to buy huge content libraries. Apple held a monopoly on music mindshare during much of the late 2000s and early 2010s with iTunes. Management wants that mindshare back with Apple Music. This explains Apple's unusual arrangements with artists like Drake, Frank Ocean, and Chance the Rapper. Apple is showing us their blueprint for regaining relevancy.
This drive for relevancy also explains Apple's decision behind "Planet of the Apps." A show about apps doesn't seem to have much in common with a streaming music service. However, Apple Music has never been just about music, but rather it is about capturing relevancy. While the premise behind Planet of the Apps is similar to Shark Tank and The Voice, the integration with iOS is new and different. Planet of the Apps will include video content via an iOS app as well as broader iOS integration by having the apps that appear on the show featured prominently in the App Store. We are still firmly living in an app world. Apple thinks Planet of the Apps can get people talking - the same goal the company has for the broader Apple Music initiative.
Apple never had iTunes-like mindshare in the video space. That title went to a collection of traditional broadcast and cable companies. Looking ahead, Apple isn't trying to be like HBO, Showtime, Netflix, or Amazon Video by owning large swaths of content. Instead of buying Spotify, Apple bought Jimmy Iovine's vision for regaining relevancy in music. Apple is now looking to translate Jimmy Iovine's music vision around relationships, ideas, and mindshare into a broader strategy for video. The strategy doesn't require owning Netflix.
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Twitter Favorites: [Sean_YYZ] Snow covered Gravenhurst Station. Trains don't stop here anymore but buses and coffee runs do. https://t.co/9KsRdEu8J2
For most of my professional life, I've been somewhat annoyed by the mismatch between what we "mostly" wind up writing at a systems level (plumbing artifacts, with mostly-fixed memory and responsiveness requirements) and the tools we "mostly" wind up writing them in (arbitrary computation languages we can't even prove the memory-safety of programs in, much less bound the time or space usage of). Unlike many language people, I am not really interested in increasing programmer expressivity; I'm interested in the opposite problem: how to usefully restrict the languages we're working in, to more-closely match the problem domain (and enable stronger degrees of confidence that what we wrote won't go wildly wrong in the field).
In the past six months or so I've come to focus on 3 areas of work, all of which I feel inform and somewhat augment one another:
1. The work of Rajeev Alur (with significant digressions into Nancy Lynch's earlier work) around timed automata and visibly-pushdown automata. These are careful augmentations of finite automata with additional properties -- resettable clocks, stacks with limited rules for pushing and popping -- that retain decidability of important spatial and temporal properties. They don't "fall off the cliff" into computable functions, yet they are significantly more expressive than finite automata.
2. The work of Nobuko Yoshida and associates within the world of "choreography types" and "session types", and similar "global type" regimes. These are formalisms for describing a communication system (local or distributed) in terms of interaction-patterns between multiple (possibly transient) participants; a kind of extension of interface definition languages to cover (branching) sequences of permitted calls and returns. Protocol descriptions. The protocols so-described are, if properly designed, amenable to reasoning-about in terms of decidable automata mentioned previously.
3. The work of Andrei Sabelfeld, Heiko Mantel and associates within the world of "information flow security" or "language based security". These are not quite as obviously related to the former, except for one unusual fact: there is a type of decision that can be made about information flow -- the "non-interference" criterion, for example -- which can be expressed in a newly-emerging family of decidable HyperProperties, formulae in temporal logics that range over possible computation paths within a formal system.
So ... I'm somewhat interested to see if these mechanisms can be put to use in practical languages that systems people work in. There are encodings of a few, using fancy corners of haskell or even rust's type system. But I increasingly think there is room for "full" languages in this space, not embeddings. I think the potential exists for a language that targets compilation into reliable components, and networks-of-components, that are guaranteed to behave well; that push general-purpose languages to the periphery of those networks, as byzantine actors.
This hasn't exactly congealed into a plan yet, but it's what's percolating in my mind. We'll see if I manage to scrape up the energy to do anything about it.
If any of y'all know people, projects or things-to-read that the above list seems affiliated with, I'd be interested to hear!
This entry was originally posted at http://graydon2.dreamwidth.org/236045.html. Please comment there using OpenID.
Rezaul Huque Nayeem has been involved with Mozilla since 2013. He is from Mirpur, Dhaka, Bangladesh where he is an undergraduate student of Computer science and Engineering at the Daffodil International University. He loves to travel countrywide and hangout with friends. In his spare time, he volunteers for some social organizations.
Rezaul Huque Nayeem is from Bangladesh in south Asia.
Hi Nayeem! How did you discover the Web?
I discovered the web when I was kid, one day (2000/2001) in my uncle’s office I heard something about Email and Yahoo. That was the first time and I learned little bit about the internet on that day. I remember that I was very amazed when I downloaded a picture.
How did you hear about Mozilla?
In 2012 one of my friends told me about Mozilla and its mission. He told me how to contribute in many pathways in Mozilla.
How and why did you start contributing to Mozilla?
I started contributing to Mozilla on 20 march, 2015 by QA Marathon Dhaka. On that day my mentor Hossain Al Ikram showed me how to contribute to Mozilla by doing QA. He teached me how to test any feature on Firefox, how to verify bugs or do triage. From that day I love doing QA. Day by day I met many awesome mozillians and was helped by them. I love to contribute with them in a global community. I also like the way Mozilla works for making better web.
Have you contributed to any other Mozilla projects in any other way?
I did some localization on Firefox OS and MDN. I contributed in MLS (Mozilla Location Service). I also participated in many Web Maker focused events.
What’s the contribution you’re the most proud of?
I feel proud to contribute to QA. By doing QA now i can find bugs and help to get them fixed. That’s why now many people can use a bug free browser. And it also teaches me how to work with a community and make me active and industrious.
Please tell us more about your community. Is there anything you find particularly interesting or special about it?
The community I work with is Mozilla Bangladesh QA Community, a functional community of Mozilla Bangladesh where we are focused in contributing in QA. It is the biggest QA community and growing day by day. There is about 50 + active contributors who regularly participates in Test days, Bug Verification days and Bug triage days. Last year, we verified more than 700 bugs. We have more than 10 community mentors to help contributors. In our community every member is so much friendly and helpful. It’s a very active and lovely community.
What’s your best memory with your fellow community members?
Every online and offline event was very exciting for me. But Firefox QA Testday, Dhaka (4.dec.2015) was the best memorable event with my community for me. It was really an awesome offline daylong event.
You had worked as a Firefox Student Ambassador. Do you have any event that you want to share?
I organized two events on my institutional campus, Dhaka Polytechnic Institute. One was a Webmaker event and another one was for MozillaBD Privacy Talk. Both was thrilling for me, as I was leading those events.
What advice would you give to someone who is new and interested in contributing to Mozilla?
I will tell him that, first you have to decide what you really want to do? If you work with a community, then please do not contribute for yourself, do it for your community.
If you had one word or sentence to describe Mozilla, what would it be?
Mozilla is the One who really wants to make web free for people
What exciting things do you envision for you and Mozilla in the future?
I envision that Mozilla will give much effort on connecting devices so that world would get some exciting gear.
How Quip fuels strong teams
At the core of Quip’s product is a simple philosophy: We learn by listening. At Quip, over half of our small team works directly with customers — including all three of our product managers. We mine a mountain of deep conversations for common needs and emerging workflows that we can support through thoughtful feature design. We use our own product for this, too — Quip’s Twitter integration lets us pipe Tweets to and about @quip into a chat room where the entire team reads what people are saying. We act on urgent points, and absorb more nuanced ones into our product design and engineering process. Quip’s new design responds to some of the most consistent pieces of feedback we’ve received over the past year.
At the same time, we learn from research. Dispatches from the bleeding edge of collaboration research fly around our office, informing hallway conversations and product design. Finally, we learn by doing. We consider our small team to be a group of experimenters, always coming up with new ways of working and testing them over time. The Quip team uses Quip for absolutely everything: project plans, to-do lists, event planning, meeting notes, strategy docs. Everything. As we grow, we keep asking ourselves: How can Quip continue to serve as a tool for decisive action informed by broad awareness? And whenever we hit on a new insight, we build it into Quip as fast as we can.
Ultimately, we’ve learned that strong teams work fast, act friendly, and embrace fun. To pave the way for the future of work as we see it through that lens, we’ve redesigned Quip from the ground up. Our new design elevates focus, flow, and feedback — the three drivers of team productivity.
Quip’s new design uses color to shape focus. The bright white content area takes center stage while the dark gray, slightly translucent sidebar chills out on the sidelines, waiting to lend a hand to quick context-switching. The sidebar button becomes solid orange when notifications await, offering a clear hint of where to turn your attention next. Once the sidebar is open, the Favorites section serves as a home for the working set of documents you’ve chosen to focus on. And when you open a shared document, the conversation shows up alongside it within the bright white content area, bringing into focus what your teammates are saying and what’s changed.
Meanwhile, Quip’s emphasis on minimalistic formatting remains. All the bells and whistles of fonts and colors can be deceivingly distracting — so we built Quip with a low overhead to getting started. Docs have a fresh, legible look and feel with limited formatting options on purpose. Meanwhile, Quip’s contextual document, spreadsheet, and checklist menus come into view when your cursor is focused in a section where they’d be handy — there when you need them, gone when you don’t. The result is that work happens faster, and teams build a shared understanding of what work looks like and how it gets done. Quip’s docs are already effortlessly beautiful, so you don’t have to spend time making them that way.
Finally, Quip boosts focus by being fast. The fastest tools are built by people obsessed with technical performance, which Quip’s industry-leading engineering team certainly is. But that’s just the beginning. Fast is also about feedback loops driven by direct mentions — knowing when your attention is needed where, and being able to respond from wherever you are, whether that happens to be a web browser, one of our desktop apps, or Quip’s iOS and Android apps on the go.
Team productivity is a dance between responsive conversation and heads-down creation, and the new Quip carves out space for both. The best real-life example I can describe is my own, so here’s a typical day for me in Quip.
As a product manager, I start the morning by checking the notification bell (usually on my phone), where I can browse through what’s beckoning my attention. Just like on social networks, anytime someone mentions me in a document or a chat that I’m shared on, a notification is triggered. And now with Reminders, my past self can keep my future self on track by setting a notification that will fire off exactly when I need it to.
Once I’ve glanced through my notifications, I move to the sidebar. The sidebar is designed to give me quick access to all the docs I’ve been investing attention in recently, for as long as they’re still relevant.
After I check out my sidebar and tend to any docs and chats that need my attention, I like to scan through my Updates feed to see all the latest action on docs and chat rooms across the company. The Updates feed gives me the superpower of ambient awareness: I always have my finger on the pulse of where my teammates are spending their time, which influences how I spend mine.
For staying in your flow, there’s nothing better than Quip’s approach to keyboard shortcuts and in-line actions, which we’ve carried forward into the new design. If you buy into productivity gurus’ claims that doing everything from your keyboard without mousing around is the secret to moving at the speed of thought — and I certainly do — the messiness of traditional keyboard shortcuts is infuriating. It’s like they don’t want to be learned. Quip to the rescue, at a bunch of different levels:
For in-line actions — things you can do in context, alongside text and images — we go a step further than most productivity apps, which focus on the right-click menu.
- A comment bubble shows up to the left of the line that’s in focus, inviting you to start a conversation in context.
- The style square serves as an indicator of a text section’s style, as well as a quick-switcher.
- Selected text sports a formatting popover with bold, italic, underline, and other options.
- The Tools bubble gives an overview of everything you can add to a doc (checklists! spreadsheets! images!)
Quip can show you who’s participated where, right down to the paragraph or individual task level, and keeps people in the loop accordingly. Edits, highlights, and comments are all ways of conveying interest: “This matters to me.” And if it matters to you, we want you to know the latest. That’s why Reminders get sent to the person who writes a task in the first place — as well as anyone mentioned in the task — and why you’ll get a push notification if someone responds to a comment you’ve made. A comment can be as simple as a single emoji; at Quip, we love doing this as a way of registering an opinion on a topic while keeping things light and friendly — similar to how you might nod in agreement during a meeting. At Quip, we make decisions in docs instead of calling meetings, so we’ve found other fun and friendly ways to nod.
Quip also lets you control the flow of feedback you’re receiving with the new Updates feed. This replaces the Inbox, because customers told us that calling it an “Inbox” brought to mind old email workflows. Quip represents a new way of working, so they felt words we use should reflect that, too. We agreed, so we changed it.
We also added History and Frequently Viewed to the sidebar. The more you switch contexts, the more useful it is to have pointers back to wherever you just were. Because modern work is so dynamic, seamless context-switching and context-recovery is definitely something we want to support. With Quip’s new design, we do. History is a straight reverse-chronological list of the last few items you opened, up to fifteen, and one of the features we’ve heard the most requests for over the past year. Frequently Viewed is an algorithmically-defined list of places you’ve been spending time in Quip recently. History offers a shortcut back to “that doc you know you saw a minute ago and can’t remember the name of to save your life.” Frequently Viewed is more opinionated, but it’s shaped by your opinions — by the reality of where you’re spending your time.
With improved checklists and new Reminders, we’ve added more task management tools to Quip. But we did it in a way that jives with the rest of Quip — it’s light, and it gives you what you need when you need it. Reminders and mentions let you pick dates and people to associate with your tasks, and weave those tasks into the work you’re doing. The checklists speak up to keep you on track, creating feedback loops that drive a shared definition of “done.” The goal here was flexibility, because we heard from our customers that rigid task management tools were just too overwhelming. Teams were falling back to sticky notes and whiteboards. Quip checklists offer powerful basics that everyone can use and understand.
Here at Quip, we’ve seen the future of work because we’ve lived it. At our office, we don’t even use email — no, really. When we have something quick to say, we send a chat message; when we want to plant a seed that can grow into something more, we start a document; when we want to plan something out, we use a checklist. Focus, flow, and feedback — the three drivers of team productivity — fuel our workdays, and every workday starts in Quip. Strong teams work fast, act friendly, and have fun. We’re confident that Quip will be a source of strength for your team, too.
- Hugo Mercier and Dan Sperber, The Enigma of Reason
A few weeks back, I reviewed handheld stabilizers for your phone or your GoPro. They make a huge difference in the quality of your videos—because let’s face it: Jerky looks amateur.
But you may not need one of those expensive gadgets to stabilize your footage. Turns out YouTube can perform stabilization for you!
Find your video in your Video Manager. Hit Edit. Click the Enhancements tab, then Stabilize. Then go see a couple of movies; the analysis takes a really long time.
But when it’s over, the result is a thousand times more watchable. It’s not perfect—sometimes you get little moments of weirdness, where your hand jerked a lot—but hey, it’s free.
|sillygwailo shared this story from Blog - Susan J. Fowler.|
As most of you know, I left Uber in December and joined Stripe in January. I've gotten a lot of questions over the past couple of months about why I left and what my time at Uber was like. It's a strange, fascinating, and slightly horrifying story that deserves to be told while it is still fresh in my mind, so here we go.
I joined Uber as a site reliability engineer (SRE) back in November 2015, and it was a great time to join as an engineer. They were still wrangling microservices out of their monolithic API, and things were just chaotic enough that there was exciting reliability work to be done. The SRE team was still pretty new when I joined, and I had the rare opportunity to choose whichever team was working on something that I wanted to be part of.
After the first couple of weeks of training, I chose to join the team that worked on my area of expertise, and this is where things started getting weird. On my first official day rotating on the team, my new manager sent me a string of messages over company chat. He was in an open relationship, he said, and his girlfriend was having an easy time finding new partners but he wasn't. He was trying to stay out of trouble at work, he said, but he couldn't help getting in trouble, because he was looking for women to have sex with. It was clear that he was trying to get me to have sex with him, and it was so clearly out of line that I immediately took screenshots of these chat messages and reported him to HR.
Uber was a pretty good-sized company at that time, and I had pretty standard expectations of how they would handle situations like this. I expected that I would report him to HR, they would handle the situation appropriately, and then life would go on - unfortunately, things played out quite a bit differently. When I reported the situation, I was told by both HR and upper management that even though this was clearly sexual harassment and he was propositioning me, it was this man's first offense, and that they wouldn't feel comfortable giving him anything other than a warning and a stern talking-to. Upper management told me that he "was a high performer" (i.e. had stellar performance reviews from his superiors) and they wouldn't feel comfortable punishing him for what was probably just an innocent mistake on his part.
I was then told that I had to make a choice: (i) I could either go and find another team and then never have to interact with this man again, or (ii) I could stay on the team, but I would have to understand that he would most likely give me a poor performance review when review time came around, and there was nothing they could do about that. I remarked that this didn't seem like much of a choice, and that I wanted to stay on the team because I had significant expertise in the exact project that the team was struggling to complete (it was genuinely in the company's best interest to have me on that team), but they told me the same thing again and again. One HR rep even explicitly told me that it wouldn't be retaliation if I received a negative review later because I had been "given an option". I tried to escalate the situation but got nowhere with either HR or with my own management chain (who continued to insist that they had given him a stern-talking to and didn't want to ruin his career over his "first offense").
So I left that team, and took quite a few weeks learning about other teams before landing anywhere (I desperately wanted to not have to interact with HR ever again). I ended up joining a brand-new SRE team that gave me a lot of autonomy, and I found ways to be happy and do amazing work. In fact, the work I did on this team turned into the production-readiness process which I wrote about in my bestselling (!!!) book Production-Ready Microservices.
Over the next few months, I began to meet more women engineers in the company. As I got to know them, and heard their stories, I was surprised that some of them had stories similar to my own. Some of the women even had stories about reporting the exact same manager I had reported, and had reported inappropriate interactions with him long before I had even joined the company. It became obvious that both HR and management had been lying about this being "his first offense", and it certainly wasn't his last. Within a few months, he was reported once again for inappropriate behavior, and those who reported him were told it was still his "first offense". The situation was escalated as far up the chain as it could be escalated, and still nothing was done.
Myself and a few of the women who had reported him in the past decided to all schedule meetings with HR to insist that something be done. In my meeting, the rep I spoke with told me that he had never been reported before, he had only ever committed one offense (in his chats with me), and that none of the other women who they met with had anything bad to say about him, so no further action could or would be taken. It was such a blatant lie that there was really nothing I could do. There was nothing any of us could do. We all gave up on Uber HR and our managers after that. Eventually he "left" the company. I don't know what he did that finally convinced them to fire him.
In the background, there was a game-of-thrones political war raging within the ranks of upper management in the infrastructure engineering organization. It seemed like every manager was fighting their peers and attempting to undermine their direct supervisor so that they could have their direct supervisor's job. No attempts were made by these managers to hide what they were doing: they boasted about it in meetings, told their direct reports about it, and the like. I remember countless meetings with my managers and skip-levels where I would sit there, not saying anything, and the manager would be boasting about finding favor with their skip-level and that I should expect them to have their manager's job within a quarter or two. I also remember a very disturbing team meeting in which one of the directors boasted to our team that he had withheld business-critical information from one of the executives so that he could curry favor with one of the other executives (and, he told us with a smile on his face, it worked!).
The ramifications of these political games were significant: projects were abandoned left and right, OKRs were changed multiple times each quarter, nobody knew what our organizational priorities would be one day to the next, and very little ever got done. We all lived under fear that our teams would be dissolved, there would be another re-org, and we'd have to start on yet another new project with an impossible deadline. It was an organization in complete, unrelenting chaos.
I was lucky enough during all of this to work with some of the most amazing engineers in the Bay Area. We kept our heads down and did good (sometimes great) work despite the chaos. We loved our work, we loved the engineering challenges, we loved making this crazy Uber machine work, and together we found ways to make it through the re-orgs and the changing OKRs and the abandoned projects and the impossible deadlines. We kept each other sane, kept the gigantic Uber ecosystem running, and told ourselves that it would eventually get better.
Things didn't get better, and engineers began transferring to the less chaotic engineering organizations. Once I had finished up my projects and saw that things weren't going to change, I also requested a transfer. I met all of the qualifications for transferring - I had managers who wanted me on their teams, and I had a perfect performance score - so I didn't see how anything could go wrong. And then my transfer was blocked.
According to my manager, his manager, and the director, my transfer was being blocked because I had undocumented performance problems. I pointed out that I had a perfect performance score, and that there had never been any complaints about my performance. I had completed all OKRs on schedule, never missed a deadline even in the insane organizational chaos, and that I had managers waiting for me to join their team. I asked what my performance problem was, and they didn't give me an answer. At first they said I wasn't being technical enough, so I pointed out that they were the ones who had given me my OKRs, and if they wanted to see different work from me then they should give me the kind of work they wanted to see - they then backed down and stopped saying that this was the problem. I kept pushing, until finally I was told that "performance problems aren't always something that has to do with work, but sometimes can be about things outside of work or your personal life." I couldn't decipher that, so I gave up and decided to stay until my next performance review.
Performance review season came around, and I received a great review with no complaints whatsoever about my performance. I waited a couple of months, and then attempted to transfer again. When I attempted to transfer, I was told that my performance review and score had been changed after the official reviews had been calibrated, and so I was no longer eligible for transfer. When I asked management why my review had been changed after the fact (and why hadn't they let me know that they'd changed it?), they said that I didn't show any signs of an upward career trajectory. I pointed out that I was publishing a book with O'Reilly, speaking at major tech conferences, and doing all of the things that you're supposed to do to have an "upward career trajectory", but they said it didn't matter and I needed to prove myself as an engineer. I was stuck where I was.
I asked them to change my performance review back. My manager said that the new negative review I was given had no real-world consequences, so I shouldn't worry about it. But I went home and cried that day, because even aside from impacts to my salary and bonuses, it did have real-world consequences - significant consequences that my management chain was very well aware of. I was enrolled in a Stanford CS graduate program, sponsored by Uber, and Uber only sponsored employees who had high performance scores. Under both of my official performance reviews and scores, I qualified for the program, but after this sneaky new negative score I was no longer eligible.
It turned out that keeping me on the team made my manager look good, and I overheard him boasting to the rest of the team that even though the rest of the teams were losing their women engineers left and right, he still had some on his team.
When I joined Uber, the organization I was part of was over 25% women. By the time I was trying to transfer to another eng organization, this number had dropped down to less than 6%. Women were transferring out of the organization, and those who couldn't transfer were quitting or preparing to quit. There were two major reasons for this: there was the organizational chaos, and there was also the sexism within the organization. When I asked our director at an org all-hands about what was being done about the dwindling numbers of women in the org compared to the rest of the company, his reply was, in a nutshell, that the women of Uber just needed to step up and be better engineers.
Things were beginning to get even more comically absurd with each passing day. Every time something ridiculous happened, every time a sexist email was sent, I'd sent a short report to HR just to keep a record going. Things came to a head with one particular email chain from the director of our engineering organization concerning leather jackets that had been ordered for all of the SREs. See, earlier in the year, the organization had promised leather jackets for everyone in organization, and had taken all of our sizes; we all tried them on and found our sizes, and placed our orders. One day, all of the women (there were, I believe, six of us left in the org) received an email saying that no leather jackets were being ordered for the women because there were not enough women in the organization to justify placing an order. I replied and said that I was sure Uber SRE could find room in their budget to buy leather jackets for the, what, six women if it could afford to buy them for over a hundred and twenty men. The director replied back, saying that if we women really wanted equality, then we should realize we were getting equality by not getting the leather jackets. He said that because there were so many men in the org, they had gotten a significant discount on the men's jackets but not on the women's jackets, and it wouldn't be equal or fair, he argued, to give the women leather jackets that cost a little more than the men's jackets. We were told that if we wanted leather jackets, we women needed to find jackets that were the same price as the bulk-order price of the men's jackets.
I forwarded this absurd chain of emails to HR, and they requested to meet with me shortly after. I don't know what I expected after all of my earlier encounters with them, but this one was more ridiculous than I could have ever imagined. The HR rep began the meeting by asking me if I had noticed that *I* was the common theme in all of the reports I had been making, and that if I had ever considered that I might be the problem. I pointed out that everything I had reported came with extensive documentation and I clearly wasn't the instigator (or even a main character) in the majority of them - she countered by saying that there was absolutely no record in HR of any of the incidents I was claiming I had reported (which, of course, was a lie, and I reminded her I had email and chat records to prove it was a lie). She then asked me if women engineers at Uber were friends and talked a lot, and then asked me how often we communicated, what we talked about, what email addresses we used to communicate, which chat rooms we frequented, etc. - an absurd and insulting request that I refused to comply with. When I pointed out how few women were in SRE, she recounted with a story about how sometimes certain people of certain genders and ethnic backgrounds were better suited for some jobs than others, so I shouldn't be surprised by the gender ratios in engineering. Our meeting ended with her berating me about keeping email records of things, and told me it was unprofessional to report things via email to HR.
Less than a week after this absurd meeting, my manager scheduled a 1:1 with me, and told me we needed to have a difficult conversation. He told me I was on very thin ice for reporting his manager to HR. California is an at-will employment state, he said, which means we can fire you if you ever do this again. I told him that was illegal, and he replied that he had been a manager for a long time, he knew what was illegal, and threatening to fire me for reporting things to HR was not illegal. I reported his threat immediately after the meeting to both HR and to the CTO: they both admitted that this was illegal, but none of them did anything. (I was told much later that they didn't do anything because the manager who threatened me "was a high performer").
I had a new job offer in my hands less than a week later.
On my last day at Uber, I calculated the percentage of women who were still in the org. Out of over 150 engineers in the SRE teams, only 3% were women.
When I look back at the time I spent at Uber, I'm overcome with thankfulness that I had the opportunity to work with some of the best engineers around. I'm proud of the work I did, I'm proud of the impact that I was able to make on the entire organization, and I'm proud that the work I did and wrote a book about has been adopted by other tech companies all over the world. And when I think about the things I've recounted in the paragraphs above, I feel a lot of sadness, but I can't help but laugh at how ridiculous everything was. Such a strange experience. Such a strange year.
Note: I am temporarily disabling comments because there are too many for me to keep up with!
For a long time my father has been a Nokia customer. He used a Nokia-X2. Things he liked were features like legit font, sharp screen, backlit hardware keyboard and call quality. He didn’t really use any other feature. Recently after about five years of usage; that phone conked out and with that we were in the market for a similar phone.
A lot of friends online suggested me to go with Easyfone. I was skeptical initially. I went through all the amazon reviews and feature list in detail. It seemed like a decent phone and features weren’t path breaking. So at last I made up my mind and bought it from Amazon for roughly ₹3500. It got delivered in time and in good condition. He has used it for a while now and here is our feedback.
Build quality is decent. Feels solid, light weight and fits well in the hand. Has anti skid back for slippery hand. But build quality is not as good as Nokia. And I doubt if it can survive in the harsh like Nokia. That said no other phones are as sturdy as Nokia phones. Overall not bad.
Screen is big enough, clear and has big and legible fonts. All of which we liked. Keys are well spaced, big, have clear lettering, backlit and have good tactile feedback. Again full marks there.
The phone comes with three dedicated buttons. SOS button at the back, slide-able torch button and lock/unlock button. I really like that they have a dedicated screen lock and unlock button. On a regular phone one needs to long press * or # to unlock. It used to be really difficult1 for my mother to use it. Torch is at the top and it works. It gets its own dedicated button. In fact this makes it much more useful specially in the night.
SOS functionality gets activated on long press. It begins with a countdown with an option to cancel. If you don’t cancel it then sounds an alarm. Enough to get attention in a room or corridor. Then it automatically calls the contacts on “emergency” list. You can pre-configure up-to 5 emergency contacts. It calls all five one after another until someone picks up. It calls each contact up-to 3 times. Then it puts the phone in auto-pick mode where any incoming call will be automatically received on speaker. Along with this It also sends a SOS SMS message with location details, battery strength & before stored medical information. The message is usually a link to a webpage with all the details including the lat/long.
I am not sure if the phone has GPS. I couldn’t get the details anywhere. I doubt it. Regardless in my tests the location was quite accurate, it was in 10-100 meters range. Phone sends a link which gives all the information. Hence its easy to forward if the situation requires. The SOS feature is well thought out and works. We had a couple of false alarms in the beginning due to the location of the button. My father usually holds the phone in a way that would make him press the SOS button. But it only took couple of days.
The phone has FM radio and can take memory card up to 8GB. One can use a standard 3.5mm head phone jack. It uses standard micro USB for charging. Also comes with cradle like cordless phones if you don’t want to think about charging. It’s a quad band (GSM 850/900/1800/1900) so can be used overseas. Call quality is good, its loud and clear. The speaker phone feature works, its loud and clear.
Camera is bad, it’s not even decent. But since we weren’t looking for that feature it didn’t matter to us. No internet. Again we didn’t need it.
All in all. It’s a a very good phone for seniors.
- Parkinson’s disease ↩
At MEX/11, Louisa Heinrich shared a series of techniques for creating contextually responsive digital experiences. One of the guiding principles was for designers to acknowledge the fictional narratives users create for themselves.
“Look at the calendar on my iPhone…In January, I set-up a recurring reminder to go to the gym every Monday, Wednesday and Saturday. It’s still there, I don’t want to delete it – that would be like admitting defeat. Does that mean I’m actually at the gym three times a week, though? Of course it doesn’t!” — #mexuservoice
These stories we tell ourselves about who we are, our relationship with others and the world around us, are often more important in determining our emotional response to a digital product or service than the binary facts understood by computers.
In practice, this can mean making provision for a subjective preference to override a seemingly more logical, data-driven choice in the interests of building trust and understanding with the users.
Louisa’s talk was part of MEX Pathway #14, an ongoing exploration of principles for context aware experience design, which has gone on to inform more recent thinking about artificial intelligence.
For further views on this theme, try:
- Louisa Heinrich’s MEX/11 talk and episode 5 of the MEX podcast, where she talks about robot UX.
- Principles for artificial intelligence in UX
- Episode 10 of the MEX podcast, where we talk to Nathan Benaich, partner at Playfair Capital, a VC specialising in AI investments
- How artificial intelligence nuances experience design, part of the MEX Friday inspirations series
- Episode 2 of the MEX podcast, talking to Ed Rex, CEO of Jukedeck, an artificial intelligence engine for music
- MEX Pathway #14, cataloguing ongoing work into the principles for context aware design
The principle, part of an emerging series in the MEX journal, is summarised below in a tweetable, shareable graphic. Please share and thank you for citing appropriately.
|mkalus shared this story from /index.xml.|
Since the presidential election, “fake news” has become a buzzword leveraged by both sides of the political aisle, with many organizations directing resources toward understanding and fighting it. Some efforts focus on improving technology: Facebook recently integrated fact-checking into its publication process, while Google no longer allows Google-served advertising to appear on sites that “misrepresent” information. Others focus on improving journalism: BuzzFeed Editor in Chief Ben Smith has advocated for more support for objective, accurate reporting as a way to counterbalance the fake news creeping its way across social media feeds.
What’s been missing from the conversation is a calculated look at fake news’s reach. We know little about the amount of fake news an average citizen consumes, or how it fits into their overall news diet. In fact, we don’t know much about the fake news audience, period. Are visitors to fake news sites in an echo chamber wherein they remain unexposed to conflicting information? Are they regularly consuming both fake and real news? How are audiences stumbling upon fake news? Without examining the audience, it’s impossible to know the scope of the problem.
Note: The interactive slideshow below only works on laptop and desktop.
As a PhD candidate researching journalism at Northwestern University’s Media, Technology, and Society program, I have spent the past few years using online audience data to better understand news consumption habits. Working with Northwestern Communication Studies Professor James G. Webster this fall, I used these data to take a closer look at the fake news audience. What we found calls into question the severity of the fake news crisis.
What we call ‘fake news’
As has become increasingly clear, “fake news” is neither straightforward nor easy to define. And so when we set out on this project, we referred to a list compiled by Melissa Zimdars, a media professor at Merrimack College in Massachusetts. The news sites on this list fall on a spectrum, which means that while some of the sites we examined* publish obviously inaccurate news (e.g., abcnews.com.co), others exist in a more ambiguous space, wherein they might publish some accurate information buried beneath misleading or distorted headlines (e.g., Drudge Report, Red State). Then there are intentionally satirical news sources, like The Onion and Clickhole. Our sample included examples of all of these types of fake news.
We also analyzed metrics for real news sites. That list represents a mix of 24 newspapers, broadcast, and digital-first publishers (e.g., Yahoo-ABC News, CNN, The New York Times, The Washington Post, Fox News, and BuzzFeed).
We gathered data for both the real and fake news sites from comScore, a Web analytic company that tracks online activity of about 1 million people within the US and then makes projections about the online behavior of the total US online audience.
Our analysis examined visitation (measured by unique visitors) and engagement (measured by average minutes per visitor) for real and fake news sites each month between November 2015 and November 2016. We used the averages of visits to and time spent with our real news and fake news samples to examine how real news consumption compared to fake news consumption, as well as how audiences for each changed over time. We chose November to November as our timespan because we were especially interested in observing if audience behavior changed leading up to and immediately following the election.
In addition to examining visitation and engagement, we also looked at the percentage of visitors to fake news sites who also visited real news sites, and the percentage of visits to both fake and real news sites that originated from Facebook. We looked at desktop and mobile online audiences, and found similar patterns across both platforms.
The fake news audience is real, but it’s also really small
Here’s what we found. First, the fake news audience is tiny compared to the real news audience–about 10 times smaller on average. This held true between November 2015 and November 2016. In fact, the real news audience spiked in October and November, while the fake news audience held constant.
|Month||Fake News Mobile||Fake News Desktop||Real News Mobile||Real News Desktop|
Real News Desk…
Online news audiences spent more time on average with real news than fake news. The one exception was Drudge Report, which attracts an enormous amount of audience engagement as measured by average minutes per visitor. Take last November, for example. The average minutes-per-unique-visitor for Drudge Report clocked in at an astounding 275 minutes, 12 times higher than the same metric for The Washington Post and 11 times higher than it was for Breitbart.
|The Washington Post||22|
This is the amount of time viewers spent on fake vs. real news platforms, including Drudge Report, in minutes.
|Month||Fake News Mobile||Fake News Desktop||Real News Mobile||Real News Desktop|
Real News Des…
This is the amount of time viewers spent on fake vs. real news platforms, without Drudge Report, in minutes.
|Month||Fake News Mobile||Fake News Desktop||Real News Mobile||Real News Desktop|
Real News Des…
We also found that the fake news audience does not exist in a filter bubble. Visitors to fake news sites visited real news sites just as often as visitors to real news sites visited other real news sites. In fact, sometimes fake news audiences visited real news sites more often: For example, 56 percent of Infowars’s audience visited The New York Times in October, while only 40 percent of The Washington Post’s audience did.
|Month||Fake News Audience Cross Visits||Real News Audience Cross Visits|
|Yahoo-ABC News Network||51||42|
|The New York Times||41||36|
|The Washington Post||39||32|
|Wall Street Journal||23||37|
Real News Audience C…
Last, and perhaps least surprising to everyone but Mark Zuckerberg, we saw that audiences found their way to fake news via social media at a much higher rate than they did to real news. We already know that a majority of US adults get their news via social media platforms. Here, though, we can see that nearly 30 percent of all fake news traffic could be linked back to Facebook, while only 8 percent of real news traffic could.
Fake news linked back to Facebook
|Created by||Percent of Stories|
|Traffic From Facebook||27|
|Traffic From Everywhere Else||73|
Traffic From Everywhere Els…
Real news linked back to Facebook
|Created by||Percent of Stories|
|Traffic From Facebook||8|
|Traffic From Everywhere Else||92|
Traffic From Everywhere El…
Is fake news a fake problem?
Our findings call into question the scope of the fake news problem, while complicating the way we think about it. On the one hand, the fact that the fake news audience is small and highly likely to also visit real news sites may come as a relief to those who fear this audience lives in a separate, distorted reality. But exposure to news is one thing–how these audiences interpret the news is another. If half of the fake news audience had been approaching both real and fake news for the past year with an open mind, you would expect that audience to shrink as readers eventually abandoned fake news sites. That this has not happened suggests the fake news audience isn’t reading real news because they believe it might also be accurate, but because these sources are popular and they want to know how the rest of the world “falsely” understands current events. If this is indeed the case, it means solving the fake news problem will be much trickier than limiting its supply.
*Editor’s note: We are reporting the study findings listed here as a service to our audience, but we do not endorse the study authors’ baseline assumptions about what constitutes a “fake news” outlet. Drudge Report, for instance, draws from and links to reports in dozens of credible, mainstream outlets.
|mkalus shared this story from Vancouver Sun.|
Liza Wajong, CEO and founder of Nusa Coffee in Vancouver, in the café at 2766 W. 4th Ave. in Kitsilano on Monday. See Notes / Direction / PNG
The cosy interior of Liza Wajong’s new Vancouver café — Nusa — may only be 400-square-feet in size. But beyond coffee, it may also be the Lower Mainland’s most accessible gateway to the culinary culture of the world’s fourth most-populous country.
Nusa, which means “island” in Bahasa — Indonesia’s official language — is one of the only local establishments that is dedicated to the southeast Asian country. This is despite a sizable overseas community of 14,320 (according to the 2006 census) in Canada, with about 5,000 in B.C.
But while Wajong is hopeful of her café’s potential to raise “brand awareness” for her homeland, she added the key — first and foremost — is sharing good coffee in a responsible way.
“Five per cent of our earnings go back to the family owned farms in Indonesia that we partner with,” she said, noting she wanted to support small growers who are under economic pressure to sell their land to the environmentally harmful palm-oil industry. “ … For me, the work is not pressure, because I’m doing this with a purpose — not just to be successful, but be ethical and sustainable. If we can grow the community both here and in Indonesia, then why not?”
Some brands of Indonesian coffee (specifically those from the island of Sumatra) have already become ubiquitous in North American chains. But coffee-industry officials say consumers are often not aware of the variety and quality available from the entirety of Indonesia, spread out over some 17,000 islands totalling about 1.9 million square kilometres.
Nusa Coffee is located at 2766 W. 4th Ave. in Kitsilano. Chuck Chiang / PNG
“I don’t think people understand how good this coffee is,” said Rick Masana, director of Vancouver’s Republica Coffee Roasters (which roasts Nusa’s imported beans locally). “People often go for the marketing … But (Indonesia) is one of the best for growing coffee beans in the world, and we know because we import from 54 countries.”
Masana said coffee is typically ranked in a 100-point system, with the average cup in Vancouver likely rating about 84-88 points. He said Nusa’s coffee can rate as high as 94, due partly to the nation’s abundant volcanic soil.
Nusa opened in January after two years in the planning stages, and was already selling beans as an importer from several exotic Indonesian islands before the café’s opening. Among its offerings is the renowned Kopi Luwak, made from beans eaten by — then defecated from — a catlike animal native to Indonesia.
But Wajong also made sure to feature beans from a wide range of islands such as Flores, Java and Sulawesi, adding that the coffee has already attracted a following in the café’s Kitsilano neighbourhood, as well as the attention of international students from Indonesia and local community members.
“People know about Sumatra coffee, but they can get it from anywhere,” said Wajong. “There’s much more to Indonesian coffee, and the only way to show them what we have to offer is to give it to them in a cup … I feel that people sometimes know more about Bali than they do about Indonesia. But that’s changing, especially with the new generation — and I hope this (café) is a part of that process.”
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After reading this I was motivated to look up how a toilet works on YouTube. I'm fairly confident I understand the mechanics, but I don't really have an explanation. Why doesn't the bowl simple lose water when the flapper is opened; why does the water rush out as though it is being sucked out of the toilet? Everything in the toilet is actually pulled uphill. I think it has something to do with pressure differentials or gravity (the way a siphon does) but I'm not sure, and the videos didn't help me. And that's why this article is interesting. Knowing the facts doesn't give me the explanation, which is why a mere presentation of the facts doesn't change (or inform) opinions. "Confronting and working through the complicated details of an issue... may be the only form of thinking that will shatter the illusion of explanatory depth and change people’ s attitudes."[Link] [Comment]
This is a pretty good overview of the current bot ecosystem (which contains far more than bots) along with a good graphic drawing out the major contenders and relations between them. "Bots use artificial intelligence to converse in human terms, usually through a lightweight messaging interface like Slack or Facebook Messenger, or a voice interface like Amazon Echo or Google Assistant. Since late 2015, bots have been the subject of immense excitement in the belief that they might replace mobile apps for many tasks and provide a flexible and natural interface for sophisticated AI technology."[Link] [Comment]
New reports indicate that Tesla is vying for a larger share of the Canadian automotive market.
The auto tech company recently opened an additional dealership in Oakville, Ontario, marking its third in the Greater Toronto Area and eighth in Canada, according to freelance technology journalist Peter Nowak’s recent story in Canadian Business.
Furthermore, Tesla has also installed over 22 ‘superchargers’ across the country, which have the ability to fuel a car with nearly 270 kilometres of range in 30 minutes. There are also hundreds of ‘destination charging’ setups for Tesla owners, scattered at public locations such as hotels.
This charging network supports Tesla’s electric vehicles, which don’t have as many options for range or refuelling as regular gas-driven cars. Canadian pricing for the superchargers was revealed back in January, which varies per province.
Tesla says its Model S car has 539 kilometre range, and with this network, that should be enough to keep cars going. The Model S sells for $100,000 (depending on options selected) in Canada, while the larger Model X SUV is almost $125,000.
This still, however, doesn’t help Canadians in the Prairies; according to the network map, there are no superchargers between Ontario and Alberta and only a handful of destination chargers.
As well, Tesla’s full Autopilot mode hasn’t yet been cleared by regulators for usage in Canada. This function allows the car to self-drive, letting drivers take their hands off the steering wheel when on highways. No release window has been given for this feature.
Image credit: Wikimedia Commons
Source: Canadian Business
The post Tesla continues Canadian expansion with additional dealership and ‘supercharger’ stations appeared first on MobileSyrup.
If you’re lucky, you might not know Asurion.
The Tennessee-based company is the place many Canadians go to when they’ve dropped their phone in the toilet or rolled over it in a pickup truck. It provides device protection services to Bell and Rogers, two of Canada’s largest wireless giants, and has now been picked up by Telus to do the same.
The change marks the return of a partnership between Asurion and Telus that ended in 2014 when eSecuritel’s Brightstar Device Protection took over. Now, Asurion’s protection has been instated once again, for both Telus and Koodo.
“We are thrilled to partner with TELUS again to deliver an exceptional device care product,” said Aileen Trescher, Asurion Canada vice president and general manager of client services in a statement to MobileSyrup.
“Canadian telecom providers trust Asurion to ensure their customers are quickly reconnected, and we are honoured to accept that responsibility.
The new service took effect on February 14th and is now called ‘Telus Device Care’ rather than ‘Telus Device Protection Plan.’
The monthly fee is $7 CAD monthly and the service has two potential use charges: $29 for a ‘malfunction service charge’ and $79 for a ‘damage service charge.’
Telus’ new terms and conditions define covered failure as “a defect in parts or workmanship, a power surge or accidental damage such as dropping your phone or submerging it in water.” It does not, however, cover loss, theft, viruses or non-standard accessory damage.
Previously, the Telus Device Protection Plan was $7 and offered differing replacement fees dependent upon the quality tier of the device. The details of its coverage are a bit more vague, but it appears coverage for theft and loss are covered — or at least not specifically exempt.
Image credit: Pexels via Pixabay
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Apple has released its third iOS 10.3 public beta, bringing with it chiefly CarPlay updates. Enhanced CarPlay features include quick access to last three apps and a new ‘Up Next’ screen for music.
10.3 also features a new Find My AirPods feature, the ability to use the ‘Reduced Motion’ preference in Safari web apps, a new user security section in settings, a podcast app redesign that makes it look more like Apple Music and a new podcast widget.
Apple’s public beta is free to participate in and sign up can be accessed here.
iOS 10.3 is expected to release to general public in Spring 2017.
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OpenSignal has released its latest Global State of Mobile Networks report, providing a comprehensive snapshot of the overall global wireless landscape.
The report demonstrates that LTE steadily continues to displace 3G and that Wi-Fi remains an important feature for smartphone users, especially in Canada.
“Since our last global mobile networks report, we’ve seen average overall mobile data speeds increase steadily in countries worldwide. But we’re also seeing continued reliance on Wi-Fi networks as supplemental means of accessing the mobile internet. We may be in the 4G age, but, as always, consumers are using a multitude of wireless technologies,” states OpenSignal.
In terms of overall speed of data networks, Canada has improved marginally from 18.31Mbps in the last report to 20.26Mbps. 87 different countries were included in this section of the report’s findings, and even in an age of rapid wireless improvement, the results remain extremely broad.
Canada is the only country in the west to reach 20Mbps, giving the nation a ranking of 12th on the list of the world’s fastest national networks. This is up two places from its previous 14th position slot.
South Korea maintains its first place position, though the country’s average mobile data connection speed dropped slightly since the last report was issued, to 37.54Mbps. Other countries that crossed the 30Mbps threshold include Norway, Hungary and Singapore.
Canada lands over 20 positions above its southern neighbour, the United States, which averages a much lower mobile connection speed of 12.48 Mbps. The lowest average speed recorded among the countries on this list is Costa Rica at 2.69 Mbps.
Time on Wi-Fi
Unlike the last Global State of Mobile Networks report, this recent edition also focuses on the time spent on Wi-Fi by smartphone users around the world. 96 countries were included in this section of the report and of these nations, 38 had time on Wi-Fi scores of 50 percent or greater.
Canada takes a massive leap from the last section to place fourth in the Wi-Fi component, behind the Netherlands, China and Germany. According to the report, Canadians spend approximately 60.65 percent of their time on mobile networks connected to Wi-Fi.
This represents a 10 percent higher rate than the United States, whose residents spend just over half their time on mobile networks connected to Wi-Fi. The lowest recorded time on Wi-Fi of the countries included on this list was Nigeria, whose residents spend just over 11 percent of their time connected to Wi-Fi networks.
For this report 19,257,135,678 data points were collected from 1,095,667 users of OpenSignal’s speed testing app between November 1st, 2016 and January 31st, 2017.
Image Credit: Razor512
Source: Global State of Mobile Networks
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