The advice to date has, quite rightly, to get any COVID vaccine that’s available to you. For me, that’s meant a double dose of AstraZeneca, and I’m happy about that.
But as the pandemic progresses, we need to be aware that some vaccines are more effective than others. This working paper, building on one published in Nature earlier this year, looks at how ‘fractional dosing’ of the Moderna and Pfizer vaccines could reach more people more quickly.
Needless to say, we shouldn’t be in the position where people in less developed countries are getting access to vaccines much more slowly than the rest of the world. But, pragmatically speaking, this may help.
We supplement the key figure from Khoury et al.’s paper to show that fractional doses of the Moderna and Pfizer vaccines have neutralizing antibody levels (as measured in the early phase I and phase II trials) that look to be on par with those of many approved vaccines. Indeed, a one-half or one-quarter dose of the Moderna or Pfizer vaccine is predicted to be more effective than the standard dose of some of the other vaccines like the AstraZeneca, J&J or Sinopharm vaccines, assuming the same relationship as in Khoury et al. holds. The point is not that these other vaccines aren’t good–they are great! The point is that by using fractional dosing we could rapidly and safely expand the number of effective doses of the Moderna and Pfizer vaccines.
One more point worth mentioning. Dose stretching policies everywhere are especially beneficial for less-developed countries, many of which are at the back of the vaccine queue. If dose-stretching cuts the time to be vaccinated in half, for example, then that may mean cutting the time to be vaccinated from two months to one month in a developed country but cutting it from two years to one year in a country that is currently at the back of the queue.
It’s been a while since I studied Physics, so I confess to not exactly understanding what’s going on here. However, if it speeds up my internet connection at some point in the future, it’s all good.
“Our experiment shows that the generally held misconception that nothing can move faster than the speed of light, is wrong. Einstein’s Theory of Relativity still stands, however, because it is still correct to say that information cannot be transmitted faster than the vacuum speed of light,” said Dr. Lijun Wang. “We will continue to study the nature of light and hopefully it will provide us with a better insight about the natural world and further stimulate new thinking towards peaceful applications that will benefit all humanity.”
Benedict Evans recently posted his annual ‘macro trends’ slide deck. It’s incredibly insightful, and work of (minimalist) art. This article’s title comes from his conclusion, and you can see below which of the 128 slides jumped out at me from deck:
For me, what the deck as a whole does is place some of the issues I’ve been thinking about in a wider context.
My team is building a federated social network for educators, so I’m particularly tuned-in to conversations about the effect social media is having on society. A post by Harold Jarche where he writes about his experience of Twitter as a rage machine caught my attention, especially the part where he talks about how people are happy to comment based on the ‘preview’ presented to them in embedded tweets:
Research on the self-perception of knowledge shows how viewing previews without going to the original article gives an inflated sense of understanding on the subject, “audiences who only read article previews are overly confident in their knowledge, especially individuals who are motivated to experience strong emotions and, thus, tend to form strong opinions.” Social media have created a worldwide Dunning-Kruger effect. Our collective self-perception of knowledge acquired through social media is greater than it actually is.
I think our experiment with general-purpose social networks is slowly coming to an end, or at least will do over the next decade. What I mean is that, while we’ll still have places where you can broadcast anything to anyone, the digital environments we’ll spend more time will be what Venkatesh Rao calls the ‘cozyweb’:
Unlike the main public internet, which runs on the (human) protocol of “users” clicking on links on public pages/apps maintained by “publishers”, the cozyweb works on the (human) protocol of everybody cutting-and-pasting bits of text, images, URLs, and screenshots across live streams. Much of this content is poorly addressable, poorly searchable, and very vulnerable to bitrot. It lives in a high-gatekeeping slum-like space comprising slacks, messaging apps, private groups, storage services like dropbox, and of course, email.
That’s on a personal level. I should imagine organisational spaces will be a bit more organised. Back to Jarche:
We need safe communities to take time for reflection, consideration, and testing out ideas without getting harassed. Professional social networks and communities of practices help us make sense of the world outside the workplace. They also enable each of us to bring to bear much more knowledge and insight that we could do on our own.
…or to use Rao’s diagram which is so-awful-it’s-useful:
Of course, blockchain/crypto could come along and solve all of our problems. Except it won’t. Humans are humans (are humans).
Ever since Eli Parisier’s TED talk urging us to beware online “filter bubbles” people have been wringing their hands about ensuring we have ‘balance’ in our networks.
Interestingly, some recent research by the Reuters Institute at Oxford University, paints a slightly different picture. The researcher, Dr Richard Fletcher begins by investigating how people access the news.
Fletcher draws a distinction between different types of personalisation:
Self-selected personalisation refers to the personalisations that we voluntarily do to ourselves, and this is particularly important when it comes to news use. People have always made decisions in order to personalise their news use. They make decisions about what newspapers to buy, what TV channels to watch, and at the same time which ones they would avoid
Academics call this selective exposure. We know that it’s influenced by a range of different things such as people’s interest levels in news, their political beliefs and so on. This is something that has pretty much always been true.
Pre-selected personalisation is the personalisation that is done to people, sometimes by algorithms, sometimes without their knowledge. And this relates directly to the idea of filter bubbles because algorithms are possibly making choices on behalf of people and they may not be aware of it.
The reason this distinction is particularly important is because we should avoid comparing pre-selected personalisation and its effects with a world where people do not do any kind of personalisation to themselves. We can’t assume that offline, or when people are self-selecting news online, they’re doing it in a completely random way. People are always engaging in personalisation to some extent and if we want to understand the extent of pre-selected personalisation, we have to compare it with the realistic alternative, not hypothetical ideals.
Dr Richard Fletcher
Read the article for the details, but the takeaways for me were twofold. First, that we might be blaming social media for wider and deeper divisons within society, and second, that teaching people to search for information (rather than stumble across it via feeds) might be the best strategy:
People who use search engines for news on average use more news sources than people who don’t. More importantly, they’re more likely to use sources from both the left and the right. People who rely mainly on self-selection tend to have fairly imbalanced news diets. They either have more right-leaning or more left-leaning sources. People who use search engines tend to have a more even split between the two.
Dr Richard Fletcher
Useful as it is, what I think this research misses out is the ‘black box’ algorithms that seek to keep people engaged and consuming content. YouTube is the poster child for this. As Jarche comments:
We are left in a state of constant doubt as conspiratorial content becomes easier to access on platforms like YouTube than accessing solid scientific information in a journal, much of which is behind a pay-wall and inaccessible to the general public.
This isn’t an easy problem to solve.
We might like to pretend that human beings are rational agents, but this isn’t actually true. Let’s take something like climate change. We’re not arguing about the facts here, we’re arguing about politics. Adrian Bardon, writing in Fast Company, writes:
In theory, resolving factual disputes should be relatively easy: Just present evidence of a strong expert consensus. This approach succeeds most of the time, when the issue is, say, the atomic weight of hydrogen.
But things don’t work that way when the scientific consensus presents a picture that threatens someone’s ideological worldview. In practice, it turns out that one’s political, religious, or ethnic identity quite effectively predicts one’s willingness to accept expertise on any given politicized issue.
This is pretty obvious when we stop to think about it for a moment; beliefs are bound up with identity, and that’s not something that’s so easy to change.
In ideologically charged situations, one’s prejudices end up affecting one’s factual beliefs. Insofar as you define yourself in terms of your cultural affiliations, information that threatens your belief system—say, information about the negative effects of industrial production on the environment—can threaten your sense of identity itself. If it’s part of your ideological community’s worldview that unnatural things are unhealthful, factual information about a scientific consensus on vaccine or GM food safety feels like a personal attack.
So how do we change people’s minds when they’re objectively wrong?Brian Resnick, writing for Vox, suggests the best approach might be ‘deep canvassing’:
Giving grace. Listening to a political opponent’s concerns. Finding common humanity. In 2020, these seem like radical propositions. But when it comes to changing minds, they work.
The new research shows that if you want to change someone’s mind, you need to have patience with them, ask them to reflect on their life, and listen. It’s not about calling people out or labeling them fill-in-the-blank-phobic. Which makes it feel like a big departure from a lot of the current political dialogue.
This approach, it seems, works:
So it seems there is some hope to fixing the world’s problems. It’s just that the solutions point towards doing the hard work of talking to people and not just treating them as containers for opinions to shoot down at a distance.
We Have No Reason to Believe 5G Is Safe(Scientific American) — “The latest cellular technology, 5G, will employ millimeter waves for the first time in addition to microwaves that have been in use for older cellular technologies, 2G through 4G. Given limited reach, 5G will require cell antennas every 100 to 200 meters, exposing many people to millimeter wave radiation… [which are] absorbed within a few millimeters of human skin and in the surface layers of the cornea. Short-term exposure can have adverse physiological effects in the peripheral nervous system, the immune system and the cardiovascular system.”
Situated degree pathways(The Ed Techie) — “[T]he Trukese navigator “begins with an objective rather than a plan. He sets off toward the objective and responds to conditions as they arise in an ad hoc fashion. He utilizes information provided by the wind, the waves, the tide and current, the fauna, the stars, the clouds, the sound of the water on the side of the boat, and he steers accordingly.” This is in contrast to the European navigator who plots a course “and he carries out his voyage by relating his every move to that plan. His effort throughout his voyage is directed to remaining ‘on course’.”
on rms / necessary but not sufficient(p1k3) — “To the extent that free software was about wanting the freedom to hack and freely exchange the fruits of your hacking, this hasn’t gone so badly. It could be better, but I remember the 1990s pretty well and I can tell you that much of the stuff trivially at my disposal now would have blown my tiny mind back then. Sometimes I kind of snap to awareness in the middle of installing some package or including some library in a software project and this rush of gratitude comes over me.”
Screen time is good for you—maybe(MIT Technology Review) — “Przybylski admitted there are some drawbacks to his team’s study: demographic effects, like socioeconomics, are tied to psychological well-being, and he said his team is working to differentiate those effects—along with the self-selection bias introduced when kids and their caregivers report their own screen use. He also said he was working to figure out whether a certain type of screen use was more beneficial than others.”
Understanding extinction — humanity has destroyed half the life on Earth(CBC) — “One of the most significant ways we’ve reduced the biomass on the planet is by altering the kind of life our planet supports. One huge decrease and shift was due to the deforestation that’s occurred with our increasing reliance on agriculture. Forests represent more living material than fields of wheat or soybeans.”
Honks vs. Quacks: A Long Chat With the Developers of ‘Untitled Goose Game’(Vice) — “[L]ike all creative work, this game was made through a series of political decisions. Even if this doesn’t explicitly manifest in the text of the game, there are a bunch of ambient traces of our politics evident throughout it: this is why there are no cops in the game, and why there’s no crown on the postbox.”
What is the Zeroth World, and how can we use it?(Bryan Alexander) — “[T]he idea of a zeroth world is also a critique. The first world idea is inherently self-congratulatory. In response, zeroth sets the first in some shade, causing us to see its flaws and limitations. Like postmodern to modern, or Internet2 to the rest of the internet, it’s a way of helping us move past the status quo.”
It’s not the claim, it’s the frame(Hapgood) — “[A] news-reading strategy where one has to check every fact of a source because the source itself cannot be trusted is neither efficient nor effective. Disinformation is not usually distributed as an entire page of lies…. Even where people fabricate issues, they usually place the lies in a bed of truth.”
Today’s title comes from John Berger’s Ways of Seeing, which is an incredible book. Soon after the above quotation, he continues,
The eye of the other combines with our own eye to make it fully credible that we are part of the visible world.
That period of time when you come to be you is really interesting. As an adolescent, and before films like The Matrix, I can remember thinking that the world literally revolved around me; that other people were testing me in some way. I hope that’s kind of normal, and I’d add somewhat hastily that I grew out of that way of thinking a long time ago. Obviously.
All of this is a roundabout way of saying that we cannot know the ‘inner lives’ of other people, or in fact that they have them. Writing in The Guardian, psychologist Oliver Burkeman notes that we sail through life assuming that we experience everything similarly, when that’s not true at all:
A new study on a technical-sounding topic – “genetic variation across the human olfactory receptor repertoire” – is a reminder that we smell the world differently… Researchers found that a single genetic mutation accounts for many of those differences: the way beetroot smells (and tastes) like disgustingly dirty soil to some people, or how others can’t detect the smokiness of whisky, or smell lily of the valley in perfumes.
I know that my wife sees colours differently to me, as purple is one of her favourite colours. Neither of us is colour-blind, but some things she calls ‘purple’ are in no way ‘purple’ to me.
So when it comes to giving one another feedback, where should we even begin? How can we know the intentions or the thought processes behind someone’s actions? In an article for Harvard Business Review, Marcus Buckingham and Ashley Goodall explain that our theories about feedback are based on three theories:
Other people are more aware than you are of your weaknesses
You lack certain abilities you need to acquire, so your colleagues should teach them to you
Great performance is universal, analyzable, and describable, and that once defined, it can be transferred from one person to another, regardless of who each individual is
All of these, the author’s claim, are false:
What the research has revealed is that we’re all color-blind when it comes to abstract attributes, such as strategic thinking, potential, and political savvy. Our inability to rate others on them is predictable and explainable—it is systematic. We cannot remove the error by adding more data inputs and averaging them out, and doing that actually makes the error bigger.
Buckingham & Goodall
What I liked was their actionable advice about how to help colleagues thrive, captured in this table:
Finally, as an educator and parent, I’ve noticed that human learning doesn’t follow a linear trajectory. Anything but, in fact. Yet we talk and interact as though it does. That’s why I found Good Things By Their Nature Are Fragile by Jason Kottke so interesting, quoting a 2005 post from Michael Barrish. I’m going to quote the same section as Kottke:
In 1988 Laura and I created a three-stage model of what we called “living process.” We called the three stages Good Thing, Rut, and Transition. As we saw it, Good Thing becomes Rut, Rut becomes Transition, and Transition becomes Good Thing. It’s a continuous circuit.
A Good Thing never leads directly to a Transition, in large part because it has no reason to. A Good Thing wants to remain a Good Thing, and this is precisely why it becomes a Rut. Ruts, on the other hand, want desperately to change into something else.
Transitions can be indistinguishable from Ruts. The only important difference is that new events can occur during Transitions, whereas Ruts, by definition, consist of the same thing happening over and over.
In life, sometimes we don’t even know what stage we’re in, never mind other people. So let’s cut one another some slack, dispel the three myths about feedback listed above, and allow people to be different to us in diverse and glorious ways.
Also check out:
Iris Murdoch, The Art of Fiction No. 117(The Paris Review) — “I would abominate the idea of putting real people into a novel, not only because I think it’s morally questionable, but also because I think it would be terribly dull.”
A brief history of almost everything in five minutes(Aeon) —According to [the artist], the piece ‘is intended for both introspection and self-reflection, as a mirror to ourselves, our own mind and how we make sense of what we see; and also as a window into the mind of the machine, as it tries to make sense of its observations and memories’.
Let’s start this with an admission: my wife and I limit our children’s time on their tablets, and they’re only allowed on our games console at weekends. Nevertheless, I still maintain that wielding ‘screen time’ as a blunt instrument does more harm than good.
There’s a lot of hand-wringing on this subject, especially around social skills and interaction. Take a recent article in The Guardian, for example, where Peter Fonagy, who is a professor of Contemporary Psychoanalysis and Developmental Science at UCL, comments:
“My impression is that young people have less face-to-face contact with older people than they once used to. The socialising agent for a young person is another young person, and that’s not what the brain is designed for.
“It is designed for a young person to be socialised and supported in their development by an older person. Families have fewer meals together as people spend more time with friends on the internet. The digital is not so much the problem – it’s what the digital pushes out.”
I don’t disagree that we all need a balance here, but where’s the evidence? On balance, I spend more time with my children than my father spent with my sister and I, yet my wife, two children and me probably have fewer mealtimes sat down at a table together than I did with my parents and sister. Different isn’t always worse, and in our case it’s often due to their sporting commitments.
So I’d agree with Jordan Shapiro who writes that the World Health Organisation’s guidelines on screen time for kids isn’t particularly useful. He quotes several sources that dismiss the WHO’s recommendations:
Andrew Przybylski, the Director of Research at the Oxford Internet Institute, University of Oxford, said: “The authors are overly optimistic when they conclude screen time and physical activity can be swapped on a 1:1 basis.” He added that, “the advice overly focuses on quantity of screen time and fails to consider the content and context of use. Both the American Academy of Pediatricians and the Royal College of Paediatrics and Child Health now emphasize that not all screen time is created equal.”
That being said, parents still need some guidance. As I’ve said before, my generation of parents are the first ones having to deal with all of this, so where do we turn for advice?
“Just because [kids] may meet an unsavory person in the park, we don’t ban them from outdoor spaces,” said Mimi Ito, director of the Connected Learning Lab at University of California-Irvine, at the 10th annual Women in the World Summit on Thursday. After years of research, the mother of two college-age children said she thinks parents need to understand how important digital spaces are to children and adjust accordingly.
Taking away access to these spaces, she said, is taking away what kids perceive as a human right. Gaming is like the proverbial water cooler for many boys, she said. And for many girls, social media can bring access to friends and stave off social isolation. “We all have to learn how to regulate our media consumption,” Ito said. “The longer you delay kids being able to use those muscles, the longer you delay kids learning how to regulate.”
I feel a bit bad reading that, as we’ve recently banned my son from the game Fortnite, which we felt was taking over his life a little too much. It’s not forever, though, and he does have to find that balance between it having a place in his life and literally talking about it all of the freaking time.
One authoritative voice in the area is my friend and sometimes collaborator Ian O’Byrne, who, together with Kristen Hawley Turner, has created screentime.me which features a blog, podcast, and up-to-date research on the subject. Well worth checking out!
Also check out:
Teens ‘not damaged by screen time’, study finds(BBC Technology) — “The analysis is robust and suggests an overall population effect too small to warrant consideration as a public health problem. They also question the widely held belief that screens before bedtime are especially bad for mental health.”
Human Contact Is Now a Luxury Good(The New York Times) — “The rich have grown afraid of screens. They want their children to play with blocks, and tech-free private schools are booming. Humans are more expensive, and rich people are willing and able to pay for them. Conspicuous human interaction — living without a phone for a day, quitting social networks and not answering email — has become a status symbol.”
As an historian, I’m surprisingly bad at recalling facts and dates. However, I’d argue that the study of history is actually about the relationship between those facts and dates — which, let’s face it, so long as you’re in the right ballpark, you can always look up.
Understanding the relationship between things, I’d argue, is a demonstration of higher-order competence. This is described well by the SOLO Taxonomy, which I featured in my ebook on digital literacies:
This is important, as it helps to explain two related concepts around which people often get confused: ‘artificial intelligence’ and ‘machine learning’. If you look at the diagram above, you can see that the ‘Extended Abstract’ of the SOLO taxonomy also includes the ‘Relational’ part. Similarly, the field of ‘artificial intelligence’ includes ‘machine learning’.
There are some examples of each in this WIRED article, but for the purposes of this post let’s just leave it there. Some of what I want to talk about here involves machine learning and some artificial intelligence. It’s all interesting and affects the future of tech in education and society.
If you’re a gamer, you’ll already be familiar with some of the benefits of AI. No longer are ‘CPU players’ dumb, but actually play a lot like human players. That means with no unfair advantages programmed in by the designers of the game, the AI can work out strategies to defeat opponents. The recent example of OpenAI Five beating the best players at a game called Dota 2, and then internet teams finding vulnerabilities in the system, is a fascinating battle of human versus machine:
“Beating OpenAI Five is a testament to human tenacity and skill. The human teams have been working together to get those wins. The way people win is to take advantage of every single weakness in Five—some coming from the few parts of Five that are scripted rather than learned—gradually build up resources, and most importantly, never engage Five in a fair fight.” OpenAI co-founder Greg Brockman told Motherboard.
Deepfakes, are created via “a technique for human image synthesis based on artificial intelligence… that can depict a person or persons saying things or performing actions that never occurred in reality”. There’s plenty of porn, of course, but also politically-motivated videos claiming that people said things they never did.
There’s benefits here, though, too. Recent AI research shows how, soon, it will be possible to replace any game character with one created from your own videos. In other words, you will be able to be in the game!
It only took a few short videos of each activity — fencing, dancing and tennis — to train the system. It was able to filter out other people and compensate for different camera angles. The research resembles Adobe’s “content-aware fill” that also uses AI to remove elements from video, like tourists or garbage cans. Other companies, like NVIDIA, have also built AI that can transform real-life video into virtual landscapes suitable for games.
It’s easy to be scared of all of this, fearful that it’s going to ravage our democratic institutions and cause a meltdown of civilisation. But, actually, the best way to ensure that it’s not used for those purposes is to try and understand it. To play with it. To experiment.
Algorithms have already been appointed to the boards of some companies and, if you think about it, there’s plenty of job roles where automated testing is entirely normal. I’m looking forward to a world where AI makes our lives a whole lot easier and friction-free.
Also check out:
AI generates non-stop stream of death metal(Engadget) — “The result isn’t entirely natural, if simply because it’s not limited by the constraints of the human body. There are no real pauses. However, it certainly sounds the part — you’ll find plenty of hyper-fast drums, guitar thrashing and guttural growling.”
Experts Weigh in on Merits of AI in Education (THE Journal) — “AI systems are perfect for analyzing students’ progress, providing more practice where needed and moving on to new material when students are ready,” she stated. “This allows time with instructors to focus on more complex learning, including 21st-century skills.”
As I get older, I’m more aware that some things I do are very affected by the world around me. For example, since finding out that the intensity of light you experience during the day is correlated with the amount of sleep you get, I don’t feel so bad about ‘sleeping in’ during the summer months.
So it shouldn’t be surprising that this article in The New York Times suggests that there’s a good and a bad time to eat:
A growing body of research suggests that our bodies function optimally when we align our eating patterns with our circadian rhythms, the innate 24-hour cycles that tell our bodies when to wake up, when to eat and when to fall asleep. Studies show that chronically disrupting this rhythm — by eating late meals or nibbling on midnight snacks, for example — could be a recipe for weight gain and metabolic trouble.
A more promising approach is what some call ‘intermittent fasting’ where you restrict your calorific intake to eight hours of the day, and don’t consume anything other than water for the other 16 hours.
This approach, known as early time-restricted feeding, stems from the idea that human metabolism follows a daily rhythm, with our hormones, enzymes and digestive systems primed for food intake in the morning and afternoon. Many people, however, snack and graze from roughly the time they wake up until shortly before they go to bed. Dr. Panda has found in his research that the average person eats over a 15-hour or longer period each day, starting with something like milk and coffee shortly after rising and ending with a glass of wine, a late night meal or a handful of chips, nuts or some other snack shortly before bed.
That pattern of eating, he says, conflicts with our biological rhythms.
So when should we eat? As early as possible in the day, it would seem:
Most of the evidence in humans suggests that consuming the bulk of your food earlier in the day is better for your health, said Dr. Courtney Peterson, an assistant professor in the department of nutrition sciences at the University of Alabama at Birmingham. Dozens of studies demonstrate that blood sugar control is best in the morning and at its worst in the evening. We burn more calories and digest food more efficiently in the morning as well.
That’s not great news for me. After a protein smoothie in the morning and eggs for lunch, I end up eating most of my calories in the evening. I’m going to have to rethink my regime…
I don’t usually go in for detailed technical papers on stuff that’s not directly relevant to what I’m working on, but I made an exception for this. Here’s the abstract:
We construct targeted audio adversarial examples on automatic speech recognition. Given any audio waveform, we can produce another that is over 99.9% similar, but transcribes as any phrase we choose (at a rate of up to 50 characters per second). We apply our white-box iterative optimization-based attack to Mozilla’s implementation DeepSpeech end-to-end, and show it has a 100% success rate. The feasibility of this attack introduce a new domain to study adversarial examples.
In other words, the researchers managed to fool a neural network devoted to speech recognition into transcribing a phrase different to that which was uttered.
So how does it work?
By starting with an arbitrary waveform instead of speech (such as music), we can embed speech into audio that should not be recognized as speech; and by choosing silence as the target, we can hide audio from a speech-to-text system
The authors state that merely changing words so that something different occurs is a standard adverserial attack. But a targeted adverserial attack is different:
Not only are we able to construct adversarial examples converting a person saying one phrase to that of them saying a different phrase, we are also able to begin with arbitrary non-speech audio sample and make that recognize as any target phrase.
This kind of stuff is possible due to open source projects, in particular Mozilla Common Voice. Great stuff.