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By pulling this chart apart and then helping you put it back together, this story aims to help you understand: how quickly coronavirus is spreading in different countries; where Australia fits into the global picture; what we can learn from countries that appear to have curbed the rise of COVID-19; and what you can do to help keep Australians safe. But first, one concept that's vitally important to understanding a pandemic is exponential growth. This is a pattern viruses tend to initially follow, due to the way they're spread. The result is that what might seem like a small difference in the rate of growth can actually have enormous impacts on how many people are infected overall.

But because a machine learning model learns the boundaries of its world from its input data, just three people informed how any model using that dataset would interpret if 'childbirth' was emotional. This led to a perspective that has informed all of my work since: a dataset is a worldview. It encompasses the worldview of the people who scrape and collect the data, whether they're researchers, artists, or companies. It encompasses the worldview of the labelers, whether they labeled the data manually, unknowingly, or through a third party service like Mechanical Turk, which comes with its own demographic biases. It encompasses the worldview of the inherent taxonomies created by the organizers, which in many cases are corporations whose motives are directly incompatible with a high quality of life.

Wrapping your head around the scale of a global pandemic is not easy, and the volume of stats and data can be bewildering. What, for instance, are we to make of the fact Australia recorded just 109 new cases in its daily count for April 6? Given this figure peaked at around 400 new cases per day, does this mean the rate of infection is now tapering off? And what, apart from sadness, are we to make of more gruesome statistics, such as the 969 COVID-19 deaths reported in a single day in Italy on March 27? To help interpret and understand the mountains of COVID-19 data, we'll look at five commonly used methods, and explain the pros and cons of each.

'It's important to me that I make my own decisions, but I often wonder how much they are actually influenced by cultural and societal norms, by advertising, the media and those around me. We all feel the need to fit in, but does this prevent us from making decisions for ourselves? In short, can I ever be a truly free thinker?' Richard, Yorkshire. While being the lone "captain of your soul" is a reassuring idea, the truth is rather more nuanced. The reality is that we are social beings driven by a profound need to fit in - and as a consequence, we are all hugely influenced by cultural norms.

Almost one in four cancers detected in men were overdiagnosed in 2012, according to our new research, published today in the Medical Journal of Australia. In the same year, we found that approximately one in five cancers in women were overdiagnosed. Overdiagnosis is when a person is diagnosed with a "harmless" cancer that either never grows or grows very slowly. These cancers are sometimes called low or ultra-low-risk cancers and wouldn't have spread or caused any problems even if left untreated. Cancer overdiagnosis can result in people having unnecessary treatments, such as surgery, radiotherapy and hormone therapy. Being diagnosed with cancer and having cancer treatments can cause physical, psychological and financial harms.

how could two groups of 'experts' come up with such different conclusions, given they broadly agree of the evidence? David Aaronovitch in the Times identified the critical underlying issue behind the ensuing conflict: whether we take an individual- or a population-based approach. Essentially, the authors point out that any absolute risks are small from an individual perspective, and may generally be cancelled out by the enjoyment of eating, and the bother of changing habits. But these small benefits can be important from a public-health, population-wide perspective, since a lot of people making a small change, that only reduces their risk by a personally-negligible amount, can add up to thousands fewer cases of disease. That's what has generated the disagreement. It can be perfectly reasonable for guidance to be given by authorities, and it can also be perfectly reasonable for individuals to ignore it. Both can be 'right'.

Teach people to think critically about claims and comparisons using these concepts, urge Andrew D. Oxman and an alliance of 24 researchers - they will make better decisions.

Welcome! This app will help train you to make more accurate, better-calibrated predictions. For each question, you'll be prompted to say what you think the answer is and how confident you are in that answer. You should try to give the right answer whenever you can, but your main goal is to be accurate about how confident you are in each answer. In other words, your goal is to be "well-calibrated," which means that when you say you're 50% confident, you're right about 50% of the time, and when you say you're 80% confident, you're right about 80% of the time, and so on. Nobody is perfectly calibrated, but some people are much better calibrated than others, and a variety of studies suggest you can improve your calibration with the sort of practice this app provides.

A BBC episode (30 mins) on changing minds. There's a widespread belief that there's no point talking to people you disagree with because they will never change their minds. Everyone is too polarized and attempts to discuss will merely result in greater polarization. But the history of the world is defined by changes of mind -that's how progress (or even regress) is made: shifts in political, cultural, scientific beliefs and paradigms. So how do we ever change our minds about something? What are the perspectives that foster constructive discussion and what conditions destroy it? Margaret Heffernan talks to international academics at the forefront of research into new forms of democratic discourse, to journalists involved in facilitating national conversations and to members of the public who seized the opportunity to talk to a stranger with opposing political views:

False Equivalence: Why It's So Dangerous | Above the Noise

Numbers are often used to persuade rather than inform, statistical literacy needs to be improved, and so surely we need more statistics courses in schools and universities? Well, yes, but this should not mean more of the same. After years of researching and teaching statistical methods, I am not alone in concluding that the way in which we teach statistics can be counterproductive, with an overemphasis on mathematical foundations through probability theory, long lists of tests and formulae to apply, and toy problems involving, say, calculating the standard deviation of the weights of cod. The American Statistical Association's Guidelines for Assessment and Instruction in Statistics Education (2016) strongly recommended changing the pedagogy of statistics into one based on problemsolving, real-world examples, and with an emphasis on communication.

The proposal to drug test welfare recipients keeps on bouncing back. The most recent attempt, announced last week, is now the third proposal since 2017. But the tenacity with which the government is pursuing this agenda reflects, not necessarily a fixed policy position, but rather a moral stance. And this moral stance conflicts with that of the proposals' critics. Are we doomed to countless repeats of the same policy proposal? Or, as the Australian Social Policy Conference heard in Sydney this week, can we use philosophical arguments to help break the deadlock?

Everyone makes claims about what works. Politicians claim that stop-and-search policing will reduce violent crime; friends might assert that vaccines cause autism; advertisers declare that natural food is healthy. A group of scientists describes giving all schoolchildren deworming pills in some areas as one of the most potent anti-poverty interventions of our time. Another group counters that it does not improve children's health or performance at school. Unfortunately, people often fail to think critically about the trustworthiness of claims, including policymakers who weigh up those made by scientists. Schools do not do enough to prepare young people to think critically1. So many people struggle to assess evidence. As a consequence, they might make poor choices. To address this deficit, we present here a set of principles for assessing the trustworthiness of claims about what works, and for making informed choices (see 'Key Concepts for Informed Choices'). We hope that scientists and professionals in all fields will evaluate, use and comment on it.

Interesting article about how different kinds of data (like your social media data) can give insights into health, but don't have the same protections as health data

"Anonymised" data lies at the core of everything from modern medical research to personalised recommendations and modern AI techniques. Unfortunately, according to a paper, successfully anonymising data is practically impossible for any complex dataset.

Nice discussion on privacy, "How much do you value your privacy? Does it bother you what social media companies, governments know about you - your money, your body?"

"I am quite sure now that often, very often, in matters of religion and politics a man's reasoning powers are not above the monkey's," wrote Mark Twain. Having written a book about our most common reasoning errors, I would argue that Twain was being rather uncharitable - to monkeys. Whether we are discussing Trump, Brexit, or the Tory leadership, we have all come across people who appear to have next to no understanding of world events - but who talk with the utmost confidence and conviction. And the latest psychological research can now help us to understand why.

Last month, CNBC reported on a page in Google's account settings titled "Purchases" - a month-by-month list of items you've bought across online services like Amazon and other apps that are collected via Google services like Gmail. Purchases is a jarring example of how leaky our data really is and how large companies can aggregate that information unbeknown to the consumer. I, for one, was unaware that almost every concert ticket, Domino's pizza and Amazon purchase (including a 2014 accidental purchase of the film "Tango & Cash") was being logged by Google. Equally troubling: The purchases can't easily be deleted from the page without also deleting the receipt emails from your Gmail account.

Scientists have typically justified excluding female animals from experiments - even when studying conditions that are more likely to affect women - on the basis that fluctuating hormones would render the results uninterpretable. However, according to Rebecca Shansky, a neuroscientist at Northeastern University, in Boston, it is entirely unjustified by scientific evidence, which shows that, if anything, the hormones and behaviour of male rodents are less stable than those of females. Shansky is calling for stricter requirements to include animals of both sexes in research, saying the failure to do so has led to the development of drugs that work less well in women.

From climate change to armed conflict, our world is struggling with urgent global issues. But disagreements about how to solve them can spiral out of control. The only way to resolve intractable conflicts is to overcome desire to talk to allies more often than opponents. Here, a social psychologist, two ecologists and a cartoonist explain the toolbox of communication we need to resolve difficult issues.