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The big idea: should we get rid of the scientific paper? | Books

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When was the last time you saw a scientific paper? A physical one, I mean. An older academic in my previous university department used to keep all his scientific journals in recycled cornflakes boxes. On entering his office, you’d be greeted by a wall of Kellogg’s roosters, occupying shelf upon shelf, on packets containing various issues of Journal of Experimental Psychology, Psychophysiology, Journal of Neuropsychology, and the like. It was an odd sight, but there was method to it: if you didn’t keep your journals organised, how could you be expected to find the particular paper you were looking for?

The time for cornflakes boxes has passed: now we have the internet. Having been printed on paper since the very first scientific journal was inaugurated in 1665, the overwhelming majority of research is now submitted, reviewed and read online. During the pandemic, it was often devoured on social media, an essential part of the unfolding story of Covid-19. Hard copies of journals are increasingly viewed as curiosities – or not viewed at all.

But although the internet has transformed the way we read it, the overall system for how we publish science remains largely unchanged. We still have scientific papers; we still send them off to peer reviewers; we still have editors who give the ultimate thumbs up or down as to whether a paper is published in their journal.

This system comes with big problems. Chief among them is the issue of publication bias: reviewers and editors are more likely to give a scientific paper a good write-up and publish it in their journal if it reports positive or exciting results. So scientists go to great lengths to hype up their studies, lean on their analyses so they produce “better” results, and sometimes even commit fraud in order to impress those all-important gatekeepers. This drastically distorts our view of what really went on.

There are some possible fixes that change the way journals work. Maybe the decision to publish could be made based only on the methodology of a study, rather than on its results (this is already happening to a modest extent in a few journals). Maybe scientists could just publish all their research by default, and journals would curate, rather than decide, which results get out into the world. But maybe we could go a step further, and get rid of scientific papers altogether.

Scientists are obsessed with papers – specifically, with having more papers published under their name, extending the crucial “publications” section of their CV. So it might sound outrageous to suggest we could do without them. But that obsession is the problem. Paradoxically, the sacred status of a published, peer-reviewed paper makes it harder to get the contents of those papers right.

Consider the messy reality of scientific research. Studies almost always throw up weird, unexpected numbers that complicate any simple interpretation. But a traditional paper – word count and all – pretty well forces you to dumb things down. If what you’re working towards is a big, milestone goal of a published paper, the temptation is ever-present to file away a few of the jagged edges of your results, to help “tell a better story”. Many scientists admit, in surveys, to doing just that – making their results into unambiguous, attractive-looking papers, but distorting the science along the way.

And consider corrections. We know that scientific papers regularly contain errors. One algorithm that ran through thousands of psychology papers found that, at worst, more than 50% had one specific statistical error, and more than 15% had an error serious enough to overturn the results. With papers, correcting this kind of mistake is a slog: you have to write in to the journal, get the attention of the busy editor, and get them to issue a new, short paper that formally details the correction. Many scientists who request corrections find themselves stonewalled or otherwise ignored by journals. Imagine the number of errors that litter the scientific literature that haven’t been corrected because to do so is just too much hassle.

Finally, consider data. Back in the day, sharing the raw data that formed the basis of a paper with that paper’s readers was more or less impossible. Now it can be done in a few clicks, by uploading the data to an open repository. And yet, we act as if we live in the world of yesteryear: papers still hardly ever have the data attached, preventing reviewers and readers from seeing the full picture.

The solution to all these problems is the same as the answer to “How do I organise my journals if I don’t use cornflakes boxes?” Use the internet. We can change papers into mini-websites (sometimes called “notebooks”) that openly report the results of a given study. Not only does this give everyone a view of the full process from data to analysis to write-up – the dataset would be appended to the website along with all the statistical code used to analyse it, and anyone could reproduce the full analysis and check they get the same numbers – but any corrections could be made swiftly and efficiently, with the date and time of all updates publicly logged.

This would be a major improvement on the status quo, where the analysis and writing of papers goes on entirely in private, with scientists then choosing on a whim whether to make their results public. Sure, throwing sunlight on the whole process might reveal ambiguities or hard-to-explain contradictions in the results – but that’s how science really is. There are also other potential benefits of this hi-tech way of publishing science: for example, if you were running a long-term study on the climate or on child development, it would be a breeze to add in new data as it appears.

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There are barriers to big changes like this. Some are to do with skills: it’s easy to write a Word document with your results and send it in to a journal, as we do now; it’s harder to make a notebook website that weaves together the data, code and interpretation. More importantly, how would peer review operate in this scenario? It’s been suggested that scientists could hire “red teams” – people whose job is to pick holes in your findings – to dig into their notebook sites and test them to destruction. But who would pay, and exactly how the system would work, is up for debate.

We’ve made astonishing progress in so many areas of science, and yet we’re still stuck with the old, flawed model of publishing research. Indeed, even the name “paper” harkens back to a bygone age. Some fields of science are already moving in the direction I’ve described here, using online notebooks instead of journals – living documents instead of living fossils. It’s time for the rest of science to follow suit.

Further reading

Why Trust Science? by Naomi Oreskes

The Seven Deadly Sins of Psychology: A Manifesto for Reforming the Culture of Scientific Practice by Chris Chambers

Rigor Mortis: How Sloppy Science Creates Worthless Cures, Crushes Hope, and Wastes Billions by Richard Harris

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.NET 6 comes to Ubuntu 22.04 • The Register

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Ubuntu and Microsoft have brought .NET 6 to the Ubuntu repositories, meaning that you can install it without adding any extra sources to the OS.

The announcement means that Ubuntu 22.04 is catching up with the Red Hat Linux family. As per Microsoft’s online docs, you could already do this on Fedora 36 as well as the more business-like variants: RHEL 8, CentOS Stream 8 and 9, and via scl-utils on RHEL 7.

Microsoft’s blog post about the news also mentions the ability to install the runtime, or the full SDK, into Ubuntu containers. Canonical also has new versions of these. It describes Ubuntu ROCKs as “new, ultra-small OCI-compliant appliance images, without a shell or package manager,” smaller than existing Ubuntu container images thanks to a new tool called chisel.

.NET 6 is Microsoft’s cross-platform toolchain for building apps to run on multiple platforms, including Windows, Linux, macOS, and mobile OSes. Essentially, it’s Microsoft’s answer to Oracle’s JVM – the increasingly inaccurately named Java Virtual Machine, which now supports multiple languages, including Clojure, Kotlin, Scala, and Groovy.

Microsoft’s own list of .NET languages is relatively short – C#, F#, and Visual Basic – although there are many others from outside the company. The list arguably should include PowerShell, but that already has its own Linux version.

Since 2014 or so, .NET primarily means what was formerly called .NET Core. According to Microsoft’s own diagram, that means the .NET Common Language Runtime, the bit which allows “managed code” to execute, and Microsoft’s web app framework ASP.NET.

There are three separate packages: dotnet-sdk-6.0, the SDK; dotnet-runtime-6.0, the CLR runtime; and aspnetcore-runtime-6.0, the runtime for ASP.NET. All three can be installed at once via the dotnet6 metapackage.

The notable bits of .NET that aren’t included in Core are the venerable Windows Forms framework or the slightly more modern Windows Presentation Framework, WPF.

Compare and contrast: .NET Framework versus .NET Core

Diagram showing .NET Core design

Click to enlarge

So don’t get excited and think that the inclusion of .NET in Ubuntu means that graphical .NET apps, such as Windows Store apps, can now be built and run natively on Linux. Limit your expectations to server-side stuff. This is a mainly a way to deploy console-based C# and ASP.NET apps into Ubuntu servers and Ubuntu containers.

When we asked Canonical about this, a spokesperson responded: “WPF is not currently supported in .NET 6 on Ubuntu. So, you’re correct that .NET 6 on Ubuntu is aimed at developers building text/server apps rather than graphical/GUI apps.”

We’ve also asked Microsoft if they have any additional information or details, and will update when they respond.

There are cross-platform graphical frameworks for .NET, including the open-source Avalonia and as well as Uno, which got on board in .NET 5. There is also Microsoft’s own Multi-platform App UI, or MAUI, which evolved out of Xamarin Forms.

The origins of .NET lie in Microsoft’s 1996 acquisition of Colusa Software for its OmniWare tool, which Colusa billed as “a universal substrate for web programming.” As Microsoft faced off against the US Department of Justice and European Commission, and the possibility of being broken into separate apps and OS divisions, it came up with Next Generation Windows Services, which then turned into .NET: a way to use Microsoft tools to build apps for any OS.

There is still controversy over exactly how open .NET really is, as exemplified by the aptly named isdotnetopen site. ®

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How cognitive science can be used to bring AI forward

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Dr Marie Postma spoke to SiliconRepublic.com about misconceptions around AI as well its relationship with human consciousness.

AI and robots are getting ‘smarter’ all the time. From Irish-made care robot Stevie to Spot the robot dog from Boston Dynamics, these tech helpers are popping up everywhere with a wide range of uses.

The tech beneath the hardware is getting smarter too. Earlier this year, Researchers at MIT developed a simpler way to teach robots new skills after only a few physical demonstrations. And just this week, Google revealed how its combining large language models with its parent company’s Everyday Robots to help them better understand humans.

However, the advances in these areas have led to recent discussions around the idea of sentient AI. While this idea has been largely rebuffed by the AI community, an understanding of the relationship between cognitive science and AI is an important one.

Dr Marie Postma is head of the department of cognitive science and artificial intelligence at Tilburg School of Humanities and Digital Sciences in the Netherlands.

The department is mainly financed by three education programmes and has around 100 staff and between 900 and 1,000 students.

‘Technology is not the problem; people are the problem’
– MARIE POSTMA

The team focuses on different research themes that combine cognitive science and AI, such as computational linguistics with a big focus on deep learning solutions, autonomous agents and robotics, and human-AI interaction, which is mainly focused on VR and its use in education.

Postma was a speaker at the latest edition of the Schools for Female Leadership in the Digital Age in Prague, run by Huawei’s European Leadership Academy.

Postma spoke to the 29 students about cognitive science and machine learning, starting with the history of AI and bringing it up to the modern-day challenges, such as how we can model trust in robots and the role empathy could play in AI.

“We have research where we are designing first-person games where people can experience the world from the perspective of an animal – not a very cuddly animal, it’s actually a beaver. That’s intentional,” she told me later that day.

Sentient AI

Her talk brought about a lot of discussion around AI and consciousness, a timely discussion following the news that Blake Lemione, a Google engineer, published an interview with the AI chatbot and claimed that it had become sentient.

Postma said much of the media coverage around this story had muddied the waters. “The way it was described in the media was more focused on the Turing test – interacting with an AI system that comes across as being human-like,” she said.

“But then at some point they mention consciousness, and consciousness is really a different story.”

Postma said that most people who research consciousness would agree that it’s based on a number of factors. Firstly it’s about having a perceptual basis, both the ability to perceive the world around us but also what’s happening inside us and being self-aware.

Secondly, the purpose of consciousness is being able to interpret yourself as someone who has feelings, needs, actionability in the world and a need to stay alive. “AI systems are not worried about staying alive, at least the way we construct them now, they don’t reflect on their battery life and think ‘oh no, I should go plug myself in’.”

Possibilities and limitations

While AI and robots don’t have consciousness, their ability to be programmed to a point where they can understand humans can be highly beneficial.

For example, Postma’s department has been conducting research that concerns brain-computer interaction, with a focus on motor imagery. “[This is] trying to create systems where the user, by focusing on their brain signal, can move objects in virtual reality or on computer screens using [electroencephalography].”

This has a lot of potential applications in the medical world for people who suffer from paralysis or in the advancements of prosthetic limbs.

Last year, researchers at Stanford University successfully implanted a brain-computer interface (BCI) capable of interpreting thoughts of handwriting in a 65-year-old man paralysed below the neck due to a spinal cord injury.

However, Postma said there is still a long way to go with this technology and it’s not just about the AI itself. “The issue with that is there are users who are able to do that and others who are not, and we don’t really know what the reasons are,” she said.

“There is some research that suggests that being able to do special rotation might be one of the factors but what we’re trying to discover is how we can actually train users so that they can use BCI.”

And in the interest of quelling any lingering fears around sentient AI, she also said people should not worry about this kind of technology being able to read their thoughts because the BCI is very rudimentary. “For the motor imagery BCI, it’s typically about directions, you know, right, left, etc.”

Other misconceptions about AI

Aside from exactly how smart the robots around us really are, one of the biggest falsehoods that Postma wants to correct is that the technology itself is not necessarily what causes the problems that surround it.

“What I repeat everywhere I go, is that the technology is not the problem, people are the problem. They’re the ones who create the technology solutions and use them in a certain way and who regulate them or don’t regulate them in a certain way,” she said.

“The bias in some AI solutions is not there because some AI solutions are biased, they’re biased because the data that’s used to create the solutions is biased so there is human bias going in.”

However, while bias in AI has been a major discussion topic for several years, Postma has an optimistic view on this, saying that these biased systems are actually helping to uncover biased data that would have previously been hidden behind human walls.

“It becomes explicit because all the rules are there, all the predictive features are there, even for deep learning architecture, we have techniques to simplify them and to uncover where the decision is made.”

While Postma is a major advocate for all the good AI can do, she is also concerned about how certain AI and data is used, particularly in how it can influence human decisions in politics.

“What Cambridge Analytica did – just because you can, doesn’t mean you should. And I don’t think they’re the only company that are doing that,” she said.

“I’m [also] concerned about algorithms that make things addictive, whether it’s social media or gaming, that really try to satisfy the user. I’m concerned about what it’s doing to kids.”

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‘I’m buying Manchester United’: Elon Musk ‘joke’ tweet charges debate over struggling club’s future | Elon Musk

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Tesla billionaire Elon Musk briefly electrified the debate about the future of Manchester United by claiming on Twitter that he is buying the struggling Premier League club – before saying that the post was part of a “long-running joke”.

He did not make clear his views on new coach Eric ten Hag’s controversial insistence on passing out from the back, or whether unhappy star striker Cristiano Ronaldo should be allowed to leave, but he did say that if he were to buy a sports team “it would be Man U. They were my fav team as a kid”.

With the team rooted to the bottom of the league after a humiliating 4-0 away defeat to Brentford, the outspoken entrepreneur’s tweet offered hope – however –briefly – to fans who want to see the back of current owners, the Florida-based Glazer family.

Also, I’m buying Manchester United ur welcome

— Elon Musk (@elonmusk) August 17, 2022

Musk has a history of making irreverent tweets, and he later clarified the post by saying he was not buying sports teams.

No, this is a long-running joke on Twitter. I’m not buying any sports teams.

— Elon Musk (@elonmusk) August 17, 2022

Buying United, one of the biggest football clubs in the world, would have cost Musk at least £2bn, according to its current stock market valuation.

Manchester United’s recent on-pitch woes have led to increased fan protests against the Glazers, who bought the club in a heavily leveraged deal in 2005 for £790m ($955.51m).

The anti-Glazer movement gained momentum last year after United were involved in a failed attempt to form a breakaway European Super League.

But a takeover by Musk would have been a case of out of the frying pan and into the fire for the club, given the billionaire’s tendency for off-the-cuff remarks and falling foul of market regulators.

Many were quick to point out that Musk had also promised to buy Twitter for $44bn before the deal collapsed in July, and has also boasted about colonising Mars and boosting birthrates on Earth.

That’s what you said about Twitter.

— Sema (@_SemaHernandez_) August 17, 2022

Fans responded with a mixture of bafflement and optimism given the lowly status of a club used to occupying the top places in the league rather than the bottom.

Manchester United did not immediately respond to a request for comment.



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