Search Results for "bias"

Nov 30 2020

AI Doctor’s Assistant

I have discussed often before how advances in artificial intelligence (AI) are already transforming our world, but are likely to do so much more in the future (even near term). I am interested in one particular application that I think does not get enough attention – using AI to support clinical decision-making. So I was happy to read that one such project will share in a grant from the UK government.

The grant of £20m will be shared among 15 UK universities working on various AI projects, but one of those projects is developing an AI doctor’s assistant. They called this the Turing Fellowship, after Alan Turing, who was one of the pioneers of machine intelligence. As the BBC reports:

The doctor’s assistant, or clinical colleague, is a project being led by Professor Aldo Faisal, of Imperial College London. It would be able to recommend medical interventions such as prescribing drugs or changing doses in a way that is understandable to decision makers, such as doctors.

This could help them make the best final decision on a course of action for a patient. This technology will use “reinforcement learning”, a form of machine learning that trains AI to make decisions.

This is great to hear, and should be among the highest priority in terms of developing such AI applications. In fact, it’s a bit disappointing that similar systems are not already in widespread use. There are several types of machine learning. At its core, machine learning involves looking for patterns in large sets of data. If the computer algorithm is being told what to look for, then that is supervised learning. If not, then it is unsupervised. If it’s using lots of trial and error, that is reinforcement learning. And if it is using deep neural networks, then it is also deep learning. In this case they are focusing on reinforcement learning, so the AI will make decisions, be given feedback, and then iterate its decision-making algorithm with each piece of data.

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Nov 23 2020

Weaponizing Conspiracies

Published by under Conspiracy Theories

In 2019 PopSci published a flow chart they called “How to Start a Conspiracy Theory.” It’s not really about conspiracy theories themselves, but rather how to popularize an extreme idea. Many extreme claims are conspiracy theories, or at least incorporate conspiracy thinking as a way to justify themselves, so there is a lot of overlap.

What the chart really reflects is how to use social media and other outlets to weaponize disinformation. Let’s take a look at what I think are the main features, and then we can see how they apply specifically to conspiracy theories. The process starts by coming up with an idea that “resonates” with the public. This is probably the hard part as there are lots of ideas out there, and it is difficult to just invent something that will go viral. This is more like winning the lottery than an engineered result. But essentially the flow chart reflects an iterative process by which you keep tweaking the idea until it takes off.

If your goal is to manufacture viral misinformation, there are a few ways to almost guarantee this will work. The first is to already be plugged into a major information outlet, like a news network, a political party, or a celebrity. This is no guarantee, but it magnifies the chances of success by orders of magnitude over just being a member of the general public. This can also work indirectly if you have the resources to push your idea through those outlets (such as lots of money, or the resources of a country).

You can also crowd-source the iterative process. This is essentially what happens when there is an existing information ecosystem surrounding an ideology. For example, anti-vaxxers are already well established enough to have their own social media ecosystem, and they can collectively iterate ideas in their internal incubator, and then push those that seem to work best. Extreme political ecosystems work the same way, pushing all kinds of crazy ideas internally with their loyal base, and then trying to export them to the mainstream media. Occasionally an idea will hit.

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Nov 10 2020

Pre-Bunking Game

A new game called Harmony Square was released today. The game hires you, the player, as a Chief Disinformation Officer, and then walks you through a campaign to cause political chaos in this otherwise placid town. The game is based upon research showing that exposing people to the tactics of disinformation “inoculates” them against similar tactics in the real world. The study showed, among other things, that susceptibility to fake news headlines declined by 21% after playing the game. Here is the full abstract:

The spread of online misinformation poses serious challenges to societies worldwide. In a novel attempt to address this issue, we designed a psychological intervention in the form of an online browser game. In the game, players take on the role of a fake news producer and learn to master six documented techniques commonly used in the production of misinformation: polarisation, invoking emotions, spreading conspiracy theories, trolling people online, deflecting blame, and impersonating fake accounts. The game draws on an inoculation metaphor, where preemptively exposing, warning, and familiarising people with the strategies used in the production of fake news helps confer cognitive immunity when exposed to real misinformation. We conducted a large-scale evaluation of the game with N = 15,000 participants in a pre-post gameplay design. We provide initial evidence that people’s ability to spot and resist misinformation improves after gameplay, irrespective of education, age, political ideology, and cognitive style.

While encouraging, I think there are some caveats to the current incarnations of this approach. But first, let me say that I think the concept is solid. The best way to understand mechanisms of deception and manipulation is to learn how to do them yourself. This is similar to the old adage – you can’t con a con artist. I think “can’t” is a little strong, but the idea is that someone familiar with con artist techniques is more likely to spot them in others. Along similar lines, there is a strong tradition of skepticism among professional magicians. They know how to deceive, and will spot others using similar deceptive techniques. (The famous rivalry between James Randi and Uri Geller is a good example of this.)

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Nov 03 2020

Magic Amulets Do Not Prevent COVID

Published by under Pseudoscience

Retraction Watch has an interesting article about a very curious paper published in Science of the Total Environment. In fact, the paper and communication from the lead author are so bad I have to wonder if its a Sokal-like prank. If not, it is more evidence that the world has become so weird there are many things which are beyond satire. But let’s take this at face value. The title of the paper is: “Can Traditional Chinese Medicine provide insights into controlling the COVID-19 pandemic: Serpentinization-induced lithospheric long-wavelength magnetic anomalies in Proterozoic bedrocks in a weakened geomagnetic field mediate the aberrant transformation of biogenic molecules in COVID-19 via magnetic catalysis.”

Many scientific publications are extremely technical and require very long technical descriptions, but my “gratuitous jargon” alarm went off at this title. The paper itself is worse – I get the distinct impression it is using jargon not to be precise, but to impress and befuddle. But wading through the jargon, the claim here that has caught attention is this – “Nephrite-Jade amulets, a calcium-ferromagnesian silicate, may prevent COVID-19.” What? Wearing a jade amulet may prevent COVID-19? You are going to have to do better than dazzling with jargon to make that claim stick, or even to get it taken seriously. The fact that the authors reference Traditional Chinese Medicine (TCM) does not help either.

The co-founder of Retraction Watch, Ivan Oransky, wanted to get to the bottom of it also, so he wrote the following e-mail to the corresponding author, Moses Turkle Bility, PhD. Oransky wrote:

“Dr. Bility
I blog at Retraction Watch. Can you confirm that you co-authored this paper?”

That was it – a very simple query to confirm authorship. This is pretty standard in academia, just dotting all the i’s. This was Dr. Bility’s response:

Dear Dr. Ivan Oransky, yes, I published that article, and I kindly suggest you read the article and examine the evidence provided. I also suggest you read the history of science and how zealots have consistently attempted to block and ridicule novel ideas that challenge the predominant paradigm from individuals that are deem not intelligent enough. I not surprised that this article has elicited angry responses. Clearly the idea that a black scientist can provide a paradigm shifting idea offends a lot of individuals. I’ll be very candid with you; my skin color has no bearing on my intelligence. If you have legitimate concerns about the article and wish to discuss, I’ll address; however, I will not tolerate racism or intellectual intolerance targeted at me.

Whoa, where is that coming from? I suspect that Dr. Bility has already received some pushback prior to getting the very innocent query from Retraction Watch, but such a response is extremely telling. Bility immediately goes for the “small minded bigots can’t appreciate my paradigm-shifting brilliance” card. Sorry, Dr. Bility, but with that reaction you just branded yourself a crank and a pseudoscientist. Perhaps that’s not fair, but neither is this massively out-of-proportion response.

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Oct 20 2020

Daryl Bem, Psi Research, and Fixing Science

In 2011 Daryl Bem published a series of ten studies which he claimed demonstrated psi phenomena – that people could “feel the future”. He took standard psychological study methods and simply reversed the order of events, so that the effect was measured prior to the stimulus. Bem claimed to find significant results – therefore psi is real. Skeptics and psychologists were not impressed, for various reasons. At the time, I wrote this:

Perhaps the best thing to come out of Bem’s research is an editorial to be printed with the studies – Why Psychologists Must Change the Way They Analyze Their Data: The Case of Psi by Eric Jan Wagenmakers, Ruud Wetzels, Denny Borsboom, & Han van der Maas from the University of Amsterdam. I urge you to read this paper in its entirety, and I am definitely adding this to my filing cabinet of seminal papers. They hit the nail absolutely on the head with their analysis.

Their primary point is this – when research finds positive results for an apparently impossible phenomenon, this is probably not telling us something new about the universe, but rather is probably telling us something very important about the limitations of our research methods

I interviewed Wagenmakers for the SGU, and he added some juicy tidbits. For example, Bem had previously authored a chapter in a textbook on research methodology in which he essentially advocated for p-hacking. This refers to a set of bad research methods that gives the researchers enough wiggle room to fudge the results, enough to make negative data seem statistically significant. This could be as seemingly innocent as deciding when to stop collecting data after you have already peeked at some of the results.

Richard Wiseman, who was one of the first psychologists to try to replicate Bem’s research and came up with negative results, recently published a paper discussing this very issue. In his blog post about the article he credits Bem’s research with being a significant motivator for improving research rigor in psychology:

Several researchers noted that the criticisms aimed at Bem’s work also applied to many studies from mainstream psychology. Many of the problems surrounded researchers changing their statistics and hypotheses after they had looked at their data, and so commentators urged researchers to submit a detailed description of their plans prior to running their studies. In 2013, psychologist Chris Chambers played a key role in getting the academic journal Cortex to adopt the procedure (known as a Registered Report), and many other journals quickly followed suit.

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Oct 12 2020


Psychologists in the UK have created a game that pre-debunks (or “pre-bunks”) COVID-19 conspiracy theories. The game is based on research that shows it can be more effective to give people information about how to identify conspiracy theories or misinformation before they are exposed to it. This is a fantastic idea, and I love the fact that this is being done in coordination with research to show if it is effective.

The current game is called Go Viral. It puts the player in the role of someone spreading conspiracy theories about the pandemic, and their goal is to make the misinformation go as viral as possible. This way the players learn the deceptive tactics of those who spread such misinformation by doing it themselves. This tactic reminds me of magicians who are skeptics. They have learned the techniques of deception, and have experienced how easy it can be to deceive people. Stage magic is essentially the practical art of misdirection, that exploits many of the weaknesses in our ability to perceive and construct an experience of what is happening. This puts magicians into a perfect position to detect deceptive practices on the part of others.

James Randi, for example, made a career out of exactly this. He has caught faith healers, for example, using standard mentalist tricks to deceive their audience. One example is the one-ahead trick. You have everyone fill out a “prayer card” with their basic information and what they want to pray for. All these cards are placed in envelopes and are then placed in a bowl, and the preacher draws them one by one “predicting” what each one will say prior to opening the envelope and “revealing” that they were correct. The audience is flabbergasted as the preacher, by seemingly divine means, knows all about them. However, the preacher is simply stating what they just read on the previous card. If you are a magician, this technique is easy to detect – and now you can detect it much easier because I just told you about it.

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Oct 02 2020

Speaking of Venus

Published by under Astronomy

I recently discussed the exciting news of the discovery of phosphine gas in the clouds of Venus. This is exciting because phosphine is a potential marker of life. It should not exist on a small rocky world, and there is no known abiotic source on Venus. Microbes in the clouds above Venus are a plausible source, although scientists are careful to point out this is not proof of life, just a possibility. This finding has renewed interest in exploring our nearest neighbor, and even prior to this discovery NASA was planning another probe to Venus. This probe will likely have its mission altered to follow up on the phosphine discovery.

Venus is also interesting because it likely had a complex history over the last several billion years. A recent computer simulation, in fact, indicates that it may have been hospitable to life on the surface more than a billion years ago. Now the surface of Venus is hot enough to melt lead, making it the hottest planet in the solar system – even hotter than Mercury, which is closer. This is due to the extreme greenhouse effect from its mostly carbon dioxide atmosphere. The clouds above Venus are largely sulphuric acid. But a billion years ago it may have been more similar to Earth.

The dramatic change in Venus, in turn, may be tied to Jupiter. This is further connected to what we are learning about how stellar systems typically evolve, by observing exoplanetary systems. We now have many more data points than just our own solar system. We have confirmed over 4,000 exoplanets to date, with thousands more detected and awaiting confirmation. We can usually tell the mass, volume, and distance from the parent star, and so can construct a basic diagram of each system. However, depending on the method of detection used, we do not typically find every planet in an exosystem. Methods are generally biased towards larger and closer worlds.

One of the things we have discovered is that some planets are so-called hot Jupiters – they are gas giants orbiting very close to their star. About 10% of expolanets are hot Jupiters, and about 1% of systems have at least one hot Jupiter. Again – our detection systems more easily discover large and close planets, so these ratios may not represent reality and may be an overestimation. But a the very least, hot Jupiters are common throughout the galaxy.

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Aug 18 2020

How Algorithms Affect Your Life

This is one of those things that futurists did not predict at all, but now seems obvious and unavoidable – the degree to which computer algorithms affect your life. It’s always hard to make negative statements, and they have to be qualified – but I am not aware of any pre-2000 science fiction or futurism that even discussed the role of social media algorithms or other informational algorithms on society and culture (as always, let me know if I’m missing something). But in a very short period of time they have become a major challenge for many societies. It also is now easy to imagine how computer algorithms will be a dominant topic in the future. People will likely debate their role, who controls them and who should control them, and what regulations, if any, should be put in place.

The worse outcome is if this doesn’t happen, meaning that people are not aware of the role of algorithms in their life and who controls them. That is essentially what is happening in China and other authoritarian nations. Social media algorithms are an authoritarian’s dream – they give them incredible power to control what people see, what information they get exposed to, and to some extent what they think. This is 1984 on steroids. Orwell imagined that in order to control what and how people think authoritarians would control language (double-plus good). Constrain language and you constrain thought. That was an interesting idea pre-web and pre-social media. Now computer algorithms can control the flow of information, and by extension what people know and think, seamlessly, invisibly, and powerfully to a scary degree.

Even in open democratic societies, however, the invisible hand of computer algorithms can wreak havoc. Social scientists studying this phenomenon are increasing sounding warning bells. A recent example is an anti-extremist group in the UK who now are warning, according to their research, that Facebook algorithms are actively promoting holocaust denial and other conspiracy theories. They found, unsurprisingly, that visitors to Facebook pages that deny the holocaust were then referred to other pages that also deny the holocaust. This in turn leads to other conspiracies that also refer to still other conspiracy content, and down the rabbit hole you go.

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Aug 03 2020

Do Your Own Research?

A recent commentary on Forbes advises: You Must Not ‘Do Your Own Research’ When It Comes To Science. I agree  with everything the author, Ethan Siegel, says in the piece. It was a good start – but did not go far enough. For example, he did not really reach any conclusion about what people should actually do, beyond “listen to the experts.” OK – how, exactly, do we do that? This is not a criticism (I have written similar articles before) but an observation: after trying to communicate these same skeptical themes for decades and getting thousands of questions from the public, I have realized that it is perhaps not so obvious what it means to listen to the experts.

First let me amplify what Siegel gets right, although I may reframe it a bit. He correctly describes the typical process that people use when evaluating new information, although does not name it – confirmation bias. His summary is as good as any:

  • formulating an initial opinion the first time we hear about something,
  • evaluating everything we encounter after that through that lens of our gut instinct,
  • finding reasons to think positively about the portions of the narrative that support or justify our initial opinion,
  • and finding reasons to discount or otherwise dismiss the portions that detract from it.

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Jun 19 2020

News vs Commentary

The line between news and commentary has arguably become more blurred in recent decades. This has implications for libel law, which also reflects the shifting media landscape. A recent lawsuit involving Tucker Carlson illustrates the problem.

Carlson is being sued for defamation by Karen McDougal for a segment in which she claims Carlson accused her of extortion.  She is one of two women that we know of who were paid off to remain silent about affairs with Trump. Here is the money quote from Carlson:

“Two women approached Donald Trump and threatened to ruin his career and humiliate his family if he doesn’t give them money. Now that sounds like a classic case of extortion.”

For background, libel cases are hard to prove in the US. You need to demonstrate that statements were made in public that are claims to facts, that are factually wrong, where the person making the statement knew they were wrong or had a disregard for the truth, that there was malice of intent, and that actual harm resulted. For some statements you don’t have to prove harm, they are “libel per se,” such as accusing someone of pedophilia. The harm is taken for granted. If the target of the alleged defamation is a public figure, then the burden of proof is even higher.

At issue here are whether Carlson’s statements were presented as facts or opinion. Opinion is completely protected free speech, and cannot be defamatory legally. The first part of Carlson’s statement above is stated as simple fact. The second part (“that sounds like”) seems to be his analysis or opinion. Forgetting the other aspects of the defamation standard for now, this question seems to be the crux of the case. Was Carlson making a factual claim he knew to be untrue, or without concern for whether or not it was true? The defamation standard requires more than just being wrong.

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