Democracy, in a very real sense, is math. The point is to aggregate decision-making in order to arrive at the fairest outcome for the greatest number of people. Andrea Jones-Rooy, who spoke at NECSS this year, gave a great lecture about this. Here is an article she wrote about Arrow’s Theorem that goes over the basic concept, but she went into more detail during the talk. Essentially there is no system of voting that has perfect fairness (ranked choice vs least objectionable option, for example), so we just have to pick one and live with the trade-offs.

Jones-Rooy, however, was talking about different systems that work as intended, no cheating. If, however, one group puts their thumb on the scale, the democratic process can be massively distorted. Beyond a certain point you no longer even have a true democracy. Voting becomes a sham used to give a patina of legitimacy to a dictator or minority rule.

Perhaps the best known form of voting distortion in the US is gerrymandering. The best description I have heard of this is that it is a way for politicians to choose their voters, rather than voters to choose their politicians. The idea is to carve up voting districts deliberately to favor one party, so that even if they have 40% of the voters in one state, they can secure 60% or more of the representatives. (This doesn’t work for senators or presidents where voting is state-wide.)

Researchers, however, have published an article in Nature in which they describe a more insidious form of distortion – information gerrymandering. This amounts to a rigorous mathematical description of a phenomenon we have been discussing, the effect of social media networks on public opinion. They found:

Players are assigned to competing groups (parties) and placed on an ‘influence network’ that determines whose voting intentions each player can observe. Players are incentivized to vote according to partisan interest, but also to coordinate their vote with the entire group. Our mathematical analysis uncovers a phenomenon that we call information gerrymandering: the structure of the influence network can sway the vote outcome towards one party, even when both parties have equal sizes and each player has the same influence.

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The BBC reports a case in which an artificial intelligence (AI) system is named as a possible patent holder for a new invention, and interlocking food container. Apparently none of the people involved with the invention meet the criteria for being a patent holder, since they did not come up with the actual innovation.

As a result, two professors from the University of Surrey have teamed up with the Missouri-based inventor of Dabus AI to file patents in the system’s name with the relevant authorities in the UK, Europe and US.

That’s an interesting solution. It does seem that international patent law needs to evolve in order to deal with the product of machine learning creativity. I think this reveals what a true game-changer current AI can be. It’s breaking our existing categories and legal framework.

But I don’t want to talk about patent law, about which I have no expertise – I want to talk about AI, about which I also have no expertise (but I do have a keen interest and pay attention to the news). Over the last few years there have been numerous developments that show how powerful machine learning algorithms are becoming. Specifically, they are able to create solutions that the AI programmers themselves don’t fully understand. The Dabus system itself uses one component to generate new ideas, based on being fed noisy input. But then a second component evaluates those ideas and gives the first component feedback. This idea, having two AI systems play off each other, creates a feedback loop that can rapidly iterate and improve a design or solution. So essentially we have two AIs talking to each other, and humans are largely out of the loop.

AI systems have come up with simulations and other solutions that the scientists using the system do not understand. Sometimes they don’t even know how it was possible for the AI to come up with the solutions it did.

Even more interesting, AI systems have developed their own language that they use to communicate with each other, and no human currently understands that language.

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Weird things happen to most people at some point in their lives, and if not to you directly than probably to someone you know. But what is the ultimate meaning to such coincidences? They may seem amazing, and psychologically scream out for an equally amazing explanation.

Skeptics caution, however, that our tendency to see patterns and impose satisfying explanations combine with our relative lack of intuition for statistics to jump to unwarranted conclusions. If we do the math, then it becomes clear that very unlikely events should happen all the time, given enough opportunity.

Some people, however, do not want to give up the narrative value of coincidences so easily. Sharon Hewitt Rawlette, for example, has written a book about The Source and Significance of Coincidences, and prefers a more supernatural explanation. In a recent editorial for Psychology Today she strikes back at the skeptical explanation for coincidences. She basically has one point to make, but first she states the skeptical position:

Skeptics argue that, even if the odds that a particular event would occur at this particular moment to this particular person are very low, there are so many moments over the course of our lives and so many people on this planet, that even very improbable coincidences are bound to happen eventually, just by chance. This is often referred to as the Law of Very Large Numbers.

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Authenticity is a tricky concept when it comes to people, and is increasingly being challenged both in psychology and even with regard to physical objects (with regard to objects, the value rather than reality of authenticity is questioned).  Writing for Scientific American, psychologist Scott Barry Kaufman deconstructs the psychological concept of authenticity nicely. But let’s start with a standard psychology definition of what this means:

Authenticity generally reflects the extent to which an individual’s core or true self is operative on a day-to-day basis. Psychologists characterize authenticity as multiple interrelated processes that have important implications for psychological functioning and well-being. Specifically, authenticity is expressed in the dynamic operation of four components: awareness (i.e., self-understanding), unbiased processing (i.e., objective self-evaluation), behavior (i.e., actions congruent with core needs, values, preferences), and relational orientation (i.e., sincerity within close relationships). Research findings indicate that each of these components relates to various aspects of healthy psychological and interpersonal adjustment.

My issue with this definition is that each of those components don’t necessarily add up to something greater than the sum of the parts. I understand the concept of unbiased processing, for example,  but this still tells me nothing about how it leads to authenticity, and by extension what authenticity is. How is it different than just being psychologically healthy, as measured by more specific traits?

Kaufman reviews the research on authenticity and show that really it’s just a rationalization for holding a favorably biased view of ourselves. People tend to think they are being authentic when they are acting on their virtues, being their best self, and also acting in ways that are congruent with societal expectations. The concept of authenticity is, in essence, used to manage one’s reputation. I am being authentic when doing things that other people will view positively, and not being my true self when I do things that will harm my reputation.

But as Kaufman points out – everything we do is a manifestation of some aspect of our true self. If you are acting in a way that is not congruent with your core values, you are still doing it for a reason that is part of your overall personality – that is part of your “true self.” If you are engaging in biased processing, or being insincere, these are part of who you are also – otherwise you wouldn’t be doing them.

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A Reddit thread in the Skeptic subreddit is framed as criticism toward skeptical philosophy. The questions it raises are all important, and honestly the poster should have just framed his points as questions rather than criticisms, because they reflect not problems with skeptical philosophy but their poor understanding of it. So the first lesson here is – humility. Don’t assume that an entire field you don’t fully understand is wrong. Rather, start with the assumption that you have more to learn, and then let proponents make their best case.

There are many good responses in the thread, which shows that a reasonable understanding of skeptical philosophy is out there in the community. The questions are very common beginner errors, and so they are worth responding to in detail. My first response, however, (as others in the thread have pointed out) is to begin with a basic text of the subject. Read a philosophy book. I humbly suggest The Skeptics’ Guide to the Universe, which is designed to be a primer on skeptical philosophy and directly addresses all of the poster’s questions. But there are many good books out there, and even basic philosophical books on epistemology will do (they don’t have to be explicitly skeptical).

I point this out because I frequently encounter people who are trying to do philosophy without even realizing it, or without an appreciation for the depth of philosophy as an intellectual field. Philosophy is one of those things that everyone thinks they can do, even without a lick of education on the topic. Inevitably they make basic mistakes, often ones that were dealt with thousands of years ago by the first philosophers. This would be no different than making pronouncements about a highly technical field of science without ever having studied it, and without really knowing the position of experts.

He begins:

‘Fact’ – What is a ‘fact’? Google search says: “a thing that is known or proved to be true”. Here is my problem: ‘known’…by whom? I am from India and have seen both villages and towns. Different things are ‘known’ in different communities. For example, people in rural areas ‘know’ there exists witches and ghosts.

This is a basic question of epistemology – how do we know anything, and what does it mean to know something? Here is also a pearl – don’t rely on essentially a dictionary definition for insight into a technical term or concept.

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I turns out they were only “mostly dead.” Well, it depends on your definition of death.

This is an interesting study that has been widely reported, with a surprisingly small amount of hype. The New York Times writes:

‘Partly Alive’: Scientists Revive Cells in Brains From Dead Pigs
In a study that upends assumptions about brain death, researchers brought some cells back to life — or something like it.

All the reporting I have seen so far has appropriate caveats, but they are really trying hard to maximize the sensational aspects of this study. I actually wrote about this study one year ago when the data was first presented. Now it has been published, so there is another round of reporting (which interestingly ignores the prior reporting).

The quick version is that Yale neuroscientists collected decapitated pig brains four hours after death and then tried to keep the brain cells alive in order to see what would happen. It’s actually a great real-life Frankenstein type experiment, a fact not missed by some outlets. Here is what they did: Continue Reading »

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Every time I heard someone use the term “witch hunt” recently I was reminded of that quote from Indigo Montoya from The Princess Bride – “You keep using that word. I do not think it means what you think it means.” With the recent release of the Mueller report, many news outlets feel obliged to interview people on the street about their opinions. This is an inane practice that provides no useful information, just cherry-picks random opinions. Every single time I heard the term “witch hunt”, it was used incorrectly.

It’s not just random people who do not understand the term. Because Trump has used the term over 260 times and counting to refer to the Mueller probe, many political commentators have also been using the term – mostly incorrectly. Dana Milbank, for example, wrote in the Washington Post:

Just because Trump says something, however, doesn’t automatically mean it’s wrong. The treatment of Trump by special counsel Robert S. Mueller III and other investigators does have characteristics of a witch hunt. This is because Trump has characteristics of a witch.

So says a leading authority on the history of witchcraft, Thomas J. Rushford, history professor at Northern Virginia Community College in Annandale. In an anthropological sense, Trump “is really quintessentially a witch figure,” the professor tells me, and if what is happening to Trump is a witch hunt, “it is only in a good sense, that is, this is society policing the boundaries that they believe to be ethically and morally right.”

But there is no witch hunt “in a good sense.” This misunderstands the essence of what a witch hunt is. The logic here is that if Trump is analogous to a witch, then the investigation was a witch hunt. Or, on the other side, if Trump is innocent of collusion, then by definition the investigation to determine whether or not he is guilty is a witch hunt. One random interviewed person even said that because the probe found no evidence of collusion it was a “failed witch hunt.”

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Marcelo Gleiser is an astrophysicist and science popularizer. I have not read any of his works previously and was therefore not familiar with him. He recently won the Templeton Prize, of which I am not a fan. The prize is for:

The Templeton Prize honors a living person who has made an exceptional contribution to affirming life’s spiritual dimension, whether through insight, discovery, or practical works.

Many past winners were given the award for trying to align science and religious faith, which to me is a hopeless cause. This usually results in an attempt to use science or philosophy to prove a particular religious belief, an endeavor that always fails. It’s fair to say, then, that I had negative expectations when I saw this headline in Scientific American:

Atheism Is Inconsistent with the Scientific Method, Prize-Winning Physicist Says.

Here we go, I thought, another Templeton Prize winner trying to disprove atheism. But I read the interview with an open mind to see what he actually had to say, reminding myself of the principle of charity. I was pleasantly surprised. I have to say I found nothing I could disagree with.

First, that headline is misleading (I know, shocker). Gleiser is not an atheist, but only because he is an agnostic. He explains that the notion of whether or not a god exists is beyond evidence, and therefore the only scientific opinion one can have is agnosticism. You cannot know that God, or any particular god, does not exist in a scientific way.

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One of the core concepts in my book, The Skeptics’ Guide to the Universe, is that humans are inherently good at certain cognitive tasks, and inherently bad at others. Further, our cognitive processes are biased in many ways and we tend to commit common errors in logic and mental short-cuts that are not strictly valid. The human brain appears to be optimized by evolution to quickly and efficiently do the things we need to do to stay alive and procreate, and this has a higher priority than having an accurate perception and understanding of reality. (Having an accurate perception of reality has some priority, just not as much as efficiency, internal consistency, and pragmatism, apparently.)

One of the things humans are not generally good at is statistics, especially when dealing with large numbers. We have a “math module” in our brains that is pretty good at certain things, such as dealing with small numbers, making comparisons, and doing simple operations. However, for most people we quickly get out of our intuitive comfort zone when dealing with large numbers or complex operations. There is, of course, also a lot of variation here.

We give several examples to illustrate how people generally have poor intuition for statistics and certain kinds of math, and how our understanding of math runs up against our cognitive biases and flawed heuristics. These common examples include the fact that we have a poor intuitive grasp of randomness.

Probability also seems to be a challenge. How many people would you have to have in a room before having a >50% chance that two of them share the same birthday (not year, just day)? The answer is a lot less than most people guess – it’s just 23. We tend to underestimate how probabilities multiply when making multiple comparisons. This is why we are inappropriately amazed at coincidences. They are not as amazing as we naively think. The probability of someone winning the lottery twice is also a lot higher than you might think.

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The skeptical movement has always struggled with some unavoidable ironies. We are like a group for people who don’t like to join groups. We actively tell our audience not to trust us (don’t trust any single source – verify with logic and evidence). Our belief is that you really should not have beliefs, only tentative conclusions. Essentially, our ideology is anti-ideology.

This is because scientific skepticism is not about any set of beliefs or conclusions. It is all about process, just like science itself – question, observe, analyze, repeat.

This approach is both empowering and freeing. One of the most common observations I hear from those who, after consuming skeptical media for a time, abandon some prior belief system or ideology, is that they feel as if a huge weight has been lifted from their shoulders. They feel free from the oppressive burden of having to support one side or ideology, even against evidence and reason. Now they are free to think whatever they want, whatever is supported by the evidence. They don’t have to carry water for their “team”.

At the same time, this is one of the greatest challenges for skeptical thinking, because it seems to run upstream against a strong current of human nature. We are tribal, we pick a side and defend it, especially if it gets wrapped up in our identity or world-view.

All of the recent hand-wringing about fake news and a post-fact world is largely about an increase in this partisanship. People use motivated reasoning to defend their ideology against the intrusion of reality, and hyper-partisanship leads to hyper-motivated reasoning. It’s also about echochambers – ideological bubbles of information that reinforce our tribe and demonize all others. These echochambers are essentially institutionalized motivated reasoning, prepackaged misinformation and rationalizations.

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