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Things July 2019: Bias, Co-operation, Location, Video Games

Extremely Generic Questions

In earlier iterations of Things I would often set readers a puzzle or ask a tricky question, with answers reviewed in the next edition. I’d like to start a new series of these that I’m calling Extremely Generic Questions: questions often asked, but not very specific or even necessarily well-defined. The puzzle is not only to try to find the best answer to a question, but also to understand why it is so often asked.

So, the first question: what is wrong with young people today?

Subconscious bias

If you want to make optimal decisions, and also just be a decent person, I think subconscious bias is a very important factor to be aware of. Many people believe their judgement of aptitude is not influenced by gender (or any other unrelated characteristic), but data suggests this is not be the case.

Anecdotally but compellingly, there’s the email signature swap story, in which a male and female colleague swap their email signatures for a week and observe radical differences in how clients interact with them. Pleasingly, you can read the accounts of this from each side.

Auditions for an orchestra have the advantage that they can be conducted in a thoroughly meritocratic manner without ever actually seeing the candidates. It turns out that blind orchestra auditions improved women’s chances of success by 50%.

Similarly, scientific proposals for time using the Hubble Space telescope tried going partially blind; the results again showed women benefited from a more meritocratic process.

As I am sometimes involved with hiring people for work, I tried a version of this by making sure names were removed from CV’s before I reviewed them. Of course, I don’t have any large scale data to compare results, but the feeling of trying to assess a nameless CV was alarmingly transformative! It became very clear that as soon as I saw a name, I would start to construct a mental image based on (irrelevant) associations I had with people similarly named, and would then build on that image as I read the rest of the CV. Without a name as a starting point, the process of evaluation immediately felt like harder work, but also a lot more objective. Based on this and the above findings, I highly recommend it.

Thinking, Fast And Slow

After many years of seeing it recommended, I finally read Daniel Kahneman’s “Thinking, Fast and Slow”, which covers a lot of the biases I’ve been fascinated by for so long from essentially the very coal-face of that research.

I found it fascinating throughout and can see why so many recommended it, although I didn’t always agree with the interpretations. Given that I’m just some guy who studied maths/physics and read a few things, and the author is a Nobel prize winner with decades in the field, I have to recognise that my position on this is likely tenuous, but at least as far as maths go I feel I can comment.

Here’s my brief highlights.

Probability Problems
There is a strange and fuzzy line between not understanding what a question means, and not getting the answer right. I could ask people what 3 χ 4 is, and if they think it’s 12, that doesn’t mean they’re mysteriously misguided, it more likely means they just don’t know chi-notation*.  In many of the studies, participants were shown to give incorrect answers to statements involving probability, but one could just as well argue that participants didn’t really understand the statement and so were guessing. To be fair, the book goes on to show how phrasing probability questions differently (to my mind, more clearly) helps people reach more accurate results.

This is what I talked about in Things 122 on the topic of the Linda Problem / Conjunction Fallacy.

Forecasting and regression to the mean
I have to do quite a bit of forecasting at work, and I was surprised I had never come across this excellent rubric for anticipating a certain amount of regression to the mean.

Briefly: if you evaluate, say, fifty people on a task that involves some luck as well as skill, like accurately throwing something, then the people who did the very best (or the very worst) on their first attempt are unlikely to do as well (or badly) on a second attempt; their results were probably mostly flukes, and they will tend to ‘regress to the mean’.

If I am evaluating 12 different marketing campaigns and trying to forecast how well they do in future, the same kind of rule applies. The one that did very best was at least partially ‘lucky’, so will not necessarily be the best in future.

The rubric is as follows:
a) If the measure you want to predict has zero correlation with their future values (which you can figure out by viewing historical data), then you should predict that regardless of how they did, they will all perform averagely in future.

b) If the measure you want to predict perfectly correlates with the future, so whatever is the best now will be the best in future, then obviously you should predict that.

c) If the correlation between the present and the future is x%, then you should forecast any present deviation from average performance will decrease by (1-x)%!

That’s the terse version, you can read more about it here.

Evaluation of experiences
How much you liked or disliked an experience would intuitively be based on how long it was, and how much you were liking or disliking it at the time. Something that was unpleasant for 10 minutes should surely be ranked as worse than something that was unpleasant for only 5 minutes.

In practice, this isn’t how we evaluate things at all. We very highly weight our peak enjoyment (or discomfort), and how happy (or unhappy) we were at the very end of the experience, and a little bit the beginning; the absolute duration plays only a small part.

This probably means you should take fewer, shorter holidays, but it also depends on how you weight the importance of what Kahneman calls the “experiencing self” and the “remembering self”, which is quite a tricky philosophical problem.

Life is like an Iterated Prisoner’s Dilemma, except different

As a student I was very interested in the Prisoner’s Dilemma, and the iterated version, in which one must choose to Co-operate with (C) or Defect against (D) another player making the same choice, knowing that you will come out best (and they worst) if you D while they C, but you will both do terribly if you both choose D.

One critical element: you can’t communicate with the other player. In the iterated version, the choice of C and D is effectively the method by which you communicate.

Meanwhile in real life, most of the time, the thing most likely to help you is another human, and the thing most likely to do you harm is also another human, which means interacting with other humans is a pretty crucial business. In particular it’s good to be able to figure out – and influence – who is likely to co-operate (C) with you and who is likely to try to take advantage of (D) you.

I studied maths and physics as a student, but struggled to understand human behaviour. By studying subjects where exam answers were simply right or wrong, and doing quite well at those, I (and I suspect many others in the same situation) thought that I must be quite clever, and the reason I can’t understand human behaviour is because other people are just acting irrationally.

Now, it is true that people act irrationally a lot of the time (see the last Things), but that also includes me, and a lot of the things I couldn’t understand eventually made more sense when I realised that life was like an iterated Prisoner’s Dilemma, except that rounds aren’t discrete or simultaneous and there are multiple and varying pay-off matrices in play all the time.

For example, I noticed people asked “How are you?” but didn’t actually want to know, which seemed irrational. This was laid bare for me in a dentist’s waiting room when one elderly person entered and recognised another, and the following exchange took place:

A: Oh, hello there! How are you?
B: I’m fine, how are you?
A: I’m fine thanks. So [short pause] how are you then?
B: Well, I’ve been having this awful pain in my side, so I went to the doctor last week …

Similarly, as a marketing grad I was sent out with a cameraman to stop people on the street and get their opinions on climate change for a vox pop montage. I would walk up to people and ask them right away, and nobody stopped to answer. The cameraman, who had done this before, told me I should ask them how they were first. This seemed ridiculous, as a person approaching you with a microphone and film camera obviously doesn’t care how you are, they just want to film you saying something. But I tried asking anyway, and suddenly just about everyone was then happy to give their opinion on climate change for the camera.

I realised the whole “How are you” bit is like a tiny move in an iterated Prisoner’s Dilemma in which you are really communicating “I will co-operate with you”, and the other person can demonstrate a reciprocal intention by asking you the same thing back. This then sets the scene for further and deeper co-operation.

Moves aren’t just made in speech either. I thought buttoned shirts were ridiculous in comparison with t-shirts: uncomfortable, more time-consuming to put on and remove, and harder to clean. Why would anyone choose to wear one? But it turns out clothing is a widely understood opening move in our co-operation dialogues. We learn that we can estimate by someone’s clothes how likely they are to co-operate with or benefit us in certain ways; uniforms do this in an overt way, but even a slight deviation from your company’s dress code sends a signal.

Cat and girl covered this, of course.

More generally, these kinds of behaviours make a society cohesive – by doing what everyone else does, you tacitly signal that you are a good co-operator in your society. At the same time it can make society conservative, as anyone deviating from locally normal behaviour (even for rational reasons) might be read as less co-operative, and so they will encounter more friction.

Location Encoding

What3Words (W3W) assigns each 3m x 3m square on Earth a three word designation (e.g. Each.Useful.Shark). This makes it fantastic for real-world treasure hunts, so long as the participants can use the mobile app, and I’ve made a couple of events that leveraged it to (I thought) rather fun effect.

However, Richard brought to my attention that among people interested in the general problem of addressing, W3W is viewed very negatively. Why is that?

Reading up on the subject (this post was particularly useful), it seems like W3W lacks some attributes a truly general Location Encoding system should really have. But what really annoys people who understand this area well is that W3W tends to put out PR that claims to be strong in the areas it is weak. In brief:

  • W3W is a private company (probably hoping to be acquired by another one). Location/address is something that works best when it’s a standard, and having a private company own a standard leads to conflicts of interest. (See the Microsoft ‘Embrace, Extend, and Extinguish’ strategy for an example of how private companies fight public standards).
  • W3W is not a good solution for emergency situations (calling an ambulance to your location; calling a Fire Engine to a location you see on fire).
  • W3W is not error tolerant and has no hierarchy (e.g. one mis-spelt/mis-remembered character has very little chance of being corrected, in contrast with traditional addresses, where post accurately addressed apart from saying “Brighton” instead of “Hove” still successfully gets to Hove with the word Brighton angrily crossed out and corrected).

Still, I do think W3W has some value, and it would be unreasonable to discard it entirely because it can’t do everything – indeed, no address system can meet all the requirements we might ask of it.

Google Maps’ location-sharing functionality covers many options, and has the benefit of being already available in many people’s pockets, but I recently had a situation where both intuitive addressing and Google failed: meeting at the “Joe’s Café in Soho” does not specify a unique location, and the inaccuracy of GPS meant a shared Google location didn’t resolve the matter either. W3W is actually pretty excellent for this sort of spontaneous meeting. All things considered though, the best thing about it really does seem to be the opportunities for Treasure Hunts.

Video Games

I’ve played some games since the last Things, some of which I recommend, and some of which I don’t!

Baba Is You (Steam, Humble store, itch.io, Switch)

The mostly instantly-gettable trailer seems to be in this tweet:

For Things readers partial to self-referentiality and all things meta (and I know there are a bunch of you), this is certainly worth a look. As the above video shows, the game is played by pushing things around, including words that define the rules of the game.

In practice it’s even more mind-boggling than I expected, but not actually as much fun as I had hoped.

Celeste (Steam, itch.io, Switch, PS4, Xbox One, Pico-8 prototype)
If you want a platform game with puzzle elements and enjoy dying repeatedly while you slowly get better at doing difficult things, this is extremely the thing for you. The soundtrack is quite lovely too.

My save file, 44 hours, 10,000+ deaths, is a review in itself (implicit spoilers split-by-level version is here):

Lovers in a Dangerous Space Time (Steam, Switch, PS4, Xbox One)
Looks exactly like what it is: a rather nice local co-op shooter in which you and some friends control characters running around a ship manning the helm/gun/shield/panic-button and rescuing animals in space.

Thomas Was Alone (Direct for Mac or PC, iOS, Android, Steam)
A kind of “self-aware” puzzle-platformer that everyone was going on about a few years ago; I finally tried it and found it dull and not at all as funny as it seemed to think it was, with frustratingly vague platforming physics.

The Legend of Zelda: Breath of the Wild (Switch and Wii U only)
An open world epic about saving the world which I tried – and failed – to enjoy for about 12 hours before giving up. Almost everything about it felt like a chore and I couldn’t understand how it gained such universal acclaim.

After a weirdly long time adventuring in my underwear, I finally found someone who would sell me clothes.

To pick one example, a complaint I had heard from some was that weapons could only be used a certain amount of time before they fell apart and had to be replaced. I thought this was just misguided resentment of a feature clearly designed to add strategy to battles, but then I spent the first hour of the game picking up and discarding 37 differently ineffectual sticks (you can only hold a few at a time) and fought about 5 monsters. It felt like I spent substantially more time managing my ineffectual stick inventory than having battles, and so the whole weapons feature then felt like busywork.

Loading screen tip: read loading screen tips. By definition, this is useful to nobody.

Perhaps the worst part is I still feel like I “should” give it more of a chance, or at least get more entertainment for my money, when rationally I know there must be more games out there like Celeste which were an order of magnitude more fun for a fraction of the price.

Horizon Zero Dawn (PS4 only)
Snakes on a Plane is a great title for a film because it perfectly sells the premise. Horizon Zero Dawn is a terrible name in that regard, but the promotional art sells the premise perfectly:

Tribal humans hunting robot dinosaurs! Which immediately looks like something I want to try, and also very quickly raises the question of just how such a scenario could even come about. It turns out the game is exactly about those two things: hunting robot dinosaurs while figuring out how this happened!

It certainly stands on the shoulders of giants in terms of the use of ‘Open World’ game conventions, but it adds a few interesting ideas and does just about everything you would hope to extremely well.

*I made up “chi-notation”, because I couldn’t think of a clearer example, it seemed funny, and illustrates the point just as well.

– Transmission finally ends

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Things April 2017: Multiplayer Mobile games, Weight loss and Physics, Paranoia and Tolerance

This issue of Things was initially drafted in January 2016 and for various reasons is just coming out now. Let’s see how out of date it is…

Mobile Game of the Moment: Dreii

Mobile gaming is very exciting, because touch-interface location-aware always-online devices open up an amazing new landscape of interactive possibilities. Mobile gaming is also very depressing because these possibilities are rarely harnessed in an interesting way, and even when they are it rarely leads to commercial success.

This is exactly why I’m recommending you get Dreii right now (available on Android, iOS and also on Steam).

It’s an elegant physics-based puzzler in which you try to stack objects under various challenging constraints. The really brilliant bit is that you get to co-operate with anyone else that happens to be playing the same level (on any device) at the same time as you. There’s also a rather lovely map visualisation in which you can see what levels others are playing to better seek them out – or go back and help another player make it through to the one you’re stuck on!

The helpfulness of others is massively varying, which is part of the charm. I recommend it right now as the recent launch ensures a goodly surge of currently active players.

Update: well, that was written about a year ago, so I can’t really recommend it as much because few are now playing it. You can do local co-op with someone else playing at the same time though, so it’s still worth a go if you can arrange for that!

Or go and play the other brilliant game I got into in the intervening time: Snakebird (iOS, Android, Steam), an incredibly simple yet extremely difficult puzzle game.

Or go and play Crash of Cars (iOS, Android), which is real-time arcade-style car combat and is being played by a few million people at the time of writing.

Humans are More Complicated than Physics, part 94: Weight vs Diet

If you want to lose weight, don’t eat. This is not medicine, it’s thermodynamics. If you take in more than you use, you store it.
– Michael Bloomberg

It seems most people agree with Bloomberg’s appealing logic. It turns out, as it often does, that humans are more complicated than simple physics would suggest.

Vox has a great look at the energy-in energy-out model here. The most striking conclusion of their wide-ranging review of research is that exercise is great for health, but not for weight loss. For weight loss, diet is a much more important component. So Bloomberg is sounding roughly right, but the mystery then deepens when we consider a study that found people on the same diet and exercise regimes put on more weight now than they did in the 80’s.  Note that although the Atlantic’s headline is “Why It Was Easier to Be Skinny in the 1980s”, the article doesn’t answer the question, because we don’t actually know. We just have some theories.

Finally, on Aeon, David Berreby dives a lot deeper into this mystery. Most striking for me was the finding that over the last two decades, animals as well as humans have gained weight – including lab mice, which have gained an average of 11% per decade despite having rigorously consistent diets. If you want to read about some fascinating theories on why this might be happening (light? BPA? A virus?), go check it out.

Since that was all a bit depressing, here’s some fun data on how the UK’s diet has changed over time.

Paranoia in Politics

Quite a few months ago (er, a year ago now) Charlie Stross wrote about the Paranoid Style in politics. He cites two fascinating essays charting the relationship between paranoia / conspiracy-theories and US Republicans (one from 50 years ago and one more recent). Things like “9/11 was an inside job”, vaccine-related conspiracies, or any time you hear the phrase “Liberal elite”. Stross then adds his own interpretation of how the internet has reinforced this and given rise to (take a deep breath) an “ad-hoc movement of angry ideologues who have jabbed their fungal hyphae into the cerebral cortex of Reddit and n-chan to parasitically control the rageface collective.”

Well, a year has gone by and this has all become rather more clear. I think the only useful thing to add is that Popularism (in the sense of a political movement that believes most of the existing power structures are self-serving, corrupt, and out-of-touch) is clearly a close relative of the Paranoid Style.

Google Image Reverse Search growing in Intelligence?

If you want to search based on an image (to find where it came from, or a higher resolution version) you can use TinEye and get limited but exact results. Or you can use Google’s “Search by image” functionality to get a wide range of approximate results. I do this quite a lot while trying to track down the artists behind work I post on my daily drawing Tumblr.

I recently tried to use it to trace the origin of this piece:

I was unable to find the artist, but I was extremely impressed that Google suggested a page of ‘similar images’ which were indeed a lot of paintings of cats with a similar colour palette and often distorted proportions:

You can of course use these properties of the search algorithm to generate art.

Tolerating the Tolerable

“I can Tolerate anything except the Outgroup” is an essay by Scott Alexander on filter bubbles and tolerance. It’s so interesting to me that I’ll summarise it all below, but I recommend reading it in full.

  • Alexander defines Tolerance as “respect and kindness toward members of an Outgroup”, and defines an Outgroup as a group that has “proximity plus small differences”: a group of people who live in the same neighbourhood but who are ‘slightly’ different to you. I’m capitalising these terms because the definitions aren’t sufficiently general – for example, you could be racist but still Tolerant under this definition.
  • He broadens typical US political alignments into ‘tribes’: Conservatives are Red tribe, Liberals are Blue tribe (the US political colour binary reverses the UK’s). As a side note he also identifies a libertarian-leaning Grey Tribe, which I’ve found to be a useful concept – the Grey tribe is typified by:

“…libertarian political beliefs, Dawkins-style atheism, vague annoyance that the question of gay rights even comes up, eating paleo, drinking Soylent, calling in rides on Uber, reading lots of blogs, calling American football “sportsball”, getting conspicuously upset about the War on Drugs and the NSA, and listening to filk”

  • Alexander then asserts that the liberal Blue tribe’s outgroup is in fact the Red tribe. He gives the interesting example of being roundly criticised by Blues for expressing any kind of relief at Osama bin Laden’s death, only to later see those same people openly celebrating the death of Margaret Thatcher.
  • Finally, he suggests that political articles that reference ‘Americans’ or ‘White people’, written by Blue tribe people (who are notionally included in those groups), are tacitly actually about Red tribe members, and when a Blue says “I can tolerate anything except intolerance”, they are identifying intolerance with the Red tribe and are actually saying “I can tolerate anything except the Red tribe / my Outgroup” which no longer sounds that impressive.

In an excellent coda, Alexander then realises that he’s doing the same thing: criticising a group he notionally is a member of (the Blue tribe), but actually criticising his Outgroup, as he realises he’s probably Grey.

While I think this is an interesting argument, I do think it’s important to note that being intolerant of a group of people who hold opposing political views (which can’t be identified on sight, and can change) seems far less egregious than being intolerant of people who simply look a certain way. Views are, after all, one step away from Actions, but that’s a distinction I’ll get to in the next edition of Things.

– Transmission finally ends

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Things October 2015: Social Status, External Staircase, Gangster Cats, Music Variants

Human Nature: Social Status, and Laughter

I know of two particularly powerful ideas for explaining a lot of human nature.

First, in this article, Kevin Simler writes up his findings after reading up on the literature regarding social status. The key insight is that we recognise social status through just two different strategies: Dominance, and Prestige. There are some interesting snippets about how we negotiate these differently; for example, you tend to avoid eye-contact with someone that has a higher Dominance-based status than you, but you actively seek eye contact if their status is through Prestige. There’s a lot of other interesting points so you should really just go read it, even if the author does slightly overstate the whole red-pill/rabbit hole bit.

Secondly, some years ago I read a theory about why we smile and laugh from neuroscientist Vilayanur Ramachandran that had an impressive amount of explanatory power. The central idea is that we smile or laugh to signal that something that seems like a “threat” is actually fine. Over millennia, that response has applied to ever more general types of “threat”, such as someone saying something that doesn’t make sense until you re-interpret what they must mean (like a joke). I’m not sure where I originally read it, but it’s covered quite well by William Herkewitz here.

 

Conical Helix Church Spire External Staircase!

I went to Copenhagen recently, and one of my favourite things was climbing the spire of the Church of our Saviour (Vor Frelsers Kirke), because the staircase climbs the outside part of the spire:

I particularly enjoyed the way it continues to spiral in at the very top until it’s too narrow for a human to squeeze up, creating a brilliant combination of claustrophobia and acrophobia:

 

AudioBooks to watch out for

Last time I pointed out how you can borrow audiobooks from your local library remotely using Overdrive. Having tried it out, I particularly recommend HP Lovecraft’s Nyarlathotep for a highly condensed 10 minutes of Lovecraftian madness, juxtaposed mind-bogglingly with the creepily up-beat and optimistic pre- and post audio that bigs up the company behind the recording.

I don’t recommend listening to Hunter S. Thomson’s The Rum Diary. I naively thought it would be a reasonable introduction to his work, but it turns out to be a book he wrote in his early 20’s and couldn’t get published; it finally saw print in the 90’s when he needed the money and had made his name with better work.

 

Gangster cat videos

Having watched a bunch of cat videos with “gangster” soundtracks in the hope that there would be more as good as the first two I had seen, I can confirm that there aren’t, so these are all you need to bother with:

(In case of removed video, try this search)

 

(In case of removed video, try this search)

 

Extreme theme park rides

Back in 2013 I attended some of the London International Animation Festival, and included a couple of the highlights in Things 130. In a strand that included both documentary and animation shorts, my favourite was “The Centrifuge Brain Project”, which I couldn’t find online when I published Things 130 but has now in fact appeared! Check it out:

(In case of removed video, try this search)

 

Musical Covers and related concepts

Last time I gave some examples of what I considered to be notable covers. Simon pointed out that the perception of a cover is strongly tied to which version you heard first, making the definition potentially subjective. In my case I only distantly remembered Kylie’s Hand On Your Heart when I heard Jose Gonzalez’s version, which gave it an eerie familiarity, but when I then went back to listen to Kylie’s it sounded like a ridiculous imitation of Gonzalez. This problem multiplies when a cover gains significantly more attention than the original, and seems ridiculous in the context of the strategy in the 40’s and 50’s of releasing as many covers as possible to maximise the return for a composition: as Kottke draws together, Baby, It’s Cold Outside saw 9 releases in 1949, with some covers beating the “original” to the market.

Laurence commented:

“How are we defining ‘cover’ here? For example, while the lyrics are entirely unrelated, Frank Sinatra’s ‘My Way’ uses the same melody as the French song ‘Comme d’habitude’.”

… which made me wonder about the terminology used for other musical combinations. Here’s a review of what I see in the area (if you like music, get ready to open and pause a lot of YouTube tabs, or just open this playlist to get all the YouTube links in sequence):

  • Cover: A new performance of an existing song by a different artist. The lyrics and melody will remain virtually identical, but the individual phrasing of lines and overall structure may differ. See the previous post for examples. This would also be used if the lyrics have been translated, such as in the Waters of March, in which the month is accurately translated but the season referred to naturally switches with the hemispheres; this is also the song used in the lovely animation Omlette that I linked to in Things 128.
  • Mashup: Overlaying or mixing at least two other existing recordings, typically combining the vocal track from one with the instrumental track from the other. Substantial re-ordering of structure and speed alterations may be applied to facilitate the mix. Most awesomely demonstrated in “Smells Like Booty“, more recently with “Shake it Off (The Perfect Drug)“.
  • Remix: A recording that takes the original ‘stems’ of an existing recording, and possibly some new material, and combines them in various ways to create a new track. My personal favourite being Jon Hopkins’ beautiful and sedate “The Low Places” being remixed by Geese as some sort of free-form jazz by a band that can’t quite remember how the original track went (worth making it through the opening cacaphony).
  • Sampling: The use of a typically small sample of an existing recording within a new one. The new song may be composed entirely out of samples from other recordings.
Clearly many variations on these rules are possible, but not that many are common. So let’s see what other combinations could exist.

As per Laurence’s example: Same melody, different lyrics. If the lyrics are just marginally different (such as Coulton’s cover of ‘Baby Got Back’), it counts as a cover. If they’re totally different… we don’t seem to have a term. It’s a little rare (presumably for copyright reasons) but not totally unheard of. Perhaps we could call it a Relyric.

One step removed from this would be to use the actual original instrumental recording (or re-perform the instrumental part in just the same way as it was originally recorded) and put new lyrics over it. A ‘reprise‘ in a musical is something like this, but otherwise I think it’s pretty rare, for copyright reasons. Similarly you could take a purely instrumental work and add lyrics to it, as per the Final Fantasy 4 song I cited in Things back in 2008.

You could take an existing vocal part and record new music behind it. This doesn’t seem very common but I think tends to be called a Remix when it does occur (even though it’s the mirror image of the relyric, which I don’t think could be termed a Remix). For example, Bjork’s original All Is Full Of Love (with that memorably NSFW Android video) vs. Plaid’s lovely remix.

You could take an existing track and perform it with some (perhaps substantial) alterations to lyrics, melody, phrasing and instrumentation, but somehow retain something sufficiently distinctive from the original that clearly forms the basis of the song. You haven’t used any of the original music so it isn’t really a remix, but what is it? I suspect if the original artist is involved and consents to the recording it would still count as a remix (compare Bjork’s original Cosmogony with the El Guincho remix; this is also what’s going on in the Geese remix of The Low Places I mentioned above). I rather liked Max Richter’s take on Vivaldi’s Four Seasons which was along these lines (and was termed “Recomposed” which seems a fitting term); it explicitly plays against the melodies that would be cued in your mind from a familiarity with the original work:

Finally an outlier category: a song with a completely different melody, structure and lyrics, which nonetheless clearly recreates what you might term the “defining funk” of an earlier work. This seems near-impossible to define reasonably and probably shouldn’t be included in this continuum, I only mention it because it came up in the case of Robin Thicke’s Blurred Lines (excellently summarised and contextualised here), a song in which he inexplicably chooses to sing about his personal lurid musings on women and his cavalier approach to consent. A jury found that despite differing from Marvin Gaye’s Got To Give It Up in any musical sense, the defining funk had been “copied”. The actual musical similarities were excellently examined by Joe Bennett.

 – Transmission finally ends 

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Things 109: Jonathan’s Card, Dr Who Cats, Mix Shift Visualisation

Question – Nothing to Hide
As technology makes surveillance of many kinds ever easier, some people  are worried about Big Brother, two words which conveniently encompass the general idea that this would be bad, via Orwell’s 1984, which incidentally is one of those classics that you really should read if you haven’t yet as it is only becoming more relevant.

In response to this, others say “If you have nothing to hide, then you have nothing to fear,” which is powerfully concise rebuttal to these vague fears.

I can think of some counterarguments to that, but they tend to be long, and as noted by The Brads, something that takes more than 140 characters to explain doesn’t generally spread. So: this week’s challenge is to come up with a counterargument for “nothing to hide” that is 140 characters long or fewer.

Link
A while ago, as an experiment, Jonathan Stark made his Starbucks card details public, so anyone could add credit and anyone could spend that credit. His page explaining this is here. (Note the caveat at the top – this no longer works).

Sam Odio found an easy way to transfer credit to his own Starbucks card, and I recommend reading his take on the idea (and his exploit) here.

If you don’t have time for that, you could just read this summary of the whole story over at Good, which lays out the whole strange tale.

Quote
Les Dawson:

“There is a remote tribe that worships the number zero. Is nothing sacred?”

Picture (via Jason)
Pure internet linkbait, but with an execution this good, it deserves to be: Dr Who cats.

Previous Puzzle
Last time I asked for ways to visualise data in such a way that mix shifts affecting conversion rate would be readily apparent.

Adam naturally had a full consultant’s answer, explaining how he would show the data different ways depending on the audience (sales director, website content manager, SEO manager…), and how he might talk through the component parts of the change in a sequence of slides, which is all very sensible. However, what I really want is something that I as an analyst can look at to apprehend the whole situation, ideally in a generic way, so any given shift becomes clear.

Simon described an interesting single-view answer, but in preparing this post I realised I needed to confirm some of its details with him, so that will have to wait for a later edition of Things.

On to my answer… the data set was as follows:

[before mix shift | after mix shift]:

Banjo section visits [10,000 | 20,000] – lots more traffic
Banjo section sales [100 | 220]
Banjo section conversion [1.0% | 1.1%] – conversion increases!

Gun section visits [1,000 | 1,000] – same traffic as ever
Gun section sales [100 | 110]
Gun section conversion [10% | 11%] – conversion increases!

Overall conversion before:
(100 + 100) / (10,000 + 1,000) = 1.82%
Overall conversion after:
(220 + 110) / (20,000 + 1,000) = 1.57% – overall conversion has decreased!

My solution looks like this:

This shows how the total visits and orders (black lines) are composed of the individual sections (red/gun and blue/banjo). While both the blue and red arrows get steeper (representing improved conversion, although it’s hard to see this on the red arrow), the angle of the black line decreases (representing the overall decrease in conversion), since the blue arrow became so much longer.

This pretty much works for the extreme example given. However, it has significant weaknesses as a general solution:

  • It doesn’t work as a trended view – conceivably it could be animated, but that seems like overkill
  • It’s hard to compare the angle of arrows when traffic changes significantly, as in the gun section above
  • It tends to encode all the interesting information into a narrow diagonal band of the chart.

Further improvements are of course welcome!

-Transmission Ends