Econstudentlog

Stuff

i. World Happiness Report 2013. A few figures from the publication:

Fig 2.2

Fig 2.4

Fig 2.5

ii. Searching for Explanations: How the Internet Inflates Estimates of Internal Knowledge.

“As the Internet has become a nearly ubiquitous resource for acquiring knowledge about the world, questions have arisen about its potential effects on cognition. Here we show that searching the Internet for explanatory knowledge creates an illusion whereby people mistake access to information for their own personal understanding of the information. Evidence from 9 experiments shows that searching for information online leads to an increase in self-assessed knowledge as people mistakenly think they have more knowledge “in the head,” even seeing their own brains as more active as depicted by functional MRI (fMRI) images.”

A little more from the paper:

“If we go to the library to find a fact or call a friend to recall a memory, it is quite clear that the information we seek is not accessible within our own minds. When we go to the Internet in search of an answer, it seems quite clear that we are we consciously seeking outside knowledge. In contrast to other external sources, however, the Internet often provides much more immediate and reliable access to a broad array of expert information. Might the Internet’s unique accessibility, speed, and expertise cause us to lose track of our reliance upon it, distorting how we view our own abilities? One consequence of an inability to monitor one’s reliance on the Internet may be that users become miscalibrated regarding their personal knowledge. Self-assessments can be highly inaccurate, often occurring as inflated self-ratings of competence, with most people seeing themselves as above average [here’s a related link] […] For example, people overestimate their own ability to offer a quality explanation even in familiar domains […]. Similar illusions of competence may emerge as individuals become immersed in transactive memory networks. They may overestimate the amount of information contained in their network, producing a “feeling of knowing,” even when the content is inaccessible […]. In other words, they may conflate the knowledge for which their partner is responsible with the knowledge that they themselves possess (Wegner, 1987). And in the case of the Internet, an especially immediate and ubiquitous memory partner, there may be especially large knowledge overestimations. As people underestimate how much they are relying on the Internet, success at finding information on the Internet may be conflated with personally mastered information, leading Internet users to erroneously include knowledge stored outside their own heads as their own. That is, when participants access outside knowledge sources, they may become systematically miscalibrated regarding the extent to which they rely on their transactive memory partner. It is not that they misattribute the source of their knowledge, they could know full well where it came from, but rather they may inflate the sense of how much of the sum total of knowledge is stored internally.

We present evidence from nine experiments that searching the Internet leads people to conflate information that can be found online with knowledge “in the head.” […] The effect derives from a true misattribution of the sources of knowledge, not a change in understanding of what counts as internal knowledge (Experiment 2a and b) and is not driven by a “halo effect” or general overconfidence (Experiment 3). We provide evidence that this effect occurs specifically because information online can so easily be accessed through search (Experiment 4a–c).”

iii. Some words I’ve recently encountered on vocabulary.com: hortatory, adduce, obsequious, enunciate, ineluctable, guerdon, chthonic, condignphilippic, coruscate, exceptionable, colophon, lapidary, rubicund, frumpish, raiment, prorogue, sonorous, metonymy.

iv.

v. I have no idea how accurate this test of chess strength is, (some people in this thread argue that there are probably some calibration issues at the low end) but I thought I should link to it anyway. I’d be very cautious about drawing strong conclusions about over-the-board strength without knowing how they’ve validated the tool. In over-the-board chess you have at minimum a couple of minutes/move on average and this tool never gives you more than 30 seconds, so some slow players will probably suffer using this tool (I’d imagine this is why u/ViktorVamos got such a low estimate). For what it’s worth my Elo estimate was 2039 (95% CI: 1859, 2220).

In related news, I recently defeated my first IM – Pablo Garcia Castro – in a blitz (3 minutes/player) game. It actually felt a bit like an anticlimax and afterwards I was thinking that it would probably have felt like a bigger deal if I’d not lately been getting used to winning the occasional bullet game against IMs on the ICC. Actually I think my two wins against WIM Shiqun Ni during the same bullet session at the time felt like a bigger accomplishment, because that specific session was played during the Women’s World Chess Championship and I realized while looking up my opponent that this woman was actually stronger than one of the contestants who made it to the quarter-finals in that event (Meri Arabidze). On the other hand bullet isn’t really chess, so…

April 15, 2015 - Posted by | astronomy, Chess, Lectures, papers, Psychology

2 Comments »

  1. Re the elometer chess tool: “… so some slow players will probably suffer using this tool” – Full disclosure: I scored 1803 with 95% CI (1594-2012). I play mostly almost exclusively 3 and 5-min games, and for a long time dabbled in 2-min games online, so I am not a slow player. Yet, I found this tool… questionable at best. Here’s my thought process:

    ELO is supposed to measure the relative relative chess skill of players vs other players in a game, not against chess position. In a game, even a 3 min one, you have a great measure of control over what kind of position emerges on the board, and you modify the position with each following move. Most moves are not moves that change the character of the position or require a new plan – you are working towards a goal, and you have the benefit of thinking on your opponent’s time, so they take no time at all. Not infrequently, there no “radical” moves in a game – e.g. you start a standard Sicilian as white, you attack on the King side, you break through first, you win. If a “radical” move is needed, I’d often spend 1+ min on it. The elometer kind of puts you in a position of looking for a “radical” move each time. You have to evaluate a position without any knowledge of how you arrived at it, try to guess what the plan was that brought you to it (or worse yet, come up with your own), and proceed. All the while, in quite a few examples, you had to spend extra time fending off cheapo mates that, in a normal game I would know I am safe from. You don’t know how much time your opponent has, and thus do not know whether it’s in your interest to complicate or simplify the position. Half of the time elometer puts you in a position that you would almost never encounter in your games – too closed, too open, too imbalanced, etc. This seriously hurts your estimated ELO, but would barely hurt your performance against an opponent.

    And then there’s the whole “just make the best move” thing. Define “best”. One that would improve Rybka’s evaluation of the position the most? One that would make it most likely I’d win against Dan? Or against Mohammed? One that most (grandmasters? chess-players? people?) would consider best?

    I guess what I was trying to say, probably in greater length than needed, is that this tool is not favoring blitz/bullet players either. It favors problem solvers – I got 3 positions I recognized from Lazslo Polgar’s book. It’s like target shooting – it’s nice if you are good at it, but has pretty low correlation with your being a good soldier.

    Comment by Plamus | April 17, 2015 | Reply

    • “It’s like target shooting – it’s nice if you are good at it, but has pretty low correlation with your being a good soldier.”

      I feel like I want to agree with this – you mention some reasons to be skeptical and I actually had quite a few others in mind as well which I decided not to include in my post, so there are certainly lots of reasons to be skeptical – but I think to some extent this all comes down to how (well) the tool has been validated; they’ve obviously spent some time trying to figure out how to estimate the confidence intervals and the player base on which the tool was developed according to the description spanned both weak players and strong grandmasters. They’ve put some thought into this, so even though I think using a simple tool like this can only tell you so much, ‘how much’ seems to me … unclear.

      I mostly play 1 or 3 minute games online, but I usually get into time trouble when I’m playing regular time control games (3-4 hour games) in part because I have no problem spending 15-20 minutes on a complicated position and I often think of myself as rather slow (this was one of the original arguments for playing short games online – if I’m getting into time trouble anyway, I might as well improve my ability to make moves with little time on the clock. However nowadays I mostly do it because I enjoy playing short games…) – I’ll rarely spend less than a minute or two on a move in a standard game unless it’s an opening move or an obvious/forced recapture. For that reason I thought the time was a serious issue as I’m not used to making decisions that fast in a context where the decision ‘matters’ at all; what it reminded me most of was actually neither blitz nor regular games, but rather regular time control games during the phase where you’re in time trouble (playing on the increment). But I actually sort of assume the time dimension is useful to include in an instrument like this because it ‘amplifies the signal’, rather than the opposite; it would make sense if it did – I’m almost certain the time limitation was not random, and I have to assume they gave some thought as to what would be the ‘best’ sort of limitation to impose in the context of the instrument.

      In a similar vein, it also makes sense that an instrument like this focuses more on forcing moves/radical moves than on ‘regular moves’, because such moves are more likely to win games so you’d need more positions if you were to avoid them in a tool like this. In that context it also makes a lot of sense that not all positions have forced winning lines; I’ve previously argued elsewhere that a combination of positions which include both some forced winning lines and some lines where you just need to ‘play the best move, even if it isn’t particularly great’ is much superior in terms of helping your practical play than are problems where there’s always a winning line (and as mentioned, if no positions included winning tactics I think the power of the tool would go down a lot because you’d need a lot more positions to get the same degree of accuracy) – so I assume an instrument like this is better for mixing positions as well because it’ll give you a more accurate reading of playing ability. It’s partly speculation because I don’t have any data to back it up, but if their testing approach was informed by the achieved fit, which you sort of have to assume it was, that on its own actually lends support to this impression of mine.

      “You have to evaluate a position without any knowledge of how you arrived at it, try to guess what the plan was that brought you to it (or worse yet, come up with your own), and proceed.”

      Actually I think this is not a bad way to evaluate positional understanding. ‘Here’s a position – quick, what are the main ideas, key squares, is the king safe, is there a tactic?’ And although your play is usually very path-dependent in practical games, it’s very useful to be able to look at every position with fresh eyes. ‘You know, that rook really belongs on e1, not d1, and even if I’ll have to spend two moves instead of one getting it there, Rd1 is still the best move in this position’ – these sorts of decisions can be really important. Looking at a position without caring how you got there can make it easier to spot problems or resources you’d overlooked and it seems to me obvious that good players are better at this.

      But this is all very theoretical; I don’t have a good instrument to evaluate this tool against, as there’s no way to compare it against some well-established standard besides the actual Elo ratings. I can think of lots of reasons why it wouldn’t be a good instrument, but the developers matched the performances with the Elo ratings of initial test-takers which is presumably where the confidence intervals are coming from. Those may be too narrow and the estimates may be biased, but I think it’s hard to say ‘how much too narrow’ etc. because it’s difficult to know what to compare these estimates with to get at ‘the truth’. One thing I do believe, however, is that a lot of the redditors in the thread to which I link are right that the instrument is probably overestimating their playing strengths; 1600-1700 Elo players aren’t bad players, and I have a hard time believing lots of random people from the internet with far from impressive online ratings would be able to play as well as these guys do in the tournament context; I know from experience that most people who start out in a club take a while to get to that level, and some people never get that far despite playing tournament chess for years.

      One thing to note is that the confidence intervals are actually quite wide already, so it’s not like they’re hiding the uncertainty. A guy with a rating of 1859 (the lower bar of my estimate) has an expected score of 0.26 against a guy with a rating of 2039 (the point estimate) and an expected score of 0.11 (losing 8 out of 9 games…) against a guy with a rating of 2220 (the upper bound) (calculated using this tool) (the estimate is even wider in your case; the expected score of a 1594 player against a 2012 player is 0.08, ignoring the 400 point rule…). (Of course confidence intervals not informed by priors in this context are problematic because the priors should in some situations be highly informative (i.e. when a test taker have an Elo rating), and it seems odd to me that the ratings provided by test takers towards the end are not used to update the confidence interval (estimates seem to be independent of the information provided after the test is over, though I may be wrong about that) – but that’s a different discussion).

      Comment by US | April 17, 2015 | Reply


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