## Binary search in the Old Testament

### August 10th, 2015

The lot is cast into the lap,
but its every decision is from the Lord.
(NIV Proverbs 16:33)

 …“Lux et Veritas”… Seal of Yale University image from Wikimedia Commons.

The seal of Yale University shows a book with the Hebrew אורים ותמים (urim v’thummim), a reference to the Urim and Thummim of the Old Testament. The Urim and Thummim were tools of divination. They show up first in Exodus:

Also put the Urim and the Thummim in the breastpiece, so they may be over Aaron’s heart whenever he enters the presence of the Lord. Thus Aaron will always bear the means of making decisions for the Israelites over his heart before the Lord. (NIV Exodus 28:30; emphasis added)

Apparently, the Urim and Thummim worked like flipping a coin, providing one bit of information, a single binary choice communicated from God.1 Translations of Urim as “guilty” and Thummim as “innocent” indicate that the divination was used to determine guilt: “Thummim you win; Urim you lose.” An alternate translation has Urim “light” and Thummim “truth”, hence “Lux et Veritas” in the Yale seal’s banner.

Saul, King of Israel and father-in-law of King David, uses the binary choice provided by Urim and Thummim divination in 1 Samuel to unmask the party who violated the king’s oath:

Then Saul prayed to the Lord, the God of Israel, “Why have you not answered your servant today? If the fault is in me or my son Jonathan, respond with Urim, but if the men of Israel are at fault, respond with Thummim.” Jonathan and Saul were taken by lot, and the men were cleared. Saul said, “Cast the lot between me and Jonathan my son.” And Jonathan was taken. (NIV2 1 Samuel 14:41-42)

Saul executes a small (and highly unbalanced) binary search. He first divides the population into two parts. He and his son Jonathan are assigned Urim and all the rest get Thummim. God responds with Urim. Then to decide between Saul and Jonathan, the process is repeated, and Jonathan is fingered as the guilty party. (The method apparently works; the preceding verses of 1 Samuel give the story of Jonathan’s transgression.)

The universality of binary as an information conveying method has a longer history than one might have thought.

1. The Old Testament Urim and Thummim should not be confused with the “higher bandwidth” device of the same name that Joseph Smith claimed to use to receive the translation of a now lost 116 pages of the Book of Mormon. This device purportedly resembled a pair of spectacles with transparent rocks for lenses, a kind of “oraculus rift”. For the extant Book of Mormon, Smith changed his method to scrying with a “seer stone” placed in his hat. A photograph of the stone, coincidentally, has just recently been released by the LDS church.
2. The use of a Septuagint-based version of the Bible, here the New International Version, is important, as this verse is considerably shortened in versions such as the King James based on the Masoretic text, leaving out the use of Urim and Thummim to make a binary decision.

## Becoming tin men

### August 3rd, 2015

From the 2015 introduction to the 1965 novel The Tin Men by Michael Frayn:

“I hadn’t in those days heard of the Turing Test—Alan Turing’s proposal that a computer could be said to think if its conversational powers were shown to be indistinguishable from a human being’s—so I didn’t realise that what I was suggesting was a kind of converse of it: a demotion of human beings to the status of machines if their intellectual performance was indistinguishable from a computer’s, and they become tin men in their turn. The William Morris Institute is about to be visited by the Queen for the opening of a new wing, and I realise with hindsight that I’ve used a similar idea quite often since: the grand event that goes wrong, and deposits the protagonists into the humiliating gulf that so often in life opens between intention and achievement. My characters at the Institute could have written a story programme for me and saved me a lot of work. I’ve become a bit of a tin man myself.”

## Plain meaning

### June 26th, 2015

In its reporting on yesterday’s Supreme Court ruling in King v. Burwell, Vox’s Matthew Yglesias makes the important point that Justice Scalia’s dissent is based on a profound misunderstanding of how language works. Justice Scalia would have it that “words no longer have meaning if an Exchange that is not established by a State is ‘established by the state.’” The Justice is implicitly appealing to a “plain meaning” view of legislation: courts should just take the plain meaning of a law and not interpret it.

If only that were possible. If you think there’s such a thing as acquiring the “plain meaning” of a text without performing any interpretive inference, you don’t understand how language works. It’s the same mistake that fundamentalists make when they talk about looking to the plain meaning of the Bible. (And which Bible would that be anyway? The King James Version? Translation requires the same kind of inferential process – arguably the same actual process – as extracting meaning through reading.)

Yglesias describes “What Justice Scalia’s King v. Burwell dissent gets wrong about words and meaning” this way:

Individual stringz of letterz r efforts to express meaningful propositions in an intelligible way. To succeed at this mission does not require the youse of any particular rite series of words and, in fact, a sntnce fll of gibberish cn B prfctly comprehensible and meaningful 2 an intelligent reader. To understand a phrse or paragraf or an entire txt rekwires the use of human understanding and contextual infrmation not just a dctionry.

The jokey orthography aside, this observation that understanding the meaning of linguistic utterances requires the application of knowledge and inference is completely uncontroversial to your average linguist. Too bad Supreme Court justices don’t defer to linguists on how language works.

Let’s take a simple example, the original “Winograd sentences” from back in 1973:

1. The city councilmen refused the demonstrators a permit because they feared violence.
2. The city councilmen refused the demonstrators a permit because they advocated violence.

To understand these sentences, to recover their “plain meaning”, requires resolving to whom the pronoun ‘they’ refers. Is it the city councilmen or the demonstrators? Clearly, it is the former in sentence (1) and the latter in sentence (2). How do you know, given that the two sentences differ only in the single word alternation ‘feared’/‘advocated’? The recovery of this single aspect of the “plain meaning” of the sentence requires an understanding of how governmental organizations work, how activists pursue their goals, likely public reactions to various contingent behaviors, and the like, along with application of all that knowledge through plausible inference. The Patient Protection and Affordable Care Act (PPACA) has by my (computer-aided) count some 479 occurrences of pronouns in nominative, accusative, or possessive. Each one of these requires the identification of its antecedent, with all the reasoning that implies, to get its “plain meaning”.

Examining the actual textual subject of controversy in the PPACA demonstrates the same issue. The phrase in question is “established by the state”. The American Heritage Dictionary provides six senses and nine subsenses for the transitive verb ‘establish’, of which (by my lights) sense 1a is appropriate for interpreting the PPACA: “To cause (an institution, for example) to come into existence or begin operating.” An alternative reading might, however, be sense 4: “To introduce and put (a law, for example) into force.” The choice of which sense is appropriate requires some reasoning of course about the context in which it was used, the denotata of the subject and object of the verb for instance. If one concludes that sense 1a was intended, then the Supreme Court’s decision is presumably correct, since a state’s formal relegation to the federal government the role of running the exchange is an act of “causing to come into existence”, although perhaps not an act of “introducing and putting into force”. (Or further explication of the notions of “causing” or “introducing” might be necessary to decide the matter.) If the latter sense 4 were intended, then perhaps the Supreme Court was wrong in its recent decision. The important point is this: There is no possibility of deferring to the “plain meaning” on the issue; one must reason about the intentions of the authors to acquire even the literal meaning of the text. This process is exactly what Chief Justice Roberts undertakes in his opinion. Justice Scalia’s view, that plain meaning is somehow available without recourse to the use of knowledge and reasoning, is unfounded even in the simplest of cases.

## In support of behavioral tests of intelligence

### May 7th, 2015

 …“blockhead” argument… “Blockhead by Paul McCarthy @ Tate Modern” image from flickr user Matt Hobbs. Used by permission.

Alan Turing proposed what is the best known criterion for attributing intelligence, the capacity for thinking, to a computer. We call it the Turing Test, and it involves comparing the computer’s verbal behavior to that of people. If the two are indistinguishable, the computer passes the test. This might be cause for attributing intelligence to the computer.

Or not. The best argument against a behavioral test of intelligence (like the Turing Test) is that maybe the exhibited behaviors were just memorized. This is Ned Block’s “blockhead” argument in a nutshell. If the computer just had all its answers literally encoded in memory, then parroting those memorized answers is no sign of intelligence. And how are we to know from a behavioral test like the Turing Test that the computer isn’t just such a “memorizing machine”?

In my new(ish) paper, “There can be no Turing-Test–passing memorizing machines”, I address this argument directly. My conclusion can be found in the title of the article. By careful calculation of the information and communication capacity of space-time, I show that any memorizing machine could pass a Turing Test of no more than a few seconds, which is no Turing Test at all. Crucially, I make no assumptions beyond the brute laws of physics. (One distinction of the article is that it is one of the few philosophy articles in which a derivative is taken.)

The article is published in the open access journal Philosophers’ Imprint, and is available here along with code to computer-verify the calculations.

## The two Guildford mathematicians

### February 18th, 2015

 …the huge ledger… Still from Codebreaker showing Turing’s checkout of three Carroll books.

The charming town of Guildford, 40 minutes southwest of London on South West Trains, is associated with two famous British logician-mathematicians. Alan Turing (on whom I seem to perseverate) spent time there after 1927, when his parents purchased a home at 22 Ennismore Avenue just outside the Guildford town center. Although away at his boarding school, the Sherborne School in Dorset, which he attended from 1926 to 1931, Turing spent school holidays at the family home in Guildford. The house bears a blue plaque commemorating the connection with Turing, the “founder of computer science” as it aptly describes him, which you can see in the photo at right, taken on a pilgrimage I took this past June.

 …the family home… The Turing residence at 22 Ennismore Avenue, Guildford

And this brings us to the second famous Guildford mathematician, who it turns out Turing was reading while at Sherborne. In the Turing docudrama Codebreaker, one of Turing’s biographers David Leavitt visits Sherborne and displays the huge ledger used for the handwritten circulation records of the Sherborne School library. There (Leavitt remarks), in an entry dated 11 April 1930, Turing has checked out three books, including Alice in Wonderland and Through the Looking Glass, and What Alice Found There. (We’ll come back to the third book shortly.) The books were, of course, written by the Oxford mathematics don Charles Lutwidge Dodgson under his better known pen name Lewis Carroll. Between the 1865 and 1871 publications of these his two most famous works, Carroll leased “The Chestnuts” in Guildford in 1868 to serve as a home for his sisters. The house sits at the end of Castle Hill Road adjacent to the Guildford Castle, which is as good a landmark as any to serve as the center of town. Carroll visited The Chestnuts on many occasions over the rest of his life; it was his home away from Christ Church home. He died there 30 years later and was buried at the Guildford Mount Cemetery.

 …through the looking glass… Statue of Alice passing through the looking glass, Guildford Castle Park, Guildford

Guildford plays up its connection to Carroll much more than its Turing link. In the park surrounding Guildford Castle sits a statue of Alice passing through the looking glass, and the adjacent museum devotes considerable space to the Dodgson family. A statue depicting the first paragraphs of Alice’s adventures (Alice, her sister reading next to her, noticing a strange rabbit) sits along the bank of the River Wey. The Chestnuts itself, however, bears no blue plaque nor any marker of its link to Carroll. (A plaque formerly marking the brick gatepost has been removed, evidenced only by the damage to the brick where it had been.)

 …The Chestnuts… The Dodgson family home in Guildford

Who knows whether Turing was aware that Carroll, whose two Alice books he was reading, had had a home a mere mile from where his parents were living. The Sherborne library entry provides yet another convergence between the two British-born, Oxbridge-educated, permanent bachelors with sui generis demeanors, questioned sexualities, and occasional stammers, interested in logic and mathematics.

But there’s more. What of the third book that Turing checked out of the Sherborne library at the same time? Leavitt finds the third book remarkable because the title, The Game of Logic, presages Turing’s later work in logic and the foundations of computer science. What Leavitt doesn’t seem to be aware of is that it is no surprise that this book would accompany the Alice books; it has the same author. Carroll published The Game of Logic in 1886. It serves to make what I believe to be the deepest connection between the two mathematicians, one that has to my knowledge never been noted before.

 …Carroll’s own copy… Title page of Lewis Carroll, The Game of Logic, 1886. EC85.D6645.886g, Houghton Library, Harvard University.

After watching Codebreaker and noting the Game of Logic connection, I decided to refresh my memory about the book. I visited Harvard’s Houghton Library, which happens to have Carroll’s own copy of the book. The title page is shown at right, with the facing page visible showing a sample card to be used in the game. The book was sold together with a copy of the card made of pasteboard and counters of two colors (red and grey) to be used to mark the squares on the card.

The Houghton visit and the handling of the game pieces jogged my memory as to the point of Carroll’s book. Carroll’s goal in The Game of Logic was to describe a system for carrying out syllogistic reasoning that even a child could master. Towards that goal, the system was intended to be completely mechanical. It involved the card marked off in squares and the two types of counters placed on the card in various configurations. Any of a large class of syllogisms over arbitrary properties can be characterized in this way, given a large enough card and enough counters, though it becomes unwieldy quite quickly after just a few.

 … marked off in squares… The game card depicting a syllogism. Lewis Carroll, The Game of Logic, 1886. EC85.D6645.886g, Houghton Library, Harvard University.

(The photo at right shows the card and counters that came with the book. I’ve placed the counters in such a way as to depict the syllogism:

 No red apples are unripe. Some wholesome apples are red. ∴ Some ripe apples are red.         )

To computer scientists, this ought to sound familiar. Just six years after checking out The Game of Logic from his school library, Turing would publish his groundbreaking paper “On computable numbers”, in which he describes a system for carrying out computations in a way that is completely mechanical. It involves a paper tape marked off in squares, and markings of at least two types placed on the tape in various configurations. Any of a large class of computations over arbitrary values can be characterized in this way, given a large enough tape and enough markings, though it becomes unwieldy quite quickly. We now call this mechanical device with tape and markings a Turing machine, and recognize it as the first universal model of computation. Turing’s paper serves as the premier work in the then nascent field of computer science.

Of course, there are differences both superficial and fundamental between Carroll’s game and Turing’s machine. Carroll’s card is two-dimensional with squares marked off in a lattice pattern, and counters are placed both within the squares and on the edges between squares. Turing’s tape is one-dimensional (though two-dimensional Turing machines have been defined and analyzed) and the markings are placed only within the squares. Most importantly, nothing even approaching the ramifications that Turing developed on the basis of his model came from Carroll’s simple game. (As a mathematician, Carroll was no Turing.) Nonetheless, in a sense the book that Turing read at 17 attempts to do for logic what Turing achieved six years later for computation.

I have no idea whether Lewis Carroll’s The Game of Logic influenced Alan Turing’s thinking about computability. But it serves as perhaps the strongest conceptual bond between Guildford’s two great mathematicians.

Update February 25, 2015: Thanks to Houghton Library Blog for reblogging this post.

## The Turing moment

### November 30th, 2014

 …less histrionic… Ed Stoppard as Alan Turing in Codebreaker

We seem to be at the “Turing moment”, what with Benedict Cumberbatch, erstwhile Sherlock Holmes, now starring as a Hollywood Alan Turing in The Imitation Game. The release culminates a series of Turing-related events over the last few years. The centennial of Turing’s 1912 birth was celebrated actively in the computer science community as a kind of jubilee, the occasion of numerous conferences, retrospectives, and presentations. Bracketing that celebration, PM Gordon Brown publicly apologized for Britain’s horrific treatment of Turing in 2009, and HRH Queen Elizabeth II, who was crowned a couple of years before Alan Turing took his own life as his escape from her government’s abuse, finally got around to pardoning him in 2013 for the crime of being gay.

I went to see a preview of The Imitation Game at the Coolidge Corner Theatre’s “Science on Screen” series. I had low expectations, and I was not disappointed. The film is introduced as being “based on a true story”, and so it is – in the sense that My Fair Lady was based on the myth of Pygmalion (rather than the Shaw play). Yes, there was a real place called Bletchley Park, and real people named Alan Turing and Joan Clark, but no, they weren’t really like that. Turing didn’t break the Enigma code singlehandedly despite the efforts of his colleagues to stop him. Turing didn’t take it upon himself to control the resulting intelligence to limit the odds of their break being leaked to the enemy. And so on, and so forth. Most importantly, Turing did not attempt to hide his homosexuality from the authorities, and promoting the idea that he did for dramatic effect is, frankly, an injustice to his memory.

Reviewers seem generally to appreciate the movie’s cleaving from reality, though with varying opprobrium. “The truth of history is respected just enough to make room for tidy and engrossing drama,” says A. O. Scott in the New York Times. The Wall Street Journal’s Joe Morgenstern ascribes to the film “a marvelous story about science and humanity, plus a great performance by Benedict Cumberbatch, plus first-rate filmmaking and cinematography, minus a script that muddles its source material to the point of betraying it.” At Slate, Dana Stevens notes that “The true life story of Alan Turing is much stranger, sadder and more troubling than the version of it on view in The Imitation Game, Morton Tyldum’s handsome but overlaundered biopic.

Of course, they didn’t make the movie for people like me, that is, people who had heard of Alan Turing before. And to the extent that the film contributes to this Turing moment — leading viewers to look further into this most idiosyncratic and important person — it will be a good thing. The Coolidge Corner Theatre event was followed by commentary from Silvio Micali and Seth Lloyd, both professors at MIT. (The former is a recipient of the highest honor in computer science, the Turing Award. Yes, that Turing.) Their comments brought out the many scientific contributions of Turing that were given short shrift in the film. If only they could duplicate their performance at every showing.

Those who become intrigued by the story of Alan Turing could do worse than follow up their viewing of the Cumberbatch vehicle with one of the 2012 docudrama Codebreaker, a less histrionic but far more accurate (and surprisingly, more sweeping) presentation of Turing’s contributions to science and society, and his societal treatment. I had the pleasure of introducing the film and its executive producer Patrick Sammon in a screening at Harvard a couple of weeks ago. The event was another indicator of the Turing moment. (My colleague Harry Lewis has more to say about the film.)

To all of you who are aware of the far-reaching impact of Alan Turing on science, on history, and on society, and the tragedy of his premature death, I hope you will take advantage of the present Turing moment to spread the word about computer science’s central personage.

## Inaccessible writing, in both senses of the term

### September 29th, 2014

My colleague Steven Pinker has a nice piece up at the Chronicle of Higher Education on “Why Academics Stink at Writing”, accompanying the recent release of his new book The Sense of Style: The Thinking Person’s Guide to Writing in the 21st Century, which I’m awaiting my pre-ordered copy of. The last sentence of the Chronicle piece summarizes well:

In writing badly, we are wasting each other’s time, sowing confusion and error, and turning our profession into a laughingstock.

The essay provides a diagnosis of many of the common symptoms of fetid academic writing. He lists metadiscourse, professional narcissism, apologizing, shudder quotes, hedging, metaconcepts and nominalizations. It’s not breaking new ground, but these problems well deserve review.

I fall afoul of these myself, of course. (Nasty truth: I’ve used “inter alia” all too often, inter alia.) But one issue I disagree with Pinker on is the particular style of metadiscourse he condemns that provides a roadmap of a paper. Here’s an example from a recent paper of mine.

After some preliminaries (Section 2), we present a set of known results relating context-free languages, tree homomorphisms, tree automata, and tree transducers to extend them for the tree-adjoining languages (Section 3), presenting these in terms of restricted kinds of functional programs over trees, using a simple grammatical notation for describing the programs. We review the definition of tree-substitution and tree-adjoining grammars (Section 4) and synchronous versions thereof (Section 5). We prove the equivalence between STSG and a variety of bimorphism (Section 6).

This certainly smacks of the first metadiscourse example Pinker provides:

“The preceding discussion introduced the problem of academese, summarized the principle theories, and suggested a new analysis based on a theory of Turner and Thomas. The rest of this article is organized as follows. The first section consists of a review of the major shortcomings of academic prose. …”

Who needs that sort of signposting in a 6,000-word essay? But in the context of a 50-page article, giving a kind of table of contents such as this doesn’t seem out of line. Much of the metadiscourse that Pinker excoriates is unneeded, but appropriate advance signposting can ease the job of the reader considerably. Sometimes, as in the other examples Pinker gives, “meta­discourse is there to help the writer, not the reader, since she has to put more work into understanding the signposts than she saves in seeing what they point to.” But anything that helps the reader to understand the high-level structure of an object as complex as a long article seems like a good thing to me.

The penultimate sentence of Pinker’s piece places poor academic writing in context:

Our indifference to how we share the fruits of our intellectual labors is a betrayal of our calling to enhance the spread of knowledge.

That sentiment applies equally well – arguably more so – to the venues where we publish. By placing our articles in journals that lock up access tightly we are also betraying our calling. And it doesn’t matter how good the writing is if it can’t be read in the first place.

## Switching to Markdown for scholarly article production

### August 29th, 2014

With few exceptions, scholars would be better off writing their papers in a lightweight markup format called Markdown, rather than using a word-processing program like Microsoft Word. This post explains why, and reveals a hidden agenda as well.1

### Microsoft Word is not appropriate for scholarly article production

 …lightweight… “Old two pan balance” image from Nikodem Nijaki at Wikimedia Commons. Used by permission.

Before turning to lightweight markup, I review the problems with Microsoft Word as the lingua franca for producing scholarly articles. This ground has been heavily covered. (Here’s a recent example.) The problems include:

Substantial learning curve
Microsoft Word is a complicated program that is difficult to use well.
Appearance versus structure
Word-processing programs like Word conflate composition with typesetting. They work by having you specify how a document should look, not how it is structured. A classic example is section headings. In a typical markup language, you specify that something is a heading by marking it as a heading. In a word-processing program you might specify that something is a heading by increasing the font size and making it bold. Yes, Word has “paragraph styles”, and some people sometimes use them more or less properly, if you can figure out how. But most people don’t, or don’t do so consistently, and the resultant chaos has been well documented. It has led to a whole industry of people who specialize in massaging Word files into some semblance of consistency.
Backwards compatibility
Word-processing program file formats have a tendency to change. Word itself has gone through multiple incompatible file formats in the last decades, one every couple of years. Over time, you have to keep up with the latest version of the software to do anything at all with a new document, but updating your software may well mean that old documents are no longer identically rendered. With Markdown, no software is necessary to read documents. They are just plain text files with relatively intuitive markings, and the underlying file format (UTF-8 née ASCII) is backward compatible to 1963. Further, typesetting documents in Markdown to get the “nice” version is based on free and open-source software (markdown, pandoc) and built on other longstanding open source standards (LaTeX, BibTeX).
Poor typesetting
Microsoft Word does a generally poor job of typesetting, as exemplified by hyphenation, kerning, mathematical typesetting. This shouldn’t be surprising, since the whole premise of a word-processing program means that the same interface must handle both the specification and typesetting in real-time, a recipe for having to make compromises.
Lock-in
Because Microsoft Word’s file format is effectively proprietary, users are locked in to a single software provider for any and all functionality. The file formats are so complicated that alternative implementations are effectively impossible.

### Lightweight markup is the solution

The solution is to use a markup format that allows specification of the document (providing its logical structure) separate from the typesetting of that document. Your document is specified – that is, generated and stored – as straight text. Any formatting issues are handled not by changing the formatting directly via a graphical user interface but by specifying the formatting textually using a specific textual notation. For instance, in the HTML markup language, a word or phrase that should be emphasized is textually indicated by surrounding it with <em>…</em>. HTML and other powerful markup formats like LaTeX and various XML formats carry relatively large overheads. They are complex to learn and difficult to read. (Typing raw XML is nobody’s idea of fun.) Ideally, we would want a markup format to be lightweight, that is, simple, portable, and human-readable even in its raw state.

Markdown is just such a lightweight markup language. In Markdown, emphasis is textually indicated by surrounding the phrase with asterisks, as is familiar from email conventions, for example, *lightweight*. See, that wasn’t so hard. Here’s another example: A bulleted list is indicated by prepending each item on a separate line with an asterisk, like this:

 * First item
* Second item

which specifies the list

• First item
• Second item

Because specification and typesetting are separated, software is needed to convert from one to the other, to typeset the specified document. For reasons that will become clear later, I recommend the open-source software pandoc. Generally, scholars will want to convert their documents to PDF (though pandoc can convert to a huge variety of other formats). To convert file.md (the Markdown-format specification file) to PDF, the command

 pandoc file.md -o file.pdf

suffices. Alternatively, there are many editing programs that allow entering, editing, and typesetting Markdown. I sometimes use Byword. In fact, I’m using it now.

Markup languages range from the simple to the complex. I argue for Markdown for four reasons:

1. Basic Markdown, sufficient for the vast majority of non-mathematical scholarly writing, is dead simple to learn and remember, because the markup notations were designed to mimic the kinds of textual conventions that people are used to – asterisks for emphasis and for indicating bulleted items, for instance. The coverage of this basic part of Markdown includes: emphasis, section structure, block quotes, bulleted and numbered lists, simple tables, and footnotes.
2. Markdown is designed to be readable and the specified format understandable even in its plain text form, unlike heavier weight markup languages such as HTML.
3. Markdown is well supported by a large ecology of software systems for entering, previewing, converting, typesetting, and collaboratively editing documents.
4. Simple things are simple. More complicated things are more complicated, but not impossible. The extensions to Markdown provided by pandoc cover more or less the rest of what anyone might need for scholarly documents, including links, cross-references, figures, citations and bibliographies (via BibTeX), mathematical typesetting (via LaTeX), and much more.For instance, this equation (the Cauchy-Schwarz inequality) will typeset well in generated PDF files, and even in HTML pages using the wonderful MathJax library.$\left( \sum_{k=1}^n a_k b_k \right)^2 \leq \left( \sum_{k=1}^n a_k^2 \right) \left( \sum_{k=1}^n b_k^2 \right)$(Pandoc also provides some extensions that simplify and extend the basic Markdown in quite nice ways, for instance, definition lists, strikeout text, a simpler notation for tables.)

Above, I claimed that scholars should use Markdown “with few exceptions”. The exceptions are:

1. The document requires nontrivial mathematical typesetting. In that case, you’re probably better off using LaTeX. Anyone writing a lot of mathematics has given up word processors long ago and ought to know LaTeX anyway. Still, I’ll often do a first draft in Markdown with LaTeX for the math-y bits. Pandoc allows LaTeX to be included within a Markdown file (as I’ve done above), and preserves the LaTeX markup when converting the Markdown to LaTeX. From there, it can be typeset with LaTeX. Microsoft Word would certainly not be appropriate for this case.
2. The document requires typesetting with highly refined or specialized aspects. I’d probably go with LaTeX here too, though desktop publishing software (InDesign) is also appropriate if there’s little or no mathematical typesetting required. Microsoft Word would not be appropriate for this case either.

Some have proposed that we need a special lightweight markup language for scholars. But Markdown is sufficiently close, and has such a strong community of support and software infrastructure, that it is more than sufficient for the time being. Further development would of course be helpful, so long as the urge to add “features” doesn’t overwhelm its core simplicity.

### The hidden agenda

I have a hidden agenda. Markdown is sufficient for the bulk of cases of composing scholarly articles, and simple enough to learn that academics might actually use it. Markdown documents are also typesettable according to a separate specification of document style, and retargetable to multiple output formats (PDF, HTML, etc.).2 Thus, Markdown could be used as the production file format for scholarly journals, which would eliminate the need for converting between the authors’ manuscript version and the publishers internal format, with all the concomitant errors that process is prone to produce.

In computer science, we have by now moved almost completely to a system in which authors provide articles in LaTeX so that no retyping or recomposition of the articles needs to be done for the publisher’s typesetting system. Publishers just apply their LaTeX style files to our articles. The result has been a dramatic improvement in correctness and efficiency. (It is in part due to such an efficient production process that the cost of running a high-end computer science journal can be so astoundingly low.)

Even better, there is a new breed of collaborative web-based document editing tools being developed that use Markdown as their core file format, tools like Draft and Authorea. They provide multi-author editing, versioning, version comparison, and merging. These tools could constitute the system by which scholarly articles are written, collaborated on, revised, copyedited, and moved to the journal production process, generating efficiencies for a huge range of journals, efficiencies that we’ve enjoyed in computer science and mathematics for years.

As Rob Walsh of ScholasticaHQ says, “One of the biggest bottlenecks in Open Access publishing is typesetting. It shouldn’t be.” A production ecology built around Markdown could be the solution.

1. Many of the ideas in this post are not new. Complaints about WYSIWYG word-processing programs have a long history. Here’s a particularly trenchant diatribe pointing out the superiority of disentangling composition from typesetting. The idea of “scholarly Markdown” as the solution is also not new. See this post or this one for similar proposals. I go further in viewing certain current versions of Markdown (as implemented in Pandoc) as practical already for scholarly article production purposes, though I support coordinated efforts that could lead to improved lightweight markup formats for scholarly applications. Update September 22, 2014: I’ve just noticed a post by Dennis Tenen and Grant Wythoff at The Programming Historian on “Sustainable Authorship in Plain Text using Pandoc and Markdown” giving a tutorial on using these tools for writing scholarly history articles.
2. As an example, I’ve used this very blog post. Starting with the Markdown source file (which I’ve attached to this post), I first generated HTML output for copying into the blog using the command
pandoc -S --mathjax --base-header-level=3 markdownpost.md -o markdownpost.html

A nicely typeset version using the American Mathematical Society’s journal article document style can be generated with

pandoc markdownpost.md -V documentclass:amsart -o markdownpost-amsart.pdf

To target the style of ACM transactions instead, the following command suffices:

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## No, the Turing Test has not been passed.

### June 10th, 2014

 …that’s not Turing’s Test… “Turing Test” image from xkcd. Used by permission.

There has been a flurry of interest in the Turing Test in the last few days, precipitated by a claim that (at last!) a program has passed the Test. The program in question is called “Eugene Goostman” and the claim is promulgated by Kevin Warwick, a professor of cybernetics at the University of Reading and organizer of a recent chatbot competition there.

The Turing Test is a topic that I have a deep interest in (see this, and this, and this, and this, and, most recently, this), so I thought to give my view on Professor Warwick’s claim “We are therefore proud to declare that Alan Turing’s Test was passed for the first time on Saturday.” The main points are these. The Turing Test was not passed on Saturday, and “Eugene Goostman” seems to perform qualitatively about as poorly as many other chatbots in emulating human verbal behavior. In summary: There’s nothing new here; move along.

First, the Turing Test that Turing had in mind was a criterion of indistinguishability in verbal performance between human and computer in an open-ended wide-ranging interaction. In order for the Test to be passed, judges had to perform no better than chance in unmasking the computer. But in the recent event, the interactions were quite time-limited (only five minutes) and in any case, the purported Turing-Test-passing program was identified correctly more often than not by the judges (almost 70% of the time in fact). That’s not Turing’s test.

Update June 17, 2014: The time limitation was even worse than I thought. According to my colleague Luke Hunsberger, computer science professor at Vassar College, who was a judge in this event, the five minute time limit was for two simultaneous interactions. Further, there were often substantial response delays in the system. In total, he estimated that a judge might average only four or five rounds of chat with each interlocutor. I’ve argued before that a grossly time-limited Turing Test is no Turing Test at all.

Sometimes, people trot out the prediction from Turing’s seminal 1950 Mind article that “I believe that in about fifty years’ time it will be possible to programme computers, with a storage capacity of about $$10^9$$, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent. chance of making the right identification after five minutes of questioning.” As I explain in my book on the Test:

The first thing to note about the prediction is that it is not a prediction about the Test per se: Turing expects 70 percent prediction accuracy, not the more difficult 50 percent expected by chance, and this after only a limited conversation of five minutes. He is therefore predicting passage of a test much simpler than the Test.

Not only does the prediction not presuppose a full Turing Test, but it could well be argued that it had already come to pass with the advent of Joseph Weizenbaum’s Eliza some thirty-five years early. Weizenbaum developed a simple computer program that attempted to imitate the parroting conversational style of a Rogerian psychotherapist…. Although the methods used were quite simple – repeating the user’s question after adjusting some pronouns, throwing in a stock phrase every now and then – the result was, in its own way, extremely convincing.

Second, “Eugene Goostman” uses the very techniques that began with Weizenbaum’s  “Eliza” program from the 1960’s. We see the same tricks – repeating the judge’s statements with simple substitutions, keyword-triggered responses, falling back on vague or unresponsive replies, and the like. Those tricks are no more successful than they have been in the two decades of runnings of the Loebner Prize Competition, another ill-conceived attempt at running a Turing-like test. And there too, entrants used the trick of having their programs emulate humans with built in excuses.  “Eugene Goostman” purports to be a non-English-fluent child, rather than a fluent adult.1

In fact, anyone with the slightest familiarity with chatbots, the modern incarnations of “Eliza”, could unmask “Eugene Goostman” quickly. (The judges at the recent competition were apparently not so familiar.) Scott Aaronson has provided a transcript of his own interaction with “Eugene Goostman”, which shows the telltale signs as soon as the computer’s first reply, which blatantly ignores an utterly trivial question and tries to change the subject:

Scott: Which is bigger, a shoebox or Mount Everest?

Eugene: I can’t make a choice right now. I should think it out later. And I forgot to ask you where you are from…

Here’s an appeal to cute, vague language:

Scott: How many legs does a camel have?

Eugene: Something between 2 and 4. Maybe, three? :-))) By the way, I still don’t know your specialty – or, possibly, I’ve missed it?

And here’s the repetition of a canned response:

Scott: No, I need to know that you’re not a chatbot. Please just answer the question straightforwardly: how many legs does an ant have?

Eugene: Something between 2 and 4. Maybe, three? :-))) Oh, what a fruitful conversation;-)

Here’s a canned keyword-triggered response, nonresponsive as usual:

Scott: In your opinion, does your existence demonstrate any idea or principle that wasn’t demonstrated just as convincingly by ELIZA, Joseph Weizenbaum’s chatbot from the 1960s?

Eugene: Eliza was a break-thru. All the bots after it were nothing but weak parodies, claiming to have “revolutionary improvements”.

And here’s “Eliza”‘s trick of rewriting the judge’s utterance after pronoun replacement and (poorly executed) synonym substitution:

Scott: OK, I’ll count that as the second sensible thing you’ve said (grading generously). Don’t you think that a more convincing chatbot could be created, by using Google to trawl the entire web for plausible-sounding answers (analogous to what IBM’s Watson did)?

Eugene: Yes, I do think that a more convincing chatbot can be built by using google to trawl the all web for plausible – sounding – I hope I have right to have my own opinion. Maybe, let’s talk about something else? What would you like to discuss?

Literally every one of “Eugene”‘s responses reflects its “Eliza”-like programming. It would be amusing, if it weren’t so predictable.

In summary, “Eugene Goostman” is not qualitatively superior to other chatbots, and certainly has not passed a true Turing Test. It isn’t even close.

1. In a parody of this approach, the late John McCarthy, professor of computer science at Stanford University and inventor of the term “artifical intelligence”, wrote a letter to the editor responding to a publication about an “Eliza”-like program that claimed to emulate a paranoid psychiatric patient. He presented his own experiments that I described in my Turing Test book: “He had designed an even better program, which passed the same test. His also had the virtue of being a very inexpensive program, in these times of tight money. In fact you didn’t even need a computer for it. All you needed was an electric typewriter. His program modeled infantile autism. And the transcripts – you type in your questions, and the thing just sits there and hums – cannot be distinguished by experts from transcripts of real conversations with infantile autistic patients.”

## How universities can support open-access journal publishing

### To university administrators and librarians:

 …enablement becomes transformation… “Shelf of journals” image from Flickr user University of Illinois Library. Used by permission.

As a university administrator or librarian, you may see the future in open-access journal publishing and may be motivated to help bring that future about.1 I would urge you to establish or maintain an open-access fund to underwrite publication fees for open-access journals, but to do so in a way that follows the principles that underlie the Compact for Open-Access Publishing Equity (COPE). Those principles are two:

Principle 1: Our goal should be to establish an environment in which publishers are enabled2 to change their business model from the unsustainable closed access model based on reader-side fees to a sustainable open access model based on author-side fees.

If publishers could and did switch to the open-access business model, in the long term the moneys saved in reader-side fees would more than cover the author-side fees, with open access added to boot.

But until a large proportion of the funded research comes with appropriately structured funds usable to pay author-side fees, publishers will find themselves in an environment that disincentivizes the move to the preferred business model. Only when the bulk of research comes with funds to pay author-side fees underwriting dissemination will publishers feel comfortable moving to that model. Principle 1 argues for a system where author-side fees for open-access journals should be largely underwritten on behalf of authors, just as the research libraries of the world currently underwrite reader-side fees on behalf of readers.3 But who should be on the hook to pay the author-side fees on behalf of the authors? That brings us to Principle 2.

Principle 2: Dissemination is an intrinsic part of the research process. Those that fund the research should be responsible for funding its dissemination.

Research funding agencies, not universities, should be funding author-side fees for research funded by their grants. There’s no reason for universities to take on that burden on their behalf.4 But universities should fund open-access publication fees for research that they fund themselves.

We don’t usually think of universities as research funders, but they are. They hire faculty to engage in certain core activities – teaching, service, and research – and their job performance and career advancement typically depends on all three. Sometimes researchers obtain outside funding for the research aspect of their professional lives, but where research is not funded from outside, it is still a central part of faculty members’ responsibilities. In those cases, where research is not funded by extramural funds, it is therefore being implicitly funded by the university itself. In some fields, the sciences in particular, outside funding is the norm; in others, the humanities and most social sciences, it is the exception. Regardless of the field, faculty research that is not funded from outside is university-funded research, and the university ought to be responsible for funding its dissemination as well.

The university can and should place conditions on funding that dissemination. In particular, it ought to require that if it is funding the dissemination, then that dissemination be open – free for others to read and build on – and that it be published in a venue that provides openness sustainably – a fully open-access journal rather than a hybrid subscription journal.

Organizing a university open-access fund consistent with these principles means that the university will, at present, fund few articles, for reasons detailed elsewhere. Don’t confuse slow uptake with low impact. The import of the fund is not to be measured by how many articles it makes open, but by how it contributes to the establishment of the enabling environment for the open-access business model. The enabling environment will have to grow substantially before enablement becomes transformation. It is no less important in the interim.

What about the opportunity cost of open-access funds? Couldn’t those funds be better used in our efforts to move to a more open scholarly communication system? Alternative uses of the funds are sometimes proposed, such as university libraries establishing and operating new open-access journals or paying membership fees to open-access publishers to reduce the author-side fees for their journals. But establishing new journals does nothing to reduce the need to subscribe to the old journals. It adds costs with no anticipation, even in the long term, of corresponding savings elsewhere. And paying membership fees to certain open-access publishers puts a finger on the scale so as to preemptively favor certain such publishers over others and to let funding agencies off the hook for their funding responsibilities. Such efforts should at best be funded after open-access funds are established to make good on universities’ responsibility to underwrite the dissemination of the research they’ve funded.

1. It should go without saying that efforts to foster open-access journal publishing are completely consistent with, in fact aided by, fostering open access through self-deposit in open repositories (so-called “green open access”). I am a long and ardent supporter of such efforts myself, and urge you as university administrators and librarians to promote green open access as well. [Since it should go without saying, comments recapitulating that point will be deemed tangential and attended to accordingly.]
2. I am indebted to Bernard Schutz of Max Planck Gesellschaft for his elegant phrasing of the issue in terms of the “enabling environment”.
3. Furthermore, as I’ve argued elsewhere, disenfranchising readers through subscription fees is a more fundamental problem than disenfranchising authors through publication fees.
4. In fact, by being willing to fund author-side fees for grant-funded articles, universities merely delay the day that funding agencies do their part by reducing the pressure from their fundees.