The Worst Ideas. Updates every Monday!

Your weekly source for terrible ideas.

Category: Language

The secret of SMART JUSTIFIED columns of text. This strange formatting tip will make ONE HUNDRED TIMES more employers look at your resume! Stop formatting your resume so amateurishly, and await your reward of gold and rubies from your future employer.

Background:

Columns of text in a book or newspaper are generally formatted in the fully justified style (Figure 1), where the text always lines up exactly on both the left and right edges.

justify-text-icon

Fig. 1: The “justify text” button (circled in red) can be found in nearly every text editor.

The issue:

Justified text works well if columns are wide and there are a lot of words to fill out each line.

But it becomes aesthetically dubious if the columns are narrow or there aren’t enough words, which result in either:

  • Extremely wide spaces between words if there are too few words (example: “this______column”)

or

  • Excessive spacing between letters if there is only one word (example: “c__o__l__u__m__n”)

In the worst-case scenario, a column of text may look like:

  • This____is_____a
  • n__a__r__r__o__w
  • c__o__l__u__m__n.

See figure 2 for a comparison of fully-justified text and ragged-edge (flush left) text.

justify-text-heres-the-problem.png

Fig. 2: Part A (left) shows a few problems with fully-justified text: “the age of” has excessive spacing and the between-letter spacing in “w i s d o m” is aesthetically questionable. Unfortunately, the ragged edge of the text in part B (formatted as “flush left / ragged right”) is not a huge improvement either.

Previously, a publisher would at least know how wide a column of text would be, so they could manually adjust the text to fit in an aesthetically-appealing fashion.

But with modern web pages and e-books, font sizes and column widths can be changed by the user—so there’s no way for a publisher to plan around it.

Proposal:

This problem can be fixed by using semantically-aware SMART justification to make each line of text an optimal length.

This is accomplished as follows:

If a line of text is too short, it can be lengthened by the following steps:

  • Add meaningless filler words (e.g. “um,” “like,” “basically,” “you know”)
  • Add superfluous adjectives (like “very” or “extremely”)
  • Replace words with longer synonyms (e.g. “rain -> precipitation”—this can also be used in reverse to shorten a line)
  • Replace pronounces with their antecedent (e.g. “her scepter” -> “Queen Elizabeth’s scepter”)

Figure 3 shows the performance of each method of text justification. The “meaning-aware SMART justification” is the only method that avoids ragged edges while also keeping a fixed amount of whitespace between words.

justify-text-annotated

Fig. 3: Left: a traditional example of fully-justified text. Middle: flush-left text, with an unappealing ragged right edge. Right: the vastly improved “smart” justification method, which has been recently made possible by advances in computational technology and machine learning.

Application of this method to famous books:

  • Original: “But man is not made for defeat,” he said. “A man can be destroyed but not defeated.” (The Old Man and the Sea, Hemingway)
  • Modified with superfluous filler words and synonyms:  “But man is, generally, not made for defeat,” he stated. “Basically, a man can be destroyed but, as you know, not forced to surrender.” 

 

  • Original: “War is peace. Freedom is slavery. Ignorance is strength.” (1984, Orwell)
  • Modified:  “War is peace. Additionally, the state of freedom is slavery. Finally, in conclusion, ignorance is strength, it must be admitted.”

 

  • Original: “In general, people only ask for advice that they may not follow it; or, if they should follow it, that they may have somebody to blame for having given it”.” (The Three Musketeers, Dumas)
  • Modified: “In general, people only make a request for suggestions, that those same people may not abide by it. Or, if they should in fact follow it, that those people may have somebody to blame or hold responsible for having given it”.” 

 

PROS: This is the ONLY text-formatting method that both 1) preserves inter-word spacing AND 2) aligns text in neat columns.

CONS: None!

Programmers love this one weird trick to handle Unicode characters without any complexity! “Visual-literation” replaces the old-fashioned way of transliteration. Watch as linguists wail mournfully at the years they wasted trying to transliterate sounds between alphabets!

The issue:

Many computers are unable to handle letters that don’t fall into the set of Latin characters used by English.

Even though the Unicode standard has greatly improved multi-character-set accessibility, problems still arise:

  • A character might not exist in a chosen font. For example, “Egyptian Hieroglyph of a bird catching a fish” is probably not available in Comic Sans.
  • Systems may be unable to cope with characters that look exactly the same (“homoglyphs”: https://en.wikipedia.org/wiki/Homoglyph).
    • For example, “Latin A” and “Cyrillic A” look identical, but have different underlying Unicode codes.
    • So an email from “YOUR BANK.COM” might actually be from a different site, with an imposter letter “A” (https://en.wikipedia.org/wiki/IDN_homograph_attack).
    • (This is an issue in English as well, with 0 (zero) versus O (capital “o”) and “I / l / 1” (capital i, lower-case L, numeral 1).)
  • Systems may not allow certain letters for certain situations; for example, if your username is “Linear B ‘stone wheel’ + Mayan jaguar glyph,” it is extremely unlikely that you will have an easy time logging into your user account.

The current failure mode is usually to display a blank rectangle instead, which is unhelpful.

Proposal:

Instead, we can use a sophisticated image-recognition system to map each letter from every language onto one or more Latin characters (Fig. 1).

Usually, this is called transliteration (https://en.wikipedia.org/wiki/Transliteration). But in this case, rather than using the sound of a symbol to convert it, we are using the symbol’s visual appearance, so it’s more like “visual-literation.”

easy-vs-hard

Fig. 1: With a limited character set, it may be easy to display the “Å” as  “A”, or “ñ” as “n.” But it’s unclear what should be done with the Chinese character at the bottom, which isn’t similar to any specific Latin letter.

more-abstract

Fig. 2:

Top: Image analysis reveals that the Chinese character (meaning “is”) can be most closely matched to the Latin capital “I.” Bottom: The Greek capital “∏” (pi) is disassembled into two Ts.

Some letters actually do somewhat resemble their Latin-ized versions (like “∏” as “TT”). However, some mappings are slightly less immediately obvious (Fig 3).

highly-unrelated

Fig. 3: Many complex symbols can—with a great degree of squinting—be matched to multi-letter strings.

Conclusion:

Linguists will love this idea, which forever solves the problem of representing multiple character sets using only the very limited Latin letters.

PROS: Gives every word in every language an unambiguous mapping to a set of (26*2) = 52 Latin letters.

CONS: Many symbols may map to the same end result (for example, “I” could be the English word “I,” or it could have been a “visual-literated” version of ““).

 

letter-translation

Fig. 4: A collection of potential mappings from various symbols to an ASCII equivalent. Finally, the days of complex transliteration are over!

 

 

The secret language that they don’t want you to know: Oneglish (“1NGLISH”)—return English to its ancient roots with a new one-syllable version! Save hours every day. Also: how many syllables are in the English language, anyway? Answer: probably at least 972,465, if you believe the assumptions below!

The issue:

English has a large number of words with multiple syllables. We could save so much time if all these words were replaced with unique singlesyllable equivalents!

Proposal:

For example, in the section above, we would change the following words:

  • English -> Eng
  • number -> noim
  • multiple -> mult
  • syllable(s) –> syllb(s)
  • replace(d) -> roup(ed)
  • unique -> neek
  • single -> soing
  • equivalents(s) -> eevt(s)

The final result would be:

  • Eng has a large noim of words with mut syllbs. We could save so much time if all these words were rouped with neek soing-syllb eevts!

See Figure 1 for an illustration of how this would save time. This new language could be referred to as “Eng” or perhaps “one-glish” (or “1NGLISH”), as shown in Figure 2.

one-glish

Figure 1: The phrase “English words with multiple syllables” in normal English in blue (top) and 1NGLISH (or just “Eng”) in yellow (bottom). Note that the 1NGLISH version is approximately 25% faster to say in this totally fabricated figure.

english-one-syllable-logo-3

english-one-syllable-logo-1

Figure 2: Above: a couple of possible logos that resemble ones from a bankrupt Internet company. Effective advertisement and branding is important!

Obstacle #1: Is it feasible for large quantities of people to learn a new language?

Attempts at language reform / constructed languages have failed in the past.

For example, Esperanto (https://en.wikipedia.org/wiki/Esperanto) never really took off.

But, there are a couple of successes worth pointing out here:

Obstacle #2: Are there even enough syllables for this to work?

How many possible syllables are there in the English Language?

Answer: a lot.

Depending on who you believe, there are around ~30 distinct vowel sounds and ~60 distinct possible consonants. A list with pronunciations is, as you might expect, available on Wikipedia:

However, a lot of these are almost indistinguishable to an English speaker. I have pared a list down to:

  • 23 vowels
  • 23 consonants
  • (This doesn’t include things like “clicks” and other possible sounds that aren’t used normally in English.)

English apparently supports the following configurations of syllables: (V = Vowel, c = consonant)

Commonly supported configurations of vowels and consonants:

  • V (just a vowel sound and nothing else, like “Aye” or “Oh”)
  • Vc (e.g. “am, it, on“)
  • cV (e.g. “ma, he“)
  • Vcc
  • cVc
  • ccV
  • Vccc (“oinks“)
  • cVcc (“lamp“)
  • ccVc (“plan“)
  • ccV (“spray“)
  • ccVcc (“plank“)

There are also some more-suspect configurations that occasionally work, such as:

  • cVccc (“balks,”)
  • ccVcccc (“glimpsed“)

And things that theoretically could make words, but don’t seem to actually have examples:

  • cccVcccc (“spranksts” <– not a word, but it has a valid pronunciation)

For the sake of argument, we’ll restrict ourselves to the “commonly supported” list above.

If we make the conservative assumption that there are only 15 “valid” vowels / consonants at each position (instead of the full list of 23), we end up with the following number of possibilities for each vowel/consonant configuration:

  • V, 15
  • Vc, 225
  • cV, 225
  • Vcc, 3,375
  • cVc, 3,375
  • ccV, 3,375
  • Vccc, 50,625
  • cVcc, 50,625
  • ccVc, 50,625
  • cccV, 50,625
  • ccVcc, 759,375

Adding these up, we get a total of 972,465 single-syllable utterances that would be recognized as a potentially valid English word.

Since the Oxford English Dictionary only contains < 200,000 words that are in current use (plus another ~50,000 obsolete words), there is more than enough space for every even remotely plausibly useful English word to be replaced by a totally unique single-syllable equivalent.

This will save a TON of time in communication!

Testing: Real-world speed of English vs 1NGLISH:

The testing process is as follows:

  1. A phrase is chosen
  2. The phrase is said TWICE, with a 0.4 second pause between repetitions
  3. The total time of both phrases AND the pause is measured
  4. Example: if a phrase takes exactly 1.0 seconds to say once, then it would have a score of 2.4 seconds here (2.4 = 1.0 + 1.0 + 0.4)

Below are four totally normal sentences, before and after the 1NGLISH-ification process, along with their waveforms.

Example of how 1NGLISH shortens a sentence #1:

ENGLISH: “Observing this brutalist architecture gives me heart palpitations. Please survey the lobby for defibrillators!”

  • 10.35 seconds to say twice

1NGLISH: “Ob this brulj arzsk gives me heart paln. Please saiv the lorb for drenb.”

  • 9.03 seconds to say twice (87% as long)

1 Observing this brutalist architecture gives me heart palpitations. Please survey the lobby for defibrillators.png

Example of how 1NGLISH shortens a sentence #2:

ENGLISH: “Reprehensible scoundrels have absconded with my assortment of petit fours!”

  • 7.09 seconds to say twice

1NGLISH: “Raibl scraid have abdr with my sote of payt fours.”

  • 5.31 seconds to say twice (75% as long)

2 Reprehensible scoundrels have absconded with my assortment of petit fours.png

Example of how 1NGLISH shortens a sentence #3:

ENGLISH: “Librarian, I request the seventh treatise on philology from the bookshelf.”

  • 7.93 seconds to say twice

1NGLISH: “Laib, I rerqt the sev tront on phrend from the bornf.”

  • 6.47 seconds (82% as long)

3 Librarian, I request the seventh treatise on philology from the bookshelf.png

Example of how 1NGLISH shortens a sentence #4:

ENGLISH: “In Parliament, the foreign plenipotentiary negotiates with the defense minister.”

  • 8.01 seconds to say twice

1NGLISH: “In Parlt, the frnai plort nairt with the deif marne.”

  • 5.53 seconds to say twice (69% as long)

4 In Parliament, the foreign plenipotentiary negotiates with the defense minister.png

Conclusions:

For the four sentences tested above, we see a (roughly) 20–30% improvement in speed.

That’s called SCIENCE.

english-one-syllable-logo-2

Figure 3: 1NGLISH will need to demonstrate its superiority in order to convince people to learn it!

PROS: Speeds up your verbal communications—and perhaps also typing speed—by approximately 25%.

CONS: None! It’s the ultimate language. Learn it now!

Obsolete password requirements cost over 50 billion dollars in lost productivity per year—solve the problem forever with these new password requirements!

Background:

You’re probably familiar with web sites that have very particular password requirements:

  • “Your password must contain a number, capital letter, and special character.”
  • “Your password must contain the name of a Triple Crown-winning horse.”
  • “Your password cannot contain your username.”

The purpose of these requirements is usually to either:

  1. Require that the password not be instantly guessable by hackers
  2. Require that the password be specific to a particular web site. Although this is quite rare, it does exist. For example, a bank could require that “$” appear in a password four times, which would prevent you from re-using your other passwords. (This is the same principle used by colleges that have weird essay prompts, preventing an individual from re-using other essays.)

The issue:

There are relatively few variants of these requirements, and they are all extremely unimaginative.

For example, the password pa#ss@W0rd can probably be used on most sites—so when one of them gets hacked, your bank account will be imperiled!

Three proposals:

The following proposals are for more creative methods of enforcing unique passwords (which generally would not be usable between sites).


password-angular

Figure 1 / Proposal 1: Require that CURVED letters and ANGULAR letters alternate in the password. Very straightforward!

Font nerd bonus feature: See bonus figure A (at bottom) for more details about the degree to which this property depends on the specific font you are using.


password-symbols

Figure 2 / Proposal 2: Require that a password contain a number, letter, Chinese character (light blue), Devanagari syllable (purple) Greek letter (dark blue), and accented letter (orange). Those specific character sets are arbitrary, so different users could be given different language requirements. There is no shortage of options: there are ~32 character sets for currently-written languages in the current Unicode build plus approximately 100 historical scripts no longer in standard use.

Downside to this method: If you got really unlucky, your password might require the following: an Egyptian hieroglyph, Chinese obsolete seal-script character, Sumero-Akkadian cuneiform mark, and linear B symbol. Probably you should just register a new user account at that point. If you got incredibly unlucky, the site might even require a script that is not in Unicode yet (perhaps Maya glyphs). In that case, presumably you would have to draw (or carve) the appropriate Maya glyph and upload a picture with your cell phone camera.


password-line

Figure 3 / Proposal 3: Require that a password solve a certain type of visual puzzle. In this case, we require that a continuous line be drawn through all the symbols (this is shown as a yellow highlight).

Downside to this method: this puzzle would be extremely font-specific; the “p -> c” line and “c -> 6” line are a bit questionable even here.


Conclusion:

If you run a web site, you should change your obsolete password requirements immediately!

PROS: Makes password re-use between sites impossible.

CONS: Probably you’ll use a password manager and then it will get hacked and/or you’ll forget the master password.

futura

Bonus Fascinating Typeface Fun Fact Figure A: As a surprising feature of English typography, curved-and-non-curved letters (which are important to distinguish in the “curved vs angular” proposal in Figure 1) are consistent among nearly all non-handwriting fonts.

For example, a capital “M” is nearly always 4 straight lines, whereas a lower-case “m” is almost always two curved arches. The only counterexample I found in a non-exotic font was that a lower-case “j” is normally curved, but it is completely straight in the font “Futura.”  Futura is one of the few not-totally-a-gimmick fonts that defies the conservation-of-letter-curve.

Lawyers hate it! Linguists love it! Never be confused by contradictory and confusing laws again, now that you have a fully logical legal annotation language, or “legal markup language.”

Background:

Misunderstandings of meaning are often encountered due to ambiguities in human language.

This causes problems in several ways, particularly in:

  1. Translation between languages
  2. Interpretation of laws

1) In regards to translation:

For any non-trivial translation between two languages, a human is still required in order to figure out the meaning of it and a sentence and translate it accordingly—despite the fact that the meaning is all (theoretically) already present in the text.

2) In regards to interpretation of laws:

Ambiguity in laws can cause much consternation. One famous example is the Second Amendment of the U.S. Constitution, which reads:

“A well regulated Militia, being necessary to the security of a free State, the right of the people to keep and bear Arms, shall not be infringed.”

The significance (or, alternatively, the lack thereof) of “a well regulated militia” continues to be debated. This confusion could all have been avoided by wording official documents in an unambiguous language.

Proposal:

We will create a new, exceedingly detailed form of annotation that will related human concepts in an unambiguously logical fashion.

This annotation will be more like an HTML-style markup language than a standard human language.

(A theoretically unambiguous language called “Lojban” (https://en.wikipedia.org/wiki/Lojban) already exists, but it requires learning an entirely new language, whereas the proposal here is an extension of one’s existing language.)


Example #1: The Eighth Amendment to the U.S. Constitution:

Original text: “Excessive bail shall not be required, nor excessive fines imposed, nor cruel and unusual punishments inflicted.”

…and now a version in unambiguous annotated format:

  • Statement:
    • Forbid:
      • bail (noun, a specific payment for those awaiting trial, unspecified quantity)
        • only_present_if:
          • is also excessive (large in quantity)
      • fines (noun, payment required from an individual, 2+):
        • type: required / mandatory
          • required by: the government
        • only_present_if:
          • is also excessive (large in quantity)
      • infliction / imposition:
        • thing to be inflicted: punishments (plural, 2+)
        • only_present_if:
          • all_conditions_true:
            • is cruel (adj., see also merciless, evil)
            • is_not:
              • usual / common / standard / as expected

And when translated back to English:

The following 3 things are forbidden: 1) bail, only if excessive or too large in quantity, 2) fines, only if excessive or too large in quantity, and 3) infliction of punishment, only if both of the following conditions are met: the punishment is cruel or merciless, and also the punishment is also unusual or nonstandard.

See Fig. 1 for an example of the annotation format in flowchart form.


Unambiguous text - 8th amendment flowchart

Fig 1: The Eighth Amendment to the U.S. Constitution, rendered as a “diagrammed sentence”-style graph of logical concepts.


Example #2: Shakespeare, a famous soliloquy by Hamlet:

HAMLET: To be, or not to be—that is the question: 

Whether ’tis nobler in the mind to suffer

The slings and arrows of outrageous fortune

Or to take arms against a sea of troubles

And by opposing end them.


…and now a version in unambiguous annotated format:

  •  Pose_Question:
    • type: posed abstractly
      • posed_to: abstract audience of indefinite nature (informal)
      • posed_by: Hamlet (male, singular, nobility, age_of_majority, informal)
    • option: Continued existence
    • option: Annihilation
    • requirement: select 1 option
    • evaluation criterion: none
  • var MY_ENDURE =
    • subject (noun): enduring / persisting:
      • the one who endures: a human (abstract, no number or gender specified)
      • the thing to be endured: injury (abstract)
        • a.k.a.: new var TROUBLE1
          • caused_by: projectiles (plural, 2+):
            • projectile_1: causative agent (plural, 2+): a sling
            • projectile_2: causative agent (plural, 2+): arrows
            • source (of projectiles): abstract_entity:
              • fortune / luck
  • var MY_RAISE_ARMS_CAUSE_END =
    • var RA1 = verb / action: raise arms / raise weapons / struggle
      • struggle against what: troubles / problems (plural, many)
        • a.k.a.: new var TROUBLE1
        • assert that: TROUBLE1 is identical to TROUBLE1 in MY_ENDURE
      • var RA2 = noun
        • end / cessation of TROUBLE1
      • action:
        • RA1 leads to RA2 (RA1 -> RA2)
        • frequency of action causing result: always
  • Pose_Question:
    • type: posed abstractly
      • posed_to: abstract audience of indefinite nature (informal)
      • posed_by: Hamlet (male, singular, nobility, age_of_majority, informal)
    • option: Continued existence
    • option: Annihilation
    • requirement: select 1 option
    • evaluation criterion: “is nobler” (is superior, is more admirable)
    • item to evaluate #1: MY_RAISE_ARMS_CAUSE_END
    • item to evaluate #2: MY_ENDURE

And when translated back to English:

HAMLET: I pose the following abstract question: Is continued existence preferred, or is the non-continuance of existence preferred?

HAMLET: I pose the additional abstract question: Is it preferable for an unspecified individual to endure troubles, specifically multiple injuries caused by abstract fortune / luck, where these injuries are inflicted by one or more arrows, and one or more unspecified projectiles sent by means of a sling, or is it preferable for that individual to by means of arming oneself or applying weapons, struggle against against the same troubles referred to earlier in this question, where this struggle also results in the end of the specified troubles.

 

Conclusion:

For laws, its interesting to see how verbose and incomprehensible even a single sentence can be in “unambiguous” format. As for Hamlet, it may lack the elegance of the original, but now it can be translated between languages by machine without loss of information!

This would probably actually work for very limited types of input: e.g. cookbook recipes, scientific methods / protocols, product warranties, instruction manuals, etc…

PROS: Machine translation will finally work right!

CONS: The “unambiguous” format is basically impossible to read.


 

Below are the above examples in image format, with color-coded sections to indicated corresponding text.

Unambiguous text - Hamlet

Fig 2: An excerpt from Hamlet: original -> unambiguous annotation -> back to English, in an image. See above for this information presented as selectable text. Note that the colors are supposed to match up regions of (mostly) identical information content.

 

Unambiguous text - 8th amendment text

Fig 3: The Eighth Amendment: original -> unambiguous annotation -> back to English, in an image. See above for this information presented as selectable text.


 

Clean up old files on your computer easily with this ONE BIZARRE TRICK. Scholars of ancient languages hate it!

 

Background:

Over time, old files tend accumulate on one’s computer. However, cleaning out a computer is an annoying and time-consuming task.

In the past, storage increased at a rate such that old files could be safely ignored forever. But modern laptops may actually have less (although faster) storage than ones from five years ago. Now it’s important to be able to tell which files are old and which are not!

The proposal:

Here is an example of a normal file (Fig. 1):

file-2000s

Fig 1: A standard file, modified recently. Nothing remarkable about it!

We don’t really need to pay much attention to this file; we used it recently, and may want to use it again.

But an older file (which we should probably either archive or delete) could be called out by using an old computer font and icon, as seen in figure 2.

file-1980s

Fig 2: This older file is visually apparent, thanks to the classic font and pixelated icon.

file-magna-cartafile-greekfile-egypt

Fig 3: Even older files may be marked with different fonts, as seen above. The hieroglyphic font (of randomly-chosen hieroglyphs) could be reserved for the very oldest files on the system.

file-future

Fig 4: Finally, some files are accidentally set to a “future” modification time. Although this is currently impossible with our understanding of physics, these files nevertheless brazenly display a creation / modification date far in the future. We assume that robots will rule the earth in the far future, and thus have chosen a barcode font to represent the data for these files.

PROS: Accurately displays computer file age in easy-to-read visual form. Assists in freeing disk space.

CONS: Historical accuracy is questionable; hieroglyphs were not in widespread use during the early days of computing in the 1970s.

A call to action: stop being a slacktivist—it’s time to update emoji to prevent emoji obsolescence! (Or: emoji serve inadvertently as a time capsule of the early 2000s.)

Background:

As time goes on, certain emoji will become obsolete. Some of them already have! Although this is not a huge problem right now, it may become one in the future: will anyone understand what the “pager” emoji means in 100 years?

pager

Fig 1: In a hundred years, this pager icon will will baffle and befuddle all but the most erudite historians.

Fig 2: For people of the future, the pager icon will be as perplexing as this device probably is to you, unless you work in a historical re-creation village or something (This is an apple peeler.) Image citation.

The plan: periodically update emoji symbols

So we need to update our symbolic language to take into account the new technology.

Below are some examples of what emoji would have looked like if they had been created in years past.

These should serve as a cautionary tale and convince you of the necessity of occasional emoji symbol updates!

historical_emoji_MEDIUM_SIZE

Fig 3: This figure should convince you of the necessity of occasional emoji updates. If the emoji in the right column had been created in ancient times and never updated, we would be stuck with the no-longer-representative icons in the left column. For example, we would still have to use the “plague doctor” icon to refer to medical professionals.

Suggestion:

We may occasionally be able to predict certain aspects of the future and fix our soon-to-be-obsolete emoji ahead of time.

Future Emoji

Fig 4: Even in the early 2000s, we have the opportunity to add a few “for future use” emoji before we absolutely need them. Here are some examples of easy ones that are guaranteed to be correct. Also, we can probably remove emoji for most extinct animals in the future. Sorry, soon-to-be-extinct animals!

Possible Difficulty:

Due to the convergence of technology, sometimes multiple devices in the past will end up being the same icon in the modern era. For example, the camera, camcorder, phone, pager, fax machine, and computer have all been combined into the modern cell phone. It is unclear how to deal with this scenario in a satisfactory manner.

Convergent technological development

Fig 5: One issue with updating emoji is that multiple former-era-emoji may map to a single emoji in the current era, as seen above.

Conclusion:

As usual, this is a great idea!

PROS: Prevents emoji from becoming confusing and obsolete.

CONS: May make old documents unreadable if old symbols are retired or replaced, and thus rarely or never encountered except by historians.

Sources of certain images: