The challenge of inclusive language design

I have something to say: design is not everything. 

For better and for worse: it will not receive all the praise or have to support all the criticism. Human language as a communicative need is a tool that, according to the scientific journal Science Advances, arose two and half million years ago. Therefore, language effectively existed before we became aware that design could call the tune.

Biased language can be blamed on the heritage of a society built on historic patriarchal foundations, not on design. As we have said, language is one thing and design is another, but… who is responsible when we have had the chance to do things well and we have not done so?

Language, by its very nature, is evolutional. It changed, it changes, and it will change whilst we live because it is no more than a reflection of what happens, the tool with which we can express, tell, transmit and communicate all the realities that exist. However, why is it so difficult to make a space for these changes in our speech? 

History repeats itself when we talk about how countries such as France, Spain or Israel have had, and continue to have, problems with their respective language academies, which affirm that inclusive language is an aberration and a mortal danger for the language itself. Why is there still a debate about the fact that the vehicle that articulates and frames the way we think is what limits us?

But where does the current problem with language really lie?

Let us start at the beginning:

The way we speak matters. Very much.

It is hard to realize that after all this time, when we have been using the generic masculine, we are more likely to remember male rather than female politicians, famous men rather than famous women. The way we speak matters when it limits the way we think.

It so happens that they have made us believe that withdrawing the famous “Man” to refer to “humanity” and using in its place “all” (in Spanish, the masculine “todos”) as a clear example of generic masculine (using masculine terms as a neutral form from the gender perspective) would convince us. But the truth is that the generic masculine is still no more than just masculine. A subtle trap.

Here is an example:

The study “Gendered or Neutral? Considering the language of HCI” shows how a group of participants was asked to think about the words, user/participant/person/designer and researcher, for ten seconds and then to draw them. The study showed that these “generic masculine” words were not so neutral as it seemed since the probabilities of their being perceived as masculine or feminine were not the same. Even women tended to interpret the words as masculine. 

More worrying is the case of a similar study among Pakistani boys and girls of 9 and 10 years of age in which they were invited to draw the word “us”. No boys and hardly any girls drew women. And I say more worrying because in the end time is running out and it is probable that the generations who are reading this will never completely rid ourselves of this vitiated language. However, it scares me that girls of 9 do not feel represented because there is no driving force more powerful than aspiring to be like somebody you admire.

The structures of language

An analysis by the World Economic Forum in 2012 showed how countries with languages that have gender inflection, in which almost all statements include firm ideas of masculine and feminine, are the least fair in gender matters. 

But here an interesting peculiarity can be observed: countries with languages without grammatical genders (such as Hungarian and Finnish) are not the fairest. This prize goes to a third group: that of countries with “natural gender languages” such as English. 

These languages make it possible to indicate gender but in most cases it is not incorporated in the actual words (female doctor, male teacher).

And dear readers, let nothing inspire more fear in you than a set idea with no ambition or aspiration to be moved.

In line with these changes, Caroline Criado says in her book “The invisible woman” that when in 2017 the first female commissioner of the London Fire Brigade, Dany Cotton, proposed replacing the word fireman with the current standard term (much cooler, by the way) of firefighter, changing a masculine noun to a neutral one, she received countless offensive emails.

In languages with gender inflection, the transition is a bit more complicated at a structural level and the generic masculine is more comfortably established. We have interiorized its use so much that we no longer even see it and job offers were not going to be the exception. Jobs are normally advertised in masculine (especially when they are for managerial positions). In view of the studies I mentioned before, it is not bizarre or conspirationist to think that may women feel excluded or undeserving of these positions just by reading the characteristics. 

But like haters gonna hate I will say that this stupidity could not be so stupid when, since 2008, the European Parliament has recommended that at the end of job offers in languages with gender inflection (m/f) should be added. It is a step, I don’t know in which direction, but a step.

The problem

I am especially concerned by the possible transcendence of this language that, without setting out to be harmful, ends up affecting our capacities, or rather: that ends up limiting the possibilities of girls, who in a few years will be women who have grown up hearing things like “el médico” (the male doctor), “el abogado” (the male lawyer), “la enfermera” (the female nurse).

In countries with gender inflected languages such as Italy or Spain, when girls read or listen to a profession in masculine, they imagine a man. All the socially “respectable” positions are held by men in our heads. And is this not a form of limitation? That which is absent runs the risk of being invisible and that is the danger.

Modern language

It is tempting to think that the masculine bias that is so deeply rooted in language is a mere relic of past times, but reality goes in another direction. 

The language with the fastest growth rate, used by 90% of the world internaut population, is that of emoticons.

The emoticons that we have in the operating systems of our mobile telephones and computers are selected by the Unicode Consortium (formed by a group of organizations with headquarters in Silicon Valley that work together to guarantee quality standards in universal emoticon software). It is Unicode that decides when to add a new emoticon to the current line-up available. Once decided, it designs and indicates in which code it is to be used and each platform or social media designs its own interpretation of that emoticon. A face with hearts in the eyes is common to all, the only variation is whether the hearts are more or less rounded. 

Unicode gives the indications but does not set the gender of the emoticon. The consortium would merely say “add a runner” and the other companies would design (obviously) a man running, interpreting once again the neutral terms as masculine (which emphasizes that generic does not quite work).

In view of this, in 2016 (the day before yesterday), Unicode decided to issue instructions for each version (male and female) of new emoticons launched. Why did they expect us to feel identified with a drawing of a man running when they have clearly felt so little reflected in the female version that they had even forgotten to propose it?

The language of Artificial Intelligence

Artificial intelligence is one of the greatest challenges of inclusive language faced by designers and it is an opportunity to rebuild the foundations from zero.

Google fascinates me. I don’t talk about it, I do it.

The most worrying examples are not those of the beginning of this article that we are all more than aware of. It is the algorithms and not the hardware. It is relatively simple to detect how hardware affects us, therefore it is “easy” to solve. Algorithms, however, the most representative product of these decades, worry me more. 

We are still working with biased data because we have not solved the previous step and, despite this, algorithms are, little by little, marking our interactions and entering all the areas of our lives.  There does not seem to be much understanding among the people who code these algorithms about the problems with the data on which they are based. Artificial intelligence ranges from voice recognition systems that do not recognize female voices (there were always authorities), to online dictionaries, or algorithms that decide whether a specific CV will ever be seen by human eyes.

Limitation of opportunities, that is what this article is about.

— Sara Antolín.