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A panel proposed at UNESCO in 2021 held the premise that "to be smart, the digital revolution has to be inclusive". If we do not take into account all possible audiences, we are talking about a "revolution" only for some sectors, and the purpose of the digital revolution and artificial intelligence is to facilitate and streamline processes for all people interacting in the digital ecosystem.
The reality is that brands have long since begun to leave behind the idea that audiences are homogeneous, structured, and limited. The days of defining a company's target audience as "married men and women aged 30 to 50" are over. There is a reality: in 2023, we know that each user's lifestyle, gender identity, marital status, and sexual orientation can be as diverse as their first and last names. And certainly, no one should be excluded from technological advances because of issues that simply make up each person's individuality.
As in all areas of technology, it is essential to take this issue into account when developing a conversational strategy and training the artificial intelligence in charge of interacting with our audience with an inclusive perspective. Below, we will delve deeper into this topic and discuss some strategies for creating fair and inclusive conversations.
What is gender bias and how does it impact the digital age?
By definition, a gender bias is an assumption or presumption that deliberately assigns traits for or against a specific gender. Gender biases often lack scientific evidence, and are mostly based on unconscious beliefs that people have about the different genders, based on learned socio-cultural stereotypes.
At a commercial level, the premise is simple: brands that do not adapt to the new codes will sooner or later lose out. Audiences are increasingly demanding in every sense: they want fast, accurate, and personalized responses. And a very important part of personalization is that brands do not contribute to promulgating stereotypes that may be offensive or discriminatory to any user segment.
That's not all: trends indicate that users are placing increasing value on the inclusivity aspect of the brands they consume. Not only are they paying more and more attention to the way they communicate, but also to what they do behind closed doors. Inclusivity cannot be "window dressing": in fact, it can work against a company. Gender training and inclusion applied on a day-to-day basis are just as important as communication without gender bias.
Gender Bias in Artificial Intelligence
Artificial intelligence is not exempt from generating gender biases. AI engines draw on external information provided by companies, IT teams or directly from the vast knowledge pool of the internet itself. This, in fact, may make artificial intelligence even more prone to reproduce certain stereotypes, since its information sources are most likely biased as well.
The truth is that technology is not unbiased in any field, and examples abound. In 2020, some Twitter followers complained that the app was cropping images for tweet previews by reproducing gender and racial biases and, for example, prioritizing showing images of white people. The company eventually acknowledged this, explaining that this preview was automatically selected by a (clearly biased) AI algorithm.
Without going any further, ChatGPT, the latest development in the world of conversational AI processors, gives us a clear picture of this:
Of course, the tool itself is not responsible for the reproduction of such strong gender stereotypes, but the responsibility lies with the information with which the engine was trained.
Related Article: ChatGPT: Training Process, Advantages and Limitations
Types of gender bias
- Decision makers
This bias is based on the premise that the final decision-makers are always men. It can be reflected in a simple final question such as "are you sure you want to cancel this purchase?".
- Glass ceiling
This is the case of the bias cast by ChatGPT in the previous section. The glass ceiling presumes that hierarchically higher positions are always held by men and lower positions by women.
This bias occurs when previous research (whether to load data into a bot, to define a target, put together a mass communication, launch a new product, etc.) is based exclusively on male study subjects.
- Cognitive and emotional capabilities
A very common bias when looking at human representations in brands. It is that the soft and emotional part of a company is represented with a female figure, implying that only women have the ability to show emotions. This is very much the case when it comes to virtual assistants: the ability to help and accompany is intrinsically linked to femininity, and bots are represented as willing and decisive women. In the next section, we will delve more deeply into this point.
How to create a virtual assistant that does not reproduce gender stereotypes?
As we mentioned earlier, in the world of virtual assistants that act as the visible face of a brand's customer service, it is quite common to find that most of them are represented as women. Of course, this is not a deliberate bad intention on the part of the person who configures it.
In most cases, it is not even part of a conscious decision to attribute the female gender to a bot because it is related to helping and empathy -characteristics historically related to femininity-. The reality is that the decision, in most cases, is simply motivated at an unconscious level by the cultural and historical associations that society as a whole has with the female gender.
To banish these associations, which are nothing more than stereotypes, the first step is to make them conscious and review all the aspects that influence their repetition when configuring a bot. Here is a list of steps to follow to start creating inclusive virtual assistants with as few gender biases as possible
Know your target audience
The first key question to ask any person or team setting up an AI bot is: who will be interacting with it? Understanding the target audience is crucial to encompass all possible answers. Configure their idioms when speaking, understand what age range we are communicating with, what level of schooling they have, what they do for a living, and so on.
The most important thing is not to assume that, because they are from a certain industry or because they are customers of a particular company, all users are female or male, or that they all do the same thing.
For example, when configuring a virtual assistant for an international spa, avoid assuming that all users are female, and offer the possibility of configuring the bot's language to avoid assuming that all the target audience understands the same language.
Review the team that will configure it
When setting up the bot, it is important to pay attention to who is setting it up: is it a diverse team with different points of view and from different social groups? If the answer is yes, the bot content will most likely reflect this. But if the answer is no, we could be dealing with a gender-biased virtual assistant.
If the team that configures the bot is made up entirely of a homogeneous group belonging to the same social segment, it is unlikely that the content it produces will be representative of other user segments, simply because the team does not have a deep knowledge of other more diverse realities.
Ideally, teams are made up of men and women of different ages and races, and all provide input and review the content to ensure that it does not reproduce stereotypes of any kind.
Don't assume the gender of the person you are talking to
If the bot has no way of knowing the gender of the person it is talking to (i.e., if it is not asked), it is important that it does not assume it. For this, the team has the option of choosing to load gender-neutral content and avoid gender-marked words.
Instead of saying "Are you satisfied with our service?", assuming the interlocutor is male, you can simply opt to ask "Do you consider our service satisfactory?".
Opt for a no-code platform
Finally, to facilitate the reduction of gender bias and to more easily and quickly implement all of the above steps, having a no-code conversational platform is crucial. With the implementation of a no-code platform, the content of the engine can be constantly changed and updated by anyone on the team, without the need for technical interventions or programmers. This not only gives the company full control of the content handled by the platform but also allows it to customize the content based on the company's values.
It is important to mention that not all conversational AI-powered platforms are no-code, and not all allow full control over the content provided. AgentBot, Aivo's conversational AI chatbot, gives content owners complete control to constantly update information from a friendly and easy-to-manage no-code platform.
Offer fair and inclusive conversations
As we have already seen, gender biases are ingrained in the collective unconscious and it takes work and commitment to begin to banish them for a true digital revolution. The points we mentioned previously are small steps to deliver truly personalized and inclusive conversations that do not perpetuate inequality or stigmatization.
If you want to get started with a no-code conversational AI platform, with a team on hand to help you deliver inclusive conversations, feel free to contact us.