Textio
Textio is an AI-powered platform that helps reduce unconscious biases in writing job
descriptions and other texts. It uses machine learning algorithms to analyze language patterns
and suggest changes that could eliminate bias and enhance inclusivity in recruitment and
communication. Textio is based in Seattle and was founded in the fall of 2014 the founders of
this company are Jesen Harris and Kieran Snyder they created Textio after working on
productivity tools at Microsoft, the idea of creating Textio according to co-founder Kieran
Snyder was that Jensen Harris had an idea about a predictive text, Their motivation stemmed
from recognizing the subtle yet impactful biases embedded in language, affecting hiring
practices and perpetuating inequalities in employment opportunities at that time they had
found patterns in documents they had performed well, they make it possible for how your
document would perform before you published it and that is how Textio was born.
As the first test, they wrote a birthday post. In this small business were seven full-time
employees and also their first intern. They also recently launched Textio Talent, with the idea
of changing the way writers write their job listings to get more qualified and diverse people to
apply, it also promises that artificial intelligence to speed up the writing process and help
business users turn notes into blocks of fully developed text automatically. To be more
familiar with this platform we can say that Textio's platform predicts how the user's writing
will complete, suggests changes, and writes alongside the user to make the text more neutral.
Textio operates by using a continuous data-fueled learning loop, which provides the platform
learning skills to develop more faster and efficiently depending on the number of people who
write. Every document written in Textio gets a score indicating how efficient the writing is
for recruiting qualified applicants. Besides that, it also offers a Bias Meter which helps to
identify and mitigate gender bias in hiring content making an unconscious bias visible as the
user writes in real-time, highlighting phrases that unintentionally skew gender balance, often
going unnoticed in the human eye.
The interaction with Textio involves a user-friendly and diverse interface that allows users to
check their documents, whether it is a job description, email, or any form of written content.
Overall Textio technological framework is purpose-built to provide a user-friendly
experience and ensures practicality, accessibility, and support in addressing biases within
language usage.
Textio addresses various cognitive biases prevalent in written communication, often in
contexts like job postings or professional content, these biases can include:
● Gender Bias: Textio can detect language that can favor one gender over another in job
descriptions or other written content, certain words can occasionally associate with
one gender and can discourage applicants of the opposite gender, thus Textio suggests
neutral alternatives to ensure a more balanced appeal.
● Ageism: job postings often indicate preferences for certain groups of a specific age,
Textio manages to neutralize such language, ensuring that attracts diverse age groups,
and generates a more inclusive hiring process.
● Accessibility Bias: Biases can also include language that excludes individuals with
disabilities. Textio helps identify and modify these languages that can present a
barrier for candidates with disabilities, making a more inclusive hiring process.
Textios´s role in reducing biases is indispensable by creating more inclusive and welcoming
content, contributing to a diverse and equitable environment. Textio promotes fairness and
diversity in various professional contexts.
Textio stands out among pre-existing language correction tools due to its unique features and
focus on bias reduction.
This platform mainly focuses on grammar spelling and corrections, offering real-time
analysis of language, specifically targeting unconscious biases in contexts like job postings
empowering users to make informed adjustments in the moment. While it checks the
grammar and spelling tools, it's designed specifically to detect and mitigate biases in written
content, the algorithm is finely adjusted to recognize language patterns that unintentionally
exclude some biases, suggesting to enhance inclusivity.
Moreover, Textio uses an advanced machine-learning algorithm and predictive analysis to
improve the suggestions to the writer, the algorithm learns from a huge amount of
information to refine its recommendations, adapting to evolving language according to the
writer's ideal. This advanced characteristic makes Textio adapt more efficiently and
distinguishes it as a dynamic tool for bias reduction. Textio´s integrations with different
writing environments, such as word processors and online platforms, make it more userfriendly, allowing a smooth writing experience, the platform innovation prevails in its realtime analysis, reduction of biased content, and machine learning capabilities, for these
features distinguish it from others editing tools. Therefore Textio stands out as a solution to
combat biases in written communication.
Co-founder Snyder alleges that the platforms feature the company started building a few
years back is becoming more and more important to its writing experience, she said that the
biggest impact of the rise of technology (on Textio and everyone else) is not just the advance
in tech but also reinvented market expectations. She also remarks that other AI platforms
besides their flaws and biases, are important because show the potential to generate AI for
millions of people, thus making people expect experiences that feel out of this world and
magical because they have felt what those experiences are with the generated AI.
As for companies' impact, Textio also witnessed a significant shift in the diversity of
applicants, for instance, they have seen an increase of 25% in female applicants for technical
roles and engineering roles, this implementation helps to increase diversity to a richer talent
group, allowing companies to have a wider range in reaching for skills and perspective.
As we have read before Textio aids organizations in job postings to reduce biased language,
with companies attracting candidates from diverse backgrounds who might have felt
excluded, this lets companies find the best-suited candidates based on qualifications and
skills. By actively addressing biases in language, Textio aids in reducing unconscious biases
that can interfere with decision-making processes. Job posting and professional
communication are set with inclusivity in mind opening a door for a workplace more
inclusive. The companies witnessing the impact in the applicant pool after implementing
Textio in the process highlight the improvement in organizational dynamics contributing to a
more equitable and inclusive professional group that benefits society at large.
Using morphological analysis to enhance Textio involves a detailed examination of potential
improvements, the platform algorithm can improve by gathering more comprehensive and
diverse datasets that are specific to different regions and cultural contexts, and by improving
its algorithm can easily identify biases that are inherent in local language use. This iterative
process would let Textio learn and adapt to specific cultural and regional biases.
Textio can expand its capabilities beyond job postings to implement a wider range of
communication domains such as marketing content, and educational materials. By analyzing
biases Textio can help create more inclusive and respectful communication in diverse fields.
To sum up, morphological analysis suggests that Textio involves a deep understanding of
different aspects of biases, with a strategic expansion into various communication domains,
taking into account the challenges offer a greater inclusivity and impact across diverse
contexts are substantial.
Sources:
● I have used generated AI to help me complete the specific information about the
company Textio, along with the specific mechanism of work and framework they use,
etc.
● I collected information from the company's original platform about the impact, work,
implementation methods, and specific impact on society and other companies, among
the rest of the information provided to complete this essay.