Enabling Aging Workers to Excel in the Modern Job Market
A machine learning & natural language processing browser plug-in that enables aging workers to take control of their futures.
Our Vision
A world where the job-hunting process pays attention to the specific needs of aging workers and an empowered workplace that effectively manages the impacts of ageism.
Early Adopters:
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Aging workers between the ages of 40 - 60
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Retired workers 60+ looking to re-enter the workforce
Features
Sage is a seamlessly integrated browser plug-in, backed with a powerful natural language processing ML model.
Age Unfriendly
NLP model can detect ageist language in a site and inform the user. This insight enables aging workers to adjust their actions accordingly. For example, when layered into LinkedIn, this can help detect ageist job posts which discriminate against aging workers.
Help Buttons
The plug-in allows aging workers to ask for help when navigating a site. Pop-ups assist users on how to proceed with a given task online.
Speech-to-Text
Users may apply to jobs using their voice for speech to text form fill. This is useful for users who are not digitally savvy or may have difficulty typing.
Font Size,
Color Contrast Adjuster
Adjust font/color contrast due to symptoms of aging. This allows for a pleasant user experience when navigating online sites.
Declutter
Reduce the amount of images and text on a site by using the declutter feature. This allows for better focus by creating a page that is simpler and easier to read.
How Sage Works
Flag Ageist Language
Input Text
(From Job Post)
The role requires a friendly, energetic, tech enthusiast who understands our values and can make sure they are shining in every interaction with our potential clients. In other words, an absolute winning mentality. You're also a digital native with a keen interest in pop culture.
Modeling
Output: Flagged Text
The role requires a friendly, energetic, tech enthusiast who understands our values and can make sure they are shining in every interaction with our potential clients. In other words, an absolute winning mentality. You’re also a digital native with a keen interest in pop culture.
Age Bias Tracker
The age bias tracker shows the number of age-unfriendly terms found on the job post page. A scroll bar is located in the section with the terms so that no matter how long the list of terms is, it can be kept within the same vertical distance. These terms are determined by the NLP model which detects age unfriendly language. This insight enables users and/or employers to detect job posts with ageist language.
Declutter
To offer a focused reading view for users, declutter page removes all unnecessary elements except for the job title, features, apply and save buttons, and description. The user is able to reduce the amount of images and text on the LinkedIn page and allows the job description to take up the entire page to promote focus. The feature is included with the goal of reducing the cognitive load of aging users.
Speak-to-Fill Out Form
When filling out a job application form, the user can open the speak to fill form tool, which prompts a movable popup with a microphone button to turn on/off voice detection. Instructions on how to use the feature are included below the button, stating “Click the text box you want to fill out and speak”. This feature helps those with hand issues, carpal tunnel syndrome, or who simply want to fill out forms using their voice.
Read Page Text Outloud
On a webpage with text, the user can open the read page text out loud tool, which prompts a movable popup with a play/pause button, a 10-second forward button and a 10-second back button, and varying speed buttons. Instructions on how to use the feature are included below the button, stating “Click and drag to select the text you want to read out loud”. This feature aims to help those with vision problems or lower visual acuity to hear the text on a webpage, and not have to rely solely on their vision.
Help Center
The plugin allows aging workers to access help when navigating a site. The questions featured in the help center include “How do I use this plugin?”, “How safe is my data?”, “Give us your feedback”, and “Learn how we detect potential age bias”. These questions were determined based on which areas our team members thought it would be most useful to have information on and from what was heard in feedback throughout the design process.
Our Story
Led by the belief that age should never limit someone's ability to contribute meaningful work
Our all-women founding team at Sage are master's students studying Information Management & Systems at UC Berkeley. We are passionate about making meaningful change in the world using technology and deeply believe that anyone, regardless of age, can make valuable contributions in the workplace.