Inspiration

We were inspired by the dialogue and panels held at Capgemini's Social Good Hackathon, especially discussions about how bias influences recruitment and how specific groups are underrepresented and marginalized in the tech industry. Bias operates at many levels - from the primacy effect, where first impressions can leave a lasting impact - to how a lack of education, professional experience, or specific qualities can prevent one from acquiring jobs despite clear, demonstrated skills.

Through a minimalist, project-based platform where candidates don't have to worry about listing their education or professional experience, we aim to level the playing field by allowing them to showcase what is relevant to secure entry-level and project-based positions. This mitigates the implicit and explicit bias exhibited by recruiters and employers since their immediate perception of a candidate would be the work they've already developed and how they contributed, which serves as a valuable jumping off point towards recruiting these candidates.

We aimed to create a proof of concept interface to demonstrate the viability of a full product, there is much value in an accessible and streamlined user experience that is dedicated to users who have traditionally been left out of tech fields - such as individuals without college degrees, people with invisible or visible disabilities, the formerly incarcerated, veterans, and even people switching careers.

What it does

Users are able to craft portfolios of work where they can provide their project descriptions, screenshots, and links to demos and source code. The Watson Natural Language Understanding API parses their portfolio for keywords on their experience and matches it with potential jobs.

Employers can create accounts and create job postings, these job postings will be matched to users and the two will be able to contact one another. Only when an employer expresses interest in a candidate will their contact information be given, and communications established. Recruiters and employers will be directly able to see the types of projects and skills exhibited by the person, which allows for quicker recruitment with less bias, as these people are being judged by the quality and effort of their work.

SteppingStone is not a replacement for established platforms like LinkedIn or Glassdoor, but a supplement to allow underrepresented groups to gain confidence and get a foot in the door so they have a chance of completing projects and securing positions, and be rewarded for the work they put in instead of being the victims of bias and structurally unjust systems.

How I built it

We built it in React with the Watson Natural Language Understanding API processing user project and job descriptions to generate keywords.

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