In many fast-growing startups, there are new team members joining all the time. Yet often times there is insufficient time for the rest of the team to get to know new team members due to occupied schedule. Living in a globalized, interconnected world, everyone has a unique story and background, as well as the way they would like to be perceived. Unfortunately, channels and platforms are often lacking when it comes to communicate the way individuals would like to be perceived, thus it often leads to misunderstanding, frustration and offense, undermining the trust and respect a team could potentially cultivate from the get-go.

What it does

This methodology is to reinvent new joiners' onboarding process. Simply by collecting data from new joiners in the way he would like to be perceived, as well as analyzing his communication style through Crystal API, the rest of the team can get to know new joiners at the time of their convenience through a simple chatbot, which includes one's conflict resolution style, communication style, as well as new joiners' personal story that is beyond a linkedin public profile.

By so doing, it gives new joiners a voice to communicate his/her preference, as well as respecting and empowering the way an individual would like to be perceived as ( since one's nationality and skin color often does not do one's justice in illustrating one's unique background).

How I built it

First we created a detail custom questionnaire/assessments that allow new joiners to share their preferences. Then through Crystal API, an analysis of one's communication style is generated. Afterwards, by using machine learning and natural language processing, other team members can utilize a chatbot to learn about new joiners in time of their convenience.

Challenges we ran into

It is challenging and will continue to be a challenge to integrate machine learning model to our idea and accurately analyzing data from user's input.

Accomplishments that I'm proud of

Our team received honorable mentions from judges as one of the most 'out-of-the-box' solutions presented and was being recognized as being innovative in tackling the challenge from a very different angle. We also delivered and made a MVP that illustrates our concepts and ideas that would help others to understand.

What I learned

Despite the existence of bias in Artificial Intelligence, I think what developers and UX designers need to be more aware of is not just the existing data bias but how data is used in adding value to end-users and user experience. Sometimes user experience is not related to data bias at all , given the fact that there are many other cues, such as context, situation, relationships that affect the message of the text, which are, many times, subtle and hidden from messaging platfom or other media outlets.

What's next for In Their Shoes

This is one of the use cases Machine Learning and AI can be applied in empowering teams. This methodology can be applied to fast-growing start ups, international conferences/ charities that require high level of collaboration. For future development, it could be integrated into slack for streamlined, centralized communication for teams.

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