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Capstone
PERVADE
Interactive decision support tools for data scientists
to help guide ethical decision-making.
The tool is about to launch!
Type
UX/UI
My Role
UX Designer/ Researcher & facilitator
Tools
Figma
Time
9-months ( Sep 2021-Present)
Problem
When it comes to the ethic in research, The problem which arises is most students and data science students wait till the very end right of their research to be like, oh wait is everything that I've done ethically? they need to pinpoint is where they starting to think about these ethical questions.
Solution
To help achieve this objective To find the best solution Pervade team wants to help the researcher to be thinking about it sooner, rather than later. And create the tool that allows them to sort of push that agenda a little bit. So It will help researchers to answer questions such as: Is this legal? Is this ethically defensive? It will also help identify considerations for writing, publishing, and presenting work.
Each Sprint's Goals
Sprint #1 Goal: Determine the primary needs of Data science students when implementing and understanding ethical practices in data science.
Sprint #2 Goal: Focus on Educators’ perspectives when creating 2nd design iteration in order to refine the developing prototype
Sprint #3 Goal: Develop a product structure and corresponding use cases; identify interaction patterns; refine new version of prototype that embeds client-provided decision tree
Sprint #4 Goal: Explore how gamification interfaces with the team-based approach. Create a team-based interface for friendly competition and classroom/educational settings; Implement shareability functions within an updated decision tree scenario as well as for certifications and credentials; Establish more clarity of navigation functions and buttons through tooltips and modals.
Focus
we want to create a tool that will assist researchers in determining the best practices for ethics and they're doing research.
Process
over the course of the project. our team completed tasks iteratively, in five 4-5 week " design sprints", where each sprint involves research and analysis, ideation, design, evaluation, and refinement.
DISCOVERY
Project Overview
PERVADE:
Pervasive Data Ethics for Computational Research project is in its final year. Based on their findings, the team hopes to build interactive decision support tools for data scientists to help guide ethical decision-making.
The project has produced a large amount of data on user expectations for big data reuse in various contexts, data science norms and controversies, and regulation, as well as guiding principles for researchers. They would now like to build tool that makes use of that data to help guide researcher and industry decision-making.
Competitive research
After we defined scope of the project, we started our competitive research into the existing products on the market, and here is the key takeaways:
Key Takeaways
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Large information Hub
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Information is overwhelming
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High-level process steps limited situational considerations and examples
Goals & Target User Behaviors:
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Increase user awareness of data ethics
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Encourage users to incorporate, engage with, and explore ethical considerations in the course of their work
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Facilitate continued engagement with data ethics by creating a platform that elevates the learning experience from a baseline “must fulfill” compliance activity to a rewarding and fun activity.
Considering both our target user and the business side of the project, we identified 3 goals for our user:
Business Goals:
for the business side of the project, we identified 2 goals:
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After we started our competitive research into the existing products on the market and defined the minimum viable product (“MVP”), we landed on an educational-learning platform with a focus on ethics. We are hoping that by creating this platform, data researchers can learn more about data ethics and incorporate it into their research. By giving researchers the ability to learn more about the subject and test that knowledge via scenario testing and interactive decision trees, we hope to build a workable tool that takes data ethics beyond a minimal, baseline approach and encourages them to explore data ethics on a deeper and more voluntary scale.
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The PERVADE project has produced a large amount of data on user expectations for big data reuse in various contexts, data science norms and controversies, and regulations, as well as guiding principles for researchers. They would now like to build a tool that makes use of that data to help guide researchers and industry decision-making.
Persona
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Given that ethics is a broad topic and PERVADE would like to highlight its importance across the entire field of data research, our primary user base is equally broad - data researchers, both academic and industry, on a global level. That said, one must walk before one can run, so as our design evolved, we specifically targeted three key user bases within the arena of US-based researchers:
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students just getting started with the field of data research and ethics,
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educators teaching those students about the field of data research and the role of ethics in that field, and
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researchers active in the field of data ethics (both industry and academic) who are looking to enhance their knowledge and mastery of data ethics.
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User Scenarios
Problem Statement
To come up with the extensive problem statement for our project, we implemented 2 scenarios:
A student who is forced to do CITI training for his/her class research project,
How might we design the tool that
makes this process interesting and engaging? How do they have a sense of progress through this process?
Scenario 1:
Scenario 2:
An ongoing researcher is picking up a new project next month,
How might we design the tool that
spin up new skills for the new datasets they’re working with?
Storyboard
To visualize the whole process for ourselves we decided to use a storyboard that help us visually predict and explore a user’s experience with a product.
Sketches
Sketches were developed by each team member based on the analyzed data gathered. The sketches were then reviewed and voted on via the Art Museum decision process.
Key Findings:
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Although some educators and professionals are interested in the implementation of ethics in data science, many view this as a “checklist” activity and are not eager to explore data ethics further than absolutely required.
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There is very little centralized information about data ethics that carries universal authority - PERVADE hopes to remedy this by becoming a centralized platform.
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Data scientists want all of the information collected and available for perusal without having to jump between platforms (video modules, academic journals, discussion boards, decision trees, etc.)
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Interviewing educators and researchers within the field of ethics noted that ethics implemented in class settings is conversational and not a primary focus every data lifecycle step.
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The needs of students, educators, and independent researchers differ and the tool must be flexible to allow for these differences
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Educators/Data Researchers want to see the roots of the decision tree and how changing scenarios would affect the decision tree
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Excessive gamification may lead to negative competition; Experts are intrigued by the idea of appropriate gamification
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Students want control over what information is visible to others - although they understand the need for instructors to see all of their work, they do not want this same transparency extended to their peers by default.
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Users want (and sometimes need, professionally) to share their progress and demonstrate mastery of the topics covered.
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Data Researchers have a wide array of needs and expertise when it comes to data ethics - creating an “all-in-one” tool that serves all users equally is a constant tension
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Solution Ideas & Product Concepts:
Potential Solutions:
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“Test My Scenario”:
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In order to allow users to see how ethics applies to their individual research, we created a scenario testing tool that gives insight into ethical compliance.
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To avoid this taking on the role of a “baseline,” we added additional screens to the results that demonstrate how the results would have changed with different inputs, as well as links to key considerations and further research.
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We also provided a download button for this feature to make the resource easily available and shareable in both a personal and professional context.
Flow
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“Video Modules”:
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This is one of the core functionalities of the tool and is designed to give users a clear, entertaining, and consistent means of learning about data ethics.
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Videos are organized into modules to allow for batch learning on specific topics, and the catalog of videos is searchable and filterable by critical metrics such as area of interest, industry, dataset, etc.
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“Interactive Decision Tree”:
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This serves as a collaborative, interactive, virtual workstation for users
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By giving users the ability to collaborate with their peers, users gain fun and interactive way to find unexpected interactions between different areas of interest and immediately share them with fellow users.
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“Badge System & Gamification”:
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Users can earn a number of badges for doing various tasks within the tool (watching videos, logging inconsistently, etc.).
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These add an element of fun to the tool and give users a natural point of connection with other users.
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Additionally, the badge tree allows users to see a natural progression of earning badges, encouraging them to dive deeper into the tool and learn more about data ethics.
Sketches for Gamification feature
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“Tailorable Interface: ”:
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To allow for differing needs between user groups, we created a number of customizable elements within the tool, including toggleable tooltips and gamification.
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This allowed us to create a single tool that met all needs as opposed to building separate tools for educators, students, and researchers.
Click!
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badge tree allows users to see a natural progression of earning badges, encouraging them to dive deeper into the tool and learn more about data ethics.
Click!
Challenges & Surprises Along the Way
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Challenges
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Creating a tool that is fun and engaging, but still carries weight in a linear, data-driven field is difficult.
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Convincing users that ethics is worth incorporating into their research as more than a “checklist item” is (also) difficult!
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Ensuring that the tool’s effectiveness wasn’t being compromised in an effort to cater to all user groups was a constant tension.
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Surprises
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Gamification and hard science can coexist!
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Data researchers care a surprising amount about design (color, dark mode, fonts, etc.)
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There is a surprising absence of competing products in the space - users were just glad PERVADE is developing the tool at all.