Accountability can save lives
A Call for Code for Racial Justice solution that captures all viewpoints at the scene of a police report
No matter the situation, all viewpoints matter. As can be seen over the years, with a particular focus on 2020, having a variety of perspectives that are not only captured, but utilized at the scene of a potential crime is critical to the livelihood of so many people that are falsely accused. In the wake of George Floyd, Ahmaud Arbery, Breonna Taylor, and too many other tragedies that have unjustly occurred, it’s critical that there is a marketplace of vantage points that are covering the incident, so no one voice can unfairly overshadow another.
Accountability is achieved through transparency, and as Call for Code for Racial Justice demonstrates, transparency can be achieved through technology. One solution that is leading the charge in diminishing police report bias through data is Incident Accuracy Reporting System (IARS). This solution comes from a group of problem solvers inspired by the prospects of mitigating inaccurate and systemically biased information in police reports by leveraging IBM services to increase the level of transparent and accurate data available to assess police behavioral infractions.
The team is comprised of ten individuals: Abiola Asojo, Brandon Kravitz, Kalonji Bankole, Laura Bennett, Tunde Olokodana, Osai Osaigbovo, Lucia Ramos, Debra Scott, Shalisha Witherspoon, and Shonda Witherspoon. Call for Code Digest was able to catch up with the group to learn about their inspiration behind taking action on Call for Code for Racial Justice and building IARS:
What was your motivation for getting involved in Call for Code for Racial Justice?
Shalisha Witherspoon: With the spotlight on racial injustice and systemic racism in America highlighted by the repeated killings of unarmed black victims such as George Floyd and Breonna Taylor, both at the hands of law enforcement, I and countless others in my community felt a sense of helplessness as to what could be done to end this. So, when Call for Code for Racial Justice was announced by IBM, I didn’t hesitate to jump at the chance to contribute to something that could help end systemic racism, and transform my helplessness into action. Seeing so many diverse IBMers from all over the world take on the call to action was truly inspiring, and kept me motivated to make a difference in my community.
Why is racial injustice an issue that can be addressed by the tech community and why is now the time to do so?
Shonda Witherspoon: Tech has enabled incredible solutions across a variety of industries as well as many of the world’s top problems — the swift response to adapt to the pandemic comes to mind. However, systemic racism and all the issues inherited from it have existed for far longer, but has historically been out of the spotlight. With multiple tools at our disposal, such as data analysis and machine learning, AI, and even blockchain, we proved that there are tools readily available today to address many areas of racial injustice that exist. I feel it’s important for others in the tech community to take advantage of the momentum from last summer’s reckoning with racial injustice issues and continue to find tools we have today to solve issues that were long overdue yesterday.
Who can you see benefiting from your solution and how?
Lucia Ramos: First of all, our solution enables civilians (victim/witnesses) to contribute statements/evidence related to specific police incident reports, with the ability to check for inconsistencies and create a tamper-proof record with all accounts of the incident. This means that victims of racial injustice will have a voice, and be able to upload evidence to our system in an effort to have it analyzed. Our solution can also help police officers and detectives to have all the evidence needed to understand the situation and take appropriate action. So again, our system can help victims, witnesses and the justice system to have a 360 view of an incident and enable accountability.
What would you say to fellow technologists around the world who may be interested in contributing to CFCFRJ?
Shalisha Witherspoon: I would share with them how rewarding it is to contribute to something that could change the lives of countless people in a positive way. There’s still so much work that needs to be done for each solution to realize its full potential, and any amount of help would make it one step closer to achieving that. Hopefully fellow technologists around the world can see the impact that CFCFRJ brings in, helping make an end to systemic racism and injustice, and realize it’s never too late to join the call to action — or Call for Code!
Debra Scott: From the start, the efforts behind our solution benefited from having global team member participation, which brought real value and ideas. Global technologists would have an opportunity to give back to a global community that extends far beyond making a difference locally. It’s also a rewarding opportunity to build new skills and bring unique experiences and perspectives together that will help in creating a robust solution.
Are there any key learnings you have had from developing the solution to this point?
Tunde Olokodana: The biggest lesson for me is the power of unity, both at the micro and macro levels, as well as the beauty of diversity. For example, we are a cross-functional team that cuts across races and geographies, and we were all united and determined to defeat racial injustice through the power of technology. I now have a better appreciation for diversity than I ever did. Besides this, I was exposed to some technologies I had little knowledge about such as blockchain and user interface design. I also learned about an efficient way of collaborating virtually, since there wasn’t any face-to-face interaction with any member of the team throughout the course of the project.
Which components of the solution do you think developers can help in further improving your solution
Osai Osaigbovo: Developers can further build on our solution through the following suggestions:
- Develop a security (Authentication) model for victim/witnesses using the application
- Develop a mobile app version of the solution
- Embed a search capability to filter uploaded media by type
- At the moment videos and/or audio is uploaded, developers can add the ability to upload photos to the witness page and then use Visual Recognition/ OCR software to extract information from it — for example, a car number.
- Surface the machine learning code as an API using IBM Watson Machine Learning or Flask API. This allows the UI application to be decoupled from the other components of the application. Also, the ML component can then be consumed by a mobile, web or desktop app.
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