We frequently highlight how data science and machine learning approaches may help your organization or business achieve its financial objectives. However, these algorithms and projects aren’t only about generating profits but using artificial intelligence models to do social good.
Developing innovative applications that use AI’s predictive capability to assist society and underserved populations is a valuable effort for Data Scientists who want to increase the world’s beneficial effect of machine learning.
We’ve picked up some of our favorite projects from organizations that are building cool things to develop solutions to address social problems, inequality, or wildlife research and conservation.
Data Science for Social Good
Their mission is to foster the use of data science for positive social impact. By training and supporting a new generation of data scientists, providing direct support to nonprofits, and developing tools that ensure data science and artificial intelligence are used to positively and equitably benefit people all over the world.
We list the most interesting projects for social good.
1. Aequitas
It’s an open-source bias audit toolkit for machine learning and artificial intelligence developers, analysts, and policymakers to audit machine learning models for discrimination and bias, and make informed and equitable decisions around developing and deploying predictive risk assessment tools.
Thus, You can access the tool at the following link: http://aequitas.dssg.io
2. Triage
It’s an open-source machine learning toolkit to help data scientists, machine learning developers, and analysts quickly prototype, build and evaluate end-to-end predictive risk modeling systems for public policy and social good problems.
Triage lets you focus on the problem you’re solving and guides you through design choices you need to make at each step of the machine learning pipeline.
Hence, you can access the tool at the following link https://dssg.github.io/triage/dirtyduck/
DrivenData
DrivenData focuses on initiatives in sectors such as international development, health, education, research & conservation, and public services that combine data science with social impact.
Consequently, they provide access to data science capabilities for companies, as well as engage more data scientists in social problems where their expertise can make a difference.
Below you can find our favorite projects for social good using data science and machine learning.
1. Deon: An Ethics Checklist for Data Scientist
Ethics in data science, machine learning, and AI is becoming increasingly essential and it could be used to do social good. So, Deon’s mission is to further that discourse by providing tangible, actionable reminders to developers who have a say in how data science is done.
Deon is a command-line tool that allows you to easily add an ethics checklist to your data science projects. It supports creating a new, standalone checklist file or appending a checklist to an existing analysis in many common formats.
Thus, You can access the tool at the following link https://deon.drivendata.orghttps://deon.drivendata.org
2. Project Zamba
It’s a computer vision project for wildlife research and conservation. Also, it is an open-source Python package that identifies 23 animals in video data.
It was created at the end of 2017 when data scientists from more than 90 countries around the world drew on more than 300,000 video clips in a competition to build the best machine learning models for identifying wildlife from camera trap footage. Following the competition, the top-performing submission was packaged into an open-source software tool and made available for general use by researchers and conservationists.
You can access the web live application for the project at https://www.zambacloud.com
Also, you can follow the development of the project at Github https://github.com/drivendataorg/zamba
3. Concept To Clinic
This open-source project is an end-to-end application that allows radiologists to better interact with state-of-the-art AI as part of their diagnostic process.
In the Concept to Clinic challenge, hundreds of data scientists and engineers from around the world came together to build open-source tools to fight the world’s deadliest cancer. The prototype developed during the live challenge period between August 2017 and January 2018 focused on helping clinicians flag, assess, and report concerning nodules from CT scans.
You can access the project at the following link: https://concepttoclinic.drivendata.org/
Also, you can check the codebase at Github and follow the progress of the project. https://github.com/drivendataorg/concept-to-clinic
At Origo, we also believe that engineering solutions should have people and society’ well-fare in mind. That’s why we like to partner with NGOs and Non-Profits to deliver solutions with high impact.
For more information contact us at info@origo.ec