TL;DR: Shut up and show me the map.
Humanity is reaching an inflection point in terms of its technological development. At the same time, we are reevaluating our place on Earth and rethinking how to build a fairer society. Can artificial intelligence (AI, machine learning, statistical learning or however you want to call it) serve to tackle societal and environmental challenges? Yes, absolutely. In fact, the same algorithms used to recommend products on an e-commerce website, or choose the ads shown to you, can be applied to solve real human problems. All data scientists, from aspiring ones to researchers, have the opportunity (and even the responsibility) to take advantage of the current data revolution to improve our world.
But let’s be clear, this is a complex endeavour, which requires cross-disciplinary and multi-sector collaborations involving governments, NGOs, private organizations and academia. Otherwise, it will be too easy to fall for the AI hype instead of understanding it as a tool to augment our abilities. Only solutions backed up by research and deep understanding of the respective problem domain will be robust (remember the scientific method) and effective in the long term.
But is academic research the only way to use AI for good? How can we as data scientists help? My initial impulse was to browse the web and look for existing initiatives. This browsing-the-web exercise got a bit more serious than initially planned (it’s cold outside anyways). Turns out, there are many caring people and great initiatives related, in some or other way, to the Data Science and AI for good movement. This is very encouraging, but there is still so much to be done!
Mind mapping the AI for good movement
Without further ado, the Data Science and AI for good mind map can be found here. On the right panel, you will find the map itself (choose the Map tab) and on the left the content associated with each topic or node. Open a node by double clicking it. The Live tab provides a less cluttered view of the map so you might find it easier to navigate.
You will find useful resources regardless of what stage of your career you are in or the amount of time you are willing to commit. For instance, go to the root node if you are just looking for inspiration and interesting reads. The child nodes (the ones in dark green color) cover the following topics:
- challenges and competitions : contains information about individual projects, hackathons and data challenges you could work on during your weekends (the best way to improve your data skills!),
- bootcamps and fellowships : resources for students eager to learn data science while working on projects with social impact. These internships last 2-3 months in general,
- events : a section with links to some relevant academic conferences and meetups,
- initiatives : this node lists initiatives by tech companies. Its child nodes point to communities, multi-sector networks and other efforts that aim to address the world’s challenges with AI,
- organizations : leads to institutions and organizations. It might be interesting to those looking for volunteering or consulting opportunities,
- entrepreneurship : this node points to grant opportunities for AI/tech startups working on social good or pro-environmental causes.
Now that you know the different ways you can serve the common good with data and technology, what are you waiting for? I’ve picked a couple of projects for the coming months. If you know of any resources that are missing and deserve to be added, please reach out via email or by using the issues section of the corresponding GitHub repository.
PS: A similar TW+TM web application is being prepared with a larger mind map exploring the landscape of AI and data science, full of free and valuable resources. Stay tuned!