As the number of entities and organizations steering towards becoming social enterprises and businesses is increasing, technology can help advance the social impact agenda forward — with values and programs that align with their workforce’s social impact agendas. In this context, Microsoft Tech for Social Impact focuses on providing pertinent, affordable, and cutting-edge cloud solutions to help non-profits address the world’s biggest challenges and have an even more significant impact. When combined with other networks and computing technologies like 5G, the edge, satellite, and IoT devices, cloud technology can help unlock the potential of non-profits and international organizations that provide first-response relief, and deliver critical care and vital services.

In addition, Michael and Sadia engaged in a stimulating conversation about the role of artificial intelligence (AI) in society, and how it can be used ethically to empower the social sector in Bangladesh with tools, resources, and research while engaging with partners across all sectors to have the most significant impact. For example, in 2021, the Governor of Puerto Rico declared a state of emergency due to gender-based violence. With the support of Microsoft’s grants program and as a part of the AI for Humanitarian Action project, a chatbot was developed by Seguro Project and Coordinadora Paz para las Mujeres to offer a confidential and interactive interface for accessing support when it is needed. Available 24/7, the chatbot reduces the strain on support professionals so they can help more people in need, and provide victims of gender-based violence the power to regain control. Therefore, AI agents able to perform multiple tasks, chatbots, and the arrival of powerful image generators are exciting prospects for reducing inequalities in areas such as gender, education, and disaster risk response.

We are still in the early stages of raising awareness of how AI can support non-profits and humanitarian organizations amplify their impact and improve lives, especially in Bangladesh. Social media or search engine data that might be relevant for improving outcomes in health or education (which social network structures increase community resilience and social mobility), for example, are expensive or impossible to access. Even if it were possible, it is likely that they would provide a biased assessment of the situation, excluding or underrepresenting some vulnerable groups. In this context, Michael and Sadia talked about how data gaps could be overcome by investing in data collection, standardization, and integration. As Michael mentions