At ICRA 2022, Benjamin Rosman delivered a keynote presentation on an organization he co-founded called "Deep learning Indaba". Deep Learning Indaba is based in South Africa and their mission is to strengthen Artificial Intelligence and Machine Learning communities across Africa. They host yearly meetups in varying countries on the continent, as well as promote grass roots communities in each of the countries to run their own local events. An indaba is a Zulu word for a gathering or meeting. Such meetings are held throughout southern Africa, and serve several functions: to listen and share news of members of the community, to discuss common interests and issues facing the community, and to give advice and coach others.

Amazon applied science manager Dr. Nashlie Sephus has lived in New York City, Atlanta, Silicon Valley, and Seoul while pursuing her education and work in machine learning. She knows the look of a community that's thriving from technology and innovation, but she didn't see that growth happening in her hometown of Jackson, Mississippi. That's why last week she concluded an 18-month process by signing contracts to secure 12 acres of land that will be home to the Jackson Tech District. The Bean Path, a nonprofit organization created by Sephus, will operate a maker and innovation space on the land. There will also be restaurants and residential lofts spread across eight buildings, all located near the historically Black Jackson State University.

No technology comes into being by accident, and inequalities are baked in from the outset. Algorithmic bias, for example, reflects the biases and prejudices of its creators. Embedded inequity is rearing its ugly head in everything from video doorbells to driverless cars to smart devices to tech in health care and criminal justice. The long-term implications are far-reaching and scary. Big Tech is belatedly waking up to this reality, as seen from the likes of IBM and Amazon announcing that they're pausing facial recognition deployment because it can enhance bias in police surveillance.