Industry is mainly driven by profit. Software in industry is developed with a focus on an individual and their specific wants. To make money software has to be developed with appropriate UIs and functionality that allows an individual to do something they would ordinarily not do if they had no access to the software. The motivations for industry thus tend to be different from those in academia. Machine learning enables even greater power in the hands of the individual, and presents new paradigms in how the software is developed and evaluated, aspects of how a software project is planned and executed, how the project is launched and maintained in production and specific issues around bias, fairness and transparency. In this talk I will touch on each of these issues with a perspective from a large non-profit organisation and a large multi-national for profit organisation.
Ernest Mwebaze obtained his doctorate in machine learning from the University of Groningen. He has over 10 years experience in academia where he was part of the faculty at the School of Computing and Informatics Technology of Makerere University in Uganda. At Makerere University he co-led the Makerere Artificial Intelligence research lab and headed several research projects. He has worked with the UN at the Pulse Lab Kampala and with Google AI, in Accra, Ghana. His current portfolio includes being a research director at Sunbird AI, an NGO focused on productization of AI for social good.