USIU-Africa holds an International Data Science Summit webinar
By Gabriel Okello
While AI becomes more and more a part and parcel of our day to day lives, how best can we integrate it into our functions, what is its role in data governance and are you ready for AI disruptions? USIU–Africa organized an International Data Science Summit on February 26 –27 with the aim of exploring inclusivity, ethical, and collaborative approaches in AI and data science development.
Facilitated by Dr. Gabriel Okello, this two-day webinar featured a variety of topics that kept participants engaged throughout the sessions. The topics centered around AI, ethics, and data governance including women’s participation in AI policy, breaking language barriers through AI, and using AI in sectors like finance and NLP. The key areas of discussions included the importance for responsible innovation, ethical AI practices, and the collaboration between academia and industry.
On the first day of the webinar, participants were enriched with relevant knowledge on AI & Ethics as well as data governance. John Matogo from IBM emphasized on the need for responsible innovation and explainability in AI, while Johnson Muthi from Jubilee Holdings highlighted the importance of governance in ensuring successful AI/ML projects.
The webinar included panel sessions where the panelists discussed bridging academia and industry, focusing on infrastructure and strategic AI adoption. Furthermore, the sessions discussed inclusion of women in AI and advocated for more women’s representation in AI policy creation and ethical AI development.
The key areas of discussion on the second day covered AI in Finance & NLP where experts discussed how AI can be used for financial forecasting and overcoming challenges in under-resourced languages. Dr. Lillian explored NLP development for African languages and addressed disinformation in NLP models. Additionally, the sessions deepened participants’ knowledge and understanding of social media engagement where they were taught and encouraged to use responsible networking techniques.
The knowledge was further enhanced through networking sessions where the lively participants engaged with speakers, and attended presentations.
This two-day training that concluded with a call to action for more inclusive, ethical, and collaborative approaches in AI and data science development, was enriching and insightful. Whether it is importance of responsible AI, transparency, and combating AI bias or the role of governance in improving AI project success or the use of AI for financial forecasting and overcoming challenges in under-resourced languages, this knowledge is quality and necessary for everyone in this modern world.
