| layout | title | abstract | author | date | ipynb | venue | transition | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
talk |
Harnessing Data Science for Africa's Socio-Economic Development |
|
2023-05-10 |
true |
DSA, Kigali, Rwanda |
None |
\include{_ai/includes/henry-ford-intro.md}
\notes{In Greek mythology, Panacea was the goddess of the universal remedy. One consequence of the pervasive potential of AI is that it is positioned, like Panacea, as the purveyor of a universal solution. Whether it is overcoming industry’s productivity challenges, or as a salve for strained public sector services, or a remedy for pressing global challenges in sustainable development, AI is presented as an elixir to resolve society’s problems.
In practice, translation of AI technology into practical benefit is not simple. Moreover, a growing body of evidence shows that risks and benefits from AI innovations are unevenly distributed across society.
When carelessly deployed, AI risks exacerbating existing social and economic inequalities.}
\include{_ai/includes/evolved-relationship-ai.md}
\include{_ai/includes/cuneiform.md} \include{_books/includes/the-future-of-professions.md}
\notes{A question, to what extent do these challenges vary for the African continent? Many of the skills that we are considering will be undermined by ChatGPT aand equivalent technologies are actually skills that are lacking on the continent, so does this provide an opportunity for DSA?}
\include{_data-science/includes/digital-revolution-and-inequality.md} \include{_policy/includes/coin-pusher.md}
\include{_ml/includes/rs-report-machine-learning.md} \include{_ml/includes/rs-report-mori-poll-art.md} \include{_ml/includes/chat-gpt-mercutio.md}
\include{_ai/includes/p-n-fairness.md} \include{_books/includes/a-question-of-trust.md} \include{_ai/includes/naca-proving.md}
\subsection{AI Proving Grounds}
\slides{* Understand the nature of the tool.
- What is the potential, what are the pitfalls?
- Build societal AI capability.}
\notes{We need mechanisms to rapidly understand the capabilities of these new tools, what is the potential of the technology, and what are the pitfalls? With this in mind we can build a societal AI capability that means understanding is pervasive.}
\notes{Innovating to serve science and society requires a pipeline of interventions. As well as advances in the technical capabilities of AI technologies, engineering knowhow is required to safely deploy and monitor those solutions in practice. Regulatory frameworks need to adapt to ensure trustworthy use of these technologies. Aligning technology development with public interests demands effective stakeholder engagement to bring diverse voices and expertise into technology design.}
\notes{Building this pipeline will take coordination across research, engineering, policy and practice. It also requires action to address the digital divides that influence who benefits from AI advances. These include digital divides within the socioeconomic strata that need to be overcome – AI must not exacerbate existing equalities or create new ones. In addressing these challenges, we can be hindered by divides that exist between traditional academic disciplines. We need to develop common understanding of the problems and a shared knowledge of possible solutions.}
\notes{\subsection{Making AI equitable}}
\include{_data-science/includes/data-science-africa.md}
\thanks
\references