04-800-D AI & Emerging Economies
Location: Africa
Units: 12
Semester Offered: Fall
Course description
This contemporary course is set at the intersection of artificial intelligence and emerging economies. It will explore AI implementation and its impact on developing countries, including those on the African continent.
AI is becoming ubiquitous, touching upon all spheres of life: Health, Wealth, and Wisdom. An understanding of technical as well as societal/policy challenges (including, for example, congruence with UN SDGs) is important for professionals and future leaders in society. This course is cross-listed for collaborating with CMU-Pittsburgh, which has students hailing from many countries, thus providing a unique opportunity for interesting class discussions and global teamwork via projects. Key concepts via a diverse set of case studies will be presented and analyzed. The focus will be on critical and creative thinking and problem-solving using data and AI, particularly in resource-constrained environments. Relevance and creative uses of local data and domain knowledge will be illustrated. Opinions from other thought leaders via guest lectures will round out the content. The final syllabus will be informed by the instructor’s recent experience with a course around AI Grand Challenges for the CMU global audience. Many of the class projects therein touched upon emerging economy issues and that is where the idea for this course germinated! Also, the course will underscore the importance of better communication and consensus, a sine qua non for trust and access, among AI producers and AI consumers (a majority of whom are based in emerging economies).
Students will be encouraged and expected to critically evaluate progress in the field of AI as well as its applicability to various domains across the globe. The course will discuss issues relating to localization, bias, and explainability. Projects will build or analyze novel applications highlighting the triad of data, domain knowledge, and tools.
The unique course design offers students the opportunity to work in global project teams with CMU students from around the world (including the main campus) to gain a better understanding of different perspectives and approaches toward AI. This is expected to enhance learning outcomes and prepare participants for the multicultural, distributed workforce of the future. Class discussions are encouraged, especially following guest lectures, that will expand learning frontiers beyond the instructor’s background and experiences.
This is an opportunity not to be missed, so enroll in “AI and Emerging Economies” today to expand your horizons!
Learning objectives
This course enables experiential learning and global engagement. At the end of the course, students will be able to appreciate many “why” aspects of AI and Data.
AI and contemporary tools like ChatGPT, experiential learning, data, and a diverse set of case studies will help inculcate critical and creative thinking as well as novel problem-solving approaches. Students will work on practical projects that apply their newfound knowledge to real-world scenarios. By the end of the course, they will have a deep understanding of the opportunities and challenges of AI in emerging economies as well as the skills and experience necessary to work effectively in global teams. The course is multi-disciplinary and germane to budding technologists, entrepreneurs, and policy influencers.
Outcomes
Upon completing this course, students will be able to:
- Understand broadly the production and consumption of AI.
- Understand the role of digital public goods and public-private partnerships.
- Appreciate AI Grand Challenges and the “why” behind many frameworks.
- Analyze AI’s unique impact on developing countries. Students should be able to evaluate the potential impact of AI on emerging economies, including its role in job creation, economic growth, and social development.
- Evaluate the ethical considerations of AI in emerging economies. Students should be able to assess the ethical implications of AI in emerging economies, including issues related to privacy, bias, and transparency.
- Identify an interesting problem and develop an AI solution. Students should be able to form a global team and design and implement a simple AI-based solution to address a challenge faced by emerging economies, such as access to healthcare, education, and financial services.
- Communicate the benefits and risks of AI to a variety of stakeholders including policymakers, industry leaders, and community members. Students should be able to advocate for responsible AI practices in emerging economies.
- Understand the effect of low-resource environments on data and solutions.
Content details
Some illustrative references include:
- A Clever Strategy to Distribute COVID Aid - With Satellite Data (WIRED)
- Digital Agriculture for Small-Scale Producers: Challenges and Opportunities (Communications of the ACM)
- MOSIP and the general concept of Digital Public Goods and possible AI overlays
References from the instructor’s research/articles include:
- What is made in India AI? (Rediff.com)
- Artificial Intelligence's Grand Challenges: Past, Present, and Future (Spring 2021 Issue of AI Magazine)
- Includes commentary from six thought leaders including Francesca Rossi, AAAI President and Frank Chen of VC firm a16z
- Article has many relevant references which will also be summarized
Other references that touch upon AI and UN SDGs include:
Resources:
- Jupyter Notebook/Google Colab (for hands-on projects)
- Shared Google Sheets
Course format
- Zoom sessions primarily
- The instructor is normally based in Pittsburgh and is expected to travel briefly to Kigali in the Fall of 2023 to meet with students and other faculty
Prerequisites
Enthusiasm for learning, critical thinking, and openness to working on projects in global teams.