Quiz 5 - Question 1

Throughout this course you have considered the importance of value alignment when identifying solutions to address in your community. Read the case study below and identify the moral values represented.

YobeReads: An AI-powered literacy initiative

YobeReads is a non-profit initiative dedicated to improving literacy levels among primary school-aged children in remote and underserved communities across Yobe State, Nigeria. The core of YobeReads is an interactive, voice-based conversational agent powered by a custom large language model (LLM), trained extensively on local dialects and educational content. Children access the platform via low-cost mobile devices, allowing them to practice reading and comprehension through personalized lessons and storytelling. The LLM adapts its teaching methods to each child's learning pace.

A key aspect of YobeReads' design is its deep integration with local community structures. Extensive consultations were held with local elders, parents, and religious leaders to understand cultural nuances. The content developed for the LLM explicitly emphasizes local fables and proverbs, reinforcing shared heritage. Furthermore, the platform encourages collaborative learning, with children often using a single device in small groups, prompting discussions and peer-to-peer support. The success is measured not just by individual literacy scores, but also by the strengthened bonds within families and communities. Every interaction fosters understanding and positive relationships.

The initiative strongly advocates for equipping every child, regardless of their background, with the fundamental right to education. It believes that access to literacy is a pathway to individual empowerment, enabling children to make informed decisions about their lives and contribute meaningfully to their society.

Based on the "YobeReads: An AI-powered literacy initiative" case study, which of the following moral values drawn from both the European and North American tradition, and Ubuntu, are clearly exemplified in the design and implementation of the platform?

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Google DeepMind: Build Your Own Small Language Model

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Google DeepMind: Build Your Own Small Language Model

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In this module, you will move beyond the manual method and explore how n-grams can be used to tokenize data. You will investigate how probabilities can be calculated to begin identifying language patterns. You will then build your own n-gram model using a small dataset and examine its limitations. Furthermore, you will consider the process researchers undertake when approaching real-world problems through the lens of Google DeepMind’s AlphaFold project. Finally, you will reflect on your own values and those of your community, as well as the role AI systems play in making decisions that involve ethical choices.

Exercise 1: N-grams Exercise 2: Lab: Experiment with N-grams Exercise 3: The limitations of n-grams Exercise 4: AlphaFold: The power of machine learning Exercise 5: Weighing values: Culture and ethics in the trolley problem Exercise 6: Applying a local ethical lens to the trolley problem Exercise 7: Quiz 2 - Question 1 Exercise 8: Quiz 2 - Question 2

In this module, you will experiment with more sophisticated transformer models and evaluate how they perform in comparison to n-gram models. You will take a deeper dive into the anatomy of language models and their core components. You will continue reflecting on the role that values play in guiding which technical problems you choose to solve. Specifically, you will consider the Ubuntu moral system and compare its characteristics with moral values popular in Europe and North America. Finally, you will design a values framework for guiding LLM development in your local community.

Exercise 1: Lab: Compare N-Gram Models and Transformer Language Models Exercise 2: Core aspects of Ubuntu Exercise 3: Develop a local values framework Exercise 4: Anatomy of a language model Exercise 5: What does it mean to train a model?Exercise 6: Quiz 3 - Question 1 Exercise 7: Quiz 3 - Question 2

In this module, you will consider the specific benefits that transformer LLMs can bring about for different sectors in your local context. You will then explore what makes a good problem statement before developing your own problem statement for a challenge around language models that you have identified in your community.

Exercise 1: Anticipating benefits Exercise 2: Challenge: Develop your problem statement Exercise 3: Quiz 5 - Question 1

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Exercise 4: Quiz 5 - Question 2

In this module, you will have the opportunity to consult additional resources and further reading to investigate the topics you have covered in more detail. Finally, you will consider your next steps and how you can build on what you have learned in the course.

Exercise 1: Summary Exercise 2: Looking forward Exercise 3: Additional resources and further reading Exercise 4: Feedback Exercise 5: Glossary