The author is exploring the importance of responsible AI and its context. They discuss four key issues: myths about AI, biased AI, unknowable AI, and inappropriate AI. The author argues that these concerns are often overlooked or downplayed, but they can have significant consequences, such as perpetuating bias, denying individuals their rights, and infringing on personal freedoms. To address these issues, the author emphasizes the need for context in AI development and deployment, including transparency, fairness, accountability, and public trust. They also highlight the limitations of AI without context, which can lead to narrow focus, subpar predictions, and a lack of transparency. The author suggests that graphs are a natural fit for adding context to AI systems, enabling them to make more informed decisions and improve their performance. Ultimately, responsible AI requires a nuanced understanding of its limitations and the importance of human values in guiding its development and deployment.