The field of AI research is moving towards a greater emphasis on ethics and anticipatory discourse, with a focus on understanding the potential consequences of emerging technologies. Recent studies have highlighted the importance of framing technologies as solutions to societal challenges, and the role of key opinion leaders in shaping public narratives around AI. There is also a growing recognition of the need for more nuanced evaluation metrics, such as Borda scores, to assess fairness and bias in AI systems. Furthermore, research has shown that public expectations and perceptions of AI development timelines vary significantly, underscoring the need for more effective communication and engagement with stakeholders. Noteworthy papers in this area include:

• The paper on Ethics Readiness of Technology, which proposes a framework for assessing the suitability of ethical approaches across different stages of technological development.
• The study on Measuring the right thing, which presents a two-step approach to justifying metrics in AI impact assessments.
• The research on A Consequentialist Critique of Binary Classification Evaluation Practices, which highlights the need for a consequentialist perspective in evaluating binary classification forecasts.