More Than "Means to an End": Supporting Reasoning with Transparently Designed AI Data Science Processes

1. 1Design AI data science systems with transparency in mind
2. 2Implement generative AI tools that support user evaluation of alternative approaches
3. 3Develop processes that enable users to reformulate problems and explore different solutions
4. 4Integrate transparent AI data science processes into high-stakes domains to support critical decision-making

Data scientists and AI engineers benefit from transparent AI data science processes as they enable the evaluation of alternative approaches and reformulation of problems, leading to more effective solutions

💡 Transparent AI data science processes are crucial for supporting reasoning and problem-solving in complex domains

🤖 Transparent AI data science processes enable effective problem-solving in high-stakes domains