Couple heuristics from someone that works in the space. Is the problem scoped well? The deliverable should be solving a specific problem. ML to detect credit c

Couple heuristics from someone that works in the space. Is the problem scoped well? The deliverable should be solving a specific problem. ML to detect credit card fraud? Yes. Synthesizing research papers to get actionable insights. No. Define a research insight? Is there large amounts of training data that exists for the problem at hand? The goal is to train a computer to do a task, you need concrete inputs and outputs. Is it a “wicked” problem? Dynamic problems where attempting to make predictions can impact the outcome are notoriously difficult. People problems like “predicting turnover” often fall under this category. Personally I’d take some time to learn about ML evaluation metrics and ask how their model is performing? If the model already exists, it needs to be compared to a baseline that is tied to a business deliverable ie how accurate does it need to be to be useful to customers? To the data scientists on HN, I realize there’s a lot of exceptions to what I just suggested. These are not meant to be absolute laws but should act as a useful rule of thumb.