Discovery Project: AI Super-Recruiter This project is about using a data science algorithm to emulate a professional recruiter in their job of finding good candidates for executive positions. A small team of students will work with a job recruiting firm in Asia. The firm will have one or more of their top recruiters mark resumes to explain what they look for in a set of 20 or more CVs for executive positions. By understanding what they look for, the team will develop a machine learning algorithm and/or rule based approach to selecting resumes. Results will be shown to the executive job search firm.

"But there are also unknown unknowns – the ones we don't know we don't know." An artificial intelligence strategy is the corporate equivalent of your spleen: everyone has one, but not everyone understands quite what it will accomplish. There are bold plans afoot everywhere in the world of AI to be sure, but its reality is still distant from the vision of artificial general intelligence (AGI) – i.e., machines displaying intelligence equivalent to the natural intelligence of humans – of popular imagination. Investors in particular need a sober and realistic view of what's achievable in the field of machine learning-driven AI today, versus what promises nothing more than a waste of time and money. There are many business problems that map to the attributes above. The key to success in AI is to focus on these classes of practical problems and solutions.