Biases & Pitfalls of AI
Accomplished business leader with first-rate educational foundation (Columbia Business School and INSA Lyon, a French Grande Ecole) who uses out of the box thinking to create value. Bugra has participated in the creation of over half a dozen startups in the Insurance, Healthcare, and Technology space. Among those was Fair Forsikring, the first direct insurer in the Nordic markets.
He has experience in Machine Learning having created the Futurist AI platform, a groundbreaking cloud-based machine learning system using natural language processing and pattern recognition to gain insights into the financial markets. Bugra can identify great investment opportunities and execute quickly. Invested over $1.1 Billion equity. Responsible for 4 very successful exits with IRRs over 35%. Worked on over 50 M&A transactions (including buy-side and sell-side).
He has also successfully turned around 3 companies. Worked as interim management. Developed and implemented turnaround plans. Increased revenues substantially (over 30% in one case) and reached break-even.
This talk will be lightly technical and mathematical in nature and will use concrete examples to illustrate every point and make it entertaining. My talk will touch on what must be true to create a successful "AI", the key challenges of building a successful "AI", biases important to consider in the context of developing a machine learning-based solution.
- Use a machine learning solution is appropriate and when it's not.
- Understand the importance of biases and how it can totally skew the results.
- Recognize the limitation of today's AI solutions illustrated with concrete examples.