Alexandra Ebert is an ethical AI, synthetic data & privacy expert and serves as Chief Trust Officer at MOSTLY AI. She regularly speaks at international conferences on AI and privacy and hosts The Data Democratization Podcast. As a member of the company's senior leadership team, she is engaged in public policy issues in the emerging field of synthetic data and ethical AI and responsible for engaging with the privacy community, with regulators, the media, and with customers. Alexandra is active in various sectors, including Finance, Insurance, Healthcare, and the Public Sector. Besides being an advocate for privacy, Alexandra is deeply passionate about ethical AI and ensuring the fair and responsible use of machine learning algorithms. She is the co-author of an ICLR paper and a popular blog series on fairness in AI and fair synthetic data. Apart from her work at MOSTLY AI, she serves as the chair of the IEEE Synthetic Data IC expert.
- Synthetic Data
- Responsible AI
- Privacy & PETs
- Open Data & Data for Good
- Public Speaking
Publications & Blog post of Alexandra Ebert
- Paper and popular* series on Fair Synthetic Data and Fairness in AI: *featured in Forbes, by distinguished AI expert Andrew Ng, Slate, IEEE Spectrum.
- Research paper on Fair Synthetic Data
- Fairness Series
- Part 1: Why Bias in AI is a Problem and why Business Leaders should care
- Part 2: 10 Reasons for Bias in AI & what to do about it
- Part 3: We want Fair AI Algorithms - But How to Define Fairness?
- Part 4: Tackling AI Bias at its Source - with Fair Synthetic Data
- Part 5: Diving Deep into Fair Synthetic Data Generation