- KDnuggets™ News 19:n36, Sep 25: The Hidden Risk of AI and Big Data; The 5 Sampling Algorithms every Data Scientist needs to know - Sep 25, 2019.
Learn about unexpected risk of AI applied to Big Data; Study 5 Sampling Algorithms every Data Scientist needs to know; Read how one data scientist copes with his boring days of deploying machine learning; 5 beginner-friendly steps to learn ML with Python; and more.
- Beyond Explainability: A Practical Guide to Managing Risks in Machine Learning Models - Sep 20, 2019.
This white paper provides the first-ever standard for managing risk in AI and ML, focusing on both practical processes and technical best practices “beyond explainability” alone. Download now.
- What is missing when AI makes a decision? - Apr 5, 2019.
We explain the need for caution when it comes to using AI in real-life situations and outline the importance of asking the right question to deliver the right impact.
- AI, Data Science, Analytics Main Developments in 2018 and Key Trends for 2019 - Dec 3, 2018.
Review of 2018 and Predictions for 2019 from our panel of experts, including Meta Brown, Tom Davenport, Carla Gentry, Bob E Hayes, Cassie Kozyrkov, Doug Laney, Bill Schmarzo, Kate Strachnyi, Ronald van Loon, Favio Vazquez, and Jen Underwood.
- The Evolution of Build Engineering in Managing Open Source [Webinar Replay] - Nov 13, 2018.
Explore how the role of build engineering is evolving to reconcile two key trends: massive wide-scale adoption of open source; the most devastating cyber-attacks in recent history tied to unpatched dependencies and other vulnerabilities.
- How to Mitigate Open Source License Risks - Oct 30, 2018.
This whitepaper from ActiveState investigates the various types of OSS licenses, common myths and risks, DIY risk management, the importance of enterprise legal indemnification, and more.
- Key Takeaways from AI Conference SF, Day 1: Domain Specific Architectures, Emerging China, AI Risks - Oct 29, 2018.
Highlights and key takeaways include Domain Specific Architectures – the next big thing, Emerging China – evolving from copying ideas to true innovation, and Addressing Risks in AI – Security, Privacy, and Ethics.
- NYC Taxi Hackathon – find privacy risks in public taxi datasets - Sep 19, 2016.
The NYC TLC has been a pioneer in sharing big data since 2010, but earlier data releases have been de-anonymized. TLC is considering releasing taxi data again, subject to a new anonymization method. This hackathon is to help test it.
- Advantages and Risks of Self-Service Analytics - Apr 13, 2016.
Self-service analytics is likely to spread in all the business layers, and with proper care to avoid certain risks, the culture of self-service analytics will help all organizations.