A little background ...

I've provided a formal bio in the next section. For new visitors, here's the gist:

I'm Q McCallum. I'm a consultant, writer, and researcher. My work centers on applying emerging, disruptive technology to business use cases.

People mostly know me from my work in machine learning/artificial intelligence (ML/AI), including books, articles, and conference talks.

My technology work is shaped by my experience in the financial world, which has led me to study risk/complexity, N-sided marketplaces, and asset bubbles.

I periodically publish blog posts (on topics such as executive-level data literacy, building a data team, and AI risk management ). I've summarized some of those blog posts into one-pager guides like "Will AI Help Here?" and "How Do I Do AI?"

If you've landed on this page you are likely looking for one of the following:

• My consulting practice, through which I apply a risk management approach to AI strategy, product guidance, and due diligence services.
• Complex Machinery, my newsletter on AI, risk, and related topics.
• My blog on a mix of ML/AI, marketplaces, and risk. Popular posts include:
  • My guide on how to develop your company's data/AI strategy (originally published in 2016, and still relevant today)
  • How to manage risk in your generative-AI (LLM) chatbots
  • Lessons from the Knight Capital meltdown of 2012
  • The risks of building services atop hosted, SaaS-style AI model providers
  • What to look for in your company's first data hire
  • A series on ideas that AI shops can borrow from algorithmic trading
  • A combined 80+ articles on executive-level data literacy and AI-related risk management
• A list of books and articles I've published and select speaking engagements.
• My O'Reilly Radar articles, longer reads on topics as varied as remote work, N-sided marketplaces, automated machine learning, and navigating the pandemic.
• My one-pager websites, such as "Will AI Help Here?" and "How Do I Do AI?"
• Block & Mortar, my previous newsletter on all things web3. (Now inactive.)

Bio

Q McCallum is a consultant, writer, and researcher. He's spent his career applying emerging and disruptive technology to business use cases. His consulting practice focuses on matters of strategy and risk management in machine learning and artificial intelligence (ML/AI).

Q's published work includes Twin Wolves: Balancing risk and reward to make the most of AI ; Black Box Tactics: Best practices for AI, from the world of algorithmic trading ; Understanding Patterns of Disruption: Lessons Learned from the Cloud, Machine Learning, and More; Business Models for the Data Economy; Parallel R: Data Analysis in the Distributed World; and Bad Data Handbook: Mapping the World of Data Problems. He has also been featured on O'Reilly Radar.

He maintains a blog on AI and risk at his website and publishes Complex Machinery a newsletter on AI, risk, and related topics. The archives for Block & Mortar, his previous newsletter on all things web3 (blockchain, cryptocurrencies, NFTs, and metaverse), are still available online.

Q's speaking engagements span industry conferences and private events.

His research interests include:

• The intersection of ML/AI and business models (data monetization, human/AI interaction, AI-based automation)
• The application of financial concepts (such as risk, N-sided marketplaces, and asset bubbles) to other domains