The latest issue of Complex Machinery: The bot doesn't always have to talk
The latest issue of Complex Machinery: The bot doesn't always have to talk
You didn't build it yourself, so you have to take some things on faith.
To borrow a phrase about the cloud ...
The latest issue of Complex Machinery: AI is magic. In various meanings of the word.
The latest issue of Complex Machinery: Sometimes AI is a better fit for that task. Emphasis on "sometimes"
The latest issue of Complex Machinery: Machines conquered Wall Street, then learned to play a mean game of poker.
A new perspective on risk management
The latest issue of Complex Machinery: AI use cases, as driven by fraud and stunts. And squeeze bottles.
The latest issue of Complex Machinery: Cookies can tell us a lot about AI use cases. Especially the more questionable variety.
The latest issue of Complex Machinery: More lessons from the CrowdStrike incident
The latest issue of Complex Machinery: How the CrowdStrike incident reflects a key risk in complex systems
The latest issue of Complex Machinery: The shady side of the AI business.
The latest issue of Complex Machinery: Understanding the race against time that is AI's popularity.
The latest issue of Complex Machinery: Pondering the easy money in AI, and when it will come due.
The latest issue of Complex Machinery: Google changes path on its AI Overviews product
The latest issue of Complex Machinery: the new GPT-4o trips, Google's AI Overview stumbles, and asking what-if questions when building AI products
Is AI having its bubble moment? If so, why would that matter?
The latest issue of Complex Machinery: Some short-term AI annoyances, plus some optimism about the future
The latest issue of Complex Machinery: Pricing out the risk of your latest AI adventure
The latest issue of Complex Machinery: A look into auto manufacturers passing driver details to data brokers
The latest issue of Complex Machinery: thinking about our approaching bot-on-bot future
The latest issue of Complex Machinery: the randomness inside every AI model
The latest issue of Complex Machinery: deepfakes for crime, facial recognition, and minding the robots
Complex Machinery is my new newsletter on AI, risk, and related topics.
AI chatbots are great, but they're still a little rough around the edges
Seven questions to help you improve your training data.
Lessons from an AI chatbot's terrible recipe ideas.
Reflections on operational risk, in light of the anniversary of the Knight Capital meltdown
The risks and rewards of using vendor APIs for generative AI models
A reminder that risk and reward are a package deal
Releasing an AI chatbot exposes your company to new risks. Here are some ideas on how to handle them.
A reminder of generative AI's chaotic potential
Risk mitigation for your ML/AI projects
A short list of ways an ML/AI modeling project can go off the rails
Some datasets are problems in waiting.
Potential problems that can affect the entire field.
Adopt a popular expression to improve your risk awareness and assessment.
Zillow recently closed down its home-buying program. Do I see this as a failure of ML/AI? In a word: No.
I interviewed product manager Chris Butler about the role uncertainty plays in AI product management.
Best practices to balance the risk and reward of building predictive models.
Humans versus machines? To reduce your risk, the best answer is "yes."
Learning how to handle risk, from the fields that do it well.
Every company needs someone to be their extra eyes.
An introduction to risk.
Does the AI hype meet the technical term of a "bubble?"
Lemonade's recent media spotlight is a cautionary tale for any company using ML/AI.
It's bad enough when the model is wrong; even worse, when it's wrong and you didn't have to build it in the first place.
When a group predicts students' performance in lieu of holding a exam, it leads to some lessons in the deployment and use of ML/AI models.
What can the world of algorithmic (electronic) trading teach us about good ML/AI practices? (Part 8 in a series)
What can the world of algorithmic (electronic) trading teach us about good ML/AI practices? (Part 7 in a series)
ML/AI models still require a lot of human involvement.
What can the world of algorithmic (electronic) trading teach us about good ML/AI practices? (Part 6 in a series)
Three questions to help you gauge your risk of being laid off.
Business models involving ML/AI are sitting on unrecognized risk.
COVID-19 may be what gets companies to take their ML/AI efforts seriously.
The AI world is sitting on all kinds of risk ... but no one wants to talk about it.
Looking at data ethics through the lens of risk. (Part 5 in a series.)
Looking at data ethics through the lens of risk. (Part 4 in a series.)
Looking at data ethics through the lens of risk. (Part 3 in a series.)
Looking at data ethics through the lens of risk. (Part 2 in a series.)
Looking at data ethics through the lens of risk. (Part 1 in a series.)