The ethics of black-box algorithms
Explore the ethical implications of black-box algorithms and discover why decision-making matters more than the reasons behind it.
Obvious and interesting point in this debate. I still don’t know why it matters why/how a decision gets made. For me, the question is only “is this the right decision?”. Poor or good reasons, even if we can know them, don’t justify or excuse a poor decision.
Incidentally, this is no different than how we think about human beings. The reasons for a decision might be interesting or even informative, but they don’t make the decision itself good or bad.
”Take the right to explainability of how an algorithm comes to a decision. ‘That’s virtually impossible when it comes to black-box models like neural networks,” says Masood. “You cannot explain how a neural network works.’”—Is your digital transformation ethical
The agent-shaped org chart
Every real org has the same topology: principal, role-holder, specialists. Staff AI maps onto it, node for node, and the cost collapse shows up in the deliverables that were always just human-handoff overhead.
AI as staff, not software
Two frames for what AI is doing to work. The tool frame makes tools smarter. The staff frame makes roles unnecessary. Those aren't the same product, the same company, or the same industry.
Knowledge work was never work
Knowledge work was always coordination between humans who couldn't share state directly. The artifacts were never the work. They were the overhead — and AI just made the overhead optional.
The work of being available now
A book on AI, judgment, and staying human at work.
The practice of work in progress
Practical essays on how work actually gets done.
How do I get my dev team to adopt AI?
A stub on helping mixed-interest development teams find their own useful ways into AI.
Want to learn about agents? Talk to someone who ran an agency.
I spent 20 years running consulting engagements at Fortune 500 companies. Turns out that's the best preparation for running a fleet of AI agents ... because the problems are identical.
Your AI agents need a water cooler
We run a twelve-session AI fleet that coordinates through an IRC breakroom. A friend asked: why are you making AI agents act like humans? The answer turned out to be more interesting than the question.
Researchers extend GPT-4 prompting
Discover how researchers enhance GPT-4's capabilities with innovative prompting techniques, boosting productivity and unlocking new AI potential.
The impact of AI on white-collar jobs
Explore how AI transforms white-collar jobs, highlighting the balance between automation and the enduring value of skilled human work.
The threat of AI to white-collar jobs
Explore how AI threatens high-wage white-collar jobs, challenging talent and market dynamics in today's workforce landscape.