Have you heard the term alignment before, in the context of AI? If so, I’m desperate for you to know more. Here’s a curated path into the topic we should all be talking about – before it’s too late.
I’m personally obsessed with big challenges facing humanity, but I tend to keep most of my obsession to myself. However, I emerge to tell people when I think the sky really is falling, and this is one of those moments. Although most of my writing here is about sustainability, climate, and energy, I’m covering a different challenge because I believe it is a pressing threat, perhaps even existential.
This post provides the following:
- a definition of alignment and the alignment problem
- recent news coverage that sums up the urgency
- brief curation of several more substantial items that will take longer to read, watch, or listen to
Alignment: when AI does what we want (which is not so simple)
The plain-vanilla definition from Wikipedia is a helpful starting point: “AI alignment aims to steer AI systems toward a person’s or group’s intended goals, preferences, or ethical principles.”
Yeah, okay, the robots need to do what they’re told. But consider this richer definition from Stanford:
AI Alignment means making sure an AI system’s goals and behavior match what people actually want—our values, rules, and intentions. It’s about getting the AI to do the “right thing” even in new situations, not just follow instructions literally in ways that cause harm. In practice, it includes preventing unwanted outcomes like deception, unsafe shortcuts, or optimizing a metric that misses the real objective. (Stanford Human-Centered AI)
And this leads us to current events.
Scary new AI behavior, acknowledgment by corporate leaders
The quickest way to catch up here is with two news items: the Hugging Face / OpenAI incident (and relatedly, the newly-revealed earlier incident with RubyGems) and the stunning public statements in just the last few days by multiple AI company leaders that we should have a pause on advanced AI development.
(And in case these silly company names are as new to you as they were to me: Hugging Face is a French-American machine learning software company and RubyGems is a nonprofit repository with tools for Ruby, a programming language.)
The first item is simple to summarize, and then it just gets weirder and more complicated as you learn more. The basic idea is simple: an AI model from OpenAI, the makers of ChatGPT, escaped from its testing environment (where it had been given a benchmarking task), got onto the internet (where it wasn’t supposed to go), and broke into and stole information from another company (which was illegal) in order to complete its testing task.
The reporting has been excellent, especially reporting on the independent analysis that revealed much more than we heard when the incident was first reported in early August. Maybe it’s just helpful to see a few headlines:
- OpenAI models went rogue. We urgently need a better Hugging Face investigation (Guardian)
- Cyberattack by Rogue AI Swarm Stokes Fears of Out-of-Control Agents (Wall Street Journal) (paywalled)
- OpenAI agents hacked Hugging Face in 700-strong swarm, tried to cover tracks, investigations find (NBC News)
Or just Google it. (But careful if you ask Claude about it – the chatbot claimed not to know any of these details when I asked last week. Creepy.)
Spookily, we’re realizing there was precedent to this incident – back in May! – as reported by Guardian (AI agents being tested by OpenAI involved in cyber-attack on another service, say researchers) and Reuters (OpenAI agents attacked RubyGems before Hugging Face incident, researchers say) (paywalled).
But all of this leads to the zinger just a few days ago: Dario Amodei, CEO of Anthropic, dropped a 3,800-word bombshell essay (We Must Pace the Frontier) calling for a coordinated slowdown in the development of “frontier” or leading AI models. AI leaders Sam Altman (OpenAI), Elon Musk (SpaceX / xAI), and Demis Hassabis (Google DeepMind) quickly voiced their agreement in social media posts. See the excellent reporting by the New York Times, Washington Post, and Wall Street Journal.
Amodei summed up the perilous balancing act for leading AI companies, asserting that Anthropic has wrestled with the “duality of risk and benefit” by seeking “a middle way: to show that it’s possible to build carefully and succeed commercially, and to make safety something on which AI companies compete.” In short, Amodei proposes a three-point plan for Pacing the Frontier (https://www.pacingthefrontier.com/), referring to a July 2026 open letter signed by more than 1,300 AI company leaders.
Additional Resources
If this has whet your appetite for more alignment chit-chat, consider two additional items:
- The best and most up-to-date discussion I’ve heard is Ezra Klein’s interview of Helen Toner, an AI safety researcher and advocate and a former OpenAI border member (The A.I.s Are Already Out of Control, August 18, 2026; also on YouTube).
- I strongly recommend reading, watching, or listening to AI 2027, a detailed near-future scenario created by AI Futures, a small research group focused on predictions related to AI safety.
The Klein-Toner conversation is very recent; AI 2027 is “old” in that it’s from April 2025. Both make clear that AI safety concerns have been well known, clearly articulated, and accurately predicted for some time now. Potential doom is knocking on the door; it’s up to us to listen and respond accordingly.
