In February OpenAI catapulted itself into the public eye when it produced a language model so good at generating fake news that the organization decided not to release it. Some within the AI research community argued it was a smart precaution; others wrote it off as a publicity stunt. The lab itself, a small San Francisco-based for-profit that seeks to create artificial general intelligence, has firmly held that it is an important experiment in how to handle high-stakes research.

Now six months later, the policy team has published a paper examining the impact of the decision thus far. Alongside it, the lab has released a version of the model, known as GPT-2, that’s half the size of the full one, which has still not been released.

In May, a few months after GPT-2’s initial debut, OpenAI revised its stance on withholding the full code to what it calls a “staged release”—the staggered release of incrementally larger versions of the model in a ramp-up to the full one. In February, it published a version of the model that was merely 8% of the size of the full one. It published another roughly a quarter of the full version before the most recent release. During this process, it also partnered with selected research institutions to study the full model’s implications.

The report details what OpenAI learned throughout this process. It notes that both the staged release and research partnership agreements proved to be processes worth replicating in the future. They helped OpenAI better understand and anticipate the possible malicious uses of GPT-2. And indeed, the research partners were able to better quantify some of the threats that were only previously speculative. A study conducted by collaborators at Cornell University, for example, found that readers on average believed GPT-2’s outputs to be genuine news articles nearly as often as New York Times ones. Several researchers outside of official partnerships also began tackling the challenge of detecting machine-generated text.