PerspectiveArtificial Intelligence Research Needs Responsible Publication Norms
After nearly a year of suspense and controversy, any day now the team of artificial intelligence (AI) researchers at OpenAI will release the full and final version of GPT-2, a language model that can “generate coherent paragraphs and perform rudimentary reading comprehension, machine translation, question answering, and summarization—all without task-specific training.” Rebecca Crootof writes in Lawfare that when OpenAI first unveiled the program in February, it was capable of impressive feats: Given a two-sentence prompt about unicorns living in the Andes Mountains, for example, the program produced a coherent nine-paragraph news article. At the time, the technical achievement was newsworthy—but it was how OpenAI chose to release the new technology that really caused a firestorm.
After nearly a year of suspense and controversy, any day now the team of artificial intelligence (AI) researchers at OpenAI will release the full and final version of GPT-2, a language model that can “generate coherent paragraphs and perform rudimentary reading comprehension, machine translation, question answering, and summarization—all without task-specific training.”
Rebecca Crootof writes in Lawfare that when OpenAI first unveiled the program in February, it was capable of impressive feats: Given a two-sentence prompt about unicorns living in the Andes Mountains, for example, the program produced a coherent nine-paragraph news article. At the time, the technical achievement was newsworthy—but it was how OpenAI chose to release the new technology that really caused a firestorm.
She writes:
There is a prevailing norm of openness in the machine learning research community, consciously created by early giants in the field: Advances are expected to be shared, so that they can be evaluated and so that the entire field advances. However, in February, OpenAI opted for a more limited release due to concerns that the program could be used to generate misleading news articles; impersonate people online; or automate the production of abusive, fake or spam content. Accordingly, the company shared a small, 117M version along with sampling code but announced that it would not share key elements of the dataset, training code or model weights.
While some observers appreciated OpenAI’s caution, many were disappointed. One group of commentators accused the organization of fear-mongering and exaggerating the dangers of the technology to garner attention; others suggested that the company had betrayed its core mission and should rename itself “ClosedAI.” In May, OpenAI released a larger, 345M version of the model and announced that it would share 762M and 1.5B versions with limited partners who were also working on developing countermeasures to malicious uses. Again, some applauded. Others remained unimpressed.
Regardless of whether GPT-2 was dangerous enough to withhold, OpenAI’s publication strategy spurred a much-needed interdisciplinaryconversation about principles and strategies for determining when it is appropriate to restrict access to AI research.
