October 24, 2019
Artificial 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.” 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.
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.
Read the full article from Lawfare.
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