Yacine Jernite's fears about bias in artificial intelligence were vividly affirmed in 2017, when a Facebook translation error led Israeli police to arrest a Palestinian construction worker. The man had posted a picture of himself leaning against a bulldozer with the caption, in Arabic, "good morning." Facebook mistakenly translated it, in Hebrew, as "attack them." The error was quickly discovered and the man released, according to a report in Haaretz, but the incident cemented personal concerns about AI for Jernite, who joined Facebook's AI division soon after. As the child of Moroccan parents in post-9/11 America, Jernite said he has "spent hours upon hours in immigration secondary interviews -- in a way that I could not at the time trace to the technology that was being applied."

Open & Responsible AI licenses ("OpenRAIL") are AI-specific licenses enabling open access, use and distribution of AI artifacts while requiring a responsible use of the latter. OpenRAIL licenses could be for open and responsible ML what current open software licenses are to code and Creative Commons to general content: a widespread community licensing tool. Advances in machine learning and other AI-related areas have flourished these past years partly thanks to the ubiquity of the open source culture in the Information and Communication Technologies (ICT) sector, which has permeated into ML research and development dynamics. Notwithstanding the benefits of openness as a core value for innovation in the field, (not so already) recent events related to the ethical and socio-economic concerns of development and use of machine learning models have spread a clear message: Openness is not enough. Closed systems are not the answer though, as the problem persists under the opacity of firms' private AI development processes.

Almost a year ago to the day, the Center for Research on Foundation Models (CRFM) – which was then a new initiative of the Stanford Institute for Human-Centered Artificial Intelligence (HAI) – held a virtual workshop on Foundation Models. They chose "Foundation" as the name for these models as they entail training one model on a huge amount of data, then adapting it to many applications. The data can be text, images, speech, and more. The tasks that such models can perform include – but are not limited to – answering questions, analyzing sentiments, extracting information form text, labeling images, and recognizing objects. These Foundation Models use self-supervised learning, and they work because they can effectively apply knowledge learned in one task to another task.

Researchers have warned against possible harms from AI that processes and generates text.Credit: Getty An international team of around 1,000 largely academic volunteers has tried to break big tech's stranglehold on natural-language processing and reduce its harms. Trained with US$7-million-worth of publicly funded computing time, the BLOOM language model will rival in scale those made by firms Google and OpenAI, but will be open-source. BLOOM will also be the first model of its scale to be multilingual. The collaboration, called BigScience, launched an early version of the model on 17 June, and hopes that it will ultimately help to reduce harmful outputs of artificial intelligence (AI) language systems. Models that recognize and generate language are increasingly used by big tech firms in applications from chat bots to translators, and can sound so eerily human that a Google engineer this month claimed that the firm's AI model was sentient (Google strongly denies that the AI possesses sentience).

A language model bigger than GPT-3 has arrived with a bold ambition: freeing AI from Big Tech's clutches. Named BLOOM, the large language model (LLM) promises a similar performance to Silicon Valley's leading systems -- but with a radically different approach to access. While tech giants tend to keep their vaunted LLMs hidden from the public, BLOOM is available to anyone for free. These features could democratize access to technology that's set to make a deep impact on society. Powerful AI models can be trained and released in an open way.

Researchers have warned against possible harms from AI that processes and generates text.Credit: Getty An international team of around 1,000 largely academic volunteers has tried to break big tech's stranglehold on natural-language processing and reduce its harms. Trained with US$7-million-worth of publicly funded computing time, the BLOOM language model will rival in scale those made by firms Google and OpenAI, but will be open-source. BLOOM will also be the first model of its scale to be multilingual. The collaboration, called BigScience, launched an early version of the model on 17 June, and hopes that it will ultimately help to reduce harmful outputs of artificial intelligence (AI) language systems. Models that recognize and generate language are increasingly used by big tech firms in applications from chat bots to translators, and can sound so eerily human that a Google engineer this month claimed that the firm's AI model was sentient (Google strongly denies that the AI possesses sentience).