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We introduced reusability reports, an article type to highlight code reusability, almost two years ago. On the basis of the results and positive feedback from authors and referees, we remain enthusiastic about the format.
To deliver value in healthcare, artificial intelligence and machine learning models must be integrated not only into technology platforms but also into local human and organizational ecosystems and workflows. To realize the promised benefits of applying these models at scale, a roadmap of the challenges and potential solutions to sociotechnical transferability is needed.
There is a tendency among AI researchers to use the concepts of democracy and democratization in ways that are only loosely connected to their political and historical meanings. We argue that it is important to take the concept more seriously in AI research by engaging with political philosophy.
The public release of ‘Stable Diffusion’, a high-quality image generation tool, sets new standards in open-source AI development and raises new questions.
Policymakers and researchers consistently call for greater human accountability for AI technologies. We should be clear about two distinct features of accountability.
There is growing interest in using machine learning to mitigate climate change. But as avoiding catastrophic temperature rises becomes more urgent, action is also needed to understand the environmental impact of machine learning research.
As with last summer, COVID-19 is still with us, but there is a semblance of what life was like before the pandemic. Here, we recommend AI podcasts from the past year that may inform, inspire or entertain, as we get an opportunity to travel or take time away from regular activities.
China is pushing ahead of the European Union and the United States with its new synthetic content regulations. New draft provisions would place more responsibility on platforms to preserve social stability, with potential costs for online freedoms. They show that the Chinese Communist Party is prepared to protect itself against the unique threats of emerging technologies.
Artificial intelligence (AI) can support managers by effectively delegating management decisions to AI. There are, however, many organizational and technical hurdles that need to be overcome, and we offer a first step on this journey by unpacking the core factors that may hinder or foster effective decision delegation to AI.
Soon into the COVID-19 pandemic, civil-rights groups raised the alarm over the increase in digital surveillance infringing on individual rights. But there are other potential harms as tech companies accelerate their expansion into new areas essential to public-service provision.
Considering the potential for unintended harmful applications of AI tools can lead to deeply concerning findings. An urgent question is how to achieve the right balance between keeping science open and preventing misuse or malicious repurposing.
Common-sense reasoning has recently emerged as an important test for artificial general intelligence, especially given the much-publicized successes of language representation models such as T5, BERT and GPT-3. Currently, typical benchmarks involve question answering tasks, but to test the full complexity of common-sense reasoning, more comprehensive evaluation methods that are grounded in theory should be developed.
The number of graph neural network papers in this journal has grown as the field matures. We take a closer look at some of the scientific applications.
