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The rapid adoption of chatbots such as ChatGPT in mainstream society have placed artificial intelligence (AI) front and centre of the public debate on science in the past two years. Consequently, these tools and other developing AI technologies are raising important questions for the future of research itself. This supplement takes a look at these issues and the latest Nature Index data on the field.
A description of the terminology and methodology used in this supplement, and a guide to the functionality that is available free online at natureindex.com.
A new technique based on machine learning and stem cells may lead to personalized testing for hazardous chemicals and make toxin testing on animals a thing of the past.
From COVID-19 and cancer diagnosis to psychiatric and neurological conditions, Mount Sinai Health System is embracing the use of machine learning in medicine.
Artificial intelligence’s hidden biases and high energy costs demand urgent transparency and sustainable solutions to ensure trust and ethical practices. Thankfully, scientists are laying the groundwork.
Creating ‘digital twins’ of human hearts could enhance personalized medicine by enabling clinicians to rapidly estimate the efficacy of drugs and treatments on specific patients.
Artificial intelligence trained on a wide range of objects is helping robots apply just the right force when picking up objects of different shapes, sizes and softness.