CNS 2024 | The 13th Annual Distinguished Career Contributions Award (DCC) Congratulations to Kia Nobre our 2024 Fred Kavli Distinguished Career Contributions Awardee. Kia will accept this prestigious award and deliver her lecture in Toronto, Canada, April of 2024 at the Sheraton Centre Toronto Hotel. ‘Focus through Time’ Kia Nobre Wu Tsai Institute and Department […]
In 1983, Time Magazine named the computer its “Machine of the Year.” A few months later, radical Detroit newspaper Fifth Estate responded by naming the sledgehammer its Tool of the Year.
“Today the computer promises utopia, reassures us that it will usher in freedom and dreams,” they wrote. “Tomorrow we will be chained to it.”
Protecting against misuse without forfeiting the potential benefits is key The global market for artificial intelligence (AI) for healthcare is booming. Currently valued at $15bn (£12bn; €14bn), it is expected to near $200bn by 2030.12 Public sector spending on AI for healthcare is also on the rise. The UK government, for example, has already invested more than £123m in AI for healthcare technologies.3 Of course, previous AI “summers” were followed swiftly by AI “winters,” when the gap between expectations and the reality of AI grew too wide. This summer’s heat and longevity can largely be attributed to the advent of generative AI. Generative AI is a type of machine learning capable of generating data in a range of formats (including text, image, audio, video, or code) and adapting to new tasks in real time, following simple text based prompts. These capabilities make generative AI flexible, as one “model” (for example, ChatGPT or DALL-E) can be used for a variety of tasks—including medical research tasks—without having to be retrained. This flexibility makes generative AI appealing …
Luciano Floridi
Emmie Hine
Paris Marx
Jess Morley
