With artificial intelligence becoming ever more prominent in biomedical labs and research, biomedical scientist turned ethicist Sarah E Carter looks at the pressing issues.
Artificial intelligence (AI) is increasingly prevalent in all aspects of life, including the biomedical scientist’s laboratory. While a universal definition of AI is still a matter of debate, the Institute of Electrical and Electronics Engineers in the US broadly defines AI as: “The theory and development of computer systems that are able to perform tasks which normally require human intelligence such as, visual perception, speech recognition, learning, decision-making, and natural language processing.”
In the lab, we now see examples of these intelligent computer systems tackling research tasks, such as tissue imaging and data visualisation. They have also pushed the boundaries of what was possible in biomedical research through their ability to model data on a massive scale, allowing researchers to utilise new tools, such as in silico drug development models. As AI use in the lab becomes more pervasive, an increasing number of research groups now employ a data specialist, and more and more computer science courses are requirements of biomedical graduate programmes. It’s clear that the future of biomedical research will be fuelled by data, AI, and computing power.
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