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Artificial Intelligence: A Powerful Research Tool in Environmental Health

 By: Jessica Medina

Photo by ipopba, Getty Images/iStockphoto

    Artificial intelligence (AI) is a branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. It’s interesting how AI applies deep learning and machine learning, which refers to how computer algorithms improve at performing assigned tasks with increasing experience.
    The researchers had utilized AI to estimate pollution levels throughout the U.S. and were able to gain results. However, they are still progressing in terms of quantifying how good the guesses from machine learning are because it is unreliable outside the areas where the model was initially trained. The unique aspect of this research is that AI is so versatile that it can be useful in many ways and can have multiple purposes, such as mapping mosquito habitats and floodplains, finding patterns in time-series data, and assessing air quality.
    AI advances environmental sustainability by addressing many unsolved challenges around how best to utilize large and complex data sets through unique varied models. Therefore, it helps individuals propose new hypotheses or effective solutions for difficult problems. One of the main trade-offs in AI is that it can generate misleading results when used incorrectly because AI algorithms can be difficult and many of their internal calculations are either proprietary information or too complex for people to understand. Nonetheless, AI in environmental health can be achieved when going slow and steady in order to identify the right approaches to each problem and also by paying attention to the data quality.  


References

Schmidt, C. W. 2020. Into the black box: What can machine learning offer environmental health research? Environmental Health Perspectives. 128:1-5.





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Comments

  1. M MendezNovember 27, 2020 at 5:02 PM

    Wow! I had not thought about using AI to either develop new hypotheses, research questions, or maybe even environmental policy. Of course, depending on the algorithm and data input, it could provide an unbiased assessment of prioritizing our environmental management.

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