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In the Future, There Will Be No Limit to What AI Can Accomplish in Science

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In the Future, There Will Be No Limit to What AI Can Accomplish in Science

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4 take-aways
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Artificial intelligence and big data are creating a limitless future for science.


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9

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  • Innovative
  • Scientific
  • Eye Opening

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Great scientists use their brilliant insights to craft scientific laws in the face of scarce data. Today, blessed with cheap sensors and electronic storage, the challenge is how to tease out the truths from an ever-growing abundance of data. AI technologies and high-powered computers are much better suited to sifting through these mountains of data than human researchers. And there are now even prototype “robot scientists,” which may soon bring about the extinction of the bespectacled researcher working late into the night in the lab. The article offers a glimpse of the future of science.

Take-Aways

  • AI is now an important tool in making scientific breakthroughs.
  • Computers are ideal for managing, manipulating and interpreting large quantities of data.
  • AI technologies will increasingly dominate scientific research as they find unsuspected relationships in data.
  • AI systems will become “robot scientists” and take over significant areas of research.

Summary

AI is now an important tool in making scientific breakthroughs.

The use of artificial intelligence has recently led to a number of new discoveries in science. AI has found new planets and helped analyze gravitational waves. In medicine, AI assisted in the discovery of new treatments for resistant strains of malaria.

“Machines are better suited to unravel the complexities of biological systems [as] even the most ‘simple’ organisms are host to thousands of genes, proteins and small molecules that interact in complicated ways.”

In climate sciences, a better understanding of glacial behavior is now possible due to the strengths of AI in data analysis and modeling. As techniques improve and the tidal wave of data becomes ever bigger, the impact of machine learning will continue to grow.

Computers are ideal for managing, manipulating and interpreting large quantities of data.

Over the last few decades, the volume of data being collected has grown quickly. Scientific success is now dependent on effectively understanding these very large data sets. Computers are better at remembering and processing this information.

With faster computational speeds and better AI methods, computers are able to do what would be difficult or impossible for human researchers.

AI technologies will increasingly dominate scientific research as they find unsuspected relationships in data.

Pre-AI analysis of data was often limited to one factor at a time, but new AI technologies and neural networks allow the combination of many data sources and the analysis of many factors at one time.

“These advances increasingly give AI superhuman reasoning abilities.” (Ross King, Manchester Institute of Biotechnology)

For example, new research on glaciers has combined data on topology, crust thickness, magnetic features and rock composition to discover the flux of heat under Greenland’s glaciers. Since no single factor properly accounts for these patterns, without AI’s special capabilities it would be very difficult to arrive at an accurate picture.

AI systems will become “robot scientists” and take over significant areas of research.

While AI is now a tool in human scientists’ toolkit, some researchers eventually hope to create “robot scientists.”

“Robot scientists are getting smarter and smarter; human scientists are not.” (King)

Robot scientists will analyze data, develop hypotheses based on that analysis, devise experiments to test the hypotheses, and carry out those experiments using robotic laboratories. The Newtons and Einsteins of the future may be robots.

About the Author

Peter Rejcek is a science journalist focusing on artificial intelligence, Antarctica and emerging technologies.

This document is restricted to personal use only.

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