Researchers play a significant role in changing — and sometimes even saving — the world. Yet, despite their hugely influential role in our society, these innovators and explorers all too often lack the support they need to make these world-altering discoveries.
During the scientific research process, researchers experience any number of challenges and setbacks. Meanwhile, they face tremendous pressure from their employers, funders, peers, and even society at large. Scientific researchers must expedite their discovery process without sacrificing the quality or accuracy of the results.
Fortunately, the scientific community agrees that one technological innovation could revolutionize scientific research for the better: artificial intelligence. Any tool that can make the discovery process more manageable is worth exploring, and in this day and age, AI seems poised to do just that.
Siddhartha Rao, a tech expert with years of experience working at leading tech companies like Amazon Web Services, is on the front lines of bringing powerful AI technology to scientific researchers. His company, Positron Networks, is dedicated to developing artificial intelligence solutions for the academic and scientific community.
How AI will revolutionize scientific research
Innovators in scientific research have found several ways in which artificial intelligence technology can be leveraged to aid researchers in their experimentation. Some of the most common use cases for AI in scientific research include:
- Predictive analytics: The use of AI in scientific research that is likely most familiar to the community is predictive analytics. “Researchers have long used neural networks and machine learning to predict future outcomes and simulate conditions that are difficult to replicate in the laboratory,” Rao states. “But the richness of today’s artificial intelligence models allows these analytics to provide more advanced and reliable insights than ever before.”
- Simulations: Researchers can also use AI to conduct simulations that replicate conditions that would be impractical, dangerous, or expensive in a laboratory setting. “For example, researchers at Johns Hopkins University recently used an AI model to simulate the atmosphere of a young Earth in a study exploring the origins of life,” Rao explains. “Recreating these conditions in a lab setting would have cost tens of millions of dollars.”
- Data analysis: Many researchers have also found ways to leverage AI’s data analysis capabilities, helping them develop their hypotheses and plan their research. “Because artificial intelligence can process data much more quickly and efficiently than humans, an AI model can analyze existing and published research to help scientists determine conclusions and knowledge gaps that may be tested in their hypotheses,” says Rao.
Why businesses and public organizations must come together to support AI in scientific research
While these capabilities may make artificial intelligence seem like a powerful agent of democratization, the truth of the technology is rarely so optimistic. “In the right hands, these tools can help scientists and researchers improve their research and experimentation processes and assist with discovery,” says Rao. “However, the lack of widespread access to these tools has created an issue of inequity, where a knowledge gap is starting to form between researchers with access to these advanced AI tools and those without.”
To fully leverage AI, scientists currently have to have a challenging combination of technical skills, data, and computing infrastructure, limiting the impact AI can have on accelerating scientific discovery. Scientific achievement, measured by the number of high-quality discoveries per dollar invested, can be accelerated by an order of magnitude if AI can be fully leveraged by all researchers.
First and foremost, operating these advanced AI models requires an extensive computing infrastructure that many public institutions do not have at their disposal. Because of this, the best, most advanced artificial intelligence tools are often reserved for researchers working for corporations with deep pockets to support the extensive costs of creating and running these models. Although there are publicly available tools, these have shortcomings of their own — often suffering from being less scalable and convenient than those available to the private sector.
There are also potentially severe consequences to a majority of the most important and useful AI models being created and held by private companies. Namely, models developed by private entities for the use of private entities will be designed and used to serve these private interests. Although this can be expected to an extent, private companies’ monopolization of these resources has created a situation where researchers serving the greater good do not always have the resources they need to conduct experiments and make discoveries efficiently.
Ultimately, the future of AI in scientific research is one where the private and public sectors collaborate to enhance discovery. Artificial intelligence technology has valuable benefits for the scientific community that will have far-reaching positive impacts on society as a whole.
“By providing equitable access to valuable computing resources through public-private partnerships like Positron Networks, we will empower scientists and researchers to conduct experiments and make discoveries that would not have been possible with the resources available to them to this point,” Rao asserts. “Positron lowers the technical skills required for researchers to deeply leverage AI in their discipline while democratizing highly scalable scientific computing infrastructure, unlocking large results with the smallest of investments and grants.”
Artificial intelligence is poised to unlock a revolution in scientific research through the power to help researchers change the world faster and smarter than ever before. Yet, to reach this transformative inflection point, access to this technology must be equalized. Only when businesses and public institutions come together will researchers be able to harness AI’s immense potential to democratize scientific discovery.
About the Author: Sean Boelman is a journalist with over five years of experience working in the entertainment field as a film critic and interviewer. His work has appeared in several outlets, including top-tier entertainment publication FandomWire, and his opinion has been featured by websites such as Indiewire, Seventh Row, and Letterboxd News. He has also been quoted several times by major studios in trailers and posters.
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