Scientific discovery, for the most part, includes a close scrutiny of large volumes of data and speculative experiments. The AI revolution in science is helping scientists to minimize the time between forming of hypotheses and getting results, so that technological progress can be accelerated further, enabling humanity to benefit more from the smartest among us.
Artificial intelligence is undoubtedly among the most remarkable, if not the most remarkable invention that humanity has contrived. The scientific community has succeeded in creating intelligent applications that can reason, learn, and behave like regular humans. These programs, although currently unable to fully replicate the entirety of the human range of capabilities, have succeeded in outperforming humans in specific actions or tasks. For instance, scientists have developed AI that can outperform human doctors in accurately detecting skin cancer in patients at a very early stage, which can potentially save thousands of lives every year.
Similarly, specialist AI applications are also becoming adept at thinking like humans and even coming up with unconventional ideas as demonstrated by an AI’s victory in a game of Go— a game requiring strategy and intuitive judgment— against the world champion. The AI, in this case, reportedly employed unconventional moves and strategies— some not even used by humans before — to outwit its opponent. This goes to show the proficiency of modern AI to not only reason and calculate with accuracy but also occasionally display hints of creativity. This newfound ability of AI to simultaneously be creative and analytical has prompted the era of AI revolution in science and technology. From being mankind’s greatest creation, AI has advanced enough to assist humans in making new breakthroughs in the field of science and innovate new technological applications.
The drudgery involved in scientific discovery
When we think of scientific discovery or technological inventions, we often picture scientists having sudden a-ha moments, when they discover a fact, or innovate a solution that makes an impact on the world. But to get to those epiphanies, scientist need to go through years and decades of scientific research, which involves extensive study, research, analysis, calculation, and experimentation. Some discoveries require the combined effort of multiple scientists from different fields and often multiple generations to get the tiniest of breakthroughs. For every fascinating breakthrough that we see in the news and magazines, there are dozens of scientists working in silence, gathering data, analyzing it, verifying it, getting it reviewed by peers, reviewing their peers’ findings, and going through careful routines to make the slightest progress towards a new discovery or invention. These scientists often have to meet deadlines to show results, making the process more complicated, since a failure to meet deadlines may result in the withdrawal of funding.
Big data is already proving to be a great tool for scientists, as it allows them to perform the analysis of large volumes of data quickly, speeding up experiments and the entire process of research and development. However, there is much more still left to be desired by the scientific community to further speed up the process of gathering and analyzing information and shortening the time period between the formation and validation of hypotheses. The beginning of AI revolution in science that we’re currently witnessing is poised to revolutionize the world of innovation, giving the scientific community what it needs, and possibly, even more.
The impact of the AI revolution in science
The use of combined use of AI and big data to gather and analyze massive volumes of data is enabling scientists to arrive at conclusions faster than before. AI is capable of performing highly complex computations with high accuracy and speed and is helping in different areas of research such as astrophysics, mathematics, and computer science. AI is also helping accelerate scientific discovery in other ways, as follows:
Deep learning is a relatively new subset of artificial intelligence that is, among other things, used to make sense of highly unstructured data. This ability of deep learning to identify hidden patterns in large volumes of data is used in biological studies to study genomics and in medicine for predicting molecular structures of effective therapeutics in drug discovery. This saves a lot of time that, if done manually, is spent in hundreds of trials and trying out different molecular structures for drugs.
Simulating conditions to test different hypotheses to understand how new systems or new products will work under different conditions. These tests can speed up the discovery of new materials, or while designing a new product. Conventionally testing new product designs would require actually creating a functional unit of the product and studying it under test conditions, which would cost a lot of time, and money. Simulations can also be used to recreate systems that are too big or too small to study by humans.
For instance, AI can be used to study materials on a molecular or atomic level to observe the interactions between those particles and understand intermolecular dynamics. This is made possible by programming the established laws of physics and the known behavior of the individual molecules into the simulation. The system simulates the interactions between different compounds in accordance with natural laws, under different conditions, which may be otherwise hard to recreate in the real world. This enables scientists to perform all kinds of ‘what if’ experiments and test a wide range of hypotheses. Similarly, scientists can also use AI to simulate large planetary bodies and their movements along with the laws that govern the outer space, so that they can solve the biggest astronomical mysteries such as discovering hidden planets and other celestial bodies.
Another futuristic application of AI in scientific discovery is to enable the exploration of places that humans cannot access. For instance, space exploration for astronauts is a long and strenuous process, and requires heavy equipment just to sustain them and requires a lot of time to train and prepare. To accelerate space exploration, we can program robots to venture into harsh regions in space armed just with a durable body and carrying much more equipment for gathering and analyzing data than can be sent with a human astronaut. This can allow more extensive research on different planets and eliminates the risk to human life in case of an accident. Similar applications can be used to explore places on earth with harsh conditions such as the depth of oceans.
Scientists are special people who are not only the smartest among us but also those who have committed their entire lives towards driving the progress of humanity and improving our understanding of the world around us. They are responsible for constantly pushing the boundaries of human knowledge as well as capabilities to ensure we have a better future. The AI revolution in science to will catalyze humanity’s collective effort to understand the world around us and to create technological tools to make our lives better.
