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Now & Next: Is AI revolutionising science?

Posted on 22 November 2024

This article was first published on The Economist Now & Next hub on 21 November 2024.

With AI turbocharging research—even powering robot scientists—a new era of faster, cheaper scientific discovery is under way

While most of the world has just started fixating on Artificial Intelligence (AI), it has actually been part of the scientific toolkit since the 1960s. For most of its life, the use of AI has been confined to disciplines like particle physics and mathematics, where practitioners are well versed in computer code. 

But now, just as AI is transforming almost every industry, it is also reshaping other scientific disciplines. The technology is a lot easier to use and more people—graduates in engineering and the sciences—know how to use it. According to CSIRO, Australia’s science agency, more than 99% of research fields were producing AI-related results by 2023. 

There are high expectations for AI to supercharge research and actually reimagine the scientific process. Scientists say that the technology is enabling them to look at problems in a different way—unleashing creativity, as well as enhancing efficiency and accuracy. For example, literature-based discovery uses AI to search through millions of research papers to find patterns and connections, and then suggest new hypotheses for scientists to investigate. It can even matchmake collaborators from different fields.

This is leading to ambitious ideas for how AI can address critical societal issues such as improving healthcare and combating climate change.

Finding the needle in the haystack

In the pharmaceutical industry, the protracted timelines and high costs of developing new drugs mean that new therapeutics for rare diseases are often considered uneconomic. However, AI tools are revolutionising the drug-discovery process, making it faster and cheaper to develop new treatments. Scientists predict that using AI in the preclinical stage of drug development could bring a time and cost saving of up to 50%. This has the potential to reshape the economics of the industry, and help people with rare and incurable conditions.

For example, AI-driven biotech company Insilico Medicine used AI to find a new treatment for idiopathic pulmonary fibrosis, a rare progressive illness of the respiratory system. Developed in 2020, the drug is now in phase 2 clinical trials, meaning it is being tested on patients with the condition. It took just 18 months and $3m to reach that stage—a fraction of the time and money normally spent.

Insilico was able to develop the treatment so quickly by using its Pharma.AI platform, which was built on years of modelling large biological, chemical and textual data sets. Similarly, Google DeepMind has created a resource for medical researchers by building a database of more than 200m protein structures. The database powers AlphaFold, an AI system that predicts a protein’s 3D structure from its amino-acid sequence. The system was used to find—in just 30 days—the structure of a protein that influences how a type of liver cancer spreads, paving the way for a new targeted treatment.

The scientist who never sleeps

Just as AI is used to automate the search for new drugs and speed the process, it is also being deployed to automate long sequences of high-frequency tasks in laboratories—something that humans cannot execute with such high levels of reproducibility.

The first fully autonomous mobile robotic chemist was created in 2020 at the University of Liverpool. Using AI to analyse data and make decisions on what experiments to do next, it navigates the lab by touch sensors and light detection and ranging. Operating on its own for eight days, the robot completed nearly 700 experiments—more than a PhD candidate would do in the four years it takes to earn their degree. It produced a photocatalyst (materials that change the rate of a chemical reaction on exposure to light—in this case, for hydrogen production from water) six times better than what human researchers had devised. 

The team that developed the robotic chemist now has two mobile robots, one working on catalysis research in the area of clean energy and the other on organic chemistry relevant to pharmaceuticals.

Keeping a (human) hand on the controls

AI promises to transform scientific research but, as in other spaces, it is not a silver bullet and must be used responsibly. Just as schoolchildren are using ChatGPT to write their essays, AI is being used by some scientists to write bogus research papers that are being published in scientific journals. This compromises the solid foundation of trustworthy findings that scientific research is based on. “Across all professions, technological progress can make us more productive, but it doesn't absolve us of the need to ensure that our output is accurate and will be used responsibly,” says Gareth Dickson, a partner at Mishcon de Reya. “That is especially true in research, where rigorous, informed peer review takes time but must be preserved given its critical role in generating trust in progress.”

“One of the key takeaways from the pandemic is that even some of those who stand to benefit from medical interventions can be quite easily led to believe that science cannot be trusted, that unusually rapid progress should be feared and that big pharma is spying on them,” notes Mr Dickson. “A careful balance must be maintained to ensure the unprecedented expansion of scientific discovery continues and is embraced by its intended beneficiaries, without stirring up greater suspicions." 

AI may be the tool but, in this case, it is the human editors and peer reviewers at journals who are not doing their jobs properly. More broadly, AI relies on humans choosing the data it learns from and creating the rules by which it operates. While it may take on more and more scientific roles, the humans remain in charge.

Alok Jha

Science and Technology Editor, The Economist

Is this the scientist of the future?  AI is driving a transformation across all fields of science.

Researchers have used AI to translate brain scans into text.

Alok Jha

Science and Technology Editor, The Economist

Promising to change how it’s done and turbo charge research.

Emily Shuckburgh

Director, Cambridge Zero

We are the start of a really important journey.

Alok Jha

Science and Technology Editor, The Economist

It could help to tackle some of the world’s most complex problems

It’s hoped that artificial intelligence will lead to break through drug discoveries.

Alok Jha

Science and Technology Editor, The Economist

Despite challenges and anxieties.

You are really delving into the unknown.

Alex Zhavoronkov

CEO, Insilico Medicine

Remember those early days when people were criticising.

Alok Jha

Science and Technology Editor, The Economist

Could AI prompt a new golden age of scientific discovery?

NOW&NEXT

Is AI revolutionising science?

Rhyl, Wales

Andy Davies

This is bear, the hair is my Siberian husky, 10 years old now but I can’t walk him anymore, he’s too strong.  Come here Bear.

Alok Jha

Science and Technology Editor, The Economist

In 2022 Andy Davies, a former soldier in the British Army was referred to hospital after suffering a persistent cough for several years.  His doctor diagnosed him with idiopathic pulmonary fibrosis, or IPF.  A lung condition in which the lungs become scarred and breathing becomes increasingly difficult.

Andy Davies

Thank you.  I should have like seven and a half litre capacity lungs.  I am down to about 4.6 litres so I look fine but I’m not fine, my lungs are getting smaller, the scarring is progressing and they will in time slowly suffocate me.  There’s nothing they can do for me bar the hope of a double lung transplant.

Alok Jha

Science and Technology Editor, The Economist

Ever since Andy has been trying to raise awareness about IPF and what it’s like to live with the condition.

Andy Davies

This is going to be my, my bedroom.  We are going to have a shower in here and hopefully I’m not going to need it just yet but getting up and down the stairs is getting more and more difficult.

Alok Jha

Science and Technology Editor, The Economist

With no cure available the outlook for people with IPF often feels bleak.  Half of patients die within 5 years of diagnosis.

Andy Davis

My mental health hit absolute rock bottom.  Then I started planning my funeral, I started picking my funeral songs and started doing all the things that I didn’t want other people to worry about doing.  I could have an exacerbation tomorrow, the scarring could progress and I could end up on full time oxygen, sat in the chair and that is the long and short of it and that happens, happens all the time to people with this, this awful disease.

Alok Jha

Science and Technology Editor, The Economist

Fortunately all may not be lost for those suffering from IPF.  Today there’s hope from a technology that’s disrupting the world, Generative AI.  These algorithmns are now being used to develop new drugs for diseases that are right now incurable. Alex Zhavoronkov runs a start-up called Insilico Medicine which in 2020 used AI to find a new treatment for idiopathic pulmonary fibrosis.

Alex Zhavoronkov

CEO, Insilico Medicine

We utilise generative AI to identify targets for proteins that are implicated in age related diseases and fibrotic diseases.

Alok Jha

Science and Technology Editor, The Economist

Insilico has created several AI pharmaceutical platforms.  One identifies the proteins in the body that might be targeted to influence the course of a disease.  Another can design potential new drug molecules.

Alex Zhavoronkov

CEO, Insilico Medicine

Instead of searching for a needle in a haystack, we can generate perfect needles with the desired properties.

Alok Jha

Science and Technology Editor, The Economist

And Insilico’s IPF drug is now in phase 2 clinical trials which means it’s currently being tested on patients with the condition.

It took just 18 months and only cost 3 million dollars to develop.  That’s a fraction of the time and money normally spent.  Using AI in the pre-clinical stage of drug development could bring a time and costs saving of 25-50%.

AI is also turbo charging aspects of biological research that have traditionally taken human scientists years.

A type of AI known as deep learning is powering Google DeepMind Alphafold.  This is an algorithm that can predict the shape of a protein from its amino acid sequence.  It’s not perfect, sometimes the shapes it predicts are wrong but Alphafold has built up a database of more than 200 million proteins and has been used by more than 2 million researchers according to Google DeepMind.

The efficiencies of cost and time on offer through AI have attracted big pharma particularly in China where investment in AI drug discovery topped 1.26 billion dollars in 2021.

Alex Zhavoronkov

CEO, Insilico Medicine

Drug discovery is forefront to many more players that are willing to bet a significant amount of capital so this democratisation, I think will lead to many more new therapeutics.

Alok Jha

Science and Technology Editor, The Economist

AI has been part of the scientific toolkit since the 1960’s.

Now here’s a man playing drums and his opponent a multi-million dollar computer.

Alok Jha

Science and Technology Editor, The Economist

For many decades it was limited to fields like mathematics or particle physics.  But in recent years the use of AI across all fields of science has exploded.

Regina Barzilay

AI Faculty Lead, MIT Jameel Clinic

Lots of graduates in engineering, in sciences are familiar with AI techniques and it is easier and easier to use them.

Alok Jha

Science and Technology Editor, The Economist

This change has empowered different kinds of AI to accelerate research in numerous fields of science.  At the University of Cambridge Emily Shuckburgh is a Professor of mathematics who specialises in using AI to improve climate science.

Emily Shuckburgh

Director, Cambridge Zero

The advances in our scientific understanding are currently not just incremental which often they are, but really leaps and bounds because of AI because it is enabling us to look at the problem in a different way.

Alok Jha

Science and Technology Editor, The Economist

Super resolution AI models can enhance low-res electron microscope images transforming images from this to this.  While a method called literature based discovery uses AI to search through millions of research papers to find patterns and connections and then suggests new hypothesis for scientists to investigate.  It can even match make collaborators from different fields.

And as well as new drug molicules AI algorithmns are helping to search for new materials for batteries and solar panels.  Improve weather prediction and transform our understanding of the mysteries of animal communication.

Tel Aviv, Israel

Alok Jha

Science and Technology Editor, The Economist

Here at the University of Tel Aviv, Adi Rachum and her colleagues are using AI in their very own bat lab.

Adi Rachum

Researcher, Yovel Lab, Tel Aviv University

Welcome to my colony.

Alok Jha

Science and Technology Editor, The Economist

These Egyptian fruit bats are recorded 24/7 to try and understand how they communicate with each other.

Adi Rachum

Researcher, Yovel Lab, Tel Aviv University

As you can see the colony was designed to mimic a cave as much as possible so the noises that they were making is because they were re-arranging.  This is part of what we are trying to learn using the communication, using the vocalisation.

Alok Jha

Science and Technology Editor, The Economist

The team uses an AI algorithm to link the calls with different behaviour patterns.

Adi Rachum

Researcher, Yovel Lab, Tel Aviv University

So I am watching a movie and I want to see what the bats are doing when they emit specific sounds.

Alok Jha

Science and Technology Editor, The Economist

AI helps the scientist to understand much more about what these individual sounds might mean.

Adi Rachum

Researcher, Yovel Lab, Tel Aviv University

In this case I consider they are fighting but the fighting is over food, it’s not just a random fight.  In the next movie, we can see that the communication is regarding mating.

Alok Jha

Science and Technology Editor, The Economist

They found that some aspects of bat communication are closer to human speech than previously thought.  The bats have their own dialects and the mother bats even use baby talk when communicating with their young.

Other scientists studying animal communication have used AI to spot regional accents among wolves and taken the first step towards decoding the sounds made by sperm whales.

However, some are sceptical about whether researchers in these fields will ever be able to record a representative range of sounds without introducing human bias into the data set.  It’s a potential pitfall Adi is conscious of.

Adi Rachum

Researcher, Yovel Lab, Tel Aviv University

It is always going to be human interpretation when we are talking about behaviour with animals but that’s why we have a lot of recordings to try to be as accurate as possible.

Alok Jha

Science and Technology Editor, The Economist

With all its promise to do good for science, AI could also end up accelerating the bad.  Fraudulent research has been under the microscope recently.

Analysis suggest that AI fakery in scientific journals is on the rise.  Some researchers have even been caught out after accidentally copying and pasting the phrase ‘regenerate response’ into their papers.

That’s the chatGTP button you press to make it re-write it’s latest answer.

Other data detectives have spotted the telltale appearance of AI generated gobbledygook in journals.

It’s the same tune and yet it’s different.

Alok Jha

Science and Technology Editor, The Economist

Big data is replaced by colossal information.  Random value is swapped for irregular esteem and artificial intelligence becomes counterfeit consciousness.  Experts have identified more than a thousand papers that seem to have identical AI produced images even though they were submitted by different labs.

Emily Shuckburgh

Director, Cambridge Zero

The absolute central pillar of the scientific world is publishing and in a sense it is how the body of scientific understanding is built upon over time.  There is obviously a role that it plays in the way in which you are judged as an individual scientist and consequently it’s also an area where there’s always concern as to whether or not there’s an opportunity for fraud to enter into that.

Liverpool, England

Alok Jha

Science and Technology Editor, The Economist

But like so many of the drawbacks we hear about AI, these are problems with us humans, not the machines.  Many scientists are optimistic and believe in the promise of a golden era of scientific discovery.

One where AI not only turbo charges research but also transforms the scientific process itself.

This robot at the University of Liverpool in Britain may look a tad unassuming but it could be a glimpse into that future.  In 2020 Andy Cooper decided to introduce some machine learning muscle into his chemistry lab.

Andy Cooper

Director, Materials Innovation Factory, University of Liverpool

We became aware of this rise of the use of mobile robots in other sectors such as automated manufacture warehouses and so on so we decided well rather than automate the instruments we will automate the chemist.

Alok Jha

Science and Technology Editor, The Economist

What he landed on was a roving robot, one that would navigate the lab by touch sensors and light detection and ranging, LIDAR.  Guided by AI this robot scientist uses the test results of one experiment to decide what to do next.

Andy Cooper

Director, Materials Innovation Factory, University of Liverpool

The robot did something like 700 experiments in this 8 day campaign and to reference that to a human chemist I’ve had PhD students previously working in the area of photo-catalysis and they wouldn’t have done that many photocatalytic experiments in a whole 4 year PhD.

Alok Jha

Science and Technology Editor, The Economist

Last year Andy’s team focussed on giving the robot scientist more sophisticated AI to test for new materials for clean energy production.

Or as the team called it, putting a brain into the robot.

Andy Cooper

Director, Materials Innovation Factory, University of Liverpool

We are now beginning to look at the use of large language models, chat GPT and other models to encode the space or to describe the space, that’s the first challenge.  The second challenge is to build in any kind of reasoning.

Alok Jha

Science and Technology Editor, The Economist

And now there’s a double act.

Andy Cooper

Director, Materials Innovation Factory, University of Liverpool

We have two mobile robots here.  This one is configured to do organic chemistry relevant to pharmaceuticals and the second one is configured to do catalysis research in the area of clean energy.  You can imagine the scenario when a large pharmaceutical lab where you have 50 fume cupboards, 20 different instruments.  We wanted to show that you could have a team of mobile robots that might be deployed in a much larger lab.

Alok Jha

Science and Technology Editor, The Economist

Unlike their human counterparts, robots can work 24/7, well at least until they need to recharge their batteries.

As a result robot scientists or self-driving labs like these could ultimately make science more productive and they can also help with what’s known as the reproducibility crisis.  There isn’t much  kudos in repeating work that’s already been done or publishing failures so human scientists tend to dodge doing this.  AI not only doesn’t suffer those hang-ups but also promises an ability to think outside the box.

Andy Cooper

Director, Materials Innovation Factory, University of Liverpool

I think ultimately the core idea is to find chemistry that helps humanity.  I think the sort of breakthrough moment which I would say hasn’t quite happened yet is when one of these systems finds something and people say that simply couldn’t realistically have been conceived by humans alone.

Alok Jha

Science and Technology Editor, The Economist

Lots of technologies through history have been hailed as the answer to the problems of human kind a usually nothing lives up to such a billing.

In the 1850’s the electric telegraph was expected to usher in world peace by bringing countries closer together, while pundits in the 1990’s said the internet would reduce inequality by making a first class education available online.  But there are stronger grounds to believe that AI could indeed deliver something huge for scientific research.

A new golden age of discovery perhaps.  Something like the one kick started by the scientific journal or the introduction of the laboratory.  However for AI to truly realise its full potential, scientists have to be willing and able to use it on a much broader scale.

Regina Barzilay

AI Faculty Lead, MIT Jameel Clinic

You need to have the fine detailing, to have the right regulation, you need to monetise it correctly.  AI technologies move so very fast but all this other aspects which require human intervention and human decision making is something that needs to be really prioritised.

Alok Jha

Science and Technology Editor, The Economist

Overcome these human obstacles and AI could change science and the world for the better.

Regina Barzilay

AI Faculty Lead, MIT Jameel Clinic

We are entering the beautiful space where AI and sciences can really create something novel and new.

Alok Jha

Science and Technology Editor, The Economist

Hello, I’m Alok Jha, Science and Technology Editor at The Economist.  If you’d like to read more about AI’s impact on science then click on the link opposite and if you’d like to watch more of our NOW&NEXT series, click on the other link.  Thanks for watching and please don’t forget to subscribe.

 

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