Tuesday, October 22, 2024

AI is set to transform science – but will we understand the results?

The Conversation
October 22, 2024 

SkillUp / Shutterstock

Artificial intelligence (AI) has taken center stage in basic science. The five winners of the 2024 Nobel Prizes in Chemistry and Physics shared a common thread: AI.

Indeed, many scientists – including the Nobel committees – are celebrating AI as a force for transforming science.

As one of the laureates put it, AI’s potential for accelerating scientific discovery makes it “one of the most transformative technologies in human history”. But what will this transformation really mean for science?

AI promises to help scientists do more, faster, with less money. But it brings a host of new concerns, too – and if scientists rush ahead with AI adoption they risk transforming science into something that escapes public understanding and trust, and fails to meet the needs of society.

The illusions of understanding

Experts have already identified at least three illusions that can ensnare researchers using AI.

The first is the “illusion of explanatory depth”. Just because an AI model excels at predicting a phenomenon — like AlphaFold, which won the Nobel Prize in Chemistry for its predictions of protein structures — that doesn’t mean it can accurately explain it. Research in neuroscience has already shown that AI models designed for optimized prediction can lead to misleading conclusions about the underlying neurobiological mechanisms.

Second is the “illusion of exploratory breadth”. Scientists might think they are investigating all testable hypotheses in their exploratory research, when in fact they are only looking at a limited set of hypotheses that can be tested using AI.

Finally, the “illusion of objectivity”. Scientists may believe AI models are free from bias, or that they can account for all possible human biases. In reality, however, all AI models inevitably reflect the biases present in their training data and the intentions of their developers.

Cheaper and faster science

One of the main reasons for AI’s increasing appeal in science is its potential to produce more results, faster, and at a much lower cost.

An extreme example of this push is the “AI Scientist” machine recently developed by Sakana AI Labs. The company’s vision is to develop a “fully AI-driven system for automated scientific discovery”, where each idea can be turned into a full research paper for just US$15 – though critics said the system produced “endless scientific slop”.


Do we really want a future where research papers can be produced with just a few clicks, simply to “accelerate” the production of science? This risks inundating the scientific ecosystem with papers with no meaning and value, further straining an already overburdened peer-review system.

We might find ourselves in a world where science, as we once knew it, is buried under the noise of AI-generated content.

A lack of context

The rise of AI in science comes at a time when public trust in science and scientists is still fairly high , but we can’t take it for granted. Trust is complex and fragile.

As we learned during the COVID pandemic, calls to “trust the science” can fall short because scientific evidence and computational models are often contested, incomplete, or open to various interpretations.

However, the world faces any number of problems, such as climate change, biodiversity loss, and social inequality, that require public policies crafted with expert judgement. This judgement must also be sensitive to specific situations, gathering input from various disciplines and lived experiences that must be interpreted through the lens of local culture and values.


As an International Science Council report published last year argued, science must recognize nuance and context to rebuild public trust. Letting AI shape the future of science may undermine hard-won progress in this area.

If we allow AI to take the lead in scientific inquiry, we risk creating a monoculture of knowledge that prioritises the kinds of questions, methods, perspectives and experts best suited for AI.

This can move us away from the transdisciplinary approach essential for responsible AI, as well as the nuanced public reasoning and dialogue needed to tackle our social and environmental challenges.

A new social contract for science

As the 21st century began, some argued scientists had a renewed social contract in which scientists focus their talents on the most pressing issues of our time in exchange for public funding. The goal is to help society move toward a more sustainable biosphere – one that is ecologically sound, economically viable and socially just.

The rise of AI presents scientists with an opportunity not just to fulfill their responsibilities but to revitalize the contract itself. However, scientific communities will need to address some important questions about the use of AI first.

For example, is using AI in science a kind of “outsourcing” that could compromise the integrity of publicly funded work? How should this be handled?

What about the growing environmental footprint of AI? And how can researchers remain aligned with society’s expectations while integrating AI into the research pipeline?

The idea of transforming science with AI without first establishing this social contract risks putting the cart before the horse.

Letting AI shape our research priorities without input from diverse voices and disciplines can lead to a mismatch with what society actually needs and result in poorly allocated resources.

Science should benefit society as a whole. Scientists need to engage in real conversations about the future of AI within their community of practice and with research stakeholders. These discussions should address the dimensions of this renewed social contract, reflecting shared goals and values.

It’s time to actively explore the various futures that AI for science enables or blocks – and establish the necessary standards and guidelines to harness its potential responsibly.

Ehsan Nabavi, Senior Lecturer in Technology and Society, Responsible Innovation Lab, Australian National University

This article is republished from The Conversation under a Creative Commons license. Read the original article.


 

Artificial intelligence is creating a new way of thinking, an external thought process outside of our minds



The 'System 0', which in the future will support and enhance our cognitive abilities, is the ongoing revolution described in the journal Nature Human Behaviour by a multidisciplinary group of scientists coordinated by experts from Università Cattolica, c



Universita Cattolica del Sacro Cuore





The interaction between humans and artificial intelligence is shaping a new thinking system, a new cognitive scheme, external to the human mind, but capable of enhancing its cognitive abilities. This is called System 0, which operates alongside the two models of human thought: System 1, characterized by intuitive, fast, and automatic thinking, and System 2, a more analytical and reflective type of thinking. However, System 0 introduces an additional level of complexity, radically altering the cognitive landscape in which we operate, and could thus mark a monumental step forward in the evolution of our ability to think and make decisions. It will be our responsibility to ensure that this progress will be used to improve our cognitive autonomy without compromising it.

 

This is reported by the prestigious scientific journal Nature Human Behaviour, in an article titled "The case for human-AI interaction as System 0 thinking" – [link](https://www.nature.com/articles/s41562-024-01995-5), written by a team of researchers led by Professor Giuseppe Riva, director of the Humane Technology Lab at Università Cattolica's Milan campus and the Applied Technology for Neuropsychology Lab at Istituto Auxologico Italiano IRCCS, Milan, and by Professor Mario Ubiali (I NEED THE COMPLETE AFFILIATION) from Università Cattolica's Brescia campus. The study was directed with Massimo Chiriatti from the Infrastructure Solutions Group, Lenovo, in Milan, Professor Marianna Ganapini from the Philosophy Department at Union College, Schenectady, New York, and Professor Enrico Panai from the Faculty of Foreign Languages and Language of Science at Università Cattolica's Milan campus.

 

A new form of external thinking

Just as an external drive allows us to store data that are not present on the computer, we can work by connecting our drive to a PC wherever we are, artificial intelligence, with its galactic processing and data-handling capabilities, can represent an external circuit to the human brain capable of enhancing it. Hence the idea of System 0, which is essentially a form of "external" thinking that relies on the capabilities of AI.

 

By managing enormous amounts of data, AI can process information and provide suggestions or decisions based on complex algorithms. However, unlike intuitive or analytical thinking, System 0 does not assign intrinsic meaning to the information it processes. In other words, AI can perform calculations, make predictions, and generate responses without truly "understanding" the content of the data it works with.

 

Humans, therefore, have to interpret on their ones and giving meaning to the results produced by AI. It's like having an assistant that efficiently gathers, filters, and organizes information but still requires our intervention to make informed decisions. This cognitive support provides valuable input, but the final control must always remain in human hands.

 

The risks of System 0: loss of autonomy and blind trust

 

“The risk,” professors Riva and Ubiali emphasize, “is relying too much on System 0 without exercising critical thinking. If we passively accept the solutions offered by AI, we might lose our ability to think autonomously and develop innovative ideas. In an increasingly automated world, it is crucial that humans continue to question and challenge the results generated by AI,” the experts stress.

 

Furthermore, transparency and trust in AI systems represent another major dilemma. How can we be sure that these systems are free from bias or distortion and that they provide accurate and reliable information? “The growing trend of using synthetic or artificially generated data could compromise our perception of reality and negatively influence our decision-making processes,” the professors warn.

 

AI could even hijack our introspective abilities, they note—i.e., the act of reflecting on one’s thoughts and feelings—a uniquely human process. However, with AI's advancement, it may become possible to rely on intelligent systems to analyze our behaviors and mental states. This raises the question: to what extent can we truly understand ourselves through AI analysis? And can AI replicate the complexity of subjective experience?

 

Despite these questions, System 0 also offers enormous opportunities, the professors point out. Thanks to its ability to process complex data quickly and efficiently, AI can support humanity in tackling problems that exceed our natural cognitive capacities. Whether solving complex scientific issues, analyzing massive datasets, or managing intricate social systems, AI could become an indispensable ally.

 

To leverage the potential of System 0, the study's authors suggest it is urgent to develop ethical and responsible guidelines for its use. “Transparency, accountability, and digital literacy are key elements to enable people to critically interact with AI,” they warn. “Educating the public on how to navigate this new cognitive environment will be crucial to avoid the risks of excessive dependence on these systems.”

 

The future of human thought

They conclude: If left unchecked, System 0 could interfere with human thinking in the future. “It is essential that we remain aware and critical in how we use it; the true potential of System 0 will depend on our ability to guide it in the right direction.”

 

People hate stories they think were written by AI. Even if they were written by people



University of Florida




Stories written by the latest version of ChatGPT were nearly as good as those written by human authors, according to new research on the narrative skills of artificial intelligence.

But when people were told a story was written by AI — whether the true author was an algorithm or a person — they rated the story poorly, a sign that people distrust and dislike AI-generated art. 

“People don’t like when they think a story is written by AI, whether it was or not,” said Haoran “Chris” Chu, Ph.D., a professor of public relations at the University of Florida and co-author of the new study. “AI is good at writing something that is consistent, logical and coherent. But it is still weaker at writing engaging stories than people are.”

The quality of AI stories could help people like public health workers create compelling narratives to reach people and encourage healthy behaviors, such as vaccination, said Chu, an expert in public health and science communication. Chu and his co-author, Sixiao Liu, Ph.D., of the University of Central Florida, published their findings Sept. 13 in the Journal of Communication.

The researchers exposed people to two different versions of the same stories. One was written by a person and the other by ChatGPT. Survey participants then rated how engaged they were with the stories.

To test how people’s beliefs about AI influenced their ratings, Chu and Liu changed how the stories were labeled. Sometimes the AI story was correctly labeled as written by a computer. Other times people were told it was written by a human. The human-authored stories also had their labels swapped.

The surveys focused on two key elements of narratives: counterarguing — the experience of picking a story apart — and transportation. These two story components work at odds with one another.

“Transportation is a very familiar experience,” Chu said. “It’s the feeling of being so engrossed in the narrative you don’t feel the sticky seats in the movie theater anymore. Because people are so engaged, they often lower their defenses to the persuasive content in the narrative and reduce their counterarguing.”

While people generally rated AI stories as just as persuasive as their human-authored counterparts, the computer-written stories were not as good as transporting people into the world of the narrative.

“AI does not write like a master writer. That’s probably good news for people like Hollywood screenwriters — for now,” Chu said.

 

World-first simultaneous lithium and magnesium extraction technology



Direct lithium extraction now possible from untapped extreme environments


Monash University

Symbolising the technology's innovative extraction of both lithium and magnesium 

image: 

Artwork created by students at the Monash Suzhou Research Institute symbolising the technology's innovative extraction of both lithium and magnesium.

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Credit: Image credit: Fangzhou Dong, Saifei Ma, Dihui Chu, Monash Suzhou Research Institute




Demand for lithium - critical to powering sustainable technologies - is rapidly growing but up to 75 percent of the world’s lithium-rich saltwater sources remain untappable using current methods.

With some predicting global lithium supply could fall short of demand as early as 2025, the innovative technology – EDTA-aided loose nanofiltration (EALNF) – sets a new standard in lithium processing. The technology uniquely extracts both lithium and magnesium simultaneously, unlike traditional methods that treat magnesium salts as waste, making it smarter, faster and more sustainable.

The work, co-led by Dr Zhikao Li, from the Monash Suzhou Research Institute and the Department of Chemical and Biological Engineering, and Professor Xiwang Zhang from the University of Queensland, promises to meet the surging demand for lithium and paves the way for more sustainable and efficient extraction practices.

Studies undertaken on brines from China’s Longmu Co Lake and Dongtai Lake, published today in Nature Sustainability, demonstrate how the innovative method could efficiently extract lithium from low-grade brines with high magnesium content. At the heart of the innovation is a type of nanofiltration that uses a selective chelating agent to separate lithium from other minerals, especially magnesium, which is often present in brines and difficult to remove.

“High-altitude salt brine flats in countries like China (Tibet and Qinghai) and Bolivia are examples of areas with tougher brine conditions that have traditionally been ignored. In remote desert areas, the vast amounts of water, chemicals and infrastructure required for conventional extraction just aren’t available either, underscoring the need for innovative technologies,” Dr Li said.

“With Monash University’s EALNF technology, these can now be commercially viable sources of lithium and valuable contributors to the global supply chain. Our technology achieves 90 percent lithium recovery, nearly double the performance of traditional methods, while dramatically reducing the time required for extraction from years to mere weeks.”

The technology also turns leftover magnesium into a valuable, high-quality product that can be sold, reducing waste and its impact on the environment.

Beyond its advanced efficiency, the EALNF system brings innovation to address major environmental concerns associated with lithium extraction. Unlike conventional methods that deplete vital water resources in arid regions, the technology produces freshwater as a by-product.

Dr Li said the system was flexible and ready for large-scale use, meaning it can quickly expand from testing to full industrial operations.

“This breakthrough is crucial for avoiding a future lithium shortage, making it possible to access lithium from hard-to-reach sources and helping power the shift to clean energy.”

https://doi.org/10.1038/s41893-024-01435-2

 

A breakthrough in the fight against greenhouse gases: Politecnico di Milano’s study on the cover of Angewandte Chemie



Research opens up new possibilities for clean energy production



Politecnico di Milano

The build-up of carbon on catalysts used for the thermocatalytic conversion of CO2 reduces the efficiency of these processes and represents a barrier to their industrial application 

image: 

The build-up of carbon on catalysts used for the thermocatalytic conversion of CO2 reduces the efficiency of these processes and represents a barrier to their industrial application. The research team headed by Prof. Matteo Maestri discovered that carbon formation is closely related to the ratio of carbon dioxide (CO2) to methane (CH4) present during the Dry Reforming reaction. The image, published on the front cover of the prestigious scientific journal Angewandte Chemie, expresses this concept and depicts a hot-air balloon flying over dark mountains, a metaphor for carbon formation. The COmolecules, present in greater numbers than the methane molecules in the basket, are the balloon’s driving force. Without the thrust provided by the CO2, the methane would tend to sink downwards, towards the undesirable formation of carbon.

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Credit: Politecnico di Milano




Milan, 22 October 2024 – Against the backdrop of the energy transition and the fight against climate change, a study conducted by Politecnico di Milano’s Department of Energy heralds in new ways of using greenhouse gases. Blazoned on the front cover of the prestigious scientific journal Angewandte Chemie, the research offers a new key to understanding how to improve the efficiency of processes that convert greenhouse gases into energy resources and reduce the impact of methane and CO2, two greenhouse gases responsible for global warming.

The research team headed by Prof. Matteo Maestri studied Dry Reforming, a chemical process that converts methane and carbon dioxide, two of the main greenhouse gases, into a synthesis gas that is used both in hydrogen production and in many sectors of the chemical and energy industries. Using supported metal nanoparticles as catalysts, the Dry Reforming process enables high conversions, accelerating the necessary chemical reactions.

However, one of the main obstacles to a more widespread application of this process is the build-up of carbon on the surface of the catalysts, a phenomenon that reduces their efficiency and makes them less suitable for large-scale use. Using operando Raman spectroscopy, an advanced technique that allows catalysts to be studied in real time during chemical reactions, the team discovered that the gradual formation of carbon is closely related to the ratio of carbon dioxide (CO2) to methane (CH4) present in the reaction.

Our work allowed us to observe how a catalyst transforms during the reaction,’ explains Prof. Matteo Maestri from the Department of Energy at Politecnico di Milano “Knowing this will help us improve the efficiency of catalysts, with a potentially significant impact on the reduction of greenhouse gas emissions and long-term energy sustainability.

The possibility of preventing or mitigating carbon build-up on catalysts paves the way for longer-lasting and more efficient technologies based on this reaction, offering new solutions for the use of CO2 biogas.