Can Faster Science Make the World Worse?

Modern societies treat scientific progress as an almost unqualified good. More papers, more labs, more funding, and faster breakthroughs are usually assumed to mean higher living standards and better futures. Yet as we develop powerful tools in biotechnology, artificial intelligence, and other sensitive domains, a pressing question arises: could speeding up science sometimes make the world worse rather than better?

This article draws inspiration from research and public discussions by economist Matt Clancy and others on the benefits and risks of accelerating science. It examines how science drives welfare, when it can increase existential threats, and what kinds of reforms and policies could make scientific progress more reliably positive for humanity.

Why Science Has Been Hugely Beneficial

To understand the stakes, it helps to recall why science has historically been a remarkable engine of progress.

• Health and longevity: Advances in medical science have driven large reductions in child mortality and dramatic increases in life expectancy through vaccines, antibiotics, and public health measures.
• Economic growth: Long-run economic growth models attribute most sustained increases in income per person to technological progress, which in turn builds on basic and applied science.
• Human capabilities: Science has enabled transformative tools such as electricity, computing, and the internet, expanding what individuals and societies can do.
• Knowledge spillovers: Discoveries in one field often spill over into others—for example, advances in physics feeding into materials science, electronics, and medical imaging.

Empirical work in the economics of innovation suggests that the social returns to research and development can be very high, often exceeding the private returns captured by firms. In other words, society as a whole typically benefits far more from new knowledge than the individual inventor or company that produces it.

How Faster Science Can Create New Dangers

Despite these large benefits, not every scientific advance is unambiguously good. Some discoveries introduce capabilities that can be misused or that increase systemic fragility.

Dual-Use Research and Weaponizable Knowledge

Many areas of science are dual-use: the same knowledge can underpin both beneficial technologies and dangerous applications.

• Biotechnology: Techniques for genetic engineering and viral manipulation enable vaccines and gene therapies but also the potential design of more transmissible or deadly pathogens.
• Nuclear physics: The science that led to nuclear power also enabled nuclear weapons, reshaping global security and creating the possibility of civilization-ending war.
• Cyber and AI tools: Research that improves secure communication or beneficial AI can also improve offensive cyber tools or autonomous weapons.

The risk is not merely hypothetical. Government and scientific bodies maintain lists of experimental approaches that are considered particularly risky—such as enhancing the transmissibility or virulence of pathogens—precisely because they could be misused for biological weapons.

When Acceleration Might Be Net Negative

Speeding up discovery in these areas can, in some scenarios, make the world more dangerous:

• Dangerous capabilities may become available before strong norms, regulations, or defense technologies are in place.
• Bad actors may exploit knowledge that becomes widely accessible through publications, preprints, or open-source code.
• States may enter destabilizing arms races in new domains like synthetic biology or AI-enabled weapons.

In extreme cases, if accelerated research disproportionately boosts offensive capabilities over defenses, the overall effect of faster science could be negative, at least for a period when societies remain unprepared.

Balancing Immediate Gains against Existential Risk

Assessing whether faster science is good overall requires weighing widely distributed, incremental benefits against low-probability but extreme harms, including existential risks.

Everyday Benefits vs. Catastrophic Downside

On the benefit side, faster science can:

• Improve treatments for common diseases and disabilities.
• Raise productivity, incomes, and standards of living.
• Help address climate change through low-carbon technologies.

On the risk side, accelerating sensitive research could:

• Increase the probability of global catastrophic biological events, whether accidental or deliberate.
• Shorten the time available for society to adapt and regulate powerful AI systems.
• Amplify geopolitical tensions as states rush to secure new military or strategic advantages.

Because global catastrophic risks involve very low probabilities but extremely large potential losses, even modest increases in risk can outweigh substantial economic gains in a formal cost-benefit framework.

Non-Philosophical Reasons to Discount the Far Future

Debates about existential risk often focus on ethical questions about how much weight to give future generations. But there are also more pragmatic, non-philosophical reasons some analysts discount very long-term impacts:

• Model uncertainty: The further into the future we look, the less reliable our models of technology, society, and politics become.
• Changing returns to science: Future science might have higher or lower marginal returns depending on whether we approach physical limits or unlock new general-purpose technologies.
• Path dependence: The value of additional discoveries may depend heavily on social and political choices that are themselves hard to predict.

Even acknowledging this, many researchers argue that we cannot ignore existential risks entirely, especially when current choices plausibly affect the probability of catastrophic outcomes in the next century.

How Science Policy Shapes Outcomes

Given that both benefits and risks depend on what kind of science we pursue, science policy becomes crucial. Governments, foundations, and major research institutions influence the direction, pace, and governance of scientific progress.

Key Policy Levers

Targeting “Use-Inspired” Research

One influential framework divides research into:

• Pure basic science (seeking fundamental understanding, with no immediate application in mind).
• Pure applied research (aimed directly at solving specific, practical problems).
• Use-inspired basic research (work that both seeks fundamental understanding and is motivated by real-world use cases).

Policymakers increasingly see use-inspired basic research as a high-leverage area, because it can generate deep scientific progress while also addressing important societal challenges such as pandemic preparedness or low-carbon energy.

Metascience: Improving How Science Works

Beyond deciding what to study, we can also ask whether the process of science could be improved. “Metascience“—sometimes called the science of science—studies how scientific institutions, incentives, and practices affect the quality and productivity of research.

Common Problems in the Current System

Researchers and policymakers have identified several recurring issues:

• Incentives to publish quantity over quality: Hiring and promotion often reward short-term publication metrics, not long-term, high-impact work.
• Publication bias and replication challenges: Positive and surprising results are favored over null findings, contributing to reproducibility problems in some fields.
• Conservative grantmaking: Peer-reviewed funding can be risk-averse, making it hard for unconventional but promising ideas to receive support.

Potential Metascience Reforms

Metascience experiments and proposals include:

• Alternative grant mechanisms: Lotteries among high-quality proposals, or funding people instead of projects, to encourage risk-taking and reduce administrative burdens.
• Better evaluation tools: Developing more reliable ways to forecast which lines of research will be impactful, potentially drawing on techniques from forecasting or expert elicitation.
• Open science practices: Pre-registration, data sharing, and replication incentives to raise reliability and transparency.

If science is on average beneficial, making it more efficient and better targeted could substantially increase social returns, even if we do not dramatically change total funding levels.

Science as a Tool for Risk Reduction

It would be a mistake to treat science only as a source of risk. In many cases, faster and better science is also our main hope for reducing existential threats.

Pandemic Preparedness

Scientific advances enabled the rapid development of vaccines and treatments for COVID-19, including the deployment of mRNA vaccines based on decades of prior research. Continued progress could:

• Shorten vaccine development timelines even further.
• Improve broad-spectrum antivirals and diagnostic tools.
• Support surveillance systems capable of detecting novel outbreaks early.

However, these benefits depend on governance choices: accelerating the beneficial side of life sciences while constraining experimentation and data sharing that could be readily weaponized.

AI for Threat Detection and Coordination

Artificial intelligence could assist in analyzing biological sequences, monitoring cyber threats, or optimizing energy systems, thereby reducing some risks. At the same time, advanced AI systems may themselves introduce novel dangers, from misuse in cyber operations to loss of human control.

Here too, the net effect depends on whether research and deployment are accompanied by robust safety standards, evaluation regimes, and international coordination.

Who Should We Trust about the Future of Science?

Forecasting the long-term impact of scientific progress is challenging. Different communities bring complementary strengths and limitations.

• Domain experts (e.g., virologists, AI researchers) understand technical details and feasibility constraints but may be overly optimistic about their own field.
• Generalist forecasters and risk analysts may be better at integrating cross-domain evidence and identifying structural uncertainties but can miss domain-specific nuances.
• Policymakers and institutions ultimately decide on regulations and funding, but their incentives may be shaped by short-term political pressures.

A pragmatic approach combines these perspectives: structured expert elicitation, transparent forecasting, and continuous feedback from real-world outcomes can all improve our ability to anticipate the consequences of accelerating science.

Practical Principles for Safer Scientific Progress

Given the complexity and uncertainty, there is no simple formula for whether we should speed up science broadly. Still, several practical principles emerge from current research and policy discussions:

• Differentiate fields: Treat areas like pandemic preparedness or clean energy differently from work that primarily increases offensive capability in biological or cyber domains.
• Emphasize defense-dominant research: Prioritize advances that make it easier to defend against many possible threats (e.g., broad-spectrum medical countermeasures, detection tools) over narrow offensive capabilities.
• Invest in metascience: Improve how research is funded, evaluated, and shared so that we get more value from each unit of effort.
• Build governance in parallel with capability: Develop regulatory, ethical, and safety frameworks as technologies advance, not decades afterward.
• Encourage international coordination: Where risks are global, standards and monitoring must also reach beyond national borders.

Frequently Asked Questions (FAQs)

Q1: Has science historically been net positive for humanity?

Most researchers in economics and public health argue that science has been strongly net positive, driving large increases in life expectancy, income, and quality of life. The concern is not about past science in general, but about how future advances in certain domains might alter risk profiles.

Q2: Does worrying about risks mean we should slow all scientific research?

No. Many areas of research—such as climate solutions, pandemic defenses, or safer energy systems—likely deserve more support. The debate focuses on how to steer or constrain specific kinds of work (for example, certain biological experiments or AI capabilities) that could significantly raise existential or catastrophic risks.

Q3: Can better policy really change the balance of risks and benefits?

Yes. Historical experience with nuclear technology, chemical weapons, and infectious disease control shows that treaties, regulations, and monitoring can reduce the misuse of dangerous knowledge while preserving many beneficial applications. Effective governance is difficult but not impossible.

Q4: What is metascience, and why does it matter for safety?

Metascience studies how research systems function—how funding, peer review, and incentives shape what scientists work on and how reliable their findings are. By reforming these systems, we can encourage more impactful, reliable, and safety-conscious research without necessarily increasing overall risk.

Q5: How can individuals interested in this topic contribute?

Potential paths include careers in science policy, biosecurity, AI governance, or metascience; support for organizations working on global catastrophic risk reduction; and participation in transparent forecasting and evaluation efforts that inform better decisions by funders and governments.

Written by

Medha Deb

Medha Deb is an editor with a master's degree in Applied Linguistics from the University of Hyderabad. She believes that her qualification has helped her develop a deep understanding of language and its application in various contexts. Medha specializes in the areas of beauty, health, sports, and wellness and is committed to ensuring that the content on the website is…