Who Gets Access to Automated Science Infrastructure?

Introduction

If AI dramatically increases the number of scientific ideas humanity can generate, then access to experiments may become one of the most important bottlenecks in the future of discovery. Cloud laboratories are an attempt to solve that problem by turning scientific experimentation into something closer to cloud computing: researchers write protocols through software, automated equipment performs the work remotely, and results are returned over the internet.[Wikipedia]WikipediaCloud laboratoryCloud laboratory

For advocates of scientific acceleration, the appeal is obvious. A graduate student in Nairobi, a startup in Manchester, or a researcher working from home could theoretically access advanced laboratory equipment without building a multimillion-pound facility. Yet the same model raises a deeper question about the future of AI-enabled science: if automated laboratories become the infrastructure through which discovery increasingly flows, who owns that infrastructure, who gets access to it, and on what terms? The answer could shape whether faster science becomes broadly available or concentrated in a relatively small number of firms, governments, and elite institutions.

How cloud laboratories could change research

Cloud laboratories emerged from a simple observation. Much of modern experimental science depends on expensive instruments that often sit idle, require specialist staff, and are difficult for smaller organisations to access. Instead of every institution buying its own equipment, cloud labs attempt to pool capacity into highly automated facilities that can be accessed remotely.[Wikipedia]WikipediaEmerald Cloud LabECL remotely conducts experiments in a automated ECL facility exactly to the scientist's specifications. The platform…

In practice, researchers design experiments through software interfaces or application programming interfaces (APIs). Robots, liquid handlers, sequencers, analytical instruments, and other equipment execute the procedures automatically. Data are collected and returned digitally, often with extensive records of settings, environmental conditions, and procedural details.[Wikipedia]WikipediaCloud laboratoryCloud laboratory[Wikipedia]WikipediaEmerald Cloud LabECL remotely conducts experiments in a automated ECL facility exactly to the scientist's specifications. The platform…

This model matters because it changes the economics of experimentation in several ways:

The comparison with cloud computing is not accidental. Just as software developers gained access to vast computing resources without owning data centres, cloud laboratories aim to provide experimental capacity without requiring every research group to own a fully equipped facility.

For the broader AI bloom vision, this is important because it potentially converts intelligence into physical scientific progress more efficiently. An AI model that proposes promising drug candidates becomes much more valuable if it can immediately trigger laboratory tests rather than waiting weeks or months for scarce human-run experiments.

From laboratory ownership to laboratory access

Historically, scientific capability has often depended on physical location. Researchers at wealthy universities or major pharmaceutical firms could access instruments unavailable elsewhere.

Cloud laboratories partially decouple capability from location. A scientist’s ability to conduct certain experiments becomes less dependent on where they live and more dependent on software access, funding, and permissions. Theoretically, this could widen participation in advanced science. Researchers in regions with weaker laboratory infrastructure could gain access to tools that previously existed only in a handful of elite centres.[The Guardian]theguardian.comcloud labs and remote research arent the future of science theyre hereThe GuardianCloud labs and remote research aren't the future of science11 Sept 2022 — Cloud labs mean anybody, anywhere can conduct exper…

Some proponents describe this as a democratisation of experimental science. Cloud labs can reduce the need for local infrastructure while making protocols easier to share, reproduce, and audit. Carnegie Mellon University’s effort to build an academic cloud laboratory reflects part of this vision: treating advanced experimentation as a shared research utility rather than a collection of isolated local facilities.[Wikipedia]WikipediaEmerald Cloud LabECL remotely conducts experiments in a automated ECL facility exactly to the scientist's specifications. The platform…

Yet access is not the same as ownership. The same system that expands access can also centralise control.

Why AI makes the access question more important

The significance of cloud laboratories increases as AI systems become better at generating hypotheses.

Traditional science often faced a shortage of ideas relative to experimental capacity. Increasingly, researchers face the opposite problem. AI systems can generate large numbers of candidate molecules, biological pathways, materials designs, and experimental plans. The challenge becomes testing them.[Wikipedia]WikipediaEmerald Cloud LabECL remotely conducts experiments in a automated ECL facility exactly to the scientist's specifications. The platform…

A future closed-loop research system might operate continuously:

If such systems become common, access to experimental throughput could become as strategically important as access to computing power is today.

That creates a potential division between two futures.

In one future, experimental infrastructure becomes widely available. Universities, startups, independent researchers, public institutions, and developing countries gain access to large pools of automated capacity. Scientific productivity rises broadly.

In the other future, a small number of organisations own most high-performance experimental infrastructure. Discovery accelerates, but access to that acceleration becomes highly unequal.

The difference is not merely technical. It is political and economic.

The economics of shared experimental capacity

Cloud laboratories promise efficiency because laboratory equipment is expensive and often underutilised.

A sequencing platform, robotic workstation, or analytical instrument may cost hundreds of thousands or millions of pounds. Small research groups often cannot justify purchasing such equipment for occasional use. Centralisation allows costs to be spread across many customers.[Wikipedia]WikipediaEmerald Cloud LabECL remotely conducts experiments in a automated ECL facility exactly to the scientist's specifications. The platform…

This resembles the logic that drove cloud computing. Instead of every company operating its own servers, many rent computing power from a small number of providers.

The economic advantages are substantial:

But the analogy with cloud computing also highlights potential risks.

Large cloud-computing markets became dominated by a relatively small number of firms. If scientific experimentation follows a similar path, research capacity could become concentrated in a handful of providers controlling critical infrastructure.

Scientific infrastructure as a platform business

Several cloud-lab companies already describe themselves in platform terms rather than purely laboratory terms.

Strateos, for example, has increasingly emphasised software platforms that coordinate automated laboratory operations and connect remote users with experimental infrastructure. Partnerships with pharmaceutical firms have explored remote-controlled laboratory access and workflow automation. Pubs - Bio-IT World[Business Wire]businesswire.comStrateos Launches its SmartLab Software Platform to…13 Jul 2021 — Hybrid cloud solution enables research teams to drive more efficient…

Emerald Cloud Lab presents itself as a comprehensive remote laboratory environment that can support startups, academic projects, industrial research, and AI-driven experimentation from anywhere with an internet connection.[emeraldcloudlab.com]emeraldcloudlab.comEmerald Cloud Lab: Remote Controlled Life Sciences LabEmerald Cloud Lab is a highly automated remote controlled life science laboratory i…

Platform businesses often benefit from scale effects. More users justify more equipment. More equipment attracts more users. Data accumulation can improve workflows and automation systems. These dynamics can make markets efficient while simultaneously concentrating power.

For science, that concentration could matter far beyond ordinary business competition because access to experimentation directly affects who can discover, invent, and publish.

Could cloud labs widen global scientific participation?

One of the strongest arguments for cloud laboratories is that they may reduce geographical inequalities in research.

Many universities around the world have talented researchers but limited access to expensive instruments. Building advanced facilities requires capital, supply chains, maintenance expertise, and regulatory support that are unevenly distributed across countries.

Remote access changes part of that equation.

A cloud laboratory cannot solve every problem. Researchers still need education, funding, internet access, materials, and scientific communities. Yet it could lower one important barrier: physical proximity to sophisticated equipment.[The Guardian]theguardian.comcloud labs and remote research arent the future of science theyre hereThe GuardianCloud labs and remote research aren't the future of science11 Sept 2022 — Cloud labs mean anybody, anywhere can conduct exper…

This possibility matters for the broader AI bloom thesis because scientific potential is widely distributed while scientific infrastructure is not. If automated laboratories allow more people to contribute to discovery, the effective pool of human and machine intelligence working on major problems could expand significantly.

Areas that might particularly benefit include:

• Rare disease research with limited local funding.
• Agricultural research relevant to developing regions.
• Materials science and energy research.
• Synthetic biology and biotechnology education.
• Startup ecosystems outside traditional scientific hubs.

The optimistic case is not that geography disappears, but that access to experimentation becomes less dependent on geography than it is today.

Governance risks around access and concentration

The same features that make cloud laboratories attractive also create governance challenges.

Traditional laboratories distribute power across thousands of institutions. Cloud models tend to centralise it. A provider can determine pricing, eligibility, permitted research categories, data policies, and operational priorities.

As automated science becomes more important, these decisions become increasingly consequential.

Who decides what research is allowed?

Cloud-lab operators already review experiments and maintain screening systems for safety and legal compliance. Providers argue that centralisation can actually improve oversight because activities are logged, monitored, and auditable.[Wikipedia]WikipediaEmerald Cloud LabECL remotely conducts experiments in a automated ECL facility exactly to the scientist's specifications. The platform…

Yet centralisation also creates gatekeepers.

A small number of organisations may gain influence over:

These decisions may be justified on safety grounds. But they can also shape the direction of science itself.

The question becomes particularly sensitive when scientific infrastructure crosses national boundaries. A laboratory physically located in one country may serve researchers in dozens of others, each operating under different legal and political frameworks.

The risk of experimental inequality

Access restrictions need not be explicit to create unequal outcomes.

Pricing alone can determine who benefits.

If automated experimentation substantially accelerates discovery, then researchers with large budgets may gain disproportionate advantages. Wealthy pharmaceutical firms, major technology companies, and well-funded universities could purchase far more experimental cycles than smaller competitors.

This dynamic already exists in science. The concern is that highly automated systems could magnify it.

In a world where scientific progress increasingly depends on the speed of AI-guided experimentation, unequal access to experimental throughput may become as important as unequal access to computing resources.

Data, lock-in, and scientific dependence

Another governance issue concerns data ownership and portability.

Cloud laboratories often store protocols, metadata, workflows, and results within integrated software environments. This improves reproducibility and collaboration. It can also create dependencies.

Researchers may become locked into particular platforms if:

Similar concerns emerged in cloud computing and enterprise software. Scientific infrastructure may face comparable debates over interoperability, portability, and open standards.[Wikipedia]WikipediaEmerald Cloud LabECL remotely conducts experiments in a automated ECL facility exactly to the scientist's specifications. The platform…

Why biosecurity concerns shape access debates

Cloud laboratories occupy an unusual position in science policy because access and security are tightly connected.

Traditionally, biological research often assumed physical presence inside a laboratory, local supervision, institutional review, and direct observation of researchers. Remote automated laboratories weaken some of those assumptions.[biosecurityhandbook.com]biosecurityhandbook.comCloud Labs and Automated BiologyThey disrupt every assumption traditional biosecurity relies on: physical presence…

Security researchers have argued that cloud labs create new governance questions because individuals can potentially design experiments remotely while robotic systems perform the physical work elsewhere. RAND researchers have similarly examined how cloud laboratories intersect with automation, AI, and emerging biosecurity concerns.[RAND Corporation]rand.orgRAND PEA3851 1RAND CorporationDocumenting Cloud Labs and Examining How Remotely…by G ZILGALVIS · 2025 — Cloud labs, which are facilities that allow…

This does not automatically imply that cloud laboratories are dangerous. Centralised facilities may actually be easier to monitor than thousands of independent laboratories. Providers can log activities, screen requests, and maintain standardised safety systems.[Wikipedia]WikipediaEmerald Cloud LabECL remotely conducts experiments in a automated ECL facility exactly to the scientist's specifications. The platform…

The challenge is balancing two legitimate goals:

• Making scientific capability broadly available.
• Preventing harmful or reckless use.

The tension is likely to become sharper if future AI systems become increasingly capable of generating experimental plans autonomously.

What would broadly shared scientific infrastructure look like?

The long-term importance of cloud laboratories may depend less on the technology itself than on the institutional choices surrounding it.

Several governance models are possible:

Each model involves trade-offs between efficiency, openness, security, innovation, and public accountability.

For supporters of the AI bloom vision, the central issue is not merely whether automated science becomes faster. It is whether the infrastructure that enables faster science becomes broadly accessible enough to expand humanity’s collective capacity for discovery.

If AI increasingly generates hypotheses while cloud laboratories increasingly test them, experimental access may become one of the defining governance questions of scientific acceleration. The future of abundance in knowledge, medicine, energy, and technology could depend not only on how intelligent our systems become, but on who is allowed to use them.[RAND Corporation]rand.orgRAND PEA3851 1RAND CorporationDocumenting Cloud Labs and Examining How Remotely…by G ZILGALVIS · 2025 — Cloud labs, which are facilities that allow…

Amazon book picks

Further Reading

Books and field guides related to Who Gets Access to Automated Science Infrastructure?. Use these as the next step if you want deeper reading beyond the article.

Book

The Coming Wave

By Mustafa Suleyman

Addresses concentration, access and governance around powerful AI-enabled infrastructure.

See on Amazon

Book

The Genesis Machine

By Amy Webb, Andrew Hessel

Cloud labs sit within the same shift toward remotely accessible, automated biological experimentation.

See on Amazon

Book

The Entrepreneurial State

By Mariana Mazzucato

Helps frame who funds, owns and benefits from shared scientific infrastructure.

See on Amazon

Book

Platform Capitalism

By Nick Srnicek

Relevant to concerns that automated science infrastructure could become platform-controlled.

See on Amazon

Browse more on Amazon:The Coming WaveThe Genesis MachineThe Entrepreneurial State

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Endnotes

1. Source: Wikipedia
Title: Cloud laboratory
Link:https://en.wikipedia.org/wiki/Cloud_laboratory

2. Source: emeraldcloudlab.com
Link:https://www.emeraldcloudlab.com/

3. Source: Wikipedia
Link:https://en.wikipedia.org/wiki/Emerald_Cloud_Lab

4. Source: rand.org
Title: RAND PEA3851 1
Link:https://www.rand.org/content/dam/rand/pubs/perspectives/PEA3800/PEA3851-1/RAND_PEA3851-1.pdf

5. Source: biosecurityhandbook.com
Title: Cloud Labs and Automated Biology
Link:https://biosecurityhandbook.com/ai-biosecurity/cloud-labs.html

6. Source: bio-itworld.com
Link:https://www.bio-itworld.com/news/2021/07/13/strateos-makes-cloud-lab-software-available-to-in-house-labs

7. Source: go.strateos.com
Title: Strateos CompanyFactSheet Oct2021 V2
Link:https://go.strateos.com/hubfs/Website%20URLs/Media%20Kit/Strateos_CompanyFactSheet_Oct2021%20V2.pdf

8. Source: theguardian.com
Title: cloud labs and remote research arent the future of science theyre here
Link:https://www.theguardian.com/science/2022/sep/11/cloud-labs-and-remote-research-arent-the-future-of-science-theyre-here

9. Source: egnyte.com
Title: cloud labs
Link:https://www.egnyte.com/guides/life-sciences/cloud-labs

10. Source: businesswire.com
Link:https://www.businesswire.com/news/home/20210713005442/en/Strateos-Launches-its-SmartLab-Software-Platform-to-Power-the-Digital-Transformation-of-Life-Science-Research-Laboratories

Additional References

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Link:https://aws.amazon.com/startups/learn/how-emerald-cloud-lab-is-revolutionizing-the-laboratory-using-aws

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