Eurasia Press & News
Abstract: Driven by digital technologies and commercial processes, the field of biology has fundamentally evolved, with widespread implications for war and peace. Biology’s trajectory resembles the advancement of computer software and hardware during the 20th century, making the tools to manipulate life open and accessible. Today, it is easy to read (DNA sequencing), write (DNA synthesizing), alter (gene editing), and share (via the internet) genetic code. Addressing biosecurity requires expertise in computer science, data analysis, and artificial intelligence. Bioterrorism with known agents remains a concern, but the greater threat will be novel risks from trained insiders, unethical tinkerers, and state-sponsored proxies.
Many people worldwide can now read, write, alter, and share the building blocks of life. This development is as significant as the invention of the printing press or the discovery of human genetics, and it is changing what biology is and why it matters. Biology has become engineering, using computer power to make or create anything with a genetic code. New tools and approaches emerge daily, especially at the intersections of biology, materials science, computing power, big databases, and artificial intelligence. So, assessing the security risks and opportunities of today’s rapidly developing biotechnology demands a broad focus and agile thinking, or we will miss things.
The standard approach of using historical incident data or case studies of terrorist attacks or bioarms programs may not take account of radical developments in biotechnology. Life’s software and the hardware to dissect it are evolving. Driven by a juggernaut of commercial profit-making, a biological revolution is unfolding that echoes the computer revolution of the last century, and it is directly or indirectly affecting everything, including war and peace, as well as the impact, likelihood, and provenance of bioweapons.
What follows first is a description of the broad global revolution underway in biology, especially its open patterns of technological innovation, which differ from those of the 20th century. Our thinking and frameworks must also change. Second, it explains how progress in biotechnology echoes the evolution of computer software, programming cells as if they were individual computers. Biological hardware is also evolving, the third section argues. It is getting smaller, cheaper, and more accessible—just as computers evolved from mainframes to laptops in the last century. But truly understanding bioweapons requires looking not only at biology but also at clusters of new digital technologies, and the fourth section explains why and what these are. Fifth, given all these new developments, we examine the implications for bioterrorism. The sixth section considers where the greatest future threats are emerging—notably insider threats, unethical tinkerers, and proxies clandestinely supported by states. Finally, the conclusion draws together the themes and suggests policy solutions.
The Open Biology Revolution
The field of biology has changed in the past five years, and commercial processes drive those changes. Reading (DNA sequencing), writing (DNA synthesizing), altering (gene editing), and sharing (via the internet) genetic code is now easily done. In assessing what this means for future threats, looking exclusively to states, conventions, and treaties will only get you so far. Without understanding the full scope of capabilities and techniques that private biotech companies are developing, you cannot see where we are headed in terms of both risks and opportunities.
States dominated technological innovation in the 20th century. Military or scientific elites limited the availability of new technologies—things like nuclear, chemical, or biological weapons. Biological agents such as smallpox or anthrax, or Yersinia pestis (which causes plague) were hidden away in secret biological weapons facilities. Those clandestine, well-equipped laboratories required high levels of expertise, were protected by security classifications, and were very difficult to find. We spoke of the ‘proliferation’ of known bioweapons and used phrases like ‘dual use,’ meaning they had two types of users: civilian and military.
Now, given the widespread ability to create new molecules or alter existing bacteria and viruses, the term ‘proliferation’ seems inadequate. Synthetic biology and gene editing mean we may not even know what new agents or living organisms to track.1 ‘Diffusion’ better captures the concept.2 Plus, there are many types of users: professionals in private companies or universities, government scientists, “prosumers”3 (amateurs with professional equipment and interest), hobbyists (as in, the makers’ movement), and even amateurs—all well beyond ‘civilian’ and ‘military.’ The phrase ‘dual use’ is an anachronism. As Kenneth Wickiser and his co-authors concluded in this publication in August 2020, “As the technology improves, the level of education and skills necessary to engineer biological agents decreases. Whereas only state actors historically had the resources to develop and employ biological weapons, SynBio is changing the threat paradigm.”4
In the last century, we also built a robust international structure of treaties and conventions that curbed the worst state excesses, notably the 1975 Biological Weapons Convention.5 According to NDU biological weapons expert Seth Carus, in the years between 1915 and 2015, the maximum number of state biological weapons programs operating simultaneously was eight, with some existing for very short periods.6 It was not perfect: Western intelligence agencies failed to identify the Soviet Union’s large covert biological weapons program, along with those of Iraq, South Africa, Chile, and what was then Rhodesia.7 But overall, this state-centered approach stigmatized and reduced the military use of biological weapons.8
Now, patterns of innovation in biology are far more open.9 Virtually all of today’s technological advances were first initiated by publicly financed basic and applied government research during the Cold War, then commercialized in the 1990s, which vastly sped up technological progress. Genetic engineering started in 1973, when biologists Herbert Boyer and Stanley Cohen first cut a gene from one bacterium and implanted it into another.10 The field developed very slowly at first. But with advances in computing power, data storage, and machine learning at the end of the century, a wider range of scientists in private companies and universities began working on things like gene editing, synthetic biology, and using open-source datasets and AI to discover new molecules. They are producing exciting new developments that could help feed the world’s population, cure diseases, create new biofuels, and mitigate climate change.
But open technological innovation is also much harder to monitor.11 For good or ill, innovation in the life sciences is driven by commercial processes that lie outside traditional state purview. In this respect, it echoes the development of digital computers, especially commercial software, hardware, and expanding computing power.
Biological Software
Progress in biotechnology is deeply entwined with the development of digital technologies, especially computers. Both the hardware and software of biotechnology are changing rapidly, and that magnifies the risks.
This relationship to computers is not accidental. One of the founding pioneers of synthetic biology was MIT-trained computer engineer Tom Knight, who was also co-engineer of ARPANETa and spent the late 1960s and 1970s designing hardware and software at the MIT Computer Science and Artificial Intelligence Laboratory. In the 1990s, Knight went back to school to learn about biology, and then he set up a molecular biology lab within MIT’s computer science lab.12 Progress in biotechnology and computer science has been deeply intertwined ever since.
It is easier to see how commercial biotechnology patterns are unfolding if we briefly reprise the recent evolution of computer software and hardware. At the beginning of the computer age, hardware was king—clunky, expensive, and rare. By contrast, software was built collaboratively and shared. Early pioneers thought that hardware was something you paid for, while software was something you copied and shared. Indeed, in the 1970s, part of the hacker’s credo was “software wants to be free.”
When Bill Gates was first getting his start, for example, Microsoft’s BASIC spread freely among hobbyists. A crucial turning point was Gates’ 1976 “Letter to Hobbyists,” published in the Homebrew Computer Club newsletter, insisting that software should be paid for. This planted the seed of Microsoft’s business model. Gates’ software was good quality and designed to run on many types of machines, which enabled Microsoft’s software to drive the market, ultimately displacing the dominance of hardware built by powerhouses like IBM.13
Still, the communitarian ethos of computer hackers building and sharing their code for free never went away. Today, the free and open-source software movements remain potent forces that make software accessible and alterable by everyone. Richard Stallman and Linus Torvalds created the GNU and Linux open-source operating system that has been ported to more hardware platforms than any other operating system.14
A similar dynamic is happening in the biotech industry. The goal of synthetic biology companies is to program cells as if you were programming individual computers. DNA is treated as if it were code for digital software, but instead of zeros and ones, it has ATGC (Adenine, Thymine, Guanine, and Cytosine), DNA’s nitrogenous bases, as its code. The business model is predicated on building molecules essentially at cost, then licensing the right to use them, as Microsoft does its software. Now, synthetic biology companies like Gingko Bioworks own databases of new biological material at a vast scale. Like Microsoft, these biotech companies are by far the most important actors in the market, but they do not have a monopoly on the ability to create new organisms. With the right training and hardware, virtually anyone can do that.
Biological Hardware
Even in hardware, the biotech industry is following the same route the computer industry followed, decentralizing from mainframes to desktops, to laptops, to smartphones, making them more user-friendly and affordable. Makers movement and makerspace companies such as Genspace, BioCurious, and ChiTownBio have built user-friendly bio labs designed to help people experiment, especially with basic synthetic biology. The Open Source Hardware Association and related initiatives leverage 3D printing and other accessible forms of manufacturing to widen public access to science.15 These initiatives are excellent ways to bring more ordinary people into science, which is vital, and makers labs will never compete with high-end microbiological laboratories; but they do widen access to the capacity to write, edit, copy, and create new or altered organisms.
Bioprinters are the next evolution in this process. These are various types of additive manufacturingb printers that create layered arrangements of cells and support structures that theoretically could facilitate the production and delivery of biological weapons.16 Desktop bioprinters are becoming cheaper, smaller, and more accessible, and they will soon be as available as desktop printers are.
With biohacking and the makers movement, barriers to entry in gene editing are lower than they used to be. Kids can buy bacterial gene-engineering kits online for $169, and a whole genetic engineering home lab kit for less than $2,000.17 High school students compete in gene editing. The annual International Genetically Engineered Machine (iGEM) competition encourages undergraduates to create novel products via synthetic biology.18 This is mostly good, as we want people to learn to use new technology ethically, and proctored school competitions are the perfect place to teach ethical guidelines and behavior. But not everyone gets that ethical training, and experts do not even agree on what ethical oversight of biohacking should look like.19
These experiments are not advanced molecular biology, of course, and compared to that, their risk is minimal. Amateurs do not have the tacit knowledge to produce a serious threat. Certainly, this is not sophisticated biology, like editing the human genome or designing a new biological agent from scratch. But prosumers and hobbyists can do a lot more than they used to be able to do, and some of that capability is also more dangerous than it used to be. As has been well covered by other analysts,20 it is a matter of lowering the threshold of access and use, to incorporate broader numbers of people.
Like digital computers, both the software and the hardware of biology are evolving. The field is also more widely accessible and more deeply intertwined with other disciplines than it used to be. That is driving surprising new developments—especially across the full range of new and emerging digital technologies.
Clusters of Digital Technologies Are Key
We can only fully understand the threat of bioweapons if we think in terms of clusters of new and emerging technologies. Existing pathogens such as those that cause anthrax, Ebola, smallpox, tularemia, and plague, covered under the biological weapons convention, are deadly enough. But advances in materials science, computer processing power, and autonomy have brought changes in delivery systems and threat vectors.
Analysts have warned for years that autonomous drone swarms could deliver known biological or chemical agents by dispersing them over military forces or civilian populations.21 If an individual or group were able to gain access to a weaponizable pathogen, it would be feasible to use unmanned aerial vehicles to scatter it—although, as we also know from the experience of the Japanese group Aum Shinrikyo, weaponizing a pathogen (in Aum’s case, C. botulinum and B. anthracis) is a key challenge.c (To kill, maim, or intimidate civilian populations, groups are more likely to use small explosives, which are much easier to obtain.) Still, accessible, small drones are coming of age in Ukraine, where small-scale, off-the-shelf commercial drones are being used at an unprecedented scale, and extremists are presumably taking note.
But to fully understand where we are headed longer term, we must also dig deeper into the evolving nature of biotechnology itself. The field is converging with engineering, chemistry, mathematics, quantum mechanics, computer science, and information theory.22 The intersections between these areas of study are reshaping the entire landscape of what biology actually is, which in turn changes our focus regarding what a biothreat in the 21st century could look like. The most dangerous threats are coming not just from biology, but from the intersections between disciplines.
For example, in early 2022, scientists from the company Collaborations Pharmaceuticals tweaked their machine learning model and came up with a scary result that shocked them. The Swiss Federal Institute for Nuclear, Biological and Chemical Protection (Spiez Laboratory) had convened its biennial conference to study how new technological developments might affect the chemical and biological weapons conventions. Collaborations Pharmaceuticals, based in Raleigh, North Carolina, uses computational machine learning to discover new drugs for rare diseases. As you might expect, the company’s technique seeks out and jettisons anything predicted to be toxic (as it would kill the patient).
For the conference presentation, they decided to use the same technology but flip the parameters of their model to favor—rather than avoid—toxic molecules easily absorbed by humans. This was an experiment they expected to produce gibberish. To their surprise, in less than six hours, the AI designed not only a VX nerve agent but also novel, even more, toxic agents that were not even in the training datasets—a total of 40,000 new possible weapons.23 According to the authors, “By inverting the use of our machine learning models, we had transformed our innocuous generative model from a helpful tool of medicine to a generator of likely deadly molecules. … It was a thought exercise we had not considered before that ultimately evolved into a computational proof of concept for making biochemical weapons.”24 d
Using AI for developing new drugs is an example of new, cutting-edge research that the U.S. government has undertaken in its National Artificial Intelligence Initiative25—as have a wide range of commercial actors with access to the same capabilities, unmindful of national and international security risks. Of course, operators must still know about chemistry or toxicology to create extremely harmful new chemicals, toxic substances, or biological agents. And in the Collaborations Pharmaceuticals case, generating a list of chemicals did not mean the results could be synthesized or would prove stable and effective. Pharmaceutical companies use the same method to create drugs; yet out of millions of compounds, they find few viable enough to enter into production.26
Still, the team’s results came from open-source toxicity datasets using open-source software. They noted, “Without being overly alarmist, this should serve as a wake-up call for our colleagues in the ‘AI in drug discovery’ community … All you need is the ability to code and to understand the output of the models themselves.”27 And they continued, “By going as close as we dared, we have still crossed a grey moral boundary, demonstrating that it is possible to design virtual potential toxic molecules without much in the way of effort, time or computational resources.”28
Implications for Bioterrorism
Given fundamental changes in biology as opposed to chemical, nuclear, and radiological weapons (which have changed less—especially nuclear and radiological weapons), then, they should no longer be lumped together as “CBRN.”e Unconventional armaments remain an essential subject to study, as terrorists and insurgent groups are still interested in pursuing them, especially for their psychological impact.29 But CBRN framing misses the fundamental technological changes that have happened in biology and not in the other three fields. Biology is a much faster moving target.
The threat of traditional state bioweapons programs and terrorist groups using known agents has decreased in recent years. Al-Qa`ida is no longer in a position to attempt to build biological weapons like anthrax,30 for example, although it is possible the Taliban could provide a safe haven for a bio lab in the future. The Islamic State experimented with chemical agents, particularly chlorine gas and homemade sulfur mustard, out of Mosul University,31 but it has lost that facility. Affiliates like Islamic State Khorasan could theoretically redevelop one in Afghanistan.
Islamists and domestic extremists have long experimented with ricin, given the ease of extracting ricin from castor beans and access to recipes on the internet explaining how to do so; however, ricin is most effective in assassinations or small-scale attacks. State actors have been more successful, as in the infamous London assassination of dissident Georgi Markov, pricked in the thigh by an umbrella tip spring-loaded with a ricin pellet, for example.32 With state-sponsored terrorism on the rise, it is possible that such tactics will also increase.33
In any case, traditional biological weapons are difficult for individuals and small groups to deliver in large quantities. Even Aum Shinrikyo, whose members included highly trained scientists with laboratory facilities, had difficulty delivering biological weapons effectively, after years of effort.f Traditional biological weapons are now far more likely to be used in state-sponsored assassinations or small-scale targeted attacks than in mass-casualty events by non-state groups.34
Beware Insiders, Tinkerers, and State Sponsors
Biology is no longer a discrete field where biological risks come from a known staple of biological agents that are difficult to handle, acquire, and weaponize. Especially with the use of robust computing power and machine learning tools, the broad landscape of biotechnology is shifting in dramatic ways. It is becoming easy to gain access to DNA sequences from public databases, reproduce known pathogens, alter current viruses or bacteria, or dream up new ones that are neither covered in existing treaties nor even known about. In the same way, the key actors involved are no longer state-funded government laboratories or rogue non-state actors like terrorists. The most significant new risks of attacks come largely from insider threats by knowledgeable scientists with questionable motives, proxy actors backed by adversarial states, or even those experimenting with new biotechnologies irresponsibly.
Given where we are in the biological revolution, we are thinking of biothreats too narrowly. We should consider unprecedented challenges that affect security across new dimensions. The unethical use of bio data collected from unknowing individuals and used for economic or military advantage is one novel threat. For instance, Shenzhen-based BGI collects genetic data from prenatal testing kits that the firm developed with the Chinese military.35 Some 8.4 million women have used the kits in at least 50 countries, including Australia, Canada, Denmark, Germany, India, and the United Kingdom.36 Sensitive information on some mothers and their unborn babies is stored in China’s government-funded gene database, one of the largest in the world.37 Designed to screen for abnormalities such as Down syndrome, the samples yield valuable information on genetic traits across global populations, especially when analyzed with AI tools.38 China could theoretically use that data to design pharmaceuticals or target genetic vulnerabilities with engineered pathogens.39 This risk should not be overstated, of course, since biology also has a natural tendency to diversity. As Brad Ringeisen explained in the April 2022 issue of CTC Sentinel, even with the ability to rapidly scan data at scale, and regardless of how homogenous a population may appear, successful targeting is difficult. Small but important genetic variations affect the results.40 Still, the Pentagon has reportedly warned its own personnel that unwittingly sharing genetic data opens individuals to risk.41
Self-scrutiny among international scientists has failed to hold off troubling developments in synthetic biology. Despite ethical guidelines, professional stigma, and peer pressure that forbids it, gene editing is already changing the human genome. Much to the horror of their peers, Chinese scientists have been the forerunners in genomic editing. In 2015, they tried to edit the genes of a human embryo in a petri dish; discovery triggered outrage and calls not to make a baby via genetic engineering.42 Three years later, Chinese scientist He Jiankui altered the DNA of twins, Lulu and Nana, before their birth using the gene-editing tool CRISPR-Cas9. He eliminated a gene called CCR5 to make the twins immune to HIV, but evidence emerged that he may also have made them smarter by eliminating that gene. No one knows what other off-target effects might emerge—good or bad.43 It also appeared that a third baby was born following similar gene editing.44
The Chinese case was heavily publicized, eliciting outcry among gene-editing scientists. Jiankui and two collaborators were found guilty of “illegal medical practices;” Jiankui was sentenced to three years in jail.45 His two collaborators received lesser sentences of two years and 18 months, respectively.46 Nonetheless, it put in question the wisdom of relying on the ethical codes of millions of scientists throughout the world—and especially in China.
Most scientists see the complexity of making inroads in altering genes, including the human genome, and the vast majority are upstanding and ethical. Yet partially trained graduate students or tinkerers may not foresee the full impact of their experimentation. In other words, with such powerful tools now available, we have to anticipate both malign actors and incompetent ones.
This said, some of the answers to the risks of biotechnology involve creating more and better biotechnology. For example, under a program called “Safe Genes,” DARPA in 2017 began funding a $65 million program at five universities to search for treatments to switch off CRISPR and other gene-editing technologies.47 This is a fast-moving field, with more than 50 anti-CRISPR (Acr) proteins reportedly discovered thus far that interfere with CRISPR tools and may reverse their effects.48
Conclusion
We have scratched the surface of how biotechnology is evolving and why it poses novel threats. Patterns of innovation are not like those we became familiar with decades ago, because the field of biology itself is now fundamentally different, evolving via open processes. The old threats of bioterrorism remain, but they are joined by new ones that are falling between the seams of biology and other disciplines, especially engineering, data science, and computer science, and especially at the intersection between molecular biology and artificial intelligence. Biotechnology is already changing the balance of power between states, enriching private corporations at stunning speed, and opening new avenues of attack by terrorists and individuals. To preserve the promise of biotechnology, we must fully confront the risks before it is too late.
Biorisk management at the global level was well covered by Filippa Lentzos, Gregory Koblentz, and Joseph Rodgers in the April 2022 issue of CTC Sentinel.49 The following policy recommendations focus primarily on the U.S. government.
First, to protect our national security, we need more collaboration between hard scientists and human behavioral scientists. There is a troubling disconnect between those steeped in the study of biology and related digital technologies, on the one hand, and those focused on human behavior, motivations, and risk, on the other. Disciplinary stovepipes hamper us as we face a future where traditional fields are merging and recombining. Workshops, seminars, inter-disciplinary brainstorming, and cooperation is vital. We must learn to think in more agile ways across boundaries, or we will fail to recognize both risks and opportunities.
Our leaders, by and large, do not understand biotechnology. We need significant retraining, including at senior levels of government and in the military, to stop relying on outdated ways of thinking. This includes focusing on the intersection between biotechnology and artificial intelligence. We should also establish short-term training courses for early career scientists on how to talk to policymakers, write policy-relevant articles, and explain research in accessible ways for general audience outlets.
Specifically in my own field, those who study terrorism and other non-state threats must update their skills and get smarter about new technologies. Relying on the same old frameworks, case studies, and incident databases we have used in the recent past will not prepare us to meet future risks. Biology has fundamentally changed. Patterns of terrorist innovation from the last 40 years of the 20th century do not tell us much about where bioterrorism is likely to evolve.
Finally, highly trained, well-respected scientists need to be more open in acknowledging the potential for misuse of biotechnology, and young scientists need dedicated ethical training that is as high a priority as their technical training currently is. Insisting that professional norms, stigmas, and self-policing are working well is simply unsupportable. But curiosity, innovation, and professional and commercial success are not at odds with mitigating risk. Ultimately, if there is a major incident, or accident, or even additional ethical lapses like those we have seen in gene editing, the future of humankind could be jeopardized.
