21 Jun The new geopolitics of hybrid emerging risks and vulnerabilities from converging technologies
We are entering an era of hybrid opportunities and threats generated by the combination of artificial intelligence (AI) and other powerful dual-use technologies, with implications for nearly every aspect of daily lives. The convergence of AI and affective computing, cyber and biotechnologies, robotics and additive manufacturing raises complex global implications that are poorly understood, leaving the multilateral system with limited tools to anticipate and prevent emerging risks. At the same time, the spread of AI convergence across a wide range of States, non-State and transnational actors and entities means that the challenges of tomorrow must be addressed collectively and innovatively.
How can the multilateral system better understand and anticipate risks as AI convergence with dual-use technologies intrudes increasingly into the political, social, economic, and security spheres, creating new potential for systemic vulnerabilities and distributive inequalities? How can actors within the multilateral system build better anticipation and prevention capacities in the face of these risks?
Across the world, at any given moment, there are pervasive cognitive-emotional conflicts being waged for the control of populations’ thoughts, emotions and attitudes. These battles of influence do not tend to occur in wartime, but rather in peacetime, infiltrating homes and smart cities. They sow disinformation, affective manipulation and forgeries as new means of undermining social cohesion and trust. They exacerbate societal tensions and amplify public polarization. They increasingly condition and limit notions of self-determination, and could continue to do so with the future generations to come.
The rise of cognitive-emotional conflicts and the subsequent “trust-deficit disorder” they unleash is born out of the entanglement of technology, data, and geopolitics. The convergence of AI with other emerging technologies creates the potential for deception and subversive attacks that manipulate populations’ perceptions. In such “AI convergence,” AI optimizes data, processes and techniques that are part of physical, digital and biological lives.
AI is combining with an extraordinary array of other technologies, from cyber and biotechnologies, affective computing and neuro-technologies, to robotics and additive manufacturing. Computer scientists are developing deep learning algorithms that can recognize patterns within massive amounts of data with superhuman efficiency and, increasingly, without supervision. At the same time, geneticists and neuroscientists are deciphering data related to genomes and brain functioning, learning about human health, well-being and cognition.
The result? Functional capabilities for averting crises that were previously unimaginable are now real, and they are upgrading efforts from precision medicine and food security to conflict prevention. For example, deep learning algorithms are diagnosing retinopathy in patients living in rural India where there is a shortage of ophthalmologists. The same algorithms can identify malign biomarkers among large swaths of genomics data from human populations to design blood tests for various cancers. Portable genomics sequencers bring the lab to the jungle, allowing for the diagnosis of Ebola viruses in “hot zones.” In a community biolab in the Bay Area, a fifteen-year-old is using additive bio-manufacturing to print a molecular patch that could one day help treat thousands of people who, like her brother, suffer from a rare lung disease. In Shenzhen’s Open Innovation Lab, young inventors have designed wearable devices that rely on image recognition to help farmers detect diseases on crops.
AI could also become a powerful tool for the international development efforts by multilateral organizations. The World Bank, in collaboration with other global partners including the UN, is building a Famine Action Mechanism, which relies on deep learning systems, developed by Microsoft, Google and Amazon, to detect when food crises will turn into famines. The same tool allows agile financing to be connected directly to areas of food insecurity.
The combined optimization of biometrics, genomics, behavioural, and physical systems’ data is giving rise to “affective computing” – algorithms that can successfully analyse, nudge, and communicate withThis form of emotional analysis will improve human-machine interactions in applications that could empower underserved populations, from precision medicine to targeted education.
While these trends may unlock enormous potential for humankind, the convergence of AI with other emerging technologies also creates unprecedented vulnerabilities and risks for global security. Think of deep learning systems able to drastically intensify the nature and scope of cyber espionage and cyberattacks within increasingly intelligent and connected cities and laboratories. The same algorithms can rely on emotion analysis to generate deepfakes – highly realistic photos or videos of events that never occurred – which will enable propaganda, strategic deception and social manipulation to be both more scalable and targeted.
We face a new species of technologies, – those that are increasingly digitized, enable and converge with each other, and that are harnessed in cyberspace. This new species of technologies essentially exploits the data captured from physical and biological systems. Almost all physical and biological matter today can be turned into a digital blueprints or binary code, from the genomes of humans and living organisms, to organs and fingerprints, to DIY drone designs, to nuclear power plant parts, even to brainwaves and nanobots delivering tailored molecules in human bodies.
Converging technologies therefore create networks of digital information that enhance, run, shape and integrate cyberspace with daily ways of living. They slowly “invade” bodies and cities. As they become digitized, converging technologies also become more decentralized, beyond State control, and available to a wider range of actors around the world.
Under the same impulse, cyberspace has become not only a new domain of fierce competition over information, business, and strategic technological operations, but also a new battlefield, in ways that blur the line between war and peace and make each of us a potential target of postmodern conflict. Governance actors are only starting to realize how the manipulation and misuse of converging and connected technologies in cyberspace can threaten the truth, polity, and collective security.
The convergence of AI with emerging technologies can therefore raise new complex security challenges that are neither well understood nor well anticipated globally. There is a crucial need to map out and analyse for whom the convergence of dual-use technologies will generate not only new powerful opportunities to flourish, but also pervasive hybrid threats. This is part of a larger ongoing effort to investigate how legacy paradigms of global security and governance are evermore challenged by the combination of powerful dual-use technologies.
Today, converging technologies already impact digital, political, economic, and (bio)-physical security. Far beyond what was conceived through traditional security and military doctrines, we face new challenges that pertain to human, socio-economic and political security. Competitions and conflicts arise between societies, not armies. What matters is not who wins new territories, but who wins the data, the trust, the hearts and the minds of citizens within a country or polity. In this context, preserving and enhancing societal resilience will become the most important asset for leaders.
This is an excerpt of the report: The New Geopolitics of Converging Risks: The UN and Prevention in the Era of AI, by Eleonore Pauwels. Published: 29. April 2019, United Nations University Centre for Policy Research; ISBN 978-92-808-6504-2, under a Creative Commons Attribution License (CC BY NC SA 3.0).