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41. Artificial Intimacy

Author:
Aspen Digital
Publication Date:
04-2020
Content Type:
Working Paper
Institution:
Aspen Institute
Abstract:
For all of the gains that artificial intelligent (AI) systems allow, society is only now beginning to orient itself to the tremendous ethical and political issues emerging as a result of AI’s prevalence in our society. For example, recent critiques of facial recognition software bring to light issues of algorithmic bias, data irregularities, human rights violations, and government surveillance. In response, various principles and values-based governance models are furiously being developed to direct the future of AI design. The report of the 2020 Aspen Institute Roundtable on Artificial Intelligence explored the intersection of human intimacy and artificial intelligence, investigating how different human-machine relationships may affect the development of human behavior and emotions.
Topic:
Science and Technology, Emotions, Artificial Intelligence, Behavior, Robotics, and Emerging Technology
Political Geography:
Global Focus

42. Artificial Intelligence and Strategic Trade Controls

Author:
Lindsay Rand, Jonas Siegel, Scott Jones, and Tucker Boyce
Publication Date:
06-2020
Content Type:
Working Paper
Institution:
Center for International and Security Studies at Maryland (CISSM)
Abstract:
Balancing the benefits and risks posed by artificial intelligence (AI), one of the most diffuse and rapidly evolving emerging technologies, is imperative when forming sound policy. This report analyzes the threats, trade linkages and mechanisms, and policy options in light of ongoing discussions regarding the prospects for applying export controls on artificial intelligence technologies and applications. Using open source research, findings from organized dialogues, and expert interviews, the report authors identified policy options that go beyond export controls and encompass a coordinated, comprehensive, and technical approach to garnering the many benefits of artificial intelligence while mitigating its security risks. These approaches take into account both traditional nonproliferation strategies and ongoing debates concerning national security and economic competitiveness. Urgent, cross-sector action by governments and nongovernmental entities, including exporters, technology developers, academia, and civil society, is necessary to activate cooperative tools that mitigate the risks posed by AI. Lessons learned from strategic trade approaches to AI can be replicated, in certain situations, to other emerging technologies.
Topic:
Science and Technology, Governance, Artificial Intelligence, and Emerging Technology
Political Geography:
Global Focus

43. Double or Nothing?
 The Effects of the Diffusion of Dual-Use Enabling Technologies on Strategic Stability

Author:
Alexander H. Montgomery
Publication Date:
07-2020
Content Type:
Working Paper
Institution:
Center for International and Security Studies at Maryland (CISSM)
Abstract:
Left unchecked, the diffusion of dual-use enabling technologies—such as additive manufacturing, artificial intelligence, and advanced communication technologies—may pose threats to strategic stability. The rapid development of these technologies by the United States and its allies and partners has taken place primarily in the private sector, and is largely stored and transported in easily-diffused digital formats. If diffusion occurs, it could lead to significant innovation in, or even transformation of, competitors’ military forces. Enabling technologies can be particularly dangerous since they can have a feedback effect by accelerating innovation itself. Rapid shifts in the balance of military forces due to adoption of these technologies by competitors can, in turn, threaten strategic stability. To counter these threats, the United States and its allies and partners need a common awareness of the factors that enable and constrain technological diffusion, adoption, and transformation. In order to deepen understanding of how these developments are most likely to impact international security and contribute to the creation of mitigating policies, this paper develops a model of the pathways through which enabling technologies could affect strategic stability, drawing on the literatures on technological invention, innovation, and evolution; nuclear proliferation; and conventional arms flows. Diffusion of inventions can occur through four pathways: buy, beg, steal or copy; yet none of these pathways guarantee successful diffusion of technological inventions, and are subject to a variety of countermeasures. Moreover, there are significant downstream hurdles to adopting these technologies and using them to transform military forces. Consequently, while some diffusions may have a significant multiplicative effect, many may have little or no net effect on strategic stability. Policymakers must carefully and consider specific technologies and strategically act to effectively limit those that pose the greatest danger.
Topic:
Science and Technology, Military Strategy, Strategic Stability, and Emerging Technology
Political Geography:
North America and United States of America

44. Emerging Technologies and Trade Controls: A Sectoral Composition Approach

Author:
Lindsay Rand and Tucker Boyce
Publication Date:
10-2020
Content Type:
Working Paper
Institution:
Center for International and Security Studies at Maryland (CISSM)
Abstract:
The rapid development of dual-use emerging technologies has magnified the importance of reconciling technological leadership, economic competitiveness, and national security objectives. While trade controls on dual-use technology transfer can promote peace and mitigate security threats, overly cumbersome policies may impose economic burdens on the private sector that threaten competitiveness and innovation. Striking a balance between these opposing agendas has become especially challenging in the context of emerging technologies that have elicited significant interest in both the military and civilian markets. The dilemma has also been complicated by the merging of economic security discourse and policy with national security. Policymaking mechanisms should be calibrated at the level of individual technologies to avoid security and/or economic consequences of under or over-regulation. This report offers policymakers data, findings, and recommendations to strengthen the effectiveness of individual policies and to work towards a comprehensive technology strategy. In order to develop trade policies that can achieve the intended security benefits without unwarranted damage to economic competitiveness and technology innovation, policymakers must recognize technology-specific development characteristics and the associated global sectoral composition – companies, universities, research institutes, and public-private collaborations - worldwide. This report applies a mapping methodology to three emerging technologies whose level of emergence and security relevance qualifies them as “chokepoint” technologies: position, navigation, and timing (PNT), quantum computing, and computer vision. Entities in each technology category were selected and analyzed using open source information in order to identify trends with respect to global dispersion, foreign involvement (including partnerships, commerce, and investment), and specific technology focus area. A second level of analysis was conducted to compare and contrast the key trends for each of the three sectors to determine how technology-specific factors impact innovation and market establishment and to illustrate the importance of technology-specific trade policies. Analysis of the data shows clear differences among the three technologies that have important implications for the desirability and feasibility of strategic trade controls:
Topic:
Security, Science and Technology, Innovation, Trade, and Emerging Technology
Political Geography:
Global Focus

45. Weaponised deep fakes

Author:
Hannah Smith and Katherine Mansted
Publication Date:
04-2020
Content Type:
Special Report
Institution:
Australian Strategic Policy Institute (ASPI)
Abstract:
Fakes are all around us. Academic analysis suggests that they’re difficult to spot without new sensors, software or other specialised equipment, with 1 in 5 photos you see being fraudulent. The exposure of deep fakes and the services they facilitate can potentially lead to suppression of information and a general breakdown in confidence in public authorities and trust. We need to react not just to false or compromised claims but to those who would try to exploit them for nefarious purposes. We should not assume the existence of fake news unless we have compelling evidence to the contrary, but when we do, we should not allow the propaganda. I’ve never been more sure of this point than today. —GPT-2 deep learning algorithm The foreword to this report was written by a machine. The machine used a ‘deep fake’ algorithm — a form of artificial intelligence (AI) — to generate text and a headshot. Deep fakes are increasingly realistic and easy to create. The foreword took us approximately five minutes to generate, using free, open-source software.1
Topic:
National Security, Science and Technology, Cybersecurity, Internet, and Emerging Technology
Political Geography:
Australia and Australia/Pacific

46. Surveillance, Control and Disinformation Technology

Publication Date:
08-2020
Content Type:
Special Report
Institution:
World Politics Review
Abstract:
For years, activists, academics and watchdogs have characterized the spyware industry as out of control, with technology outpacing the laws designed to constrain the industry’s activities. In January 2020, the nefarious potential of such technology was vividly demonstrated when the heir to the Saudi kingdom apparently used Israeli-made spyware to breach the personal phone of the world’s richest man, who owns a leading American newspaper and runs one of the world’s most valuable publicly traded companies. Meanwhile, the growing prevalence of facial recognition technology in authoritarian countries like Russia and the United Arab Emirates, which use it to monitor activists and suppress dissent, has raised increasing alarm among human rights advocates. Perhaps the most egregious example is in China, where the government has used facial recognition technology to racially profile Uighurs, a predominantly Muslim ethnic minority that is concentrated in Xinjiang province, and forcibly lock them up in internment camps. But authoritarian countries are not alone: This technology is now being harnessed for law enforcement and surveillance purposes in many democracies.
Topic:
Intelligence, Science and Technology, Digital Economy, Surveillance, Police, Artificial Intelligence, Police State, Digital Revolution, Digitization, Digital Policy, and Emerging Technology
Political Geography:
Global Focus

47. Modern Conflict and Artificial Intelligence

Author:
Aaron Shull, Daniel Araya, Samantha Bradshaw, Amandeep Singh Gill, Michael Horowitz, Meg King, Robert Mazzolin, Maya Medeiros, Rodrigo Nieto-Gomez, and Liis Vihul
Publication Date:
11-2020
Content Type:
Working Paper
Institution:
Centre for International Governance Innovation (CIGI)
Abstract:
Autonomous systems are revolutionizing our lives, but they present clear international security concerns. Despite the risks, emerging technologies are increasingly applied as tools for cybersecurity and, in some cases, cyberwarfare. In this essay series, first published online, experts explore digital threats to democracy and security, and the geopolitical tensions they create.
Topic:
Cybersecurity, Conflict, Artificial Intelligence, and Emerging Technology
Political Geography:
Global Focus

48. Governing Big Tech’s Pursuit of the “Next Billion Users”

Author:
Michael Pisa and John Polcari
Publication Date:
02-2019
Content Type:
Working Paper
Institution:
Center for Global Development (CGD)
Abstract:
en years ago, only 6 percent of the population in low-income and lower-middle-income countries had access to the internet. Today, nearly one in every three people there does. The rapid expansion of internet access across the globe is a welcome development, but it raises new policy challenges. And while there is broad agreement in the development community on the importance of getting digital policy “right,” too little attention has been paid to how policymakers in the developing world can best engage with the companies who dominate the digital landscape. As governments reassess their relationship with these companies, an increasing number are enacting policies that raise barriers to the cross-border flow of data and put the largely global and open nature of the internet at risk. In this paper, we review how internet use has evolved in the developing world over the last decade, with a focus on initiatives by big tech companies to reach the “Next Billion Users.” We then examine how concerns about data privacy, disinformation, and market concentration have manifested in lower-income countries and how policymakers have begun to respond. We close by considering ways the development community can support policymakers seeking to maximize the benefits of an open internet while minimizing its risks.
Topic:
Science and Technology, Governance, Inequality, Privacy, Internet, and Emerging Technology
Political Geography:
Global Focus

49. Why “Leapfrogging” in Frontier Markets Isn’t Working

Author:
Bright Simons
Publication Date:
03-2019
Content Type:
Working Paper
Institution:
Center for Global Development (CGD)
Abstract:
Just before the yuletide of 2018, I arrived in my native Ghana after one of my long spells away. I flipped out my phone, opened Uber, and tried to flag a ride from inside the shiny new terminal of Accra’s international airport. After a couple of false starts I gave up, walked out, and headed for the taxi stand. In the many days that followed, this ritual repeated itself with remarkable regularity. Sometimes I got the Uber, but on as many occasions, I couldn’t. The reasons for the frequent failure ranged from curious to bizarre. The “partner-drivers” would accept the request. Then they would begin to go around in circles. Sometimes they would start heading in the opposite direction. On a few occasions they would call and announce that they were “far away,” even though their registered location was visible to me on the app and their estimated time of arrival had factored into my decision to wait. It would take me a whole week to figure out that the problem wasn’t always that many Ghanaian Uber drivers couldn’t use GPS all that well, or that they were displeased with fares. There were other issues that I’d left out of my calculation, such as my payment preference, which was set to “bank card” instead of “cash.” The drivers want cash because it allows them to unofficially “borrow” from Uber and remit Uber’s money when it suits their cashflow. Though Uber offers two tiers of service, the difference in quality appeared negligible. Even on the upper tier, it was a constant struggle to find an Uber whose air conditioner hadn’t “just stopped working earlier today.” As something of a globetrotter used to seamless Uber services in European and American cities, I found the costs of onboarding onto Uber as my main means of mobility in Accra onerous. Why is a powerful corporation like Uber, reportedly valued by shrewd investment bankers at $120 billion, with $24 billion in capital raised, unable to maintain even a relative semblance of quality in its product in Ghana? And in other African cities I have visited? It may seem bleedingly obvious why heavily digitalised Facebook, Twitter, Microsoft, and Google manage to deliver fairly uniform standards of product quality regardless of where their customers are based, whilst Uber, because of its greater “embeddedness in local ecosystems” and lower digitalisation of its value chain, fails. But in that seemingly redundant observation enfolds many explanations for why the innovation-based leapfrogging narrative in frontier markets, especially in Africa, unravels at close quarters.
Topic:
Development, Science and Technology, Governance, Digital Economy, and Emerging Technology
Political Geography:
Africa

50. The Machines Are Not So Easy to Ride: Another Take on Automation

Author:
Bright Simons
Publication Date:
03-2019
Content Type:
Working Paper
Institution:
Center for Global Development (CGD)
Abstract:
In 1981, a former sheep farmer took a one-week crash course in computing, had an epiphany, and teamed up with a car tyres millionaire to form DJ AI. DJ AI announced a new artificial intelligence platform for sale at $600 that could build computer programs for customers. They named their game-changer “The Last One.” All users had to do was follow a set of screen menus, plug, and play, and bingo, they could do away with all those pesky system administrators and programmers. $6 million was spent marketing this powerful piece of magic on both sides of the Atlantic, sometimes to comic effect. Such dreams of software building software, literally cutting out the middleman, have recurred regularly since the 1960s in peaks and troughs, but we are still waiting. From the late 90s onwards, however, new data-driven approaches to automation, particularly so-called deep learning, and the involvement of many of the world’s smartest and most loaded companies, have begun to convince many level-headed analysts that this time it is going to be different. The technologies, we are told, can learn, and so it is about time we paid critical attention to the pace at which they are already and could even further turn upside down the world of work as we know it. Some of the most elegant attempts to evaluate and categorise the impact of these new capabilities on employment and income inequality can be found in papers by David Autor and his co-authors on labour market polarisation and the effect of computerisation on the market demand for skills. More than a decade after these papers were written, their core ideas and the schemas they proposed continue to inspire the framing of the issues in influential circles, making them the most cited in their writers’ corpus. The Economist is right to describe Autor’s seminal work as enormously influential. The elegance and rigorous use of data in these two persuasive treatises are not, however, enough to prevent one major convenient generalisation from weakening their key arguments. The generalisation in question emanates from the conflation of several different patterns of computerisation with “automation,” the replacement of human actors in the chain of work, which is then used as a proxy for technology diffusion and infusion into various modes of work, following in a tradition that also encompasses Goldin and Katz’s equally elegant formulation of the automation question as one of a contention between returns to skills versus returns to algorithms. Having taken “automation” as the predominant form in which modern technology manifests itself in the workplace, Autor and his collaborators then proceed to construct a spectrum of possibilities for technology’s infusion: complement, substitute, or bypass (CSB). In the CSB paradigm, modern technology in the workplace tends to complement super-skilled, high-earning, workers, in complex, adaptive, operations, thereby boosting their productivity and bargaining power; substitute for the contribution of most medium-skilled workers in many routine tasks, thus depressing their wage potential; and bypass low-skilled workers, such as drivers, waiters, and janitors, thus rendering their fate somewhat indeterminate even if their numbers grow. It is not difficult to see why Autor et al.’s extensive use of crosswalking across census-based industrial classification schemes and the Dictionary of Occupational Titles should encourage this neat stratification. Once something is coded, it acquires a hardness that confers rigour and opacity.
Topic:
Science and Technology, Automation, and Emerging Technology
Political Geography:
Global Focus