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41. Mastering the Digital Age: Understanding Artificial Intelligence and Regulation

Author:
Olivia J. Erdelyi
Publication Date:
03-2023
Content Type:
Journal Article
Journal:
Brown Journal of World Affairs
Institution:
Brown Journal of World Affairs
Abstract:
In recent years, news about a mysterious new technology referred to as artificial intelligence (AI) has been everywhere. Even for the most tech-averse individuals, it is virtually impossible to remain oblivious to AI’s existence. While there is positive news establishing a craving for it, blunders and scandals are not far behind, invoking the wrath of the public and calls for reigning in the ac- tors, mostly perceived to be tech companies, that endanger democratic rights. 1 Leveraging the benefits provided by modern information and communication technologies, people rush to take part in the public discourse of the hour, forming strong opinions before understanding the topic. While eye-catching headlines and impassioned debates continue to spread online, few understand the concept of AI. This scenario presents a problem, as mastering the digital age requires some AI literacy.
Topic:
Science and Technology, Regulation, Artificial Intelligence, and Digital Policy
Political Geography:
Global Focus

42. Building Trust in AI: A Landscape Analysis of Government AI Programs

Author:
Susan Ariel Aaronson
Publication Date:
03-2023
Content Type:
Working Paper
Institution:
Centre for International Governance Innovation (CIGI)
Abstract:
As countries around the world expand their use of artificial intelligence (AI), the Organisation for Economic Co-operation and Development (OECD) has developed the most comprehensive website on AI policy, the OECD.AI Policy Observatory. Although the website covers public policies on AI, the author of this paper found that many governments failed to evaluate or report on their AI initiatives. This lack of reporting is a missed opportunity for policy makers to learn from their programs (the author found that less than one percent of the programs listed on the OECD.AI website had been evaluated). In addition, the author found discrepancies between what governments said they were doing on the OECD.AI website and what they reported on their own websites. In some cases, there was no evidence of government actions; in other cases, links to government sites did not work. Evaluations of AI policies are important because they help governments demonstrate how they are building trust in both AI and AI governance and that policy makers are accountable to their fellow citizens.
Topic:
Science and Technology, Artificial Intelligence, Trust, and Trust-building
Political Geography:
Global Focus

43. Protecting Democracy Online in 2024 and Beyond

Author:
Megan Shahi
Publication Date:
09-2023
Content Type:
Special Report
Institution:
Center for American Progress - CAP
Abstract:
This new report specifically anticipates risks to and from the major social media platforms in the 2024 elections, continuing CAP’s work to promote election integrity online and ensure free and fair elections globally. The report’s recommendations incorporate learnings from past elections and introduce new ideas to encourage technology platforms to safeguard democratic processes and mitigate election threats. In a world without standardized global social media regulation, ensuring elections are safe, accessible, and protected online and offline will require key actions to be taken ahead of any votes being cast—both in 2024 and beyond.
Topic:
Politics, Science and Technology, Elections, Democracy, Social Media, and Artificial Intelligence
Political Geography:
Europe, India, Global Focus, and United States of America

44. Future Warfare and Responsibility Management in the AI-based Military Decision-making Process

Author:
Alessandro Nalin and Paolo Tripodi
Publication Date:
03-2023
Content Type:
Journal Article
Journal:
Journal of Advanced Military Studies
Institution:
Marine Corps University Press, National Defense University
Abstract:
The application of artificial intelligence (AI) technology for military use is growing fast. As a result, autonomous weapon systems have been able to erode humans’ decision-making power. Once such weapons have been deployed, humans will not be able to change or abort their targets. Although autonomous weapons have a significant decision-making power, currently they are not able to make ethical choices. This article focuses on the ethical implications of AI integration in the military decision-making process and how the characteristics of AI systems with machine learning (ML) capabilities might interact with human decision-making protocols. The authors suggest that in the future, such machines might be able to make ethical decisions that resemble those made by humans. A detailed and precise classification of AI systems, based on strict technical, ethical, and cultural parameters would be critical to identify which weapon is suitable and the most ethical for a given mission.
Topic:
Ethics, Weapons, Artificial Intelligence, Machine Learning, and Decision-Making
Political Geography:
Global Focus

45. PART II: Whale Songs of Wars Not Yet Waged: The Demise of Natural-Born Killers through Human-Machine Teamings Yet to Come

Author:
Ben Zweibelson
Publication Date:
03-2023
Content Type:
Journal Article
Journal:
Journal of Advanced Military Studies
Institution:
Marine Corps University Press, National Defense University
Abstract:
Current human-machine dynamics in security affairs positions the human operator in the loop with artificial intelligence to conduct decisions and actions. As technological advancements in AI cognition, speed, and weapon sophistication increase, human operators are increasingly being shifted to an on the loop where AI takes more responsibility in warfare and defense decisions, whether tactical or even strategic. Human operators are also falling off the loop, trailing enhanced AI systems as the biological and physical limits because humans are not the same for artificial intelligence in narrow applications. Those likely will expand toward general AI in the coming decades, presenting significant strategic, organizational, and even existential concerns. Further, how natural humans respond and engage with increasingly advanced, even superintelligent AI as well as a singularity event will feature disruptive, transformative impacts on security affairs and even at a philosophical level discerning what war is.
Topic:
Science and Technology, War, Artificial Intelligence, and Machine Learning
Political Geography:
Global Focus

46. Same End By Different Means: Google, Amazon, Microsoft and Meta’s Strategies to Organize Their Frontier AI Innovation Systems

Author:
Cecilia Rikap
Publication Date:
01-2023
Content Type:
Working Paper
Institution:
City Political Economy Research Centre (CITYPERC), University of London
Abstract:
I combine quantitative methodologies and in-depth interviews to analyse United States Big Tech different strategies to organize and profit from their AI corporate innovation systems (CIS). I propose 1) “frenemies” for Microsoft, because even Chinese organizations and direct competitors integrate its CIS. 2) “University” for Google, whose AI strategy included leaving DeepMind autonomous to explore more fundamental AI but appropriation mechanisms are not translating into a clear business advantage. 3) “Secrecy” for Amazon, given its large concern with secrecty and profiting from AI. 4) And “application-centred” for Facebook; its AI CIS is the narrowest, mostly attached to its platforms.
Topic:
Science and Technology, Innovation, Artificial Intelligence, Big Tech, and Corporations
Political Geography:
Global Focus

47. Addressing the Liability Gap in AI Accidents

Author:
Amrita Vasudevan
Publication Date:
07-2023
Content Type:
Policy Brief
Institution:
Centre for International Governance Innovation (CIGI)
Abstract:
When a device controlled by artificial intelligence (AI) is involved in an accident causing bodily harm, who is at fault? The manufacturer, software developer or the user? With so many people involved in the design and production of AI-controlled technology (known as the “problem of many hands”), liability can be difficult to attribute, leaving victims and their families without recourse. As AI becomes increasingly entrenched in our daily lives, mishaps will become more common. This policy brief looks at the challenges in determining who is at fault when AI goes awry and how to address the liability gap.
Topic:
Regulation, Artificial Intelligence, Digital Policy, Emerging Technology, and Liability
Political Geography:
Global Focus

48. AI-Related Risk: The Merits of an ESG-Based Approach to Oversight

Author:
Mardi Witzel and Niraj Bhargava
Publication Date:
08-2023
Content Type:
Working Paper
Institution:
Centre for International Governance Innovation (CIGI)
Abstract:
Artificial intelligence (AI) technology has been found to generate value for many firms; however, it also has unintended and undesirable consequences. The reality of AI-related risk has led to the development of AI governance frameworks and calls for greater oversight of the use of AI. The merits of an ESG (environmental, social, governance)-based approach to oversight of AI-related risk are considered in this paper, with a focus on the current trajectory of international sustainability standards development. Despite their differences, AI governance and ESG reporting both seek to address risk in the broadest sense, with proactive and transparent approaches to its management and mitigation. A preliminary set of recommendations for incorporating material AI-related risk into ESG reporting, covering both general or context-setting disclosures and industry-specific disclosures, is provided.
Topic:
Regulation, Artificial Intelligence, Industry, Oversight, and Emerging Technology
Political Geography:
Global Focus

49. The competitive relationship between cloud computing and generative AI

Author:
Christophe Carugati
Publication Date:
12-2023
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
Cloud computing providers and generative artificial intelligence (GenAI) providers nurture a close, interdependent relationship: GenAI providers need cloud providers to train, run and deploy their GenAI solutions, while cloud providers see GenAI providers as a business driver to grow their market shares in cloud and related markets, such as productivity software or search engines. The cloud/GenAI relationship takes various forms, including exclusive and strategic partnerships, especially between large cloud providers and GenAI providers across all parts of the cloud market, including infrastructure, platforms and software. Competition benefits and risks are likely to result from the relationships. Competition benefits arise from increased competition and innovation in the cloud and GenAI sectors. Risks relate to potential concentrations arising from the partnerships between cloud and GenAI providers, and from anticompetitive practices, including discrimination in the supply of IT equipment by dominant IT providers, interoperability obstacles to switching, use of business-user data, self-preferencing of cloud services over third parties, tying and pure bundling. Merger control and antitrust laws can address some of the competition risks, while laws, including the European Union’s Digital Markets Act and Data Act, can deal with competition issues in digital markets and the cloud sector. Nevertheless there are gaps. The European Commission should amend existing EU instruments, including by changing the definition of a concentration under merger control, and should specify interoperability requirements for cloud providers under the Data Act. The Commission should also closely monitor developments in and outside Europe through market investigations, including with international counterparts, and should intervene to tackle imminent competition risks using fast procedural tools, such as interim measures.
Topic:
European Union, Antitrust Law, Artificial Intelligence, Cloud Computing, and Competition
Political Geography:
Europe and Global Focus

50. Competition in generative artificial intelligence foundation models

Author:
Christophe Carugati
Publication Date:
07-2023
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
Foundation models (FMs) are the origin of breakthrough innovations in generative artificial intelligence (AI) applications, such as ChatGPT. Only responsible developments in competitive markets can help ensure that FMs deliver their full benefits at minimum risk. FM developers require language models (LMs), data and computing power to generate natural language output, such as texts, from language input. Thus, the FM value chain is composed of three main elements: LMs, data and computing resources. These markets are currently competitive, with multiple providers and degrees of openness thanks to several closed- and open-source models, open-source and proprietary data, and vigorous competition between firms at the computing-resources level, despite high degrees of concentration in some of these markets. These market characteristics ensure that FM developers face low or surmountable entry barriers. Still, potential competition issues are likely to arise in the future. Dominant firms could leverage their dominant positions, refuse to give access to their LMs, scrape data, refuse to grant access to data, impose undue barriers to switching and lock their users into their ecosystems. Firms could also use LMs to achieve an anticompetitive agreement through algorithmic collusion. Competition authorities should focus their efforts on short-term risks. They should also remain vigilant in terms of ensuring the competitive process between open- and closed-source models works and that open-source developers and public authorities do not impose undue restrictions to mitigate the risks of open-source models, which would deter their development in a way that would favour closed-source models. Finally, at this development stage, studies are lacking. Researchers and competition authorities should investigate the impact of fms on content providers and the digital advertising industry, the role of FMs in digital ecosystems, and cooperation mechanisms between competent authorities across regulatory fields and countries.
Topic:
Digital Economy, Artificial Intelligence, Competition, and ChatGPT
Political Geography:
Global Focus