Artificial Intelligence Policy Research Articles

Discursive framing and organizational venues: mechanisms of artificial intelligence policy adoption

The purpose of this article is twofold: to theoretically assess ideational and organizational explanatory factors in the adoption of artificial intelligence policies; and to examine the extent to which the European Union has managed to facilitate a coordinated artificial intelligence policy in the Nordic countries. The study utilizes a mixed-methods approach based on systematic web searching, systematic policy document analysis and key informant semi-structured interviews. The study finds that the European Union has utilized framing-based strategies to set an agenda for a coordinated European artificial intelligence policy. Moreover, the strategy has affected member-state artificial intelligence policies to the extent that key tenets of European Union artificial intelligence discourse have penetrated Nordic public documents. However, the extent to which the Nordic countries incorporate European Union artificial intelligence policy discourse diverges at the national level. Differentiated national organizational capacities among Nordic countries make the adoption of artificial intelligence policies divergent. This observation is theoretically accounted for through a conversation between organizational theory of public governance and discursive institutionalism. The study argues that the framing of European Union artificial intelligence policies is filtered through organizational structures among states. Points for practitioners The study illuminates how policymakers in the Nordic countries are affected by the European Union when crafting their own artificial intelligence policies. The European Commission profoundly influences the policymaking of member states and affiliated states through the policy strategy of policy framing. The Commission uses this soft measure to nudge member states to comply with the European Union policy framework. Second, the study shows how ‘organizations matter’: variation in national organizational capacities in the Nordic states contributes to variation in national policy adoption. Even though Nordic countries adopt European Union-level policy frames, their implementation is shaped by varying organizational capacities available at the national level.

Inteligencia Artificial (y Administración Pública)

Los algoritmos y la Inteligencia Artificial (IA) en el sector público se están adoptando en diferentes contextos. Conceptualmente, todavía no están claras las implicaciones de la IA y los algoritmos en las administraciones públicas. Sin embargo, diferentes organizaciones internacionales han definido una serie de principios éticos y cuestiones legales a tener en cuenta. Las instituciones de la Unión Europea se han convertido en el actor clave para guiar la adopción de IA, estableciendo las primeras líneas para las políticas públicas a nivel nacional. El Gobierno de España ha comenzado a desarrollar una estrategia en esa línea, si bien con unos responsables de políticas tecnológicas encargados de su implementación, que cuentan con sus propias percepciones y prioridades. Este artículo se inicia con las siguientes preguntas de carácter descriptivo y exploratorio: ¿Cómo están enmarcando ética y jurídicamente la IA los principales organismos internacionales? ¿Cuál es el marco de prioridades de la política de IA promovida por el Gobierno de España en relación con la Unión Europea? ¿Cuál es la percepción sobre la IA de los responsables de gestión de tecnologías (CIOs) en los ministerios? Para responder a estas preguntas, este trabajo se nutre de una revisión documental y de parte de los resultados de un cuestionario sobre las percepciones de los responsables de gestión de las tecnologías en los ministerios españoles. Nuestro análisis permite responder exploratoriamente las preguntas de investigación del estudio. Además, los resultados señalan algunas claves para diseñar políticas y estrategias de uso de la IA en diferentes contextos político-administrativos.

Good governance as a response to discontents? Déjà vu, or lessons for AI from other emerging technologies

ABSTRACT Recent advances in Artificial Intelligence (AI) have led to intense debates about benefits and concerns associated with this powerful technology. These concerns and debates have similarities with developments in other emerging technologies characterized by prominent impacts and uncertainties. Against this background, this paper asks, What can AI governance, policy and ethics learn from other emerging technologies to address concerns and ensure that AI develops in a socially beneficial way? From recent literature on governance, policy and ethics of emerging technologies, six lessons are derived focusing on inclusive governance with balanced and transparent involvement of government, civil society and private sector; diverse roles of the state including mitigating risks, enabling public participation and mediating diverse interests; objectives of technology development prioritizing societal benefits; international collaboration supported by science diplomacy, as well as learning from computing ethics and Responsible Innovation.

Research Design for an Integrated Artificial Intelligence Ethical Framework

Artificial Intelligence (AI) regulatory and other governance mechanisms have only started to emerge and consolidate. Therefore, AI regulation, legislation, frameworks, and guidelines are presently fragmented, isolated, or co-exist in an opaque space between national governments, international bodies, corporations, practitioners, think-tanks, and civil society organisations. This article proposes a research design set up to address this problem by directly collaborating with targeted actors to identify principles for AI that are trustworthy, accountable, safe, fair, non-discriminatory, and which puts human rights and the social good at the centre of its approach. It proposes 21 interlinked substudies, focusing on the ethical judgements, empirical statements, and practical guidelines, which manufacture ethicopolitical visions and AI policies across four domains: seven tech corporations, seven governments, seven civil society actors, together with the analysis of online public debates. The proposed research design uses multiple research techniques: extensive mapping and studies of AI ethics policy documents and 120 interviews of key individuals, as well as assorted analyses of public feedback discussion loops on AI, employing digital methods on online communities specialising in AI debates. It considers novel conceptual interactions communicated across the globe, expands the regulatory, ethics, and technological foresight, both at the individual level (autonomy, identity, dignity, privacy, and data protection) and the societal level (fairness/equality, responsibility, accountability and transparency, surveillance/datafication, democracy and trust, collective humanity and the common good). By producing an innovative, intercontinental, multidisciplinary research design for an Ethical AI Standard, this article offers a concrete plan to search for the Holy Grail of Artificial Intelligence: Its Ethics.

A robot arm digital twin utilising reinforcement learning

For many industry contexts, the implementation of Artificial Intelligence (AI) has contributed to what has become known as the fourth industrial revolution or “Industry 4.0” and creates an opportunity to deliver significant benefit to both businesses and their stakeholders. Robot arms are one of the most common devices utilised in manufacturing and industrial processes, used for a wide variety of automation tasks on, for example, a factory floor but the effective use of these devices requires AI to be appropriately trained. One approach to support AI training of these devices is the use of a “Digital Twin”. There are, however, a number of challenges that exist within this domain, in particular, success depends upon the ability to collect data of what are considered as observations within the environment and the application of one or many trained AI policies to the task that is to be completed. This project presents a case-study of creating and training a Robot Arm Digital Twin as an approach for AI training in a virtual space and applying this simulation learning within physical space. A virtual space, created using Unity (a contemporary Game Engine), incorporating a virtual robot arm was linked to a physical space, being a 3D printed replica of the virtual space and robot arm. These linked environments were applied to solve a task and provide training for an AI model. The contribution of this work is to provide guidance on training protocols for a digital twin together with details of the necessary architecture to support effective simulation in a virtual space through the use of Tensorflow and hyperparameter tuning. It provides an approach to addressing the mapping of learning in the virtual domain to the physical robot twin.

Actionable Principles for Artificial Intelligence Policy: Three Pathways

In the development of governmental policy for artificial intelligence (AI) that is informed by ethics, one avenue currently pursued is that of drawing on “AI Ethics Principles”. However, these AI Ethics Principles often fail to be actioned in governmental policy. This paper proposes a novel framework for the development of ‘Actionable Principles for AI’. The approach acknowledges the relevance of AI Ethics Principles and homes in on methodological elements to increase their practical implementability in policy processes. As a case study, elements are extracted from the development process of the Ethics Guidelines for Trustworthy AI of the European Commission’s “High Level Expert Group on AI”. Subsequently, these elements are expanded on and evaluated in light of their ability to contribute to a prototype framework for the development of 'Actionable Principles for AI'. The paper proposes the following three propositions for the formation of such a prototype framework: (1) preliminary landscape assessments; (2) multi-stakeholder participation and cross-sectoral feedback; and, (3) mechanisms to support implementation and operationalizability.

Bridging the gap: the case for an \u2018Incompletely Theorized Agreement\u2019 on AI policy

Recent progress in artificial intelligence (AI) raises a wide array of ethical and societal concerns. Accordingly, an appropriate policy approach is urgently needed. While there has been a wave of scholarship in this field, the research community at times appears divided amongst those who emphasize ‘near-term’ concerns and those focusing on ‘long-term’ concerns and corresponding policy measures. In this paper, we seek to examine this alleged ‘gap’, with a view to understanding the practical space for inter-community collaboration on AI policy. We propose to make use of the principle of an ‘incompletely theorized agreement’ to bridge some underlying disagreements, in the name of important cooperation on addressing AI’s urgent challenges. We propose that on certain issue areas, scholars working with near-term and long-term perspectives can converge and cooperate on selected mutually beneficial AI policy projects, while maintaining their distinct perspectives.

Analyzing Dilemmas Posed by Artificial Intelligence and 4IR Technologies Requires using all Available Models, Including the Existing International Human Rights Framework and Principles of AI Ethics

We are living in the epoch referred to as the ‘4th industrial revolution'. The 4th industrial Revolution (4IR) is a development characterized by a fusion of technologies that blur the digital, physical, and biological spheres (e.g., cyberspace, virtual and augmented reality, body-machine interface and robotics). Certain is the guaranteed ubiquitous adoption of these technologies, and futurism. Where the former is a reference to the increasing use and normalization of such technologies in everyday life, government service provision and industry. The latter is a reference to the philosophical/science fiction discussions that are emerging as a result of these changes (e.g. debates around the ‘singularity’, transhumanism, and posthumanism – often presented in utopian/dystopia terms). As such, the definition of digital ethics can be expanded and expressed in terms of the impacts of new digital technologies, through analysis of potential opportunities and risks in contemporary and future contexts. Many are working on forward‑looking policy frameworks and governance protocols, with broad multistakeholder engagement and buy‑in, to accelerate the adoption of emerging technologies in the global public interest, such as artificial intelligence (AI) and machine learning (ML) blockchain, 5G, data analytics, quantum computing, autonomous vehicles, synthetic biology, the internet of things (IoT), and killer robots or autonomous weapons systems (AWS). We have gained insight into the unequal distribution of the positive and negative impacts of AI on human rights throughout society, and have begun to explore the power of the human rights framework to address these disparate impacts. Although internationally recognized laws and standards on human rights provide a common standard of achievement for all people in all countries, more work is needed to understand how they can be best applied in the context of disruptive technology. AI systems raise myriad questions for society and democracy, only some of which are covered or addressed by existing laws. In order to fill these perceived gaps, a vocal group of governments, industry players, academics, and civil society actors have been promoting principles or frameworks for ethical AI. COVID-19 accelerated the use of AI in all countries and all fields. The pandemic accelerated the transition to a society that is increasingly based on the use of AI. This also increased the threats new risks related to human rights in the context of AI deployment. The human rights implications of governments' aggressive measures targeting the spread of COVID-19-related misinforation is also discussed. The question of whether corporations can act ethically is particularly relevant for Big Tech. Many of these firms are oligopolies that individuals and governments alike depend on completely, though they have little to no capacity to independently remedy issues when they arise, as Project Maven showed. Artificial intelligence and automated decision-making tools are increasing in power and centrality, and technology companies retain large troves of private data that it sells. These companies are at the forefront of technological innovation and may be caught up with the factual question of what can be done rather than the normative question of whether it should be done. All these issues arise in a field where there is little to no government regulation or intervention. The threats AI poses to society are so new, that the legal system is struggling to impose sufficient values and restrictions. Thus, a coherent approach to addressing AI ethics, values and consequences is, indeed, urgently needed. In May 2019, 42 countries adopted the Organization for Economic Co-operation and Development (OECD) AI Principles, a legal recommendation that includes five principles and five recommendations related to the use of AI. To ensure the successful implementation of the Principles, the OECD launched the AI Policy Observatory in February 2020. The Observatory publishes practical guidance about how to implement the AI Principles, and supports a live database of AI policies and initiatives globally. It also compiles metrics and measurement of global AI development and uses its convening power to bring together the private sector, governments, academia, and civil society. The AI ethics and governance initiatives discussed are cause for optimism that the global community will use all available models and brainpower for analysis and ultimately global governance of AI.

Artificial Intelligence Policy and Funding in Canada: Public Investments, Private Interests

Artificial Intelligence Policy and Funding in Canada: Public Investments, Private Interests

Human-centered artificial intelligence in education: Seeing the invisible through the visible

Abstract The inevitable rise and development of artificial intelligence (AI) was not a sudden occurrence. The greater the effect that AI has on humans, the more pressing the need is for us to understand it. This paper addresses research on the use of AI to evaluate new design methods and tools that can be leveraged to advance AI research, education, policy, and practice to improve the human condition. AI has the potential to educate, train, and improve the performance of humans, making them better at their tasks and activities. The use of AI can enhance human welfare in numerous respects, such as through improving the productivity of food, health, water, education, and energy services. However, the misuse of AI due to algorithm bias and a lack of governance could inhibit human rights and result in employment, gender, and racial inequality. We envision that AI can evolve into human-centered AI (HAI), which refers to approaching AI from a human perspective by considering human conditions and contexts. Most current discussions on AI technology focus on how AI can enable human performance. However, we explore AI can also inhibit the human condition and advocate for an in-depth dialog between technology- and humanity-based researchers to improve understanding of HAI from various perspectives.

Ethics and AI Startups

Artificial Intelligence (AI) startups use training data as direct inputs in product development. These firms must balance numerous trade-offs between ethical issues and data access without substantive guidance from regulators or existing judicial precedence. We survey these startups to determine what actions they have taken to address these ethical issues and the consequences of those actions. We find that 58% of these startups have established a set of AI principles. Startups with data-sharing relationships with large high-technology firms (i.e., Amazon, Google, Microsoft), that were negatively impacted by privacy regulations, or with prior (non-seed) funding from institutional investors are more likely to establish ethical AI principles. Lastly, startups with data-sharing relationships with large high-technology firms and prior regulatory experience with GDPR are more likely to incur negative business outcomes, like dropping training data or turning down business, to adhere to their ethical AI policies.

Exploratory Insights on Artificial Intelligence for Government in Europe

There is great interest to use artificial intelligence (AI) technologies to improve government processes and public services. However, the adoption of technologies has often been challenging for public administrations. In this article, the adoption of AI in governmental organizations has been researched as a form of information and communication technologies (ICT)–enabled governance innovation in the public sector. Based on findings from three cases of AI adoption in public sector organizations, this article shows strong similarities between the antecedents identified in previous academic literature and the factors contributing to the use of AI in government. The adoption of AI in government does not solely rely on having high-quality data but is facilitated by numerous environmental, organizational, and other factors that are strictly intertwined among each other. To address the specific nature of AI in government and the complexity of its adoption in the public sector, we thus propose a framework to provide a comprehensive overview of the key factors contributing to the successful adoption of AI systems, going beyond the narrow focus on data, processing power, and algorithm development often highlighted in the mainstream AI literature and policy discourse.

Proceduralizing control and discretion: Human oversight in artificial intelligence policy

This article is an examination of human oversight in EU policy for controlling algorithmic systems in automated legal decision making. Despite the shortcomings of human control over complex technical systems, human oversight is advocated as a solution against the risks of increasing reliance on algorithmic tools. For law, human oversight provides an attractive, easily implementable and observable procedural safeguard. However, without awareness of its inherent limitations, human oversight is in danger of becoming a value in itself, an empty procedural shell used as a stand-in justification for algorithmization but failing to provide protection for fundamental rights. By complementing socio-legal analysis with Science and Technology Studies, critical algorithm studies, organization studies and human-computer interaction research, the author explores the importance of keeping the human in the loop and asks what the human element at the core of legal decision making is. Through algorithmization it is made visible how law conceptualises decision making through human actors, personalises legal decision making through the decision-maker’s discretionary power that provides proportionality and common sense, prevents gross miscarriages of justice and establishes the human encounter deemed essential for the feeling of being heard. The analysis demonstrates the necessary human element embedded in legal decision making, against which the meaningfulness of human oversight needs to be examined.

Toward Trustworthy and Responsible Artificial Intelligence Policy Development

Artificial intelligence (AI) technologies are already creating new sectors of the economy and revitalizing industries. Governments and societies around the globe are working to determine where and how AI fits into existing legal, ethical, and regulatory frameworks or where new ones are needed. Policy and governance are paramount to ensuring emerging technologies like AI are utilized to their fullest potential to benefit humanity while mitigating inherent risks and addressing societal concerns. This article provides the views of the four American Association for the Advancement of Science (AAAS) Science & Technology Policy Fellows working on a host of issues surrounding AI along with an overview of some of the U.S. Government efforts in these areas.

The Chinese Approach to Artificial Intelligence: An Analysis of Policy and Regulation

In July 2017, China’s State Council released the country’s strategy for developing artificial intelligence (AI), entitled ‘New Generation Artificial Intelligence Development Plan’ (新一代人工智能发展规划). This strategy outlined China’s aims to become the world leader in AI by 2030, to monetise AI into a trillion-yuan (ca. 150 billion dollars) industry, and to emerge as the driving force in defining ethical norms and standards for AI. Several reports have analysed specific aspects of China’s AI policies or have assessed the country’s technical capabilities. Instead, in this article, we focus on the socio-political background and policy debates that are shaping China’s AI strategy. In particular, we analyse the main strategic areas in which China is investing in AI and the concurrent ethical debates that are delimiting its use. By focusing on the policy backdrop, we seek to provide a more comprehensive and critical understanding of China’s AI policy by bringing together debates and analyses of a wide array of policy documents.

The Chinese approach to artificial intelligence: an analysis of policy, ethics, and regulation

In July 2017, China’s State Council released the country’s strategy for developing artificial intelligence (AI), entitled ‘New Generation Artificial Intelligence Development Plan’ (新一代人工智能发展规划). This strategy outlined China’s aims to become the world leader in AI by 2030, to monetise AI into a trillion-yuan (ca. 150 billion dollars) industry, and to emerge as the driving force in defining ethical norms and standards for AI. Several reports have analysed specific aspects of China’s AI policies or have assessed the country’s technical capabilities. Instead, in this article, we focus on the socio-political background and policy debates that are shaping China’s AI strategy. In particular, we analyse the main strategic areas in which China is investing in AI and the concurrent ethical debates that are delimiting its use. By focusing on the policy backdrop, we seek to provide a more comprehensive and critical understanding of China’s AI policy by bringing together debates and analyses of a wide array of policy documents.

AI strategy of India: policy framework, adoption challenges and actions for government

Purpose The purpose of this study is to provide recommendations for policy framework on artificial intelligence (AI) in India. Design/methodology/approach Studies have been conducted through focus group discussion and the other sources such as different company websites using AI, Indian Government strategy reports on AI, literature studies, different policies implemented on AI in different locations and other relevant documents. After those studies, a charter of recommendation has been provided. This will help the authority to frame the AI policy for India. Findings This study highlights that “National Strategy for AI” for India needs improvement to provide comprehensive inputs for framing policy on AI. This study also implies that focus is to be given on security, privacy issues including issues of governance. Research limitations/implications AI-related technology has immense potential toward the development of organizations. This study implies the necessity of framing a comprehensive policy on AI for India. If there is a comprehensive policy on AI for India, the Indian industries will derive many benefits. Practical implications This study provides inputs on how the industries of India can be benefitted with the help of AI and how R&D can develop the AI activities to harness maximum benefits from this innovative technology. Social implications AI-related policy will have appreciable influence on the society in terms of human–device interactions and communications. The policy framework on AI for India is expected to project far-reaching effects toward deriving benefits to the society. Originality/value This paper has taken a holistic and unique attempt to provide inputs to the policymakers for framing a comprehensive and meaningful policy on AI for India.

Harnessing artificial intelligence (AI) to increase wellbeing for all: The case for a new technology diplomacy

The field of artificial intelligence (AI) is experiencing a period of intense progress due to the consolidation of several key technological enablers. AI is already deployed widely and has a high impact on work and daily life activities. The continuation of this process will likely contribute to deep economic and social changes. To realise the tremendous benefits of AI while mitigating undesirable effects will require enlightened responses by many stakeholders. Varying national institutional, economic, political, and cultural conditions will influence how AI will affect convenience, efficiency, personalisation, privacy protection, and surveillance of citizens. Many expect that the winners of the AI development race will dominate the coming decades economically and geopolitically, potentially exacerbating tensions between countries. Moreover, nations are under pressure to protect their citizens and their interests—and even their own political stability—in the face of possible malicious or biased uses of AI. On the one hand, these different stressors and emphases in AI development and deployment among nations risk a fragmentation between world regions that threatens technology evolution and collaboration. On the other hand, some level of differentiation will likely enrich the global AI ecosystem in ways that stimulate innovation and introduce competitive checks and balances through the decentralisation of AI development. International cooperation, typically orchestrated by intergovernmental and non-governmental organisations, private sector initiatives, and by academic researchers, has improved common welfare and avoided undesirable outcomes in other technology areas. Because AI will most likely have more fundamental effects on our lives than other recent technologies, stronger forms of cooperation that address broader policy and governance challenges in addition to regulatory and technological issues may be needed. At a time of great challenges among nations, international policy coordination remains a necessary instrument to tackle the ethical, cultural, economic, and political repercussions of AI. We propose to advance the emerging concept of technology diplomacy to facilitate the global alignment of AI policy and governance and create a vibrant AI innovation system. We argue that the prevention of malicious uses of AI and the enhancement of human welfare create strong common interests across jurisdictions that require sustained efforts to develop better, mutually beneficial approaches. We hope that new technology diplomacy will facilitate the dialogues necessary to help all interested parties develop a shared understanding and coordinate efforts to utilise AI for the benefit of humanity, a task whose difficulty should not be underestimated.

A Study on the Establishment of Intelligent National Crisis Management System in the Intelligent Information Society

정부는 4차 산업혁명기의 전개에 따라 초연결화를 바탕으로 초지능화를 확보하여 지능정보사회를 이루고 지능형 정부를 구현하기 위한 다양한 정책을 추진하고 있다. 따라서 국가위기관리도 환경변화에 대응하고 주요 정보통신기술(ICT)에 의한 지능화가 필요하다. 본 연구의 목적은 지능정보사회의 전개에 따라 국가위기관리의 지능화를 위한 정책적 방안을 모색하는데 있다. 이를 위해 인공지능(AI)을 기반으로 하는 국가위기관리의 필요성에 대하여 고찰하고, 주요 국가들의 인공지능(AI) 정책을 살펴 본 후, 인공지능(AI) 기반의 국가위기관리체계 구축을 위한 방안을 연구하였다. 연구 결과, 위기 유형별 데이터베이스화를 통해 위기관리체제의 정보화가 우선 필요하며, 이러한 정보화를 달성한 기관 간에 인프라를 구축하고, 구축한 인프라는 동일한 위기관리 플랫폼에서 운용되어야 하며, 이러한 플랫폼의 운용을 위한 전문 인력 양성과 조직 편성이 필요하다는 것을 알 수 있었다.Within the fourth industrial revolution, the South Korean government has employed various policies to establish an intelligent information society and intelligent government by securing super-intelligence based on hyper-connections. National crisis management needs to respond to environmental changes and become more intelligent using ICTs. The purpose of this study is to explore policy measures for securing intelligence for national crisis management in accordance with the development of an intelligent information society. To this end, we examined the need for AI (Artificial Intelligence)-based national crisis management and developed ways to establish AI-based crisis management system based on the review of AI policies in other major countries. The findings suggest, first setting up the IT-based system of crisis management, building and operating infrastructure among the IT-based agencies within the same platforms, and training professional manpower and restructuring organization for the operation of these platforms.

Making AI Work in Indian Education

This paper explores the potential impact of Artificial Intelligence (AI) on educational processes and outcomes. It examines key concerns with respect to rights-based development that AI policy and programming frameworks should address to support ethical, inclusive and universal education in India. The paper is based on interviews with educationists and organisations working in the area of AI and education, and desk research conducted by IT for Change.