Artificial Intelligence raises new, distinct governance challenges, as well as familiar governance challenges in novel ways. The governance of AI, moreover, is not an issue of distant futures, it is well underwayand it has characteristics akin to 'herding cats' with a mind of their own. This essay introduces the contributions to the special issue, situating them in broader political and social science literatures. It then provides a sketch of an interdisciplinary research agenda. It highlights the limits of 'explainable AI', makes the case for considering AI ethics and AI governance simultaneously, identifies as an underappreciated risk 'system effects' that arise from the introduction of AI applications, and calls for policymakers to consider both the opportunities and the risks of AI. Focusing on the (ab)uses of AI, rather than the complex, rapidly changing and hard-to-predict technology as such, might provide a superior approach to governing AI.

Artificial Intelligence (AI) technologies are expected to have numerous and diverse social implications that cut deep into our society. Due to AI’s specific nature as emergent and constantly evolving generic technology, we need new approaches, methodologies, and processes to govern and steer the utilization of AI technologies both in the public and private sectors. This is both a multilevel and multi-dimensional governance challenge. First, there has to be a shared and coordinated understanding across various social and administrational sectors on how AI is implemented and regulated. Second, good coordination between different levels of governance is crucial. Third, there is a challenge to find a balance between soft and hard governance mechanisms in varying implementation and organizational contexts. This paper presents an overview of a new Strategic Research Council funded project project entitled “Ethical AI for the Governance of the Society” (ETAIROS). The project focuses on stu...

While recent debates about societal aspects of Artificial Intelligence (AI) have largely focused on ethics principles and guidelines, questions of governance, politics and policies of AI have received less scrutiny. To address this gap, over more than three years I have been leading AI governance research programme to examine questions such as – What are the roles of the government in shaping AI development and use? And what are the roles of society? How and why AI strategies are developed and launched? And which ideas, interests and values do they prioritise and which ones do they leave out? These questions are addressed in our analysis of 49 AI policy documents adopted by national governments, international organizations, consultancies, think tanks, and civil society organizations. An interdisciplinary conceptual framework developed for this research approaches AI as an emerging technology characterized by fast growth, considerable impacts, uncertainty, hype, and positive as well as negative expectations.

The rapid developments in Artificial Intelligence (AI) and the intensification in the adoption of AI in domains such as autonomous vehicles, lethal weapon systems, robotics and alike pose serious challenges to governments as they must manage the scale and speed of socio-technical transitions occurring. While there is considerable literature emerging on various aspects of AI, governance of AI is a significantly underdeveloped area. The new applications of AI offer opportunities for increasing economic efficiency and quality of life, but they also generate unexpected and unintended consequences and pose new forms of risks that need to be addressed. To enhance the benefits from AI while minimising the adverse risks, governments worldwide need to understand better the scope and depth of the risks posed and develop regulatory and governance processes and structures to address these challenges. This introductory article unpacks AI and describes why the Governance of AI should be gaining far more attention given the myriad of challenges it presents. It then summarises the special issue articles and highlights their key contributions. This special issue introduces the multifaceted challenges of governance of AI, including emerging governance approaches to AI, policy capacity building, exploring legal and regulatory challenges of AI and Robotics, and outstanding issues and gaps that need attention. The special issue showcases the state-of-the-art in the governance of AI, aiming to enable researchers and practitioners to appreciate the challenges and complexities of AI governance and highlight future avenues for exploration.

In this article we discuss ways AI can be fruitful and inimical at the same time and consider hurdles in implementing ethics and governance of AI. We conclude with presenting solutions to overcome this issue. Artificial intelligence (AI) is a technology that allows a computer system to mimic the human mind. AI, like humans, is capable of learning and developing itself through doing tasks such as planning, organizing, and executing numerous activities. However, as we develop and expand our understanding of AI, there are a few advantages and downsides that should be addressed. Privacy and security are vital, but they conflict with the advancement of AI technology since computers and AI require a large quantity of data to Comprehend and anticipate outcomes. With the advancement of technology, we should be able to maximize security and eliminate the current drawbacks.

The increasingly pervasive role of Artificial Intelligence (AI) in our societies is radically changing the way that social interaction takes place within all fields of knowledge. The obvious opportunities in terms of accuracy, speed and originality of research are accompanied by questions about the possible risks and the consequent responsibilities involved in such a disruptive technology. In recent years, this twofold aspect has led to an increase in analyses of the ethical and political implications of AI. As a result, there has been a proliferation of documents that seek to define the strategic objectives of AI together with the ethical precautions required for its acceptable development and deployment. Although the number of documents is certainly significant, doubts remain as to whether they can effectively play a role in safeguarding democratic decision-making processes. Indeed, a common feature of the national strategies and ethical guidelines published in recent years is that they only timidly address how to integrate civil society into the selection of AI objectives. Although scholars are increasingly advocating the necessity to include civil society, it remains unclear which modalities should be selected. If both national strategies and ethics guidelines appear to be neglecting the necessary role of a democratic scrutiny for identifying challenges, objectives, strategies and the appropriate regulatory measures that such a disruptive technology should undergo, the question is then, what measures can we advocate that are able to overcome such limitations? Considering the necessity to operate holistically with AI as a social object, what theoretical framework can we adopt in order to implement a model of governance? What conceptual methodology shall we develop that is able to offer fruitful insights to governance of AI? Drawing on the insights of classical pragmatist scholars, we propose a framework of democratic experimentation based on the method of social inquiry. In this article, we first summarize some of the main points of discussion around the potential societal, ethical and political issues of AI systems. We then identify the main answers and solutions by analyzing current national strategies and ethics guidelines. After showing the theoretical and practical limits of these approaches, we outline an alternative proposal that can help strengthening the active role of society in the discussion about the role and extent of AI systems.

How does society perceive Artificial Intelligence (AI) and what do people expect from it? Is AI seen as a major force that will change global power dynamics or is it perceived as a solution to the main problems that society face today like climate change and poverty? These are some of the questions explored in the recent publications from my research programme on governance, politics and policy of AI, analysing how policy documents from Europe and the United States frame AI, its purpose and recommendations to govern it.

AI-based systems are "black boxes," resulting in massive information asymmetries between the developers of such systems and consumers and policymakers. In order to bridge this information gap, this article proposes a conceptual framework for thinking about governance for AI. M any sectors of society rapidly adopt digital technologies and big data, resulting in the quiet and often seamless integration of AI, autonomous systems, and algorith-mic decision-making into billions of human lives. 1,2 AI and algorithmic systems already guide a vast array of decisions in both private and public sectors. For example, private global platforms, such as Google and Facebook, use AI-based filtering algorithms to control access to information. AI algorithms that control self-driving cars must decide on how to weigh the safety of passengers and pedestrians. 3 Various applications, including security and safety decision-making systems, rely heavily on AI-based face recognition algorithms. And a recent study from Stanford University describes an AI algorithm that can deduce the sexuality of people on a dating site with up to 91 percent accuracy. 4 Voicing alarm at the capabilities of AI evidenced within this study, and as AI technologies move toward broader adoption, some voices in society have expressed concern about the unintended consequences and potential downsides of widespread use of these technologies. To ensure transparency, accountability, and explainability for the AI ecosystem, our governments , civil society, the private sector, and academia must be at the table to discuss gover-nance mechanisms that minimize the risks and possible downsides of AI and autonomous systems while harnessing the full potential of this technology. 5 Yet the process of designing a gov-ernance ecosystem for AI, autonomous systems, and algorithms is complex for several reasons. As researchers at the University of Oxford point out, 3 separate regulation solutions for decision-making algorithms, AI, and robot-ics could misinterpret legal and ethical challenges as unrelated, which is no longer accurate in today's systems. Algorithms, hardware, software, and data are always part of AI and autonomous systems. To regulate ahead of time is difficult for any kind of industry. Although AI technologies are evolving rapidly, they are still in the development stages. A global AI governance system must be flexible enough to accommodate cultural differences and bridge gaps across different national legal systems. While there are many approaches we can take to design a governance structure for AI, one option is to take inspiration from the development and evolution of governance structures that act on the Internet environment. Thus, here we discuss different issues associated with gov-ernance of AI systems, and introduce a conceptual framework for thinking about governance for AI, autonomous systems, and algorithmic decision-making processes. The Nature of AI Although AI-based applications are increasingly adopted in hospitals, courtrooms, schools, at home, and on the road to support (and in some instances, even guide) human decision-making,

Recent advances in AI raise questions about its social impacts and implementation. In response, governments and public administrations seek to develop adequate governance frameworks to mitigate risks and maximize the potential of AI development and use. Such work largely deals with questions of how challenges and risks should be managed, which values and goals should be pursued, and through which institutional mechanisms and principles these goals could be achieved. In this paper, we conduct a systematic review of the existing literature on the development of AI governance for public administration. The article describes principles and means by which public administrations could guide and steer AI developers and users in adopting ethical and responsible practices. The reviewed literature indicates a need for public administrations to move away from top-down hierarchical governance principles and adopt forms of inclusive policy-making to ensure the actionability of ethical and respon...