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One of the fundamental critiques against twentieth century experiments in central economic planning, and the main reason for their failures, was the inability of humandirected planning systems to manage the data gathering, analysis, computation, and control necessary to direct the vast complexity of production, allocation, and exchange decisions that make up a modern economy. Rapid recent advances in AI, data, and related technological capabilities have re-opened that old question, and provoked vigorous speculation about the feasibility, benefits, and threats of an AI-directed economy. This paper presents a thought experiment about how this might work, based on assuming a powerful AI agent (whimsically named “Max”) with no binding computational or algorithmic limits on its (his) ability to do the task. The paper’s novel contribution is to make this hitherto under-specified question more concrete and specific. It reasons concretely through how such a system might work under explicit assumptions about contextual conditions; what benefits it might offer relative to present market and mixed-market arrangements; what novel requirements or constraints it would present; what threats and challenges it would pose, and how it inflects long-standing understandings of foundational questions about state, society, and human liberty.As with smaller-scale regulatory interventions, the concrete implementation of comprehensive central planning can be abstracted as intervening via controlling either quantities or prices. The paper argues that quantity-based approaches would be fundamentally impaired by problems of principal-agent relations and incentives, which hobbled historical planning systems and would persist under arbitrary computational advances. Price-based approaches, as proposed by Oskar Lange, do not necessarily suffer from the same disabilities. More promising than either, however, would be a variant in which Max manages a comprehensive system of price modifications added to emergent market outcomes, equivalent to a comprehensive economy-wide system of Pigovian taxes and subsidies. Such a system, “Pigovian Max,” could in principle realize the information efficiency benefits and liberty interests of decentralized market outcomes, while also comprehensively correcting externalities and controlling inefficient concentration of market power and associated rent-seeking behavior. It could also, under certain additional assumptions, offer the prospect of taxation without deadweight loss, by taking all taxes from inframarginal rents.Having outlined the basic approach and these potential benefits, the paper discusses several challenges and potential risks presented by such a system. These include Max’s need for data and the potential costs of providing it; the granularity or aggregation of Max’s determinations; the problem of maintaining variety and innovation in an economy directed by Max; the implications of Max for the welfare of human workers, the meaning and extent of property rights, and associated liberty interests; the definition of social welfare that determines Max’s objective function, its compatibility with democratic control, and the resultant stability of the boundary between the state and the economy; and finally, the relationship of Max to AI-enabled trends already underway, with implications for the feasibility of Max being developed and adopted, and the associated risks. In view of the depth and difficulty of these questions, the discussion of each is necessarily preliminary and speculative.

Proposed geoengineering interventions, like other high-stakes and potentially disruptive technologies, present both a compelling case for expanded research to inform future decisions, and significant concerns about societal harms that may follow from this research, directly or indirectly. In response, there have been widespread calls to both expand research and govern this research with greater care and scrutiny than typical of the normal processes that govern all research areas. We propose that for geoengineering and similarly controversial issues, governance of research must fulfill three broad functions. First, processes are needed that enable reliable research, by providing the authorization, resources, and management necessary for research to proceed, together with the strategic planning and quality controls to ensure that research results are useful and relevant to inform societal choices. Second, processes are needed to assess potential harms or risks from research activities and ensure that these are appropriately managed. These potential harms may include both direct physical risks, and indirect risks mediated by social, economic, or political processes. Finally, processes are needed to support the legitimacy of the research program, by ensuring that the topics, methods, and conduct are compatible with relevant legal, political, and moral principles and are broadly acceptable to affected citizens. These requirements may interact closely with the processes that serve the first two functions, by requiring that research priorities, aims, conduct, participants, and results are transparently and promptly disclosed, that relevant citizen and stakeholder groups are consulted, and that broader implications of proposed research are acknowledged and addressed. Drawing on the concerns expressed in the current geoengineering debate, and on experience conducting and governing research in other areas, we discuss alternative concrete ways to provide these functions for geoengineering research. This paper was prepared as input to a workshop of senior state officials considering the implications of potential geoengineering research for California.

The works assembled here are the initial outputs of the First International Summer Institute on Artificial Intelligence and Society (SAIS). The Summer Institute was convened from July 21 to 24, 2019 at the Alberta Machine Intelligence Institute (Amii) in Edmonton, in conjunction with the 2019 Deep Learning/Reinforcement Learning Summer School. The Summer Institute was jointly sponsored by the AI Pulse project of the UCLA School of Law (funded by a generous grant from the Open Philanthropy Project) and the Canadian Institute for Advanced Research (CIFAR), and was coorganized by Ted Parson (UCLA School of Law), Alona Fyshe (University of Alberta and Amii), and Dan Lizotte (University of Western Ontario). The Summer Institute brought together a distinguished international group of 80 researchers, professionals, and advanced students from a wide range of disciplines and areas of expertise, for three days of intensive mutual instruction and collaborative work on the societal implications of AI, machine learning, and related technologies. The scope of discussions at the Summer Institute was broad, including all aspects of the societal impacts of AI, lternative approaches to their governance, and associated ethical issues.

The potential societal impacts of artificial intelligence (AI) and related technologiesare so vast, they are often likened to those of past transformative technologicalchanges such as the industrial or agricultural revolutions. They are also deeplyuncertain, presenting a wide range of possibilities for good or ill – as indeed thediverse technologies lumped under the term AI are themselves diffuse, labile, anduncertain. Speculation about AI’s broad social impacts ranges from full-on utopia todystopia, both in fictional and non-fiction accounts. Narrowing the field of view fromaggregate impacts to particular impacts and their mechanisms, there is substantial(but far from total) agreement on some – e.g., profound disruption of labor markets,with the prospect of unemployment that is novel in scale and breadth – but greatuncertainty on others, even as to sign. Will AI concentrate or distribute economicand political power – and if concentrate, then in whom? Will it make human lives andsocieties more diverse or more uniform? Expand or contract individual liberty?Enrich or degrade human capabilities? On all these points, the range of presentspeculation is vast.

Artificial intelligence (AI), particularly various methods of machine learning (ML), has achieved landmark advances over the past few years in applications as diverse as playing complex games, language processing, speech recognition and synthesis, image identification, and facial recognition. These breakthroughs have brought a surge of popular, journalistic, and policy attention to the field, including both excitement about anticipated advances and the benefits they promise, and concern about societal impacts and risks – potentially arising through whatever combination of accident, malicious or reckless use, or just social and political disruption from the scale and rapidity of change.

California's Low Carbon Fuel Standard (LCFS) is an ambitious, innovative, and controversial policy that controls greenhouse-gas emissions associated with transport fuels – a large emissions source mostly neglected by prior climate policies, with unique technical challenges of uncertainty, long time-horizons, and network effects, that hinder its response to economy-wide emissions-pricing policies. The LCFS was introduced in 2011 as one measure to pursue the goal of California's landmark 2006 climate law, returning emissions to 1990 levels by 2020. LCFS regulations were revised in 2015 and further changes are now proposed for 2019, under a new statutory target for state emissions 40 percent below 1990 by 2030.Now in effect for seven years, the LCFS is a major element of California's climate policy. It has survived early legal challenges suffering only some implementation delays, and has generated large expansions of alternative fuel supply and significant reductions in overall carbon intensity in California's fuel markets. Yet the policy remains controversial and faces continuing legal challenges and policy critiques of its effectiveness, cost, and legality.This paper provides a critical review of the LCFS, particularly regarding challenges likely to arise in pursuing deeper cuts after 2020. It is based in part on discussions at a 2015 workshop held at the Emmett Institute at UCLA School of Law, which sought to bring the LCFS to broader attention among environmental law scholars and identify key legal and policy design challenges moving forward. The paper draws on the workshop's background paper and discussions, but is substantially extended based on more recent developments and further research.

Calls for moratoria are a frequent response to controversial issues in international diplomacy and control of technology, and are now prominent in debates over governance challenges posed by climate engineering (CE) – intentional modification of the global climate to reduce changes caused by human emissions of greenhouse gases. Based on twelve historical cases of moratoria in other areas of diplomatic conflict or controversial science and technology, we present a novel analytic framework to examine purposes, design characteristics, and conditions for effectiveness of moratoria, based on a taxonomy of three ideal moratorium types: risk-management moratoria, principled-conflict moratoria, and bargaining moratoria. We use this framework to examine potential contributions and design conditions for a moratorium on CE. A moratorium for CE could seek primarily to advance risk-management aims or bargaining aims, with distinct implications for its timing, scope, associated actors, and conditions for termination. Beyond the current, high-stakes case of CE, the proposed analytic framework has broader implications for critical examination of moratorium proposals, current and future, in other areas of controversial research, technology, and governance challenges.

Continued failure to limit emissions of carbon dioxide and other greenhouse gases that are causing global climate change has brought increased attention to climate engineering (CE) technologies, which actively modify the global environment to counteract heating and climate disruptions caused by elevated greenhouse gases. Some proposed forms of CE, particularly spraying reflective particles in the upper atmosphere to reduce incoming sunlight, can cool the average temperature of the Earth rapidly and cheaply, thereby substantially reducing climate-related risks. Yet CE interventions provide only imperfect corrections for the climatic and other environmental effects of elevated greenhouse gases, and carry their own environmental risks. Moreover, they may also increase risks, by weakening political support for essential emission reductions or providing new triggers for international conflict. These technologies thus require international governance, but also pose novel and severe challenges to current international laws and institutions. Effective governance of CE will require a capacity to make decisions regarding the conditions, if any, under which specific interventions are authorized, plus real-time operational oversight of any interventions that are conducted. Decision processes must be effectively linked with scientific research and assessment, and with institutions to manage and respond to threats of CE-related conflict. We advance preliminary suggestions to address two priority areas for early investigation: how international cooperation on early CE research can help develop shared norms that can grow robust enough to support future decision needs; and how early research and development on CE can be made to complement and encourage, rather than undermining, parallel efforts to reduce climate risks by cutting emissions.

What drives innovation? In 'What Does Innovation Today Tell Us about the US Economy Tomorrow?' (Issues, Fall 2017), Jeffrey Funk starts with an assertion that puzzles me, but after that [...]

Describes documents produced at the United Nations Conference and the Global Forum: The Rio Declaration, a statement of broad principles to guide national conduct on environmental protection and development; treaties on climate change and biodiversity; forest principles statement; and Agenda 21, a presentation of work plans for sustainable development. Products of the nongovernmental organizations meetings are also discussed. (MCO)

Over the past five to ten years, policy debate on climate change has seen a surge of attention, and controversy, over technologies of climate engineering. These are engineered interventions that [...]