David G. Victor

Research managers and investors need better approaches to weigh risks and potential benefits of scalable, transformational technologies.

Liver transplantation (LT) is the definitive treatment for end-stage liver disease and certain liver cancers. This involves complex decision making across the transplant continuum. Artificial intelligence (AI), with its ability to analyze high-dimensional data and derive meaningful patterns, shows promise as a transformative tool to address these challenges. In this narrative review, we searched PubMed from January 2021 to October 2024 using keywords such as “artificial intelligence”, “machine learning”, “deep learning”, and “liver transplantation”. Only full-text, English-language studies on adult populations (with minimum sample sizes deemed appropriate by each study’s design) were included, with a total of 65 articles. These publications examined AI applications in pre-transplant risk assessment (9), donor liver assessment (11), transplant oncology (11), graft survival prediction (7), overall survival prediction (11), immunosuppression management (4), and post-transplant risk prediction (12). Tree-based methods showed high accuracy in predictive tasks, while deep learning excelled in medical imaging analysis. Despite these advancements, only 6% of studies addressed algorithmic fairness, and 41% of neural network implementations lacked interpretability methods. Key challenges included data harmonization, multicenter validation, and integration with existing clinical workflows. Despite these limitations, AI continues to show promise for optimizing critical steps along the LT continuum. As the field progresses, the focus must remain on using AI to expand access and optimize care, ensuring it supports rather than restricts transplant opportunities.

Since 1990, the state of California has implemented numerous policy instruments to support zero-emission vehicles. While battery electric vehicles (BEV) have commanded much attention, the significance of California's policies on fuel cell electric vehicles (FCEV) has not been studied systematically. Here, we perform the first-ever such analysis of FCEV and hydrogen fuel policies by conducting elicitation interviews with 46 experts from industry, government, and academia. From the literature, we identify 11 existing policy instruments—including market-based programs, subsidies, regulations, taxes, and information policies—and quantitatively evaluate their expected overall and relative impacts on California's FCEV market. Expert judgments vary, but the most important of these 11 focus on developing hydrogen refueling stations and clean hydrogen fuel supply—specifically through infrastructure grants and hydrogen capacity credits in the state's Low Carbon Fuel Standard. Views vary by expert affiliation: e.g., industry association members score refueling infrastructure highly, while transit agencies emphasize hydrogen fuel supply. Experts also emphasize broader policy strategies, including focusing support for FCEVs where they are most competitive economically (in transit bus, medium-, and heavy-duty markets) and measures to assure that infrastructure support is long-lived and durable. California cannot, by itself, transform the global FCEV market. But if the experiences of California, an FCEV market pioneer, guide FCEV policies and spur adoption in other markets, then FCEVs could become central to global decarbonization of transportation.

Abstract The Intergovernmental Panel on Climate Change estimates that societies may need to remove 5–16 GtCO 2 from the atmosphere annually to reach global net-zero CO 2 emissions within this century. Yet there has been little analysis of how quickly carbon dioxide removal (CDR) strategies could scale to meet this expected need. We develop a new integrated modeling approach for assessing scalability that combines insights from the history of analogous technological revolutions with information about the efficacy and specific constraints of CDR strategies. We illustrate our approach with genetically enhanced crops that grow larger roots and, in turn, increase soil carbon. Unlike many CDR technologies whose deployment will be slowed by the need for novel and costly infrastructures, history suggests that crop innovations can scale rapidly in countries that admit them. Within 13 years of first deployment, diffusion of enhanced crops could peak and remove 0.9–1.2 GtCO 2 yr –1 —about 7 times larger than all CO 2 offsets supplied today to the global voluntary offsets market. Upscaling depends on policy and politics, as they affect the total land area on which carbon-absorbing crops are allowed. Early scaling could allow crop engineering to play an outsized role in a portfolio of CDR strategies that, overall, scales to IPCC-like levels of carbon removal, even though carbon storage in soils is less permanent than geological storage.

Many workplaces and other institutions are grappling with how to plan and deploy electric vehicle (EV) charging networks to support their employees and other constituents who drive EVs. We develop a novel approach for designing EV charging networks that is driver-centric: it estimates drivers' charging needs based on their driving and charging habits and determines the optimal number and type of chargers to install to meet those needs. Unlike prior literature, our framework establishes a unique individual profile for each driver based on their observed behaviors and habits. We demonstrate our approach at the University of California San Diego (UCSD) EV network of 439 charging ports using behavioral data derived from 800 EV drivers. We find that using unique driver profiles significantly increases expected network usage and size—in some cases requiring fivefold more workplace charging sessions and a threefold larger network compared to the same analysis based on regionally-averaged driver data. These increases are driven by drivers' tendency to recharge with high battery state-of-charge, which increases network size by 50 % alone and implies less value in using high-power chargers. An institution's goals for supporting drivers, which are important for equity, also significantly affect network size.

Aviation is under tremendous pressure to mitigate its impacts on the climate, but the best response strategies are unknown today due to deep uncertainties. How low-emission fuels will scale to levels relevant for the industry, along with the best strategies for managing contrails and other non-CO 2 effects, are unknowable today with unknown cost and disruption. A conventional risk-based approach that involves investment across a known set of options is unworkable; instead, we argue that an experimentalist approach is needed that addresses deep uncertainties head on. This hinges on four key factors: a critical mass of actors facing strong incentives to identify solutions, a wide search for alternatives through experiments, periodic assessments, and adjustment of goals and strategies. Present strategies do not give enough attention to higher-risk alternatives with disruptive potential, because those approaches have few political and organizational supporters. Small groups of highly motivated actors─such as the nascent coalition of first movers on clean aviation already forming in Europe and the U.S.─could initiate an experimentalist program. The challenges of the aviation sector mirror other hard-to-abate sectors, making this framework potentially applicable to a wider set of sectors where technological, business, and investment choices are shrouded in deep uncertainty.

Abstract Planetary sustainability is in trouble, heading towards what pioneer of evolutionary biology, E.O Wilson, twenty-two years ago called a “bottleneck”. Created through the actions of humanity this is an increasingly narrow passage through which only some species can pass, and on which humans depend to provide the sources of re-radiation. What is lost is hard to impossible to restore. Keeping this passage as wide as possible is crucial, but the trends are not yet promising. At a time when those trends appear to be converging to a human and ecological crisis of planetary but finite duration, changed priorities are required whilst at the same time providing opportunity. In particular, strategies, such as experimental governance devised to act in the face of unknowns and uncertain knowledge provide a basis for action to hold open and successfully pass through the bottleneck, a goal which is of the highest importance for humans as we seek to achieve a sustainable future.

Abstract Empirical research aimed at understanding public awareness and opinion on climate change has focused heavily on media coverage. Nearly all prior media studies focus on the United States and on a small number of elite news sources, notably the national newspapers of record. To widen the aperture, we take advantage of a database (MediaCloud) that covers a much larger array of print and word media: 168 million articles about all subjects, derived from 9000 unique U.S. news sources. Coverage of climate change from the “heartland” sources—dominated by state and local news outlets far from the headquarters of national newspapers of record—has risen 144% from 2011 until 2022. Elite news coverage, however, has risen at twice that pace (299%). Over time, the propensity to cover climate change has diverged. In 2011 there were 104 days when the heartland news sources had more coverage of climate change than elite news outlets such as The New York Times and The Wall Street Journal . By 2022 there were only 11 such days. That year, elite news outlets produced roughly three times the coverage of climate change as heartland news outlets. We also find some differences in the topics covered by these two categories of news sources. Such disparities in the intensity of attention to climate change, along with apparently more subtle variations in topical coverage, are variations that deserve future explanation. They are also a reminder that analysis of climate coverage should choose data sources with care since the narrative around what the public is learning about climate appears to vary substantially between heartland and elite new sources.

Abstract Empirical research aimed at understanding public awareness and opinion on climate change has focused heavily on media coverage. Nearly all prior media studies focus on the United States and on a small number of elite news sources, including the national newspapers of record. Here we take advantage of a database (MediaCloud) that covers a much larger array of print and word media: 168 million articles about all subjects, derived from 9000 unique U.S. news sources. Coverage of climate change from these “heartland” sources—dominated by state and local news outlets far from the headquarters of national newspapers of record—has risen 144% from 2011 until 2022. Elite news coverage, however, has risen at twice that pace (299%). Both news sources show spikes in coverage related to similar events (e.g. negotiation of the Paris Accords or President Trump’s withdrawal from Paris); both see a decline in coverage when other events become more prominent (e.g., the first COVID-19 cases). Heartland news sources pay close attention to events such as the discussion of climate change by Pope Francis and to right-wing media campaigns; elite news sources are more focused on climate conferences and extreme weather. Over time, the propensity to cover climate change has diverged. In 2011 there were 104 days when the heartland news sources had more coverage of climate change than elite news outlets such as The New York Times and The Wall Street Journal . By 2022 there were only 11 such days. That year, elite news outlets produced roughly three times the coverage of climate change as heartland news outlets, most of which cover state and local matters.

Aligning electric vehicle (EV) charging with periods of abundant clean energy is essential for decarbonizing transportation. In solar-dominated grids, this requires shifting charging to midday hours – when vehicles are typically parked at workplaces. Yet workplace charging networks operate under institutional constraints such as shared infrastructure, bundled parking and charging services, and limited willingness to require drivers to move vehicles, making time-of-day pricing and active management difficult to implement. In a natural field experiment (n = 629 drivers) across a large workplace charging network, we randomize time-invariant price discounts and environmental nudges that emphasize the environmental benefits of daytime charging. Price discounts modestly increase workplace charging but shift charging toward off-solar periods when charger occupancy is lower, while environmental nudges re-time charging toward solar hours without increasing total demand. A follow-up experiment shows that these timing responses are driven by perceived charger scarcity and congestion under price discounts. Finally, we quantify the abatement costs per ton of of these shifts.

Enforcement is a challenge for effective international cooperation. In human rights and environmental law, along with many other domains of international cooperation, "naming and shaming" is often used as an enforcement mechanism in the absence of stronger alternatives. Naming and shaming hinges on the ability to identify countries whose efforts are inadequate and effectively shame them toward better behavior. Research on this approach has struggled to identify factors that explain when it influences state behavior in ways that lead to more cooperation. Via survey of a large (N = 910) novel sample of experienced diplomats involved in the design of the Paris Agreement, we find support for the proposition that naming and shaming is most accepted and effective in influencing the behavior of countries that have high-quality political institutions, strong internal concern about climate change, and ambitious and credible international climate commitments. Naming and shaming appears less effective in other countries, so further enforcement mechanisms will be needed for truly global cooperation. We also find that the climate diplomacy experts favor a process of naming and shaming that relies on official intergovernmental actors, in contrast with studies suggesting that NGOs, media, and other private actors are more effective at naming and shaming. We suggest that these tensions-the inability for naming and shaming to work effectively within the countries least motivated for climate action and the preference for namers and shamers that seem least likely to be effective-will become central policy debates around making cooperation on climate change more enforceable.

Abstract Analysts have long advocated a linkage between international cooperation on climate change and trade measures, such as border tariffs, as a means of enforcing agreements to achieve deeper cooperation. Nevertheless, it has remained difficult to evaluate whether policy makers will allow such linkages and whether linking climate and trade would, in reality, yield beneficial effects to international cooperation. Working with a large sample of climate experts who are highly experienced in climate diplomacy and policy, we elicited how they view the legitimacy and usefulness of linking trade and climate and what factors can explain those views. We find that experts from richer countries, especially Europe, are more likely to see linkage as legitimate and effective. These experts are particularly likely to favor universal border adjustments (UBAs) that apply to all countries to level the economic playing field, rather than trade measures that define an exclusive “club” of countries making extra efforts to cut emissions while punishing non-club members. This finding reveals tensions between a shift in academic thinking about the value of club-based strategies—including clubs that use border measures for enforcement—and what climate policy experts see as valuable. European experts are particularly likely to favor UBAs and they are also least likely to see risks in implementing trade measures. In general, countries with high quality national institutions see lower risks in using trade measures to enforce greater cooperation on climate change. A particularly robust finding is that experts who perceive their home country’s emissions reduction pledge as ambitious are more likely to see risks from using trade measures. While these are the countries that could benefit the most from using trade measures, they are also the countries that are offering the most under the existing Paris Agreement. Experts seem to be increasingly aware of the dissonance between the voluntarism of the Paris Agreement and growing political pressures to apply trade measures. We also find the attributes of experts, such as training and career experience, can affect their assessments. In some models, experts with economic or business backgrounds are more likely to favor trade measures while those with careers in natural science, diplomacy, and national government are less sanguine. Our results suggest that diverging views on the need for trade-based enforcement are robust, associated with important attributes of countries such as their commitments, and likely to persist—suggesting that policy strategies favoring the use of trade measures must pay close attention to the conditions that will determine where and how trade measures can be implemented. Experts from many countries that are the biggest supporters of the Paris approach to climate cooperation also doubt the legitimacy of trade measures.

This is the dataset and corresponding do-files to reproduce the main results from the Paper "Determining the willingness to link climate and trade policy" and from the Supplementary Information.

Abstract Even as most mainstream policy analysts support the idea of active industrial policy to create new green industries and cut carbon pollution, important dissenting voices still question whether government intervention is possible without extreme waste. We suggest that many of today’s debates, which echo debates of the 1970s, need updating to reflect the reality that a lot has been learned about where and how government can pursue effective industrial policy. The more transformative the goals, the harder it is to know which policies, technologies and business models will work, and the greater the need for ‘experimental’ approaches to policy that put uncertainty as the centerpiece. Creating industrial transformation in the context of deep uncertainty is the central challenge for industrial policy. Solving this problem requires not just attention to policy design and industrial response but also possible reforms to the institutions that design and implement policies. Today’s policy institutions, like today’s firms, are mostly organized for the current industrial system—not necessarily the future.

This is the dataset and corresponding do-files to reproduce the main results from the Paper "Naming and Shaming as a Strategy for Enforcing the Paris Agreement: The Role of Political Institutions and Public Concern" and from the Supplementary Information.

Abstract A central challenge for sustaining international cooperation to cut global greenhouse gas emissions is confidence that national policy efforts are leading to a meaningful impact on the climate. Here, we apply a detection protocol to determine when the measurable signal of atmospheric CO 2 can be distinguished from the noise of the carbon cycle and uncertainties in emission trends. We test that protocol with a database of 226 emission mitigation scenarios—the universe of scenarios vetted by the Intergovernmental Panel on Climate Change. These scenarios are descriptive of ‘baseline’ trajectories of emissions trends in the absence of new policies along with trajectories that reflect substantial policy efforts to stop warming at 1.5 °C–2 °C above pre-industrial levels, as embodied in the Paris Agreement. The most aggressive mitigation scenarios (i.e. 1.5 °C) require 11–16 years to detect a signal of demonstrable progress from the noise; 2 °C scenarios lengthen detection by at least a decade. As more climate policy analysts face the reality that goals of 1.5 °C–2 °C seem infeasible, they have developed ‘overshoot’ scenarios with emissions that rise above the agreed goal and then, later on, fall aggressively to achieve it. These pathways come at the political cost of a 1–2 decade delay in detection, even for the 1.5 °C scenarios. The Paris Agreement requires a global ‘stocktake’ that interrogates national mitigation efforts; our results suggest that this effort must grapple with the question of when the world can gain confidence that the diplomacy on climate is demonstrably making an impact.