Integrating AI into Urban Planning Workflows: Democracy Over Authoritarianism


Essay by Tyler Hinkle: “As AI tools become integrated into urban planning, a dual narrative of promise and potential pitfalls emerges. These tools offer unprecedented efficiency, creativity, and data analysis, yet if not guided by ethical considerations, they could inadvertently lead to exclusion, manipulation, and surveillance.

While AI, exemplified by tools like NovelAI, holds the potential to aggregate and synthesize public input, there’s a risk of suppressing genuine human voices in favor of algorithmic consensus. This could create a future urban landscape devoid of cultural depth and diversity, echoing historical authoritarianism.

In a potential dystopian scenario, an AI-based planning software gains access to all smart city devices, amassing data to reshape communities without consulting their residents. This data-driven transformation, devoid of human input, risks eroding the essence of community identity, autonomy, and shared decision-making. Imagine AI altering traffic flow, adjusting public transportation routes, or even redesigning public spaces based solely on data patterns, disregarding the unique needs and desires of the people who call that community home.

However, an optimistic approach guided by ethical principles can pave the way for a brighter future. Integrating AI with democratic ideals, akin to Fishkin’s deliberative democracy, can amplify citizens’ voices rather than replacing them. AI-driven deliberation can become a powerful vehicle for community engagement, transforming Arnstein’s ladder of citizen participation into a true instrument of empowerment. In addition, echoing the calls for alignment to be addresses holistically for AI, there will be alignment issues with AI as it becomes integrated into urban planning. We must take the time to ensure AI is properly aligned so it is a tool to help communities and not hurt them.

By treading carefully and embedding ethical considerations at the core, we can unleash AI’s potential to construct communities that are efficient, diverse, and resilient, while ensuring that democratic values remain paramount…(More)”.

Protests


Paper by Davide Cantoni, Andrew Kao, David Y. Yang & Noam Yuchtman: “Citizens have long taken to the streets to demand change, expressing political views that may otherwise be suppressed. Protests have produced change at local, national, and international scales, including spectacular moments of political and social transformation. We document five new empirical patterns describing 1.2 million protest events across 218 countries between 1980 and 2020. First, autocracies and weak democracies experienced a trend break in protests during the Arab Spring. Second, protest movements also rose in importance following the Arab Spring. Third, protest movements geographically diffuse over time, spiking to their peak, before falling off. Fourth, a country’s year-to-year economic performance is not strongly correlated with protests; individual values are predictive of protest participation. Fifth, the US, China, and Russia are the most over-represented countries by their share of academic studies. We discuss each pattern’s connections to the existing literature and anticipate paths for future work.Citizens have long taken to the streets to demand change, expressing political views that may otherwise be suppressed. Protests have produced change at local, national, and international scales, including spectacular moments of political and social transformation. We document five new empirical patterns describing 1.2 million protest events across 218 countries between 1980 and 2020. First, autocracies and weak democracies experienced a trend break in protests during the Arab Spring. Second, protest movements also rose in importance following the Arab Spring. Third, protest movements geographically diffuse over time, spiking to their peak, before falling off. Fourth, a country’s year-to-year economic performance is not strongly correlated with protests; individual values are predictive of protest participation. Fifth, the US, China, and Russia are the most over-represented countries by their share of academic studies. We discuss each pattern’s connections to the existing literature and anticipate paths for future work.Citizens have long taken to the streets to demand change, expressing political views that may otherwise be suppressed. Protests have produced change at local, national, and international scales, including spectacular moments of political and social transformation. We document five new empirical patterns describing 1.2 million protest events across 218 countries between 1980 and 2020. First, autocracies and weak democracies experienced a trend break in protests during the Arab Spring. Second, protest movements also rose in importance following the Arab Spring. Third, protest movements geographically diffuse over time, spiking to their peak, before falling off. Fourth, a country’s year-to-year economic performance is not strongly correlated with protests; individual values are predictive of protest participation. Fifth, the US, China, and Russia are the most over-represented countries by their share of academic studies. We discuss each pattern’s connections to the existing literature and anticipate paths for future work…(More)”.

Designing Research For Impact


Blog by Duncan Green: “The vast majority of proposals seem to conflate impact with research dissemination (a heroic leap of faith – changing the world one seminar at a time), or to outsource impact to partners such as NGOs and thinktanks.

Of the two, the latter looks more promising, but then the funder should ask to see both evidence of genuine buy-in from the partners, and appropriate budget for the work. Bringing in a couple of NGOs as ‘bid candy’ with little money attached is unlikely to produce much impact.

There is plenty written on how to genuinely design research for impact, e.g. this chapter from a number of Oxfam colleagues on its experience, or How to Engage Policy Makers with your Research (an excellent book I reviewed recently and on the LSE Review of Books). In brief, proposals should:

  • Identify the kind(s) of impacts being sought: policy change, attitudinal shifts (public or among decision makers), implementation of existing laws and policies etc.
  • Provide a stakeholder mapping of the positions of key players around those impacts – supporters, waverers and opponents.
  • Explain how the research plans to target some/all of these different individuals/groups, including during the research process itself (not just ‘who do we send the papers to once they’re published?’).
  • Which messengers/intermediaries will be recruited to convey the research to the relevant targets (researchers themselves are not always the best-placed to persuade them)
  • Potential ‘critical junctures’ such as crises or changes of political leadership that could open windows of opportunity for uptake, and how the research team is set up to spot and respond to them.
  • Anticipated attacks/backlash against research on sensitive issues and how the researchers plan to respond
  • Plans for review and adaptation of the influencing strategy

I am not arguing for proposals to indicate specific impact outcomes – most systems are way too complex for that. But, an intentional plan based on asking questions on the points above would probably help researchers improve their chances of impact.

Based on the conversations I’ve been having, I also have some thoughts on what is blocking progress.

Impact is still too often seen as an annoying hoop to jump through at the funding stage (and then largely forgotten, at least until reporting at the end of the project). The incentives are largely personal/moral (‘I want to make a difference’), whereas the weight of professional incentives are around accumulating academic publications and earning the approval of peers (hence the focus on seminars).

incentives are largely personal/moral (‘I want to make a difference’), whereas the weight of professional incentives are around accumulating academic publications

The timeline of advocacy, with its focus on ‘dancing with the system’, jumping on unexpected windows of opportunity etc, does not mesh with the relentless but slow pressure to write and publish. An academic is likely to pay a price if they drop their current research plans to rehash prior work to take advantage of a brief policy ‘window of opportunity’.

There is still some residual snobbery, at least in some disciplines. You still hear terms like ‘media don’, which is not meant as a compliment. For instance, my friend Ha-Joon Chang is now an economics professor at SOAS, but what on earth was Cambridge University thinking not making a global public intellectual and brilliant mind into a prof, while he was there?

True, there is also some more justified concern that designing research for impact can damage the research’s objectivity/credibility – hence the desire to pull in NGOs and thinktanks as intermediaries. But, this conversation still feels messy and unresolved, at least in the UK…(More)”.

Advancing Environmental Justice with AI


Article by Justina Nixon-Saintil: “Given its capacity to innovate climate solutions, the technology sector could provide the tools we need to understand, mitigate, and even reverse the damaging effects of global warming. In fact, addressing longstanding environmental injustices requires these companies to put the newest and most effective technologies into the hands of those on the front lines of the climate crisis.

Tools that harness the power of artificial intelligence, in particular, could offer unprecedented access to accurate information and prediction, enabling communities to learn from and adapt to climate challenges in real time. The IBM Sustainability Accelerator, which we launched in 2022, is at the forefront of this effort, supporting the development and scaling of projects such as the Deltares Aquality App, an AI-powered tool that helps farmers assess and improve water quality. As a result, farmers can grow crops more sustainably, prevent runoff pollution, and protect biodiversity.

Consider also the challenges that smallholder farmers face, such as rising costs, the difficulty of competing with larger producers that have better tools and technology, and, of course, the devastating effects of climate change on biodiversity and weather patterns. Accurate information, especially about soil conditions and water availability, can help them address these issues, but has historically been hard to obtain…(More)”.

Unlocking the value of supply chain data across industries


MIT Technology Review Insights: “The product shortages and supply-chain delays of the global covid-19 pandemic are still fresh memories. Consumers and industry are concerned that the next geopolitical climate event may have a similar impact. Against a backdrop of evolving regulations, these conditions mean manufacturers want to be prepared against short supplies, concerned customers, and weakened margins.

For supply chain professionals, achieving a “phygital” information flow—the blending of physical and digital data—is key to unlocking resilience and efficiency. As physical objects travel through supply chains, they generate a rich flow of data about the item and its journey—from its raw materials, its manufacturing conditions, even its expiration date—bringing new visibility and pinpointing bottlenecks.

This phygital information flow offers significant advantages, enhancing the ability to create rich customer experiences to satisfying environmental, social, and corporate governance (ESG) goals. In a 2022 EY global survey of executives, 70% of respondents agreed that a sustainable supply chain will increase their company’s revenue.

For disparate parties to exchange product information effectively, they require a common framework and universally understood language. Among supply chain players, data standards create a shared foundation. Standards help uniquely identify, accurately capture, and automatically share critical information about products, locations, and assets across trading communities…(More)”.

Digital Empires: The Global Battle to Regulate Technology


Book by Anu Bradford: “The global battle among the three dominant digital powers—the United States, China, and the European Union—is intensifying. All three regimes are racing to regulate tech companies, with each advancing a competing vision for the digital economy while attempting to expand its sphere of influence in the digital world. In Digital Empires, her provocative follow-up to The Brussels Effect, Anu Bradford explores a rivalry that will shape the world in the decades to come.

Across the globe, people dependent on digital technologies have become increasingly alarmed that their rapid adoption and transformation have ushered in an exceedingly concentrated economy where a few powerful companies control vast economic wealth and political power, undermine data privacy, and widen the gap between economic winners and losers. In response, world leaders are variously embracing the idea of reining in the most dominant tech companies. Bradford examines three competing regulatory approaches—the American market-driven model, the Chinese state-driven model, and the European rights-driven regulatory model—and discusses how governments and tech companies navigate the inevitable conflicts that arise when these regulatory approaches collide in the international domain. Which digital empire will prevail in the contest for global influence remains an open question, yet their contrasting strategies are increasingly clear.

Digital societies are at an inflection point. In the midst of these unfolding regulatory battles, governments, tech companies, and digital citizens are making important choices that will shape the future ethos of the digital society. Digital Empires lays bare the choices we face as societies and individuals, explains the forces that shape those choices, and illuminates the immense stakes involved for everyone who uses digital technologies….(More)”

How Will the State Think With the Assistance of ChatGPT? The Case of Customs as an Example of Generative Artificial Intelligence in Public Administrations


Paper by Thomas Cantens: “…discusses the implications of Generative Artificial Intelligence (GAI) in public administrations and the specific questions it raises compared to specialized and « numerical » AI, based on the example of Customs and the experience of the World Customs Organization in the field of AI and data strategy implementation in Member countries.

At the organizational level, the advantages of GAI include cost reduction through internalization of tasks, uniformity and correctness of administrative language, access to broad knowledge, and potential paradigm shifts in fraud detection. At this level, the paper highlights three facts that distinguish GAI from specialized AI : i) GAI is less associated to decision-making process than specialized AI in public administrations so far, ii) the risks usually associated with GAI are often similar to those previously associated with specialized AI, but, while certain risks remain pertinent, others lose significance due to the constraints imposed by the inherent limitations of GAI technology itself when implemented in public administrations, iii) training data corpus for GAI becomes a strategic asset for public administrations, maybe more than the algorithms themselves, which was not the case for specialized AI.

At the individual level, the paper emphasizes the “language-centric” nature of GAI in contrast to “number-centric” AI systems implemented within public administrations up until now. It discusses the risks of replacement or enslavement of civil servants to the machines by exploring the transformative impact of GAI on the intellectual production of the State. The paper pleads for the development of critical vigilance and critical thinking as specific skills for civil servants who are highly specialized and will have to think with the assistance of a machine that is eclectic by nature…(More)”.

Rethinking the Role of Nudge in Public Policy


Paper by Sema Müge Özdemiray: “The view of achieving the desired results in public policies depends on steering individuals, with decisions and actions incompatible with rationality, in a predictable way has pushed policymakers to collaborate with psychology methods and theories. Accordingly, in the recent policy design of public authorities, there is an increasing interest in the nudge approach, which is considered a less costly, more liberal, more citizen-focused alternative to traditional policy instruments. Nudging, which has produced effective solutions for different social problems, has also brought with it many criticisms. These criticisms have led to questioning alternative and advanced new policy tools in the field of behavioral public policy. In this study, the “nudge-plus” approach is discussed as one of these policy tools, which was put forward by Peter John and Gerry Stoker and which argues that the criticisms directed to nudge can be overcome by incorporating a citizen-oriented perspective into the nudge approach. This study aims to draw attention to the prediction that the use of the nudge-plus method in public policy design can produce more effective results in line with today’s participatory and collaborative administration approach…(More)”.

Informing the Global Data Future: Benchmarking Data Governance Frameworks


Paper by Sara Marcucci, Natalia González Alarcón, Stefaan G. Verhulst and Elena Wüllhorst: “Data has become a critical trans-national and cross-border resource. Yet, the lack of a well-defined approach to using it poses challenges to harnessing its value. This article explores the increasing importance of global data governance due to the rapid growth of data, and the need for responsible data practices. The purpose of this paper is to compare approaches and identify patterns in the emergent data governance ecosystem within sectors close to the international development field, ultimately presenting key takeaways and reflections on when and why a global data governance framework may be needed. Overall, the paper provides information about the conditions when a more holistic, coordinated transnational approach to data governance may be needed to responsibly manage the global flow of data. The report does this by (a) considering conditions specified by the literature that may be conducive to global data governance, and (b) analyzing and comparing existing frameworks, specifically investigating six key elements: purpose, principles, anchoring documents, data description and lifecycle, processes, and practices. The article closes with a series of final recommendations, which include adopting a broader concept of data stewardship to reconcile data protection and promotion, focusing on responsible reuse of data to unlock socioeconomic value, harmonizing meanings to operationalize principles, incorporating global human rights frameworks to provide common North Stars, unifying key definitions of data, adopting a data lifecycle approach, incorporating participatory processes and collective agency, investing in new professions with specific roles, improving accountability through oversight and compliance mechanisms, and translating recommendations into practical tools…(More)”

The Crowdless Future? How Generative AI Is Shaping the Future of Human Crowdsourcing


Paper by Leonard Boussioux, Jacqueline Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim Lakhani: “This study investigates the capability of generative artificial intelligence (AI) in creating innovative business solutions compared to human crowdsourcing methods. We initiated a crowdsourcing challenge focused on sustainable, circular economy business opportunities. The challenge attracted a diverse range of solvers from a myriad of countries and industries. Simultaneously, we employed GPT-4 to generate AI solutions using three different prompt levels, each calibrated to simulate distinct human crowd and expert personas. 145 evaluators assessed a randomized selection of 10 out of 234 human and AI solutions, a total of 1,885 evaluator-solution pairs. Results showed comparable quality between human and AI-generated solutions. However, human ideas were perceived as more novel, whereas AI solutions delivered better environmental and financial value. We use natural language processing techniques on the rich solution text to show that although human solvers and GPT-4 cover a similar range of industries of application, human solutions exhibit greater semantic diversity. The connection between semantic diversity and novelty is stronger in human solutions, suggesting differences in how novelty is created by humans and AI or detected by human evaluators. This study illuminates the potential and limitations of both human and AI crowdsourcing to solve complex organizational problems and sets the groundwork for a possible integrative human-AI approach to problem-solving…(More)”.