Toward Bridging the Data Divide


Blog by Randeep Sudan, Craig Hammer, and Yaroslav Eferin: “Developing countries face a data conundrum. Despite more data being available than ever in the world, low- and middle-income countries often lack adequate access to valuable data and struggle to fully use the data they have.

This seemingly paradoxical situation represents a data divide. The terms “digital divide” and “data divide” are often used interchangeably but differ. The digital divide is the gap between those with access to digital technologies and those without access. On the other hand, the data divide is the gap between those who have access to high-quality data and those who do not. The data divide can negatively skew development across countries and therefore is a serious issue that needs to be addressed…

The effects of the data divide are alarming, with low- and middle-income countries getting left behind. McKinsey estimates that 75% of the value that could be created through Generative AI (such as ChatGPT) would be in four areas of economic activity: customer operations, marketing and sales, software engineering, and research and development. They further estimate that Generative AI  could add between $2.6 trillion and $4.4 trillion in value in these four areas.

PWC estimates that approximately 70% of all economic value generated by AI will likely accrue to just two countries: the USA and China. These two countries account for nearly two-thirds of the world’s hyperscale data centers, high rates of 5G adoption, the highest number of AI researchers, and the most funding for AI startups. This situation creates serious concerns for growing global disparities in accessing benefits from data collection and processing, and the related generation of insights and opportunities. These disparities will only increase over time without deliberate efforts to counteract this imbalance…(More)”

The Coming Wave


Book by Mustafa Suleyman and Michael Bhaskar: “Soon you will live surrounded by AIs. They will organise your life, operate your business, and run core government services. You will live in a world of DNA printers and quantum computers, engineered pathogens and autonomous weapons, robot assistants and abundant energy.

None of us are prepared.

As co-founder of the pioneering AI company DeepMind, part of Google, Mustafa Suleyman has been at the centre of this revolution. The coming decade, he argues, will be defined by this wave of powerful, fast-proliferating new technologies.

In The Coming Wave, Suleyman shows how these forces will create immense prosperity but also threaten the nation-state, the foundation of global order. As our fragile governments sleepwalk into disaster, we face an existential dilemma: unprecedented harms on one side and the threat of overbearing surveillance on the other…(More)”.

Regulation of Artificial Intelligence Around the World


Report by the Law Library of Congress: “…provides a list of jurisdictions in the world where legislation that specifically refers to artificial intelligence (AI) or systems utilizing AI have been adopted or proposed. Researchers of the Law Library surveyed all jurisdictions in their research portfolios to find such legislation, and those encountered have been compiled in the annexed list with citations and brief descriptions of the relevant legislation. Only adopted or proposed instruments that have legal effect are reported for national and subnational jurisdictions and the European Union (EU); guidance or policy documents that have no legal effect are not included for these jurisdictions. Major international organizations have also been surveyed and documents adopted or proposed by these organizations that specifically refer to AI are reported in the list…(More)”.

When should states be creative, innovative or entrepreneurial – and when should they not?


Blog by Geoff Mulgan: “…So what about governments being entrepreneurial as opposed to creative and innovative? Here things get even trickier. The classic commentary on the subject was written by the great Jane Jacobs (in her book ‘Systems of Survival’). She pointed out the differences between what she called the ‘guardian syndrome’ and the ‘trader syndrome’. The first is common in governments, the second in business. She argued that all societies have to find a balance between these very different views of the world. The first is concerned with looking after things and protection, originally of land, and can be found in governments, ecological movements as well as aristocracies. The second is concerned with exchange and profit, and is the world of commerce and trade.

These each see the world in very different ways. But in practice they complement each other – indeed their complementarity is what helps societies to function.

In her view, however, fusions of the two tended to be malign pathologies, for example when businesses became like governments, running large areas of territory, or when governments start thinking like traders. Donald Trump was a classic example – who saw the government machine rather as an entrepreneur would see his own business. Silvio Berlusconi was another – a remarkable proportion of his initiatives were essentially designed to promote his businesses, or protect him from prosecution.

Jane Jacobs’ points become very obvious in some industries, like the contemporary digital industries that have become de facto utilities on which we depend every day. It remains far from clear that companies like Meta or Google appreciate that they risk becoming pathological fusions of business and government, without the mindsets appropriate to their new-found power.

The pathologies are also very visible in many parts of the world where the state runs a lot of industry, often with the military playing a leading role. Examples include Pakistan, Myanmar, China and Russia. In these cases public servants really have become entrepreneurs. In some cases – like Huawei – great businesses have been grown. But most of the time such fusions of government and entrepreneurialism tend towards corruption, and predatory extraction of value, because when the state’s monopoly of coercion connects to the power to make money abuses are inevitable.

There may be occasional examples where states should be entrepreneurial at least in mindset – spinning off a function or using some of the ethos of a start-up, for example to create a new digital service. But in such cases very tight rules are vital to avoid abuse, so that if, for example, a part of the state is spun out it doesn’t do so with advantages or easy money or legally guaranteed monopolies or inflated salaries. Much depends on whether you use the word entrepreneurial in a precise sense (the first definition that comes up on Google is: ‘characterized by the taking of financial risks in the hope of profit’) or as a much looser synonym for being innovative or problem-solving…(More)”.

Data Is Everybody’s Business


Book by Barbara H. Wixom, Cynthia M. Beath and Leslie Owens: “Most organizations view data monetization—converting data into money—too narrowly: as merely selling data sets. But data monetization is a core business activity for both commercial and noncommercial organizations, and, within organizations, it’s critical to have wide-ranging support for this pursuit. In Data Is Everybody’s Business, the authors offer a clear and engaging way for people across the entire organization to understand data monetization and make it happen. The authors identify three viable ways to convert data into money—improving work with data, wrapping products with data, and selling information offerings—and explain when to pursue each and how to succeed…(More)”.

On Disinformation: How to Fight for Truth and Protect Democracy


Book by Lee McIntyre: “The effort to destroy facts and make America ungovernable didn’t come out of nowhere. It is the culmination of seventy years of strategic denialism. In On Disinformation, Lee McIntyre shows how the war on facts began, and how ordinary citizens can fight back against the scourge of disinformation that is now threatening the very fabric of our society. Drawing on his twenty years of experience as a scholar of science denial, McIntyre explains how autocrats wield disinformation to manipulate a populace and deny obvious realities, why the best way to combat disinformation is to disrupt its spread, and most importantly, how we can win the war on truth.

McIntyre takes readers through the history of strategic denialism to show how we arrived at this precarious political moment and identifies the creators, amplifiers, and believers of disinformation. Along the way, he also demonstrates how today’s “reality denial” follows the same flawed blueprint of the “five steps of science denial” used by climate deniers and anti-vaxxers; shows how Trump has emulated disinformation tactics created by Russian and Soviet intelligence dating back to the 1920s; provides interviews with leading experts on information warfare, counterterrorism, and political extremism; and spells out the need for algorithmic transparency from Facebook, Twitter, and YouTube. On Disinformation lays out ten everyday practical steps that we can take as ordinary citizens—from resisting polarization to pressuring our Congresspeople to regulate social media—as well as the important steps our government (if we elect the right leaders) must take.

Compact, easy-to-read (and then pass on to a friend), and never more urgent, On Disinformation does nothing less than empower us with the tools and knowledge needed to save our republic from autocracy before it is too late…(More)”.

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)”.