> Using AI doesn’t make you evil, nor does it risk your sanity – no more than doing any of the other dangerous, compromised, unsustainable things that constitute our daily lives in this fraught moment.

Because of the unacceptable environmental and climate impact of data centers (and other stuff), I feel bad using AI and try to do so with sobriety. Am I doing enough? Am I just self-serving? Am I doing too much, even, as “AI is inevitable, and individual choice do not matter much”?

Whatever I am doing, my choices are guided by principles and heuristics that I used before. I also felt bad using cryptocurrencies. After some years of consideration and experimentation, Icame to regard them as pure speculation with zero production in the best case scenario, and an unmitigated social bad – via a business model for ransomware and a financial vehicle for criminal networks – in something closer to a real scenario. I checked it out in the early 2010s, then decided I wanted no part in it, sold whatever little I had, and never looked back. These technologies looked to me like [sociopathic innovation](https://www.cottica.net/?p=13937). A bit like asbesto: technologically interesting stuff, but you don’t want to be around it.

And now that I reflect back about it, I also feel bad using _airplanes_ (3.5% of climate change, according to [some studies](https://research.noaa.gov/aviation-is-responsible-for-35-percent-of-climate-change-study-finds/)) and try not to do it at all. When COVID arrived, my partners at [Edgeryders](https://edgeryders.org) and I were rethinking our rather nomadic working style. We embraced remote collaboration as a driver of personal freedom (my partners even wrote a book about this, *[The Anywhere Organization](https://www.goodreads.com/book/show/57601026-the-anywhere-organization)*. We rewrote our travel policy to embrace slow travel and to spend at least three nights at destination, using physical travel to build freindship and empathy while prefering digital channels to talk shop and make well-defined decisions. I have become quite good at international rail and bus travel, as well as slow tourims on foot or bicycles. There, too, I make compromises: when I accepted a United Nations job (worse, a global role, though I was outposted to Europe) in 2022 I was prepared to fight a fight to minimize my flying, but I had to accept that there would be some.

Even before that, I felt bad about _cars_. In the early 2000s I lived in Milan, and it was super clear that car civilization ws a net societal bad. I ditched my last car in 2004 and never looked back (for many years I kept a motorbike though, and ditched that too in 2017). I still drive once or twice a year, renting a vehicle as I need it. Compromises again, but no doubt my carbon and material footprint has gone down.

Where I am going with this is that, like Cory says, “AI is just another technology”. It has uses, just like cars are often a good solution for people living in rural areas; ([I have my own uses for it](https://www.cottica.net/2026/06/02/the-open-data-centaurs-interacting-with-data-via-llm-assisted-structured-queries/)). It has societal consequences, most of them bad, starting from its outsized damage to the environment and our efforts for climate change mitigation. It is peddled by a cynical industry, hyperconcentrated, monopolistic, and perched upon a harmful financial bubble. Bubble aside, the same is true, in different degrees, of the other industries we discuss here.

We cannot shop (or, rather *refuse* to shop) our way out of such tech. It is systemic. **But we can experiment ways to use them less, more deliberately, and try to live according to our values as best we can**. I do it, because it feels right. I am under no illusion that I am changing things in any meaningful way. For meaningful change, as always, we need to organize collective action to bring these systems under control, mitigating their damage and maximizing their benefits. In extreme cases there are no benefits (crypto, I am looking at you), and then we should organize to wipe these systems out altogether. With some hard work and luck, **our experiments and experiences can inspire others to join such collective action, and provide food for thoughts.** Whether we are talking about AI, commercial aviation, cars, PFOS, fast fashion, or whatever, this is not nothing, and it has to be enough, for now.

_Photo Credit: Giampaolo Macorig on flickr.com_

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At the end of the day, the fact is that mass public opinion isn’t what causes politics to happen. Politics is not a public opinion poll; it’s the mobilization of organized interests through a party system. So you shouldn’t expect things that most people believe to automatically become law. 

If you have been paying attention to the current debate about inequalities, you will be familiar with the argument that these regressive tax cuts of the Reagan-Thatcher era kicked off a self-reinforcing loop of growing inequality. Taxed less, rich people became faster at accumulating wealth, which they used to buy political power and influence, which they used to avoid taxes even more through introducing loopholes and straight-up reducing tax rates. Also, this where CEO pays started to skyrocket: nobody had much to gain by increasing CEO pay when the state got to keep 90% of the increase. With the tax cuts, executives were much more incentivized to use their bargaining power to extract more money from the companies, and again this contributed to rising inequalities.

But here is what I, at least, had not perceived: this is also when budget deficit becomes important in the US, for the first time since World War 2. And why is that? Because, according to Williamson, these tax cuts were kept “off the books”. They were not immediately financed by slashing social security programmes, or increasing taxes for the working people: rather they were funded by issuing federal debt.

This move had far-reaching consequences. First, it defanged the opposition to the tax cuts. Working class Americans did not immediately feel the pain of this regressive distribution, and basically no one without training in economics could see that pain coming. Williamson:

If you look at the George W. Bush era, this was a very conscious strategy. In principle, you could have taken the surpluses of that era and used them to shore up Social Security or do any of a number of other things. If you look at memos within the Bush administration, it was very clearly stated that in going to the voters to cut taxes in this very regressive way, they had to say there were no tradeoffs at all. Fiscally, barring the costs of debt and interest, there were no immediate consequences.

And later, of course, it left us with the permanent threat of unsustainable public debt to justify austerity even by politicians that do not present as conservative. “Mistakes were made by previous governments. Now we have no choice but sacrifice your welfare system to the financial markets, lest our country becomes insolvent and has to default on its debt, with dire consequences for us all”. Again, this narrative is hard to attack without invoking advanced economic concepts, like Modern Monetary Theory.

So that’s how an important part of the economic landscape that we live in, the “tax cuts for rich people, austerity for the working class” combo was first shaped. But Williamson’s main point here is that taxation is the price of democracy (also the title of her latest book):

And that’s because democracy isn’t just being able to vote; it’s people having the power to actually make change to their government. And if the government doesn’t have enough money to act, then, even if you can vote, it’s inconsequential.

The book shows that, since John Lackland’s Magna Charta in 1215, taxation and representation go together, and the former leads the latter. When democracy grows, taxes go up, “because, of course, the taxpayers can now have a say in what the government is doing”; the freest countries today have high taxation levels, whereas taxes are low in authoritarian states.

The corollary of this story is this: conservatives since circa 1980 have been taking loans that they had no intention to repay, using our democracies as a collateral that can be repossessed, like in a mortgage. In the short term, their tax cuts created a benefit for themselves which proved to be cumulative. And, by being kept “off the books” , they reduced the power of government to be effective and created a group of wealthy people who – because they pay next to no taxes – are free riding on the public goods financed by the rest of us, just like the wealthy owners of holiday homes threatened by the 2026 wildfires in the French peninsula of Cap Ferret benefited from the firefighting services paid for by everyone else. Democracies kept going, so far. But this debt is long-term unsustainable. With it, the wealthy class is actively eroding social cohesion and democracy itself. I can only hope it can, at some point, be held accountable. Not only in moral terms, but also in financial ones, by paying its share of taxes.

Photo credit: Mael Dubie/EPA/Shutterstock under fair use

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Bennett has become one of my favourite speculative fiction authors in later years – since, that is, I laid eyes on his Divine Cities novels. He writes well, his characters are outstanding, his worldbuilding intriguing and genre-defining. What he did not do in Divine Cities, nor in the first two Ana and Din novels, was look into matters of production, distribution and consumption (based on the reviews, it looks like he did that more in another trilogy, called Founders, but I have not yet read that). So, I was delighted to see him foreground it in A Trade of Blood, with at least one character explicitly trying to dismantle the economic engine of the Third Ring of the Empire!

The post is short because Bennett does not try to imagine an “alien economy” different from our own. He uses speculative fiction as a mirror to reflect and criticize the economic system we are already living in, late-stage capitalism. This is an operation similar to those of most (but not all) cyberpunk authors, including their doyen William Gibson. The difference is that A Trade of Blood focuses on a specific production sector: cattle farming.

Just like our world, the Khanum empire consumes a lot of meat, produced in the breadbasket lands of the Third Ring. This trade brings much prosperity to some, but again much like or world, it also entails great suffering of the animals, and massive inefficiencies, as vast expanses of prime farming land is given to growing plants usable as fodder. Additionally, meat production is downright dangerous: production is underpinned by the use of risky, unstable biotechnologies. Everybody sees the problems, but change is difficult; the families who enriched themselves in the flesh trade are powerful, and eating meat is a signifier of abundance and hospitality. Even the opposition of the Orbiis, the branch of the imperial military dedicated to environmental stewardship, was shrugged off.

A critical position on our own economy through speculative fiction is not yet economic science fiction in my view, My favourite economic speculative fiction novels speculate: they build economies that function differently from our own. But Bennett’s critique is a start, one by an incredibly gifted author. So I will take it and applaud him, and hope that the next Ana and Din will bring us to some corner of the empire where people engage in commons-based peer production, or have built up monastic economies, or some such.

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I am intrigued by post-growth economics, and its epic struggle to replace neoclassical economics as the main lens through which to view economic structures and activity. Post-growth scholars believe that exponential growth in perpetuity is neither possible nor desirable per se. The impossibility of infinite growth on a finite planet is seen as self-evident: there is a famous quip, attributed to Kenneth Boulding, that “anyone who believes exponential growth can go on forever in a finite world is either a madman or an economist”. As for the desirability of growth, scholars point out that self-reported happiness across different countries is only weakly correlated with per capita gross domestic product, a phenomenon known as Easterlin’s paradox.

In recent years, post-growth scholarship has made impressive progress. Big ideas, better theories, better models, better data, robust policy innovation… A new generation of academic superstars has emerged: Thomas Piketty, Jason Hickel, Julia Steinberger, Timothée Parrique, Kate Raworth, Stephanie Kelton, Mariana Mazzucato, Tim Jackson, Randall Wray. These are scholars that command global attention and serious research funding, and are training and inspiring a host of young researchers. They are also rediscovering the real-life “alien economies” that are all around us; neoclassical economists view them through the lens of backwardness and dismiss them, whereas new economic thinkers treat them as alternative models in their own right and learn from them.

And it’s not just progress in research. There are more and more signs that ordinary people all over the world support post-growth policies. Jason Hickel has collected results from studies, surveys and polls on public acceptance for post-growth policies and post-capitalism itself, and the numbers are impressive. A few examples: one poll finds that 56% of respondents worldwide agrees that “capitalism does more harm than good” – and that percentage is 69% in France, and 74% in India. Another one that over three quarters of respondents support the idea of a public job guarantee (72% in the UK, 78% in the USA, 79% in France). A third reports that 93% of participants in citizen assemblies in Europe supports sufficiency policies. In Belgium, where I live, a poll published in June 2026 finds that, in a representative sample, over three quarters of respondents support a tax on great wealth. This is true in all regions of the country, and across the political spectrum. For now, people underestimate the appetite of their fellow citizens for this kind of reform: a recent very large-scale (130,000 respondents) global poll finds that 89% of the population demands more robust climate action, but they also believe that others are unwilling to act to get it, though they themselves are. This, however, is nothing that political organizing cannot solve. The fact that these policies, though obviously popular, are not happening suggests regulatory capture by the wealthy, the only group which stands to lose from a move to post-growth economies.

Because these and other results are so aligned with one another, I became intrigued with a recent paper by Savin and collaborators that seeks to disentangle the support for post-growth policies to that for environmental policies. Their idea, if I understand it correctly, is the following: people assume that economic growth is bad for the climate and the environment. So, they might support post-growth policies not as such, but because of the perceived advantages for the climate and the environment. The questionnaire was not published, but I imagine they constructed it around the desirability of economic growth independent of its effects on climate and the environment (and maybe other economic and social variables, such as income- and wealth inequalities).

To address this, here we move beyond binary choices and instead examine how EU citizens perceive the importance of economic growth for achieving the wider social and environmental objectives of a sustainable society. By focusing on the desirability of growth rather than its trade-offs, we clarify whether citizens view economic growth as a necessary condition to achieve social and environmental goals.

Results: out of 19,000 respondents in 13 countries of the European Union, approximately 60% of them hold pro-growth views.

Fair enough, but what does this result actually tell us? As far as I can see there is a powerful empirical argument that economic growth does come with environmental- and climate tradeoffs. There is no need to assume them, because they have been verified: green growth is not happening at any significant scale. Tim Parrique has a very clear explainer here:

And those are not the only tradeoffs. There is another important one: that beyond growth and inequelity. Ole Peters has shown that systems that grow on average while practically all its participants are reduced into poverty are perfectly possible : indeed, such systems arise naturally when the income of individuals grows randomly and multiplicatively over time, like most financial markets most of the time. They generate not only inequality, but extreme inequality.

So, there is not much point in asking people if they like economic growth, assuming that it has no bad consequences. At best, it’s a meaningless question: of course I am in favour of anything that has no bad consequences, on the off chance that it might have some good ones. At worst, it is misleading respondents, implying that economic growth could come with no bad consequences for climate, the environments, and global equality – when empirical scholarship largely says the opposite.

Did the authors do that? Hopefully this is just me misunderstanding the paper. I have written to the authors asking to read their questionnaire.

Image credit: Washington Post, fair use

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My brothers- and sisters-in-arm of Ondata have been exploring ways to use LLMs to facilitate their interactions with online sources of open and statistical data. In so doing, they have hit on a working style that I find very promising.

The obligatory disclaimer: I do not endorse “artificial intelligence”, a highly controversial socio-technological construct. As an economist, I am irked by the economic aspects of the tech: the insane concentration indices in this industry, the information asymmetries, the gigantic losses associated with the expansion of its customer base, its “dogshit unit economics”, to quote Ed Zitron, its massive environmental and social costs, its dark politics that makes it gravitate towards disinformation and deepfakes. I could go on, but you get the idea. This is probably preaching to the choir anyway, given that most people I hang out with are very skeptical of anything that smacks of “AI”.

And yet, Andrea Borruso and Matteo Fortini (among, undoubtedly, many others) have proposed an approach that I quite like. It goes like this: if you ask a data-related question to a LLM, such as “is the unemployment rate in Guatemala growing faster or slower than that in Ethiopia?”, you get better than even odds that the LLM will just make something up. A more reliable approach is to download the pertinent data from an authoritative source, and see for yourself. Andrea and Matteo, as honoured elders in the Italian open data community, are no strangers to tracking down data warehouses, poring over API documentation, building structured queries and feeding the result of those queries to scripts that will tease answers out of the data. And their substantial experience tells them, inequivocally, that having to do this work every time you want a question asked sucks big time.

But they found an alternative: codifying their deep knowledge of structured data and structured metadata in ways that are legible to an LLM. Then, instead of asking the LLM the direct question, they can instruct it to look up the data at the source – say, the World Bank’s data warehouse. This is possible because, after 20 years of open data movement, authoritative data to address many of those questions exist, and are structured. For example, there exists an ISO standard for machine-to-machine exchange on statistical data, called SDMX and followed by many statistics agencies. So, Andrea built OpenSDMX, a command-line interface that interacts with SDMX-compliant data sources. Give it a search term (unemployment rate Guatemala), and it will search the catalog, find the relevant datasets based on the metadata, and return a menu of options of what to download. For example, do you only want to know the most recent estimate of the unemployment rate, or would you like a time series? If sub-national data are available, do you want them too? Perhaps a disaggregation by sex, or age group? And so on.

OpenSDMX works well on its own, but it was set up so that you can interact with it via any LLM. This is done via something called a skill, which is a human-readable file containing the instructions necessary to use the command line interface well. To a human it reads like good documentation: to a LLM it is a long, detailed, well structured prompt. Thanks to it, LLMs can turn the instructions of their human operator into a structured flow of interactions with SDMX-compliant data sources by means of well-formed SDMX queries – there is no need to guess, because the skill contains correct, unambiguous structures written and validated by someone like Andrea and Matteo, who knows the standard well. Further specifications of the skill (more text files) address the quirks not disciplined by the SDMX standard itself. For example, while EUROSTAT (the European Union’s statistics agency) and ISTAT (Italy’s) both comply with SDMX, the former labels its variables in lowercase, and the latter in uppercase. This is the type of quirk known for causing lots of mild irritation to data scientists: having it encoded in the skill means your LLM benefits from the experience of veteran data scientists, even if you do not bother to read the skill.

The approach works not only for statistical data, but for any kind of data and metadata as long as they are exposed according to a standard. Another conceptually similar project built by Andrea is a Model Control Protocol (MCP) server to interact with open data portals and their content. This is possible, again, because the information therein is structured according to well-documented standards. Most open data portals are built on CKAN, and the datasets hosted therein follow another standard, DCAT. The logic is the same: open data portals are somewhat standard, and over the years the community has produced lore about how to whisper to them so that they will return the data we want. Encode that lore into text files that an LLM can interpret as a prompt. Then use the LLM as a natural-language interface to the data.

In social and economic research, it happens quite often that you have a hunch that can, in principle, be validated, or disproven, by looking at data. Andrea’s and Matteo’s approach greatly reduces the distance between formulating a question and getting an initial answer. It is even more useful when you have not a question, but a hunch, and you want to get an initial look at the raw data to see if you are even remotely right.

I decided to test OpenDMX as a way to validate or invalidate a conjecture. My conjecture was:

Within the European Union, Eastern European member states are undergoing more economic upheaval than average.

I wanted to test this conjecture by comparing the rates of business creation and business destruction (as captured by the creation of new companies and the cessation of existing ones). Furthermore, I want to do it by looking at sub-national-level data, if they exist. The idea is that upheaval is in the extremes, not in the averages: I am looking at the location of regions where business creation and destruction are unusually fast. To be clear, this is a completely unfounded conjecture, but it is a conjecture of the kind that economists make all the time, so it is valid as a test.

I launched an LLM and called up the skill, then wrote a prompt:

> /sdmx-explorer
> Business creation and business cessation rates in European Union            
   countries, geographically disaggregated   

 I have found the primary datasets on Eurostat that cover business creation
  (births) and cessation (deaths) with regional disaggregation.

  The most relevant dataset is BD_SIZE_R, which provides comprehensive business
  demography data down to the NUTS 3 region level (the most granular regional
  level in the EU, roughly equivalent to provinces or counties).

  Candidate Datasets

   1. BD_SIZE_R — Business demography by size class and NUTS 3 region ⭐
      Recommended
       * Coverage: All enterprises (including those with no employees).
       * Key Indicators: Number of births, number of deaths, birth rate (%),
         death rate (%), and net growth rate.
       * Dimensions: Region (NUTS 3), economic activity (NACE Rev. 2), and size
         class.
       * Timeframe: Typically annual data.

   [...]

  How would you like to proceed?
   - Would you like to explore BD_SIZE_R (all enterprises) or focus on
     employer-only data?
   - Do you want to see the specific regions or economic sectors (NACE)
     available?
   - Are you interested in a specific year or a recent comparison?

 > Use BD_SIZE_R at NUTS 3 disaggregation. For each NUTS3 region, get birth and 
   death rate. Write to console the URL to the original query for verification  
   purposes. Next, create a scatterplot where each NUTS3 region is a point. Put 
   birth rates on the Y-axis and death rates on the X-axis. Do not label        
   datapoints for legibility. Color-code them according to macro-region:        
   Western, Northern, Eastern and Southern Europe. In the legend, provide a     
   list of the countries included in each region.

I have completed the analysis of business birth and death rates across
  European NUTS 3 regions.

  Verification URL
  You can verify the original query and data structure directly on the Eurostat
  portal:
  https://ec.europa.eu/eurostat/databrowser/view/BD_SIZE_R/default/table?lang=en
  (https://ec.europa.eu/eurostat/databrowser/view/BD_SIZE_R/default/table?lang=e
  n)

  European Macro-Regions (Legend)
  The scatterplot color-codes regions based on the following grouping:

   * Western Europe: Austria (AT), Belgium (BE), France (FR), Germany (DE),
     Ireland (IE), Luxembourg (LU), Netherlands (NL), Switzerland (CH)
   * Northern Europe: Denmark (DK), Estonia (EE), Finland (FI), Iceland (IS),
     Latvia (LV), Lithuania (LT), Norway (NO), Sweden (SE)
   * Eastern Europe: Bulgaria (BG), Czechia (CZ), Hungary (HU), Poland (PL),
     Romania (RO), Slovakia (SK)
   * Southern Europe: Croatia (HR), Cyprus (CY), Greece (EL), Italy (IT), Malta
     (MT), Portugal (PT), Slovenia (SI), Spain (ES)

  Results Summary
   * Data Source: Eurostat BD_SIZE_R (Business demography by size class and NUTS
     3 region).
   * Indicator: Birth rate (ENT_BRTHR_PC) and Death rate (ENT_DTHR_PC).
   * Geographic Detail: NUTS 3 disaggregation (counties/provinces).
   * Latest Data: Most regions reflect data from 2021 or 2022.

  The generated scatterplot scatter_demografia_final.png shows the correlation
  between business creation (Y-axis) and cessation (X-axis). Regions along the
  diagonal have a stable business population, while those above the diagonal are
  growing and those below are experiencing a net contraction in the number of
  active enterprises.

But when it is done, it can be incredibly empowering. Ukrainian open data activist Nadiia Babynska Virna reports using Andrea’s CKAN MCP server in combination with a locally-run LLM to check the openness of public sector information with no code and only basic data science skills, “in the middle of a war”. Centaur. Conclusion: while my hunch about the geography of economic upheaval was unfounded, Doctorow’s own centaur/reverse centaur model holds. In his words, it’s not what the technology does, it’s who the technology – and, I would add, the data – is for, and who it is done to.

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I have just returned from walking St James’s Way. It is perhaps the most famous of the medieval pilgrimage routes: for twelve centuries pilgrims have walked it to reach the cathedral of Santiago de Compostela, in northwestern Spain, and they still do. According to tradition, the apostle James is buried there; since the early Middle Ages, the church has granted an indulgence to pilgrims that make it to Santiago. The flow of pilgrims towards Santiago is believed to never have stopped since the Middle Ages. In modern times, it shrank to a trickle, but has been growing at double-digit since the 1990s. It is estimated that over 500,000 pilgrims walked 100 kilometers or more in 2024.

To walk the Way is to participate in a subculture in which it makes complete sense to set aside a month of your life so that you can walk six-seven hours a day, sleep in crummy hostels, deal with foot blisters and minor (and sometimes not so minor) injuries. It may sound counterintuitive, but people take to this kind of stuff so easily that I suspect it may be hardwired. Maybe we are evolved for the collective nomadism we practiced before agriculture? I have no idea. Certainly the same ease of adoption applies to endurance sports like long-distance running and its even more extreme cousins, triathlon and iron man competitions: they seem weird from the outside, but their popularity speaks for itself. You will be hard pressed to find extrinsic rewards that justifies these huge investments of time and effort. The simplest explanation for why so many people walk St James’s Way or run marathons is that they enjoy doing so. And that takes me to Keynes.

In 1930, John Maynard Keynes wrote a landmark essay, Economic Possibilities for our Grandchildren (full text). The Great Depression was raging on, but he refused to despair. Yes, the rate of technological change had temporarily outpaced the rate with which “we can find new uses for labour”. But the Depression was just a sideshow. Based on a conservative estimate of a 2% yearly increase in the stock of capital, and a 1% yearly increase in efficiency due to technical progress, Keynes concluded that “mankind is solving its economic problem”.

I draw the conclusion that, assuming no important wars and no important increase in population, the economic problem may be solved, or be at least within sight of solution, within a hundred years. This means that the economic problem is not—if we look into the future—the permanent problem of the human race.

John Maynard Keynes, “Economic Possibilities for our Grandchildren”

It was coming time for the Round-the-Worlder, which began every other perihelion. Starting from Sheffield the contestants could run east or west around the world, without wristpad or any other navigational aid, shorn of everything but the information of their senses, and small bags of food and drink and gear. They were allowed to choose any route that stayed within twenty degrees of the equator (they were tracked by satellite, and disqualified if they left the equatorial zone), and all bridges were allowed, including the Ganges Strait Bridge, which made routes both north and south of Marineris competitive, and created almost as many viable routes as contestants.

– Kim Stanley Robinson, Blue Mars

The post What do people do when they are free from need? Reflecting on St James’s Way, John Maynard Keynes and science fiction appeared first on "Belay that order, comrades".

However, many reports are rarely read. A famous 2014 World Bank study found that about a third of their reports received zero downloads. This does not mean no one reads them, but it does highlight how difficult it is for non-intended readers—like researchers or practitioners in related fields—to find them. The current system is low in serendipity. Additionally, as websites change, old URLs break, resulting in 404 errors and lost access to content. This phenomenon is known as “link rot”.

We can do better. Academia has faced the challenge of serendipitous knowledge reuse for centuries. Over the past thirty years, it has built a robust ecosystem by leveraging the digital revolution and the power of open standards and open licenses. If your work includes producing reports and publications for public consumption, you too can adopt these practices to make them more discoverable and reusable, increasing their impact.

Unique identifiers enable a digital ecosystem of services

At the heart of this ecosystem are Digital Object Identifiers (DOIs). A DOI uniquely identifies any file—article, report, dataset, or executable application. DOIs are an ISO standard, issued by Registration Agencies that maintain metadata (authors, year, organisation, keywords, etc.) in interoperable databases. The largest is Crossref, a consortium of 23,000 publishers, currently handling two billion API requests per month. In a similar way, authors are uniquely identified by ORCID – Open Researcher and Contributor ID. ORCID provides an open, API-accessible database of researchers, automatically updated as new papers are uploaded. DOIs and ORCIDs create a web of linked data: papers link to their authors, and authors link back to their works.

These open, machine-readable datasets of uniquely identified knowledge products and authors have enabled a rich ecosystem of services. Repositories like arXiv, Mendeley and Zenodo allow researchers to upload papers and assign DOIs. Applications like Altmetric index documents in these repositories to measure their impact by tracking citations and aggregating them into bibliometric indicators. These, in turn, influence inclusion in major academic databases, such as Web of Science, Scopus, Lens and Google Scholar.

Academic repositories accept papers before they get peer reviewed (“preprints”), acknowledging that some knowledge is at most useful when its fresh, and academic review processes typically takes months. So, knowledge products from non-academic organizations (like NGOs) and academic research papers have become interoperable, part of the same digital space. The research community has come to read and cite reports more often, and this adds to their serendipity and impact. UNDP and other organizations could even take advantage of this to curate their own series and even journals, displaying content from repositories via API and experimenting with forms of review and curation. The European Commission’s Open Research Europe is an example of this model. These innovations, and others that will come, are enabled by community-created software libraries to access Crossref’s APIs, for example for Python and R.

The ecosystem includes bibliography management applications like Zotero. Instead of manually creating a bibliography for every publication, researchers maintain libraries of works they cite, from which these applications create bibliography on the fly. Such applications download metadata from Crossref and transform them into citations and bibliographies in any format, via plugins for LaTeX, Word, Google Docs, Obsidian and other editing applications.

Legal interoperability unlocks the power of open

The digital revolution enables remixing and cross-referencing from a technical perspective, but legal barriers remain. Knowledge products are governed by intellectual property rights (IPRs), which by default restrict many uses. Licenses specify what can and cannot be done. For example, Google Maps data is not open. This means that you can use Google Maps as a service, but you are not allowed to do anything else with the data. Say you use Google Maps to obtain the coordinates of UNDP’s offices around the world and put the coordinates in a CSV file. Although you knew the locations of the offices and have produced the file, the fact of having used Google Maps to find out the coordinates entangles your file with Google’s IPRs. You cannot publish it without calling in the lawyers.

To be truly frictionless, knowledge products must be both technically and legally open: irrevocably cleared by their copyright holder for use, redistribution, modification, and remixing by all, as per the open definition. This is crucial for datasets, as researchers avoid data with legal hurdles. Failing to use open licenses limits the spread, and therefore the impact, of your work. If you have a say in crafting your organization’s policies on licensing its own content, I would recommend you push for an explicit and blanket authorization to publish using open licenses, like those provided by Creative Commons. 

Publish for frictionlessness

To wrap up, here’s some recommendations for publishing reports and publications. 

• Use Zenodo as a long-term repository. It provides free DOIs, supports versioning, and is run by CERN, ensuring reliability.
• Obtain a (free) ORCID for each author or contributor and include them in the metadata. Zenodo supports multiple contributor roles, such as “team leader” and “data curator”.
• If your report is based on data you collected, publish the dataset separately with its own DOI and cite it in the report. Publishing open data is nontrivial; see a detailed guide to do that.
• Use open licences, such as Creative Commons Attribution 4.0 International (versions 4 and above protects your readers from copyleft trolling), which is widely used and protects both creators and users.
• Link your website’s report page to Zenodo for downloads to centralise page views and download statistics.
• Consider using bibliometric services such as Altmetric to track your impact over time.

Image made by Notebook LLM, based on the text of the post and a prompt written by myself.

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Spring has arrived for economic alternatives

As I stood on the stage of the Istanbul Innovation Days 2025, I experienced a feeling like the beginning of spring, when you throw the windows wide open and let warm air fill the room. The economics winter was over, for good. It was March 26 – the beginning of spring indeed – and I had the honour of facilitating the plenary session on “Alternative Economic and Financial Models”. Our panel had come together to claim that bold, comprehensive economic transformation was both urgent and possible – in fact, it was already under way in many parts of the world.  

For economists such as myself, this is an extraordinary claim. Since the 1980s, the economics profession has been all but dominated by a paradigm known as neoclassical economics, vigorously promoted by many prestigious scholars associated with the University of Chicago. The Chicago school’s success was not limited to academia: it persuaded political leaders the world over that its brand of economics was the only sound, reasonable one, not only in existence, but possible. British Prime Minister Margaret Thatcher summarized it brilliantly in 1980: “there is no alternative”, no point looking for other ways. Two full generations of economists and policy makers complied, defining a half-a-century long winter of economics.  

Progress everywhere

And yet, there we were, in Istanbul, and spring had come. We were seeing robust policy innovation to equip economic decisions makers with new tools – job guarantees, universal basic income and services, carbon coins, community land trusts, local energy communities, tailor-made financial instruments, twenty minute cities, missions and moonshots, and more. We were seeing ambitious redesign of economic institutions to deploy these new tools effectively. And we were seeing rapid progress in devising indicators of economic performance to guide those deployments, indicators that move beyond GDP – with UNDP and the UN as a whole taking a leading role.  

The best part? None of this is only theoretical, and none of this is limited to a narrow club of best-in-class from affluent countries. Our panel was itself composed of doers, practitioners, with solid experience, hailing from all over the world. In Costa Rica, Eduard Müller and Costa Rica Regenerativa turned a previously extractive economic system into one that rewards the regeneration of soil and nature. In Indonesia, Natalia Arjomand and Second Muse Capital devised a highly successful financial instrument to deliver interest-free loans to small enterprises in the waste management and recycling sector. In South Africa, Miles Kubheka and Wakanda Food Accelerator build economic inclusivity around food, an economic good which also encodes conviviality and care. And in Sicily, Giacomo Pinaffo and the Messina Community Foundation have built a rich and diverse local economy in solidarity, with hundreds of businesses coordinating under a single strategic umbrella in sectors like landscaping services, bioplastics, energy production, social housing, beverages, and the arts. The anti-colonial movement played a large role in opening our eyes, letting us see these contributions (which started well ahead of, and independent from, progress in academia) not as “lagging economies”, but as viable alternatives in their own right. 

The power of local (and of science fiction) 

There is much to be learned from their stories, and the stories of practitioners like them. I, for one, am determined to continue learning for years to come. But three learnings in particular stood out for me.  

The first one is that economic transformation works, not always, obviously, but more often and better than conventional economic wisdom gives it credit for. And it stands to reason: thanks to the progress I mentioned above, reformers in this generation simply have more tools in their armory than the conservative thinkers that oppose them. Exaggerating a bit for the sake of clarity, the latter have spent half a century developing one single option, that of free markets that, once correctly liberalized, will automatically deliver the best possible outcome. If that option fails, they have nothing else to offer.  

The second one is that economic transformation tends to happen fastest and deepest at the local level. Economists invariably point out that this is non-optimal, because critical levers for economic policies are only available to states, not to regions or districts or cities. They are right: and yet this oddity tells us that collective institutions closest to the people feel the demand for economic transformation strongest. I predict that regions and cities will continue to lead in institutional and policy innovation when it comes to the economy – and also that small states might have large impacts if they get on board with the economic transformation agenda. 

The third one is that we can only build economies we can imagine. Fifty years of “there is no alternative” have weakened our ability to imagine economies more humane and egalitarian than the ones we inhabit now. We need to re-develop our economic imagination muscle if we are to design successful economic transformation. Economists are not of much help there, so Kate Beecroft and Özgür Can Özüdoğru – with remote support from complexity economist Joffa Applegate – demonstrated how science fiction (especially in its more economically inclined variants, like cli-fi, solarpunk and afrofuturism) can help us travel with our minds to alien economic systems, and try them on for size. They made this point by delivering a brilliant workshop they designed with the Science Fiction Economics Lab, that took us to a fictional future Istanbul that had seriously tackled some of the very real economic problems it is facing now, such as housing and water scarcity.  

Stories are, as ever, a potent catalyst of human transformation. People don’t abandon broken systems because they have seen graphs on inequality graphs or read critiques of GDP. They change when they see new models come to life. When Costa Rican farmers heal their lands, and see the butterflies return. When Indonesian small businesspeople are entrusted with the capital to build their vision of a circular economy. When South African “foodpreneurs” gain access to platforms where food becomes power, pride, and possibility. When Sicilian researchers, businesses and workers find ways to build a social economy from the ground up, for themselves and others.  

As we traded war stories with one another and the audience of the Istanbul Innovation Days, I believe it became clear to everyone that Margaret Thatcher was wrong. She was wrong in 1980; she is even more wrong now, in the face of all this progress and creativity. Let’s leave “there is no alternative” behind, and embrace, instead, the message of UNDP’s Human Development Report 2025: “it’s a matter of choice”. The report refers to Artificial Intelligence, but I believe it applies to economic institutions as well. Those we have, we chose. And we could, and should, choose others, if they serve us better.  

I look forward to a future where we do so, with everybody’s contribution. In fact, I am working on a draft concept note to develop a portfolio on economic transformation. Please reach out if you want to contribute, or simply know more.  

Heartfelt thanks to all panel- and workshop- participants for their suggestions in writing this blog post. 

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The Scholomance is a school for wizard children, set in the eponymous world created by fantasy author Naomi Novik. In this world, magical predators called maleficaria feed on mana, a substance that allows wizards to do magic. Both children and adult wizards have it, but the adults are more dangerous than most of the maleficaria themselves, so the latter need to feed on children. This is a major threat to wizardkind: in the wild, nineteen out of twenty wizard children are eaten before maturity. The solution to this is the Scholomance: a semi-sentient, heavily warded magical building where children are better protected while they learn to defend themselves against the maleficaria. However, this solution is far from perfect: some predators still get in, and kill three out of four students before graduation.

Novik’s Scholomance Trilogy is a hugely enjoyable read. Cory Doctorow wrote a raving review of it; he’s not wrong, and I am glad he put me onto it. Even more so because, as I went through the three novels, I discovered the literary equivalent of a secret door to… a political economy based on a particular value theory called the labour theory of value (LVT). And look, maybe I am seeing ghosts here (no pun intended). I am like into analyses of science fiction novels, so maybe I am a guy with a hammer and all I see is nails. But still… humour me here, and see if it makes sense

Let’s start with mana. Wizards can do magic, but only if they have mana to spend. A powerful wizard is like a powerful car; its power is only theoretical until you put fuel into the equation. How do you get mana? A wizard can produce mana directly by engaging in a tiring or tedious activity, like doing pushups or crochet. He or she can also receive it from another wizard who gives it willingly: in fact, this how wizards purchase from each other things that they value. Finally, a wizard can get mana from his or her own storage: besides their own bodies, wizards have access to magical artifacts that hold mana and can be drawn from as needed.

To an economist this means that mana is currency in the Scholomance world. It serves as mean of exchange, numeraire, storage of value; it is fungible. It also means that magic is derived from human labour: every act of magic requires mana, hence somebody’s effort or drudgery. In LVT terms, the socially necessary labour or absolute value (not to be confused with the exchange value) of an act of magic is equal to the amount of labour gone into producing the necessary mana. The analogy is quite strict, to the point that, as a wizard gets fitter and doing pushups becomes easier, he or she needs to do more of them to produce the same quantity of mana. (Novik: “The physical labor isn’t what counts. What turns it into mana is how much effort it costs me.”).

So far, so good. Here’s the curveball: it turns out there is another way to do magic after all. It’s called malia, and consists in pulling mana from your surroundings. Novik:

Everyone—almost everyone—uses a bit of malia here and there, stuff they don’t even think of as wicked. Magic a slice of bread into cake without gathering the mana for it first, that sort of thing, which everyone thinks is just harmless cheating. Well, the power’s got to come from somewhere, and if you haven’t gathered it yourself, then it’s probably coming from something living, because it’s easier to get power out of something that’s already alive and moving around. So you get your cake and meanwhile a colony of ants in your back garden stiffen and die and disintegrate.

So, in the Scholomance world there are two paths to doing magic: mana and malia. If you use the LVT analogy to translate this sentence in terms of our world, it reads like this: there are two paths to value production: labour and extraction. “The power’s got to come from somewhere” is Novik’s equivalent of “there is no free lunch”. If you have power and have not created it with the sweat of your brow, you have appropriated it from something or someone else.

This is a rather elegant formulation, because it puts under the same analytical umbrella two phenomena that most economists would consider distinct: negative externalities and exploitation. Negative externalities appear when an economic actor manages to shift some of the costs associated to their production onto the environment, for example through pollution. A company might be doing well, like, say, Dupont at the end of the 1990s, its profit tidy and its markets bullish – meanwhile, though, they are discharging poisonous chemicals into rivers, and people are dying of kidney and testicular cancer. Malia. Or take the example of high-octane fashion brand Armani, who was caught by Italian police subcontracting its 1,800 EUR bags, by way of a contractor, to sweatshops were workers were paid 2-3 EUR an hour to works 10 hours a day so that the sweatshops in question could sell the bags to Armani’s contractors for 93 EUR. Malia.

Some wizards go all in, only finance their magic with malia, and end up being responsible for a lot of suffering and death. Some do not want any part of this malia business, and go “strict mana”. Most are somewhere in between; they produce mana of their own, but also “cheat a little”. In the Scholomance world there are two problems with cheating a little. The first is that cheating adds up to create a negative balance on the other side of the ledger, compensating the positive balance of the additional magic that the cheater can do. Novik:

Whenever somebody needs a little more mana than they’ve got, they steal it from somewhere, seems like no big deal – but you end up with a negative flow [sic] of mana. When that negative flow gets big enough, a maleficaria will generate around it. It’s not a secret, but people do it anyway […] All the psychopatic wizards in the world put together aren’t the real problem. The problem is that everyone cheats. And the we get more maleficaria, and our kids die, and still everyone cheats, because the two things are too far apart. You can live your whole life without cheating once […] and still your kid’s just as likely to get eaten, and meanwhile someone else cheats every day and their kid sails through.

That, ladies and gents, is a textbook prisoner’s dilemma, with maleficaria in the role of negative externalities. And now to the second problem with cheating a little: by being so obviously beneficial, it makes it easier to cheat a lot more. In the Scholomance world, the highest-reputed wizards have figured out way to create magical fortresses called enclaves, that will keep maleficaria out, making their lives a lot safer and more comfortable, and give them the opportunity to acquire a lot of cheap labour by less fortunate wizards, dangling in front of them the possibility of a place in the safety of the enclave.

In the Scholomance world, safety is the main scarce resource around which the wizarding economy turns – the quantity on the left side of its production function, as it were. From an economic perspective, therefore, book three of the trilogy comes with the main plot twist: the scarcity of safety is, at least in part, manufactured.

Here’s how this happens. The protagonist, a powerful witch, discovers that making one of these fortresses requires hideous human sacrifices, and releases deadly maleficaria into the world. So, enclaves as a magical technology make the world safer for the privileged few, but less safe for everyone else. She then digs up a set of spells (a magical technology) to build enclaves without human sacrifices. “The power has to come from somewhere”, so the resources that do not come from those sacrifices must come from honestly earned mana; and the process cannot build shiny, gigantic fortresses, but only smaller ones, that would reduce the space available for each wizard.

Still, no human sacrifices and no extra terrifying wizard-eating monsters released into the wild sounds like a great value proposition. And yet, the witch has no takers at all: no wizarding community would replace their grisly foundations with something cleaner and more durable, though more modest. The idea of renouncing to their advantages is, for enclaves-dwelling wizards, simply unthinkable. As Novik is not shy to point out, the system works poorly for wizardkind as a whole, but it works brilliantly for the more privileged wizards in the enclaves, who have safety and substantial leverage on everybody else. Producing monsters is perversely useful for enclavers, because it makes wizards on the outside even more desperate to sacrifice their lives and abilities to serving the enclaves in the hope of being allowed in: in other words, it enables exploitation. Enclavers are basically in the protection business: they create a threat for other wizards, then extract services from them for partially protecting them against those threats. Creating externalities and exploiting independent wizards is how enclavers procure the mana that powers their dominance.

Something similar happens in our own real-world economy. Countries that got wealthy on the back of colonial extraction and fossil-fuels burning are not only refusing to provide proper loss and damage compensation to the countries that suffered for the very real “maleficaria” brought into existence by those behaviors. They are taking advantage of the dire conditions created by climate change in vulnerable countries to extract even more resources, like critical raw materials, in return for desperately needed capital. Like in the Scholomance world, our safety needs are, at least in part, manufactured: recent research suggests that we could meet everyone’s energy needs while remaining within planetary boundaries. But we don’t, because, like those wizards in the enclaves, we do not want to share.

I don’t know if Novik is familiar with the economic notions of sufficiency and degrowth. I suspect she does. If not, she has reinvented them, alongside the social and moral dilemmas that stand in the way of their widespread adoption. That is at the same time depressing and great: depressing, as she mercilessly rubs in our face the cruelty and injustice of the economic systems both we and the wizards live in, and great because the Scholomance trilogy makes for a great metaphor to explain capitalism to young adults. And, yes, to economists such as myself.

Photo: Public domain, from https://www.needpix.com/photo/download/1017235/witch-sorcerer-woman-female-young-medieval-magic-gothic-dark

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I am part of a group which is building a cohousing in Brussels. It’s a risky endeavor but I could just not resist it: I dislike how the real estate market has financialized the right of humans to decent housing, and I dislike how the manner of building homes have made us lonely, alienated, surrounded by strangers. As an economist, I also find modern housing incredibly inefficient, because it does not produce public goods – like common spaces and communities – that are, by definition, the most efficient goods there are. And so, after many years of longing and reflections, in late 2021 I found myself in a small group willing to try it out, and took the plunge. Our cohousing is called The Reef in tribute to the diverse webs of cooperation and competition that exists in real coral reefs, and also as an act of remembrance should all coral reefs in the world die, which is not unlikely at all.

It is an incredibly rich, life-changing experience. It is also the second most difficult thing I have ever done (the first was founding a reasonably successful punk-folk band), and the one with the first-highest stakes (for most of us it is all of our lives’ savings). Yet, I never posted about it before, with one exception at the beginning of the journey. Frankly, I was not sure of what lessons one could draw from it: we were certainly working hard, but were we getting anywhere? Were we on our way to success, or just deluding ourselves? I could not tell. In the legal framework and economic landscape of Belgium in the 2020s, building a cohousing is a highly uncertain affair. At every turn, you face another obstacle that has the potential to stop the entire project dead in its track. Will we find a site to build the cohousing in? Will we be able to work together in reasonable harmony, or will the group collapse under the weight of interpersonal conflict? Is there even enough demand for cohousings to complete a group? Will the war in the East make construction materials unaffordable, and our project with it?

Still, people around me are interested in learning about cohousing. Many have encouraged me to start sharing my reflections about it. And it is the right time: the project has reached a degree of maturity where, I think, we can start drawing some lessons from it – though it could still fail, of course. There is a lot to share, but I am going to start with only few of the clearest learnings so far.

1. Self-managed projects are surprisingly efficient

Over the years, I have spoken to many people that dream of living in a cohousing. Despite this, it is almost impossible to just go out and buy a house or an apartment that is part of one. There appears to be what economists call a market failure: there is a market demand for a more social way of living, but no supply. So, if you want to live in a cohousing you will most likely need to start a group, or join one, and have your cohousing built to specifications. Groups must make a choice as to how to organize themselves. One possibility is for the group to directly take charge of the project management: find a site to buy, negotiate with the owner, purchase it, hire an architect and a construction company, organize the financial flows and so on. The other is to hire a company that will take care of the project management for you. In Belgium we are fortunate that there exist two such companies.

The Reef chose to be a self-managed group. In practice, this means that a bunch of random people, none of whom is a real estate or construction professional, is now running a 9 million Euro real estate project. Counterintuitively, this is working better than we had any right to expect: processes are transparent and relatively fast. We learned to work as a team quite quickly, and there is a high level of accountability. The Reef is a healthier, more efficient working environment than many professional spaces I have worked in. We have to work harder, but that work will pay for itself in terms of added trasparency and fuller ownership of the project. There is pride and joy in working together as a group to build our future home, and we believe that doing it this way will make our little community even more cohesive – and we save money.

2. Building community comes natural

Most people in our group did not know each other before joining. Most of us joined not based on previous friendships or family ties, but because we are drawn to the idea of cohousing itself. Some of us thought this might pose a challenge: in this kind of project people are making large investments in an endeavor the outcome of which depends on their cohousing mates playing nice. A lot of trust is needed. Among the many challenges of cohousing, this one turned out to be fairly easy. Common involvement in this kind of project builds mutual trust, even friendships, relatively quickly. This is because the project itself gets you into repeated interactions with each other. Reputation is obviously valuable, so people do not like to drop the ball on one another. In a short time, you realize you can trust these people after all, and start to relax and enoy their company. I have no doubt that The Reef will be an imperfect but functional, and even beautiful, community.

3. Process and information tidiness are critical

In 2021, as a prequel to the formal start of the process of building The Reef, the founding group spent a few months researching cohousing. We read up on everything we could find, and engaged with extant cohousing groups to learn from their experiences. We also arranged to visit several already-built cohousings. All sources pointed to how critical good process is.

The reasoning is straightforward. Building a cohousing takes 4-7 years. During this period, you will be doing weekly meetings plus individual- or small-group work. All of this effort is unpaid, and you will still have all of your personal and professional responsibilities. You might even be asked to step up a little to cover for your cohousing mates: for example, in our group parents of small children are given a pass, and just asked to respect the deadlines and otherwise do what they can, no questions asked.

In a situation like this, it is super important to be methodical and efficient, or you will become overwhelmed. The Reef is very methodical, on two fronts. First, we are organized according to a variant of a model called sociocracy. This means plenaries + teams that report to the plenary and do the heavy lifting of preparing the decisions for the plenary to take. All meetings are facilitated (by a Team Facilitation, whose members took trainings in sociocratic methods). The entire group took trainings in non-violent communication as a measure to prevent the escalation of conflicts. This method is very efficient, and it saves time on decision making that we sorely need for operations. For example, while searching for a site we scouted the entire city on bicycles and on foot for six months, mapping and evaluating 170 potential sites. Even with a fairly large group of a dozen active adults, you see why efficiency is so important.

Second, we take information management seriously, and adopted ways inspired by the open source and open knowledge movement. All information is public by default, and protected only if there is a need for confidentiality. A very successful move was to ban emails completely, and instead move our communication onto an online forum. This reduces Inbox stress and allows people full access to every communication, letting them choose what they want to engage with. It also makes past communications very searchable (we even use tags consistently, something that I have not experienced in any other working environment). Do not underestimate the impact of using good forum software over email – let alone stuff like Facebook or Whatsapp or Slack groups, which is not, repeat not, optimized for economical and accountable communication! Our forum as of now hosts over 10,000 messages, and has over 300,000 pageviews, and the fact that it allows access while not flooding us with notifications is valuable. Transparency is also important

From open source culture we also learned the importance of good documentation: for example, we have a guide to The Reef’s digital assets, one to using tags and groups in the forum, one to making changes to the website, a manual to onboard new members, a governance document. Each one of these shares knowledge and empowers everyone in the group, removing organizational bottlenecks, at the cost of having to write things down in a clear and accessible format.

4. A cohousing ecosystem is coalescing in Brussels

Self-managed groups like ours need not be navigating uncharted waters all the time. To our surprise and delight, cohousing is something like a movement. People support each other, mostly with information that can save us enormous amount of time. The advice we received from our sister cohousings at the beginning of the journey was invaluable. Also, there are now a few professionals in Brussels that understand cohousing and have experience of building them: the architects’ studio Stekke and Fraas has already built three cohousings in Brussels; Mark Van den Dries, a retired entrepreneur that has led several successful cohousing projects (he lives in one) and now offers himself as a coach; the Namur notary Pierre-Yves Erneux. A Dutch-Belgian bank, Triodos, offers mortgages adapted to the reality of cohousing.

All this means that we have it much easier than first-generation cohousings. Like all economic movements, cohousing is cumulative: if you were to start a project now, you would face fewer uncertainties than we did, because you could build on our experience. And if you or someone you know did start a cohousing, I would be interested to learn about it, be it through a link you share or by sharing war stories over coffee.

Photo: The Reef’s group explore a candidate site for the cohousing project in summer 2024. CC-BY The Reef Cohousing

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