Tag Archives: complessità

A cool flock of birds flew overhead.

Policy making for smart swarms

My friend Vinay Gupta has come up with the idea to start the Big Picture Days series with an event on what he calls swarm cooperatives, meaning instant campaigns, unconferences, hackathons and other unorthodox constellations of people in action that are both collaborative and non-hierarchical. He got in touch and asked me to give a talk about it in the context of public policy. That sounds crazy, but it got me thinking. For years now I have been involved in policy initiatives that incorporate an element of that openness, of that fluidity. Can we really speak of policy making for swarms? If so, what does that mean?

At the heart of this concept lies a fundamental paradox. Swarms derive their uncanny efficiency from radical decentralization of decision making and action; yet, decentralization might (and does) cause the swarm to lose coherence, and its action to lose directionality. That does not work well with public policy, that requires agency: no agency, no policy. The main tool I use to debunk this paradox is network theory: I think about swarms as people in networks. In networks, nodes might be equal in the amount of top-down power over others, but they will typically be very unequal in terms of connectivity, hence the ability to spread information (including narratives and calls to action) across the network. Uneven connectivity adds some directionality to the swarm, in the sense that the most connected people get it to go their way most of the times.

Public policy is generally understood as a top-down process: some leader somewhere makes a decision and that decision is enacted. I call this the linear model. Since it misses all of the feedbacks and adaptation, the linear model does not work if the context of your policy is a complex adaptive system: the system simply changes its shape to route around the policy, or even push it back (more details). Not only do its recipes not deliver: they might cause serious harm. This provides a good case for trying to apply swarm thinking to government.

It can be frightfully difficult, because the linear model is encoded into law and hardwired into organizational charts, remits and procedures: but the potential rewards are immense. Why? Because if you want to build a swarm, you need people to want to join it. By definition, these people can’t be your employees, or anyone you have command and control over; they have to be free agents that want to cooperate. Now, there are already very many opportunities to collaborate out there, and few of them have attracted the lion’s share of available “swarming” (think Wikipedia, with tens of millions of participants). This means that people will cherrypick, and you will have to work extra hard to win them over. Swarm building is a buyers’ market. That’s a big reality check for your project right there.

The first consequence of all this: the swarm-builder’s payoff to bullshit immediately becomes negative. Well-packaged bullshit might fill a report or a PowerPoint presentation that gets past your boss, but has no chance of whipping up enthusiasm in a bunch of strangers that are not taking your money. I believe this has given some competitive edge to my own projects. Cutting corners would not do it: I had to work at full steam, or call it quits.

Vinay’s invitation gave me the opportunity to lay out tips and tricks to policy making for swarms. I ended up with a weird list, with items like Falkvinge’s Law, randomness (my favorite), timebombs, the fishing rod model, dogfood and parties. It is tentative and incomplete, but does represent the very frontier of my thinking (and my practice!) of public policy. If you are interested in this kind of stuff, you might like my slides. I added my notes, so you get a reasonable rendition of my 10-minute talk at Big Picture Days.

The learning State: integrating social innovation into mainstream policy

I joined a Council of Europe workgroup on Quality job creation through social links and social innovation (the social innovation part is a recent add to the group’s name, and I think I am partly responsible for the add). One of the issues we are discussing is this: given that there is an interesting group of people who started calling themselves social innovators; given that these people seem to have potential for improving the society they (and we) live in; given that they look like a new kind of social and economic agent, as such requiring a new kind of public policy – the ones in place for firms and nonprofit orgs might not work in their case; given all this, it follows that public authorities might soon be required to do new things, perhaps radically new ones. That’s great; but how do public authorities actually learn?

This looks like a relevant question to me. I have worked on pilot government initiatives hailed by some as innovative, like Kublai or Visioni Urbane; the challenge they now face is integration into mainstream policy, becoming a part of the default arsenal for their parent authorities to do their job. Thanks to the Council of Europe’s support I have been able to look deeper into the issue. My provisional conclusion is that the prevailing learning model for public authorities is rational-Weberian and way off the mark. Here’s how it works:

  • a new issue, after its importance has been validated by the scientific community, gains importance in the eye of the public opinion.
  • politicians, competing for votes, include it in the list of issues they promise to tackle once elected.
  • after taking office, representatives embed action to be taken thereabout into law.
  • new law is enacted into policy

This model is elegant but useless. It only works if (1) alternative courses of actions can be identified, discussed and selected already in the democratic debate phase; (2) the electorate has effective means to enforce their pact with its representatives, constraining them to keep their promise by making law; (3) law enactment is “linear”, i.e. a law translates unambiguously in a course of action at the level of the executive branch (the main tool for law enactment is generally assumed to be the impersonal, rational Weberian bureaucracy); (4) and policy is a one way street: government acts upon society, trying to mould it according to its goals, whereas society does not exert any influence on government, save through the democratic process. None of this is even remotely true.

So what? So it makes more sense to abandon Weber and the mechanism metaphor for framing governance, and embrace an ecosystem metaphor instead. I propose to look at public authorities as complex adapive systems, coevolving with society and the economy. Teaching them to deal with social innovation – or anything they never experienced before – means helping them to think of economic and social agents as driven by evolutionary forces that reward the fittest. Policy, then, works best by shaping the fitness landscape, and letting agents work their way through it towards the desired outcome. It is a policy that enables and incentivizes agents to give input, rather than forcing outcomes top-down. This has clear implication for designing policies in practice. One of them is that a constitutional architecture that enables bottom-up learning (like Common law) is inherently superior to one that does not.

If you care about this topic, you can read the paper: the Council of Europe authorized me to share it online. Thanks to Gilda Farrell and Fabio Ragonese for the kind concession.

Lo Stato che impara: come integrare l’innovazione sociale nelle politiche mainstream

Faccio parte di un gruppo di lavoro al Consiglio d’Europa che si occupa di “Quality job creation through social links and social innovation” (l’espressione “social innovation” è un’aggiunta recente al nome del gruppo; di questa aggiunta credo di essere in parte responsabile). Uno dei problemi che ci stiamo ponendo è questo: stante che esiste un gruppo di persone interessanti, che chiamano se stessi innovatori sociali; stante che queste persone sembrano avere un potenziale per migliorare la società che abitano; stante che sembra si tratti di soggetti di nuovo tipo – che, quindi, richiedono politiche pubbliche di nuovo tipo, diverse da quelle per le imprese e per il mondo del non profit; stante tutto questo, ne consegue che alle autorità pubbliche si richiede di fare cose nuove, forse anche radicalmente nuove. Bene. Ma come imparano le istituzioni?

Mi sembra una domanda importante. Ho lavorato a progetti pilota pubblici apprezzati come innovativi (Kublai o Visioni Urbane, per esempio); la sfida che attende questi progetti è la trasformazione in metodi che fanno parte del normale arsenale con cui le autorità che li hanno varati affrontano il mondo. Con il sostegno del Consiglio d’Europa ho potuto affrontare il problema in modo strutturato. La mia conclusione provvisoria è che il modello prevalente di apprendimento per le autorità pubbliche è razionale-weberiano e completamente sbagliato. Funziona così:

  • Un problema nuovo viene avvertito dalla pubblica opinione
  • Politici in concorrenza tra loro per i voti degli elettori lo incorporano nelle loro piattaforme elettorali, insieme alle soluzioni che propongono
  • Una volta eletti, i rappresentanti del popolo legiferano in conseguenza delle loro piattaforme elettorali
  • La nuova legge si trasforma, in modo lineare, in policy, cioè in azione da parte del governo

Questo modello è elegante ma inutilizzabile. Richiederebbe (1) che politiche alternative (per esempio: carbone pulito vs. rinnovabile vs. nucleare per la politica energetica) potessero venire discusse in profondità e in modo razionale già nelle campagne elettorali; (2) che l’elettorato avesse modi efficaci di vincolare gli eletti alle loro promesse elettorali; (3) che la conversione di una legge in policy fosse “lineare” e non richiedesse interpretazione da parte dell’esecutivo; e (4) che le politiche fossero una strada a senso unico, cioè un fenomeno che influenza la società ma non ne viene a sua volta influenzato. Nessuno di questi requisiti è soddisfatto, nemmeno lontanamente.

E allora? Allora ha più senso abbandonare Weber e la metafora del meccanismo come strumento per capire l’azione di governo, e abbracciare invece, quella dell’ecosistema. Propongo di considerare le autorità pubbliche come sistemi adattivi complessi che coevolvono con la società e l’economia. Insegnare loro ad avere a che fare con l’innovazione sociale – o qualunque cosa nuova, al di fuori della loro esperienza – significa cercare di aiutarle a pensare gli agenti economici e sociali come mossi dalle forze dell’evoluzione, che naturalmente premiano il più adatto. La policy, in questo contesto, diventa l’atto di strutturare un fitness landscape che porti gli agenti ad incamminarsi verso il risultato auspicato. Invece di preterminare i propri esiti top-down, essa abilita e incentiva gli agenti a fornirle input. Questo ha precise conseguenze sulla progettazione dell’azione di governo in pratica. Una di queste è che un’architettura costituzionale che abilita l’apprendimento dal basso (come la Common law) è intrinsecamente superiore a una che non lo fa.

Se ti interessa l’argomento puoi leggere il paper (in inglese): il Consiglio d’Europa mi ha autorizzato a condividerlo. Grazie a Gilda Farrell e Fabio Ragonese per la gentile concessione.