46 favorite reads on democracy, civic tech and a few other interesting things

open book lot

I’ve recently been exchanging with some friends on a list of favorite reads from 2020. While I started with a short list, it quickly grew: after all, despite the pandemic, there has been lots of interesting stuff published in the areas that I care about throughout the year. While the final list of reads varies in terms of subjects, breadth, depth and methodological rigor, I picked these 46 for different reasons. These include my personal judgement of their contribution to the field of democracy, or simply a belief that some of these texts deserve more attention than they currently receive. Others are in the list because I find them particularly surprising or amusing.

As the list is long – and probably at this length, unhelpful to my friends – I tried to divide it into three categories: i) participatory and deliberative democracy, ii) civic tech and digital democracy, and iii) and miscellaneous (which is not really a category, let alone a very helpful one, I know). In any case, many of the titles are indicative of what the text is about, which should make it easier to navigate through the list.

These caveats aside, below is the list of some of my favorite books and articles published in 2020:

Participatory and Deliberative Democracy

While I still plan to make a similar list for representative democracy, this section of the list is intentionally focused on democratic innovations, with a certain emphasis on citizens’ assemblies and deliberative modes of democracy. While this reflects my personal interests, it is also in part due to the recent surge of interest in citizens’ assemblies and other modes of deliberative democracy, and the academic production that followed.  

On Civic Tech and Digital Democracy

2020 was the year where the field of civic tech seemed to take a democratic turn, from fixing potholes to fixing democracy.

MISCELANEOUS

Finally, a section as random as 2020.

As mentioned before, the list is already too long. But if there’s anything anyone thinks should absolutely be on this list, please do let me know.

Serendipity for Online Deliberation?

(originally posted here)

I was going to reply to Paul’s comment and this actually became a post.  Having suggested the idea of inversed tag clouds as a means to enhance serendipity, Paul pointed out two cases in which serendipity can be desirable: 1) where you know that all the entries are of a certain standard and 2) where the most popular ones are likely for that reason to be less interesting.

In this respect, I would like to speculate to what extent serendipity can be desirable in large-scale deliberation processes, and how this serendipity can be induced online. To give it a fancy name, “induced redistributive serendipity”.

To make my point simpler, let’s think for instance of a cloud based on the number of views that an article / argument receives. In this case, the most viewed articles / arguments (or their respective tags) become more visible as more people view them, generating a snowball effect of intuitive mimesis.

This is more or less what happens in flawed models such as the ranking system of phase 1 of the “Open Government Initiative”, where interventions at the initial stage can (and often do) produce huge variations in the outcome. In this case, for instance, the idea of an inversed cloud could neutralize these undesirable effects.

Now, consider an online deliberation where, at least in theory, all the arguments are important and should be objects of consideration. Here, a traditional tag cloud could have disastrous consequences for the quality of deliberation. Once more, an inversed cloud based on the number of times an argument is viewed (the least viewed become more visible) could be useful for the purpose of online deliberation.

This could be particularly applicable for large-scale online deliberation. Given that people rarely take the time to go over most of the arguments that are available, an inversed cloud could have a redistributive function. As the most read arguments become less visible and vice-versa, one would expect a better distribution of the number of views each argument receives. Finally, for the participants, this could lead them to come across information that they were not looking for in the first place.

In other words, my question is: could this “induced redistributive serendipity” be used in large-scale online deliberation?