In reply to Creating a custom GPT to learn about my blog (and about myself) by Peter Rukavina

It’s not surprising that GPT-4 doesn’t work like a search engine and has a hard time surfacing factual statements from source texts. Like one of the commenters I wonder what that means for the data analysis you also asked for. Perhaps those too are merely plausible, but not actually analysed. Especially the day of the week thing, as that wasn’t in the data, and I wouldn’t expect GPT to determine all weekdays for posts in the process of answering your prompt.

I am interested in doing what you did, but then with 25 years of notes and annotations. And rather with a different model with less ethical issues attached. To have a chat about my interests and links between things. Unlike the fact based questions he’s asked the tool that doesn’t necessarily need it to be correct, just plausible enough to surface associations. Such associations might prompt my own thinking and my own searches working with the same material.

Also makes me think if what Wolfram Alpha is doing these days gets a play in your own use of GPT+, as they are all about interpreting questions and then giving the answer directly. There’s a difference between things that face the general public, and things that are internal or even personal tools, like yours.

Have you asked it things based more on association yet? Like “based on the posts ingested what would be likely new interests for Peter to explore” e.g.? Can you use it to create new associations, help you generate new ideas in line with your writing/interests/activities shown in the posts?

So my early experiments show me that as a data analysis copilot, a custom GPT is a very helpful guide… In terms of the GPT’s ability to “understand” me from my blog, though, I stand unimpressed.

Peter Rukavina

Early September I spent most of a week in Portugal, to be exact in the home of Bev and Etienne Wenger-Trayner. I was there with our entire team at The Green Land, to participate in the 3-day Systems Convening workshop that Bev and Etienne host.

It was an intensive and special week to me. Special for multiple reasons.

  • The training was hosted at home by Bev and Etienne. This creates a special dynamic, as you are in someone’s private environment and in an informal setting, while taking a deep dive in professional topics. We shared meals together, took a swim, learned to operate the coffee machine ourselves. All this serves to create more and different connections between the participants, and creates a space for much more open interactions. It’s especially pleasing that this set-up is partly inspired by Bev having attended our first birthday unconference in 2008.
  • We participated with our whole team, and there also were other participants in the group. The first effect of this is that we all returned to work with the same experience, which makes actual adoption in our work by each of us easier. It created a shared language for something that me and others are experienced in but found hard to convey to our younger team members. The second effect was that because of the presenc of participants with very different backgrounds and activities, it wasn’t just about us, which allowed us to take a bit of distance to our own work, and get more varied feedback as well.
  • Systems convening, as a practice, is something that me and my colleague Frank do almost naturally. Exploring it more deeply and methodically in this course meant not just a boost for our individual work in client projects, but also a tremendous boost in our self-perception as a company. For my own perception of my current projects as well as where I think we can go as a company this was enormously valuable too. We spent three days deeply reflecting on our work and our practices.
  • Bev and Etienne’s approach towards learning and towards working change is something I too have deeply internalised over the years, also because my own journey and my own natural behaviour is very similar to their topics of interest. It felt like my team got the opportunity to look inside my own head for three days. The type of work I do and love to do, how it connects to my understanding of the world, the type of things that are dear to me in taking a stance professionally, it’s almost as if it was a course on ‘how Ton thinks about things’.

I’ve known Bev for a very long time, and Etienne’s work has been a key ingredient in my own work since the late nineties. It was such a pleasure to bring all my colleagues to their home, and do a deep dive on social learning theory and our own practices. The way that my personal network, deeply internalised practices, the value of our own current work, our team dynamics, how all those layers fully turned into a coherent meaningful single whole was spectacular and deeply touching to me.

During the course it became very clear to me (again? for the first time?) how deeply I am emotionally tied to and invested in social learning approaches and agency in the world.

This intense emotional connection to social learning and the change work I do, clarified for me how much of that is actually a core part of my internal personal identity. In the past months I had an intermittent conversation with my friend Peter about whether I am curious or lack curiosity, and how I tend to routinely distrust or dismiss my own motives behind how I operate in the world. The experience last month in Portugal makes me realise that there actually is not much reason to be that suspicious, and much more reason to actually embrace that about myself.

At work

All course participants with Bev and Etienne

Taking a swim, and drinking a glass of wine, in Bev and Etienne’s pool with sea view

This week it was 15 years ago that I became involved in open government data. In this post I look back on how my open data work evolved, and if it brought any lasting results.

I was at a BarCamp in Graz on political communication the last days of May 2008 and ended up in a conversation with Keith Andrews in a session about his wish for more government held data to use for his data visualisation research. I continued that conversation a week later with others at NL GovCamp on 7 June 2008 in Amsterdam, an event that I helped organise with James Burke and Peter Robinnet. There, on the rotting carpets of the derelict office building that had been the Volkskrant offices until 2007, several of us discussed how to bring about open data in the Netherlands:

My major take-away … was that a small group found itself around the task of making inventory of what datasets are actually held within Dutch government agencies. … I think this is an important thing to do, and am curious how it will develop and what I can contribute.
Me, 10 June 2008

Fifteen years on, what came of that ‘important thing to do’ and seeing ‘what I can contribute’?

At first it was mostly talk, ‘wouldn’t it be nice if ..’, but importantly part of that talk was with the Ministry responsible for government transparency who were present at NL GovCamp. Initially we weren’t allowed to meet at the Ministry itself, inviting ‘hackers’ in was seen as too sensitive, and over the course of 6 months several conversations with civil servants took place in a pub in Utrecht, before being formally invited to come talk. That however did result in a first assignment from January 2009, which I did with James and with Alper (who also had participated in NL GovCamp).

With some tangible results in hand from that project, I hosted a conversation at Reboot 11 in 2009 in Copenhagen about open data, leading to an extension of my European network on the topic. There I also encountered the Danish IT/open government team. Cathrine of that team invited me to host a panel at an event early 2010 where also the responsible official at the European Commission for open data was presenting. He invited me to Luxembourg to meet the PSI Group of national representatives in June 2010, and it landed me an invitation as a guest blogger that same month for an open data event hosted by the Spanish government and the ePSIplatform team, a European website on re-using government information.

There I also met Marc, a Dutch lawyer in open government. Having met various European data portal teams in Madrid, I then did some research for the Dutch government on the governance and costs of a Dutch open data portal in the summer of 2010, through which I met Paul who took on a role in further shaping the Dutch portal. Stimulated by the Commission with Marc I submitted a proposal to run the ePSIplatform, a public tender we won. The launching workshop of our work on the ePSIplatform in January 2011 in Berlin is where I met Frank. In the fall of 2011 I attended the Warsaw open government data camp, where Marc, Frank, Paul and I all had roles. I also met Oleg from the World Bank there. In November 2011 Frank, Paul, Marc and I founded The Green Land, and I have worked on over 40 open data projects since then under that label. Early 2012 I was invited to the World Bank in the US to provide some training, and later that year worked in Moldova for them. From 2014 I worked in Kazachstan, Kyrgyzstan, Serbia and Malaysia for the World Bank until 2019, before the pandemic ended it for now.

What stands out to me in this history of a decade and a half is:

  • How crucial chance encounters were/are and how those occurred around small tangible things to do. From those encounters the bigger things grew. Those chance encounters could happen because I helped organise small events, went to events by others, and even if they were nominally about something else, had conversations there about open data with likeminded people. Being in it for real, spending effort to strengthen the community of practitioners around this topic created track record quickly. This is something I recently mentioned when speaking about my work to students as well: making time for side interests is important, I’ve come to trust it as a source of new activities.
  • The small practical steps I took, a first exploratory project, creating a small collection of open data examples out of my own interest, writing the first version of an open data handbook with four others during a weekend in Berlin served as material for those conversations and were the scaffolding for bigger things.
  • I was at the right time, not too early, not late. There already was a certain general conversation on open data going on. In 2003 the EC had legislated for government data re-use, which had entered into force in May 2008, just 3 weeks before I picked the topic up. Thus, there was an implemented legal basis for open data in place in the EU, which however hadn’t been used by anyone as new instrument yet. By late 2008 Barack Obama was elected to the US presidency on a platform that included government transparency, which on the day after his inauguration in January 2009 resulted in a Memorandum to kick-start open government plans across the public sector. This meant there was global attention to the topic. So the circumstances were right, there was general momentum, just not very many people yet trying to do something practical.
  • Open data took several years to really materialise as professional activity for me. During those years most time was spent on explaining the topic, weaving the network of people involved across Europe and beyond. I have so many open data slide decks from 2009 and 2010 in my archive. In 2008, 2009 and 2010, I was active in the field but my main professional activities were still elsewhere. In 2009 after my first open data project I wondered out loud if this was a topic I could and wanted to continue in professionally. From early 2011 most of my income came from open data, while the need for building out the network of people involved was still strong. Later, from 2014 or so open data became more local, more regular, shifted to being part of data governance, and now data ethics. The pan-European network evaporated. Nevertheless helping improve European open data legislation has been a crucial element until now, to keep providing a fundament beneath the work.

From those 15 years, what stands out as meaningful results? What did it bring?
This is a hard and easy question at the same time. Hard because ‘meaningful’ can have many definitions. If we take achieving permanent or even institutionalised results as yard stick, two things stand-out. One at the beginning and one at the end of the 15 years.

  • My 2010 report for the Ministry for the Interior on the governance and financing of a national open data portal and facilitating a public consultation on what it would need to do, helped launch the Dutch open government data portal in 2011. A dozen years on, it is a key building block of the Dutch government’s public data infrastructure, and on the verge of taking on a bigger role with the implementation of the European data strategy.
  • At the other end of the timeline is the publication of the EU Implementing Regulation on High Value Data last December, for which I did preparatory research (PDF report), and which compels the entire public sector in Europe to publish a growing list of datasets through APIs for free re-use. Things I wrote about earth observation, environmental and meteorological data are in the law’s Annexes which every public body must comply with by next spring. What’s in that law about geographic data, company data and meteorological data ends more than three decades worth of discussion and court proceedings w.r.t. access to such data.

Talking about meaningful results is also an easy question, especially when not looking for institutional change:

  • Practically, it means my and my now 10 colleagues have an income, which is meaningful within the scope of our personal everyday lives. The director of a company I worked at 25 years ago once said to me when I remarked on the low profits of the company that year ‘well, over 40 families had an income meanwhile, so that’s something.’ I never forgot it. That’s certainly something.
  • There’s the NGO Open State Foundation that directly emerged from the event James, Peter and I organised in 2008. The next event in 2009 was named ‘Hack the Government’ and organised by James and several others who had attended in 2008. It was registered as a non-profit and from 2011 became the Open State Foundation, now a team of eight people still doing impactful work on making Dutch government more transparant. I’ve been the chair of their board for the last 5 years, which is a privilege.
  • Yet the most meaningful results concern people, changes they’ve made, and the shift in attitude they bring to public sector organisations. When you see a light go on in the eyes of someone during a presentation or conversation. Mostly you never learn what happens next. Sometimes you do. Handing out a few free beers (‘Data Drinks’) in Copenhagen making someone say ‘you’re doing more for Danish open data in a month by bringing everyone together than we did in the past years’. An Eastern European national expert seconded to the EC on open data telling me he ultimately came to this job because as a student he heard me speak once at his university and decided he wanted to be involved in the topic. An Irish civil servant who asked me in 2012 about examples I presented of collaboratively making public services with citizens, and at the end of 2019 messaged me it had led to the crowd sourced mapping of Lesotho in Open Street Map over five years to assist the Lesotho Land Registry and Planning Authority in getting good quality maps (embed of paywalled paper on LinkedIn). Someone picking up the phone in support, because I similarly picked up the phone 9 years earlier. None of that is directly a result of my work, it is fully the result of the work of those people themselves. Nothing is ever just one person, it’s always a network. One’s influence is in sustaining and sharing with that network. I happened to be there at some point, in a conversation, in a chance encounter, from which someone took some inspiration. Just as I took some inspiration from a chance encounter in 2008 myself. To me it’s the very best kind of impact when it comes to achieving change.

I’ve plotted the things mentioned above in this image for the most part. As part of trying to map the evolution of my work, inspired by another type of chance encounter with a mind map on the wall of museum.

The evolution of my open data (net)work. Click for larger version.

Bookmarked a message on Mastodon by David Speier

David Speier is a freelance journalist who researches the German far right. In this thread on Mastodon he describes the work they’ve done to check statements from interviews with a former far right member, and to connect them to other source material (photos from events, other people, reports etc.). Of interest to me here is that they used Obsidian to map out people, groups, places, events and occurrences, to verify, to see overlaps and spot blind spots. Nice example of taking something that is inherently text and image based and use Obsidian to ferret out the connections and patterns. There are some topics that currently pop-up in my work in very different projects, and more purposefully teasing out the connections like in this example seems a useful notion.

In einer #Obsidian-Datenbank haben wir Kontaktpersonen, Gruppen, Orte und Ereignisse zusammengeführt. Mehr als 70 umfangreiche Belegdokumente untermauern die einzelnen Aussagen von „Michael“

David Speier

During our visit to the Neues Museum in Neuremberg last week, this mind map stood out to me. Art collector, dealer and curator René Block (1942) made it as a sort of work autobiography for the period 1964-2014.

It stood out to me because it shows the evolution of his work, the connections between major phases and individual projects.

I have a list of a few ‘big themes’ I’ve been interested in, and have worked on. (in that order, as most often my work came out of a side interest during a previous phase, also when I was employed), and over time I’ve recognised the overall topic that carries them all, a fascination with the affordances of digital technology for our agency and how it impacts how we live, learn, work and organise.

In any given moment I can think that most of my activities are a coincidence, that I happened across them on my generally undirected path, but my blog archive has often shown me that I already mentioned topics and ideas much earlier.
There’s an evolution to them, and since I’ve spotted the ‘carrier theme’ I trust that evolution.

I’m sure I can make a mind map like the one above with the different client projects, activities and key events of the past 26 years. Maybe everyone should make such a map for themselves at times, if only to spot the adjacent paths within one’s reach in the evolutionary plane of possibilities. It seems Block made this at the end of his working life when he was 72. What might it have told him if he had drawn or redrawn it at earlier times?

John Caswell writes about the role of conversation, saying "conversation is an art form we’re mostly pretty rubbish at". New tools that employ LLM’s, such as GPT-3 can only be used by those learning to prompt them effectively. Essentially we’re learning to have a conversation with LLMs so that its outputs are usable for the prompter. (As I’m writing this my feedreader updates to show a follow-up post about prompting by John.)

Last August I wrote about articles by Henrik Olaf Karlsson and Matt Webb that discuss prompting as a skill with newly increasing importance.

Prompting to get a certain type of output instrumentalises a conversation partner, which is fine for using LLM’s, but not for conversations with people. In human conversation the prompting is less to ensure output that is useful to the prompter but to assist the other to express themselves as best as they can (meaning usefulness will be a guaranteed side effect if you are interested in your conversational counterparts). In human conversation the other is another conscious actor in the same social system (the conversation) as you are.

John takes the need for us to learn to better prompt LLM’s and asks whether we’ll also learn how to better prompt conversations with other people. That would be great. Many conversations take the form of the listener listening less to the content of what others say and more listening for the right time to jump in with what they themselves want to say. Broadcast driven versus curiosity driven. Me and you, we all do this. Getting consciously better at avoiding that common pattern is a win for all.

In parallel Donald Clark wrote that the race to innovate services on top of LLM’s is on, spurred by OpenAI’s public release of Chat-GPT in November. The race is indeed on, although I wonder whether those getting in the race all have an actual sense of what they’re racing and are racing towards. The generic use of LLM’s currently in the eye of public discussion I think might be less promising than gearing it towards specific contexts. Back in August I mentioned Elicit that helps you kick-off literature search based on a research question for instance. And other niche applications are sure to be interesting too.

The generic models are definitely capable to hallucinate in ways that reinforce our tendency towards anthropomorphism (which needs little reinforcement already). Very very ELIZA. Even if on occasion it creeps you out when Bing’s implementation of GPT declares its love for you and starts suggesting you don’t really love your life partner.

I associated what Karlsson wrote with the way one can interact with one’s personal knowledge management system the way Luhmann described his note cards as a communication partner. Luhmann talks about the value of being surprised by whatever person or system you’re communicating with. (The anthropomorphism kicks in if we based on that surprisal then ascribe intention to the system we’re communicating with).

Being good at prompting is relevant in my work where change in complex environments is often the focus. Getting better at prompting machines may lift all boats.

I wonder if as part of the race that Donald Clark mentions, we will see LLM’s applied as personal tools. Where I feed a more open LLM like BLOOM my blog archive and my notes, running it as a personal instance (for which the full BLOOM model is too big, I know), and then use it to have conversations with myself. Prompting that system to have exchanges about the things I previously wrote down in my own words. With results that phrase things in my own idiom and style. Now that would be very interesting to experiment with. What valuable results and insight progression would it yield? Can I have a salon with myself and my system and/or with perhaps a few others and their systems? What pathways into the uncanny valley will it open up? For instance, is there a way to radicalise (like social media can) yourself by the feedback loops of association between your various notes, notions and follow-up questions/prompts?

An image generate with Stable Diffusion with the prompt “A group of fashionable people having a conversation over coffee in a salon, in the style of an oil on canvas painting”, public domain