Like @katejsim, I also find interesting co-occurrences when filtering the graph to k=4. For those unfamiliar with our tool, Graph Ryder, this means that we are looking the connections between codes that have been mentioned together by community members at least 4 times.
Let’s start with an overview of the conversation as a whole at k=4. This is everything that everyone is talking about across the NGI Forum.
We can see some broad themes emerging as we look at the graph as a whole. Central nodes include codes like
personal data, connected to codes like
business model and
advertising. From this
personal data node, we get an idea of some of the issues community members are wrestling with.
If we follow the
personal data code to
business model to the left and
trade-off to the right, we can see some very interesting debates emerging.
It’s clear even at this level that the use of
personal data sets up a
trade-off for a lot of participants. In
decision-making about sharing or protecting
personal data, community members are
considering larger context around its use and
assessing the impact of the trade-off.
cost is also a key consideration.
Personal data also connects strongly, if we move south, to
agency, in a highly illustrative cluster with
user experience. We see, again, trade-offs set up – between
user control and
user experience, raising questions about what one gets when one gives up
personal data, and how much control is possible. Community members also raise questions about the effort and
cost of controlling personal data in the current environment, when responsibility is highly individualised (
individualising responsibility is a salient code at a lower level of co-occurrences).
Moving these abstract concepts into concrete examples, we can look at the left of
personal data to see these applied to the specific case of advertising and
personal data for
advertising creates revenue for
journalism, without which there is an issue of
information quality. But there are other potential
business models to be considered outside of the selling of
personal data, like
subscription models. We can also see that community members understand that
"free" access to services is not always actually free, since the
catch is the selling of their
personal data. Yet
journalism, without a sustainable
business model, is facing some serious
funding issues. The fundamental problem is about
assigning value to things like journalism, which opens to the question of how to fund it without shady
advertising practices. These are all strongly connected to the question of
ethics, a key concern in
journalism writ large which is closely tied to ethical considerations around advertising, monetisation, personal data, and how to construct a sustainable business model.
Following the graph north, we can see
business model and
advertising also connected to
big tech. A series of issues around
big tech have been outlined by the community – the need for
regulation, the way it perpetuates
facebook is a key example of
big tech emerge around
open source, which has an interesting network built around it – questions of
'empowerment' (does open source empower users?), the need for
training to use open source tools, and the question of whether using open source tools opens one up to increased
risk. As a
technological solution, open source also allows community members to
imagine alternatives to the status quo. It also connects to
'human-centred design', as community members ask what exactly it would look like to design digital tools with and for humans.
open source also strongly connects with
privacy, an extremely central node in the conversation.
privacy connects back to
personal data, and we see an illustrative network of privacy concerns articulated by the community: around
smart cities and
contact tracing, and as aforementioned,
decision-making. A salient theme is the question of how to weigh up privacy trade-offs, in order to make optimal decisions about one’s own data privacy. What does it
cost? There is
uncertainty around how extensive
surveillance is, and a
distrust of the information that one is given about these technologies, which makes making quality decisions about these issues difficult for community members.
Also connected to ‘trade off’ and
assessing impact is a series of environmental concerns. Moving to the bottom-right of the graph, questions of
resource consumption and
energy are tied to
environmental sustainability and
cost, showing us a snapshot of the rich conversation emerging on platform around technology, the internet, and environmental sustainability.
Returning to the topic of trust in technology, we see an interesting web of concepts emerging around
artificial intelligence. AI is connected to
big tech. It’s also connected to issues of
oversight, as well as
effectiveness. This cluster of codes tells us that there is an ongoing conversation around what kinds of oversight of AI might a) be actually effective, rather than performative and b) lead to increased transparency of AI and
algorithms. We also see these connected to more concrete questions on what it takes to make these technological infrastructures: their
production cycle and the
raw materials needed.
@katejsim gives a great analysis of
co-working in the post above. I’d like to draw attention to the connections between the internet and online life and the concrete effects those have on life offline. We can see that
covid-19 has lead to an increase of
working remotely, perhaps unsurprisingly. But it has also lead to a shift of living conditions, particularly
co-working, totally reshaping the division of
public space and
private space, leading community members to
build alternatives and
organising space differently.
Part of the impact of
covid-19 has been a
shift to online and a corresponding
sense of loss, of
public space, of
social engagement, with
mental health impacts. One way of addressing this has been to seek a
sense of community by reworking offline spaces to increase
social interaction. For
universities, this is especially pressing.
A code I want to keep tracking is of
defining terminology, as NGI community members try to cut to the heart of some of the bigger, buzzier issues in tech and the internet.
The code is meaningfully connected to
nuancing the debate, telling us something about how to move forward and tackle the thornier, more challenging issues in this area in meaningful ways. I’m excited to keep seeing how these conversations unfold.