Streamlining Social Decision Making for Improved Internet Standards
6 July 2019
/ protocol-standards
I'm pleased to announce that EPSRC has agreed to support our new
project on "Streamlining Social Decision Making for Improved Internet
Standards"
(EP/S036075/1).
This is
joint work with Matthew Purver, Patrick Healy, Gareth Tyson, and
Ignacio Castro at Queen Mary, University of London, and will run for
three years starting January 2020.
Many decisions in today's world are made through a complex, dynamic
process of interaction and communication between people and teams with
different interests and priorities - so called "distributed
decision-making" (DDM). For example, many businesses work across
multiple geographically dispersed offices and time zones, with teams
specialising in quite diverse areas. Each team may have its own goals
and reward models, which do not necessarily coincide, and may be spread
across multiple organisational units (e.g., different businesses or
governments). Communication may happen via several different modalities
with very different timescales and properties (e.g., email, instant
messenger, and face-to-face meetings).
Unfortunately, although many organisations have started to document
these processes and even make records available, we have no way to
automatically analyse these records. If we did, we could produce tools
to automatically summarise decisions, trace who made them, and why
and how they were made (and why other decisions weren't made).
From a societal standpoint this would help make these processes
more accountable and transparent. We'd also be able to identify
collaborative failures, biases and other problems, and thus help
improve decision-making in future.
This project will develop these urgently required methods, using a
combination of natural language processing and social network analysis.
We will collate, annotate and publicly release the first multimodal
dataset of real-world distributed decision-making. We will devise
techniques to take natural language and semi-structured data to
recognise the dialogue and interaction structures in decision making,
and analyse those structures to produce summaries and evaluate the
efficacy of the decision making process. We will then use the outputs
to inform strategic interventions that can streamline and improve
decision making.
Our methods will be suitably generic to span several domains. However,
the project will focus on one particular global organisation as its
main use case: the Internet Engineering
Task Force (IETF). This is an international forum responsible for
producing Internet protocol standards - formal documents which specify
the languages by which software and hardware "speak" across the
Internet. To produce these documents, extensive international
collaboration is performed - this spans several modalities including
email discussions, collaborative document editing, face-to-face
meetings and teleconferencing. Importantly, all of these modalities
are documented via transparency reports ranging from public email
archives to minutes from meetings. This project has partnered with the
IETF to help model and streamline their decision making process. We
will borrow from their experience, and employ our methods to extract
decision making bottlenecks. We will devise tooling which will provide
advice and proposed interventions to relevant parties within the IETF.
Amongst many other things, we directly benefit the IETF, and the global
Internet standards community, by helping them to uncover biases and
help make important decision processes accountable.