What does it mean to adopt a sociotech approach to design and develop AI solutions aimed at tackling complex societal challenges?
For Baxter and Sommerville, this means that the “underlying premise of socio-technical thinking is that systems design should be a process that takes into account both social and technical factors that influence the functionality and usage of computer-based systems” leading to systems that are “more acceptable to end-users and deliver better value to stakeholders”.
Within Trilateral Research’s practice, a sociotechnical approach involves bringing together our experts in data science, social science, data engineering, data protection, ethics, software development, cloud engineering and UI/UX to understand and work together in a co-design manner. The goal is to develop suitable and explainable AI solutions aimed at tackling complex social challenges through leveraging social theory, data science and the cloud to support data-driven decision support.
Bringing together so many disciplines into a central space to work through and innovate is complex. It takes a patient, open and collaborative co-design approach to problem-solving, theoretical design and research and development.
In his book ‘Data Theory’, Simon Lindgren points to the need to bring together information and its interpretation to derive meaningful insights. For Lindgren, “this is where sociology and social theory come into the picture, as they offer a wide range of conceptual frameworks, theories, that can aid in analysis and understanding of the large amounts and many forms of social data that are proliferated in today’s world”.
Within an interdisciplinary co-design approach, everyone must have a say and provide their input to achieve the objectives being sought. For us, this goes beyond involving the Trilateral ‘crew’; when we take our co-design approach a step further, we must engage and design our solutions around the needs of end-users and those whom our solutions aim to help.
Sociotech in practice
As an example, if we take the development of the HAMOC application funded under the Defence and Security Accelerator (DASA) to develop a human security analysis capability, we can see just how complex a sociotech co-design approach is to successful innovation.
For HAMOC this involved an interdisciplinary team from Trilateral – along with our in-house domain experts with 30+ years of experience working in defence, as well as a co-design partnership with representatives from the MOD and our technical partner at DSTL. So no, our data scientists didn’t just get to go explore and show us the insights from data in pretty visualisations and pins on a map…as a team, we achieved so much more!
A snapshot of some of the sociotech work included, but is certainly not limited to:
- The social scientists and domain experts identified and developed the human security conceptual parameters (e.g., through the 1994 UNDP human development report) and Defence framework (e.g., Defence Intelligence Doctrine) for the application to be designed around and to aid and inform the UI/UX design of the frontend of the application in close collaboration with our designers, data scientists, data engineers and developers.
- The social scientists and data scientists and data engineers worked together to develop a model on which to develop natural language processing insights to extract human security events from text from military intelligence doctrine.
- The ethics, social scientists, domain experts, data scientists, data engineers, designers and developers took steps to design frontend features surrounding the reliability, validity and usability of data to overcome some of the problems in measuring human security such as bias or data availability.
- Platform testing included not just technical performance, but also the sociological meaningfulness of outputs to the Human Security environment, especially in terms of what they explain.
Every design decision required multiple inputs to ensure our focus on delivering a sociotechnical application.
Doing sociotech requires the brightest committed minds that are able and accustomed to working in a manner that is grounded in rigorous approaches to responsible research and innovation. This may sound complicated, but it’s worth it! Such an approach results in meaningful and acceptable outputs for users that can be readily deployed. It’s what we do and what we love to do!
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