Responsible Technology: The benefits of a sociotech approach

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Beki Hooper | Research Communications Officer
Ilaria Bonavita | Principal Data Scientist, Innovation & Research

Date: 28 March 2024

“Responsible technology” is a recurring buzzword now. Its core principle is creating tech that is socially responsible. But tech is often created by developers with little expertise in the humanities or social science, so how can we ensure it is socially responsible?

This is where “sociotech” comes in. Sociotech is a developing field where social scientists and data scientists work together, complementing one another’s expertise to create technology that is designed and developed with its societal impacts considered at every step. This means that cutting-edge technological solutions can be created that have as positive an impact on society as possible. Tech designed using the sociotech approach is also created with transparency in mind, such that its risks and limitations are as clearly communicated as its benefits.

Sociotech in action

At Trilateral, we implement the sociotech approach to develop socially responsible tech. We do this by fostering collaboration between data scientists, social scientists, ethicists, data protection experts, commercial teams, and end-users.

In the EU-funded DATA CELLAR project, Trilateral’s data science team, DARSI, is helping develop a platform that supports users, such as members of the public and energy companies, to safely share their energy-use data. The platform also allows its users to forecast and adjust their energy consumption using AI models. The overarching goal is to support cities’ decarbonization by empowering citizens to strategically change their energy consumption habits.

DARSI’s specific role is to make sure that users trust the AI models. This requires both a sociological and technological approach. On the sociological side, the team is working to understand what the concerns of users are, how to mitigate them, and the social implications of the models. On the technological side, the team is conducting a technical assessment of the AI models with a view to understanding their limitations and biases.

To accomplish this, the team are using a multidisciplinary approach and collaborating with social scientists, ethicists, and data protection experts to understand the explainability needs of users, i.e., what users need to know about the AI models to be able to trust the generated recommendations. To do this, the scientists are co-designing surveys, running workshops, and working across data science and software engineering teams to translate user needs into guidance for the development of “explainable AI” features. This is an iterative process with multiple feedback-loops between tech developers, software engineers, social scientists, and the users of the app, with the aim of making the app as transparent, trusted and easy to use as possible.

All tech should be sociotech

All technology impacts society. Because of this, in an ideal world, all tech would be developed using the sociotech approach, where the potential social impacts of the technology are evaluated, assessed and mitigated throughout its research and development. The end-users of the tech – who essentially co-design the product with the developers – should be aware of its impact, too.

At Trilateral, we believe that investing in the sociotech approach is worth the extra effort involved. We have a responsibility to work towards a future where technology is useful, transparent, fair, and responsible.

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