Conditions for Autonomy in the Information Society: Disentangling as a public service

An ambition for a democratic information society is providing services that maintain and even enhance citizens’ mastery and control of their life situation. Analyzing public services from a citizen autonomy perspective can indicate where the service and its IT-systems do not support user autonomy. We analyze a public service and discuss it as a sociomaterial entanglement. Based on our data on citizens’ use of a public service we identify a need to distinguish between entanglements and imbrications and suggest the notion of disentangling in order to characterize the way in which the public service advisors help the citizens. From at a design perspective we look for openings for change and improvement. Different types of entanglements need different types of competencies to address them. We make a distinction between entanglement and imbrication to open up a space for change. Finally, we discuss how the notion of disentangling tax issues can support citizen autonomy

How Can I Help You? A chatbot’s answers to citizens’ information needs

AI-based chatbots are becoming an increasingly common part of the front-line of public services. Through natural language, users can write simple queries to a chatbot which answers with appropriate information. We have investigated how a public chatbot operates in actual practice and how it answers the citizens’ questions about the rules and regulations for welfare benefits. We use the concept of citizens’ information needs to determine the quality of the chatbot’s answers. Information needs are often not formulated from the start as answerable questions. We analyse logs from chat sessions between the chatbot and the citizens, and focus on problems that arise, e.g., that the chatbot gives irrelevant answers or omits important information. The paper shows how the inner workings of the chatbot shapes the answerable questions. We conclude that responsible use of AI (such as chatbots) is a matter of design of the overall service and includes acknowledging that the AI itself can never be responsible

Strengthening Human Autonomy. In the era of autonomous technology

‘Autonomous technologies’ refers to systems that make decisions without explicit human control or interaction. This conceptual paper explores the notion of autonomy by first exploring human autonomy, and then using this understanding to analyze how autonomous technology could or should be modelled. First, we discuss what human autonomy means. We conclude that it is the overall space for action—rather than the degree of control—and the actual choices, or number of choices, that constitutes human autonomy. Based on this, our second discussion leads us to suggest the term datanomous to denote technology that builds on, and is restricted by, its own data when operating autonomously. Our conceptual exploration brings forth a more precise definition of human autonomy and datanomous systems. Finally, we conclude this exploration by suggesting that human autonomy can be strengthened by datanomous technologies, but only if they support the human space for action. It is the purpose of human activity that determines if technology strengthens or weakens human autonomy

Better supporting workers in ML workplaces

This workshop is aimed at bringing together a multidisciplinary group to discuss Machine Learning and its application in the workplace as a practical, everyday work matter. It's our hope this is a step toward helping us design better technology and user experiences to support the accomplishment of that work, while paying attention to workplace context. Despite advancement and investment in Machine Learning (ML) business applications, understanding workers in these work contexts have received little attention. As this category experiences dramatic growth, it's important to better understand the role that workers play, both individually and collaboratively, in a workplace where the output of prediction and machine learning is becoming pervasive. There is a closing window of opportunity to investigate this topic as it proceeds toward ubiquity. CSCW and HCI offer concepts, tools and methodologies to better understand and build for this future