Helsinki Connect Lab currently hosts three research projects: Algorithmic culture, Re-humanizing automated decision-making and Everyday AI.

Algorithmic culture

(Kone Foundation 2019–2022)

The study of algorithmic culture is an array of research approaches applied in pursuit of understanding how algorithmic systems become an integral part of cultural processes. 

How algorithms organise culture? Through the workings of algorithms, lived lives are increasingly datafied and entangled with corporate entities that penetrate human pursuits ever more deeply. Algorithmic systems organise the world, create crucial differentiations, and suggest issues to be addressed. In our research, this process is particularly highlighted through ethical discourses and practices, which we set out to investigate. 

How algorithms influence culture? Algorithmic processes focus on those aspects of lives that can be computationally worked on and managed. The datafied person is perceived primarily as behavioral traits and regularities that can be linked to other traits for identification of groups, making them appear as situational, open-ended, and undefined. In our research, we study the many ways in which computational processes touch upon lives, and shape ideas about us, others, and the wider world.

How algorithms make us feel? Algorithmic culture promotes emotional ambivalence. People want contradictory things from algorithmic systems, and seek both intimacy and detachment. They might oppose intrusive and creepy surveillance based on tracking of their activities, yet expect more relevant real-time analysis and probabilistic predictions that anticipate their desires and plans. In our research, we highlight the pleasures, fears and frustrations of machinic lives.

Re-humanizing automated decision-making

(Academy of Finland 2020–2024)

The project examines how automated decision-making (ADM) relates to the infrastructures of our lives and shapes imaginaries of current and desired worlds. We began our work in 2020 by closely investigating a varied range of ADM cases in Finland, including credit scoring, predictive analytics for social care, chatbots and prisoners training AI. We treat these as exemplary cases that highlight current tensions and reveal actual and potential directions for future ADM developments. By the end of the project, we hope to have a better understanding of how to respond to transformations ushered in by ADM.

By focusing on ADM as a socio-technical process transforming everyday lives, we avoid connotations of machinic intelligence operating without human involvement. By re-humanizing ADM, we refer to the uncovering of human forces at play in automation. We argue that the imagined absence of humans limits our capacities to think of how ADM systems shape and transform everyday lives and societal structures. Re-humanizing ADM establishes the human as a critical and creative agent in human-machine relationships. 

Our exemplary ADM cases trace practices of automation, explore how humans delegate responsibilities to machines, and examine how humans support or intervene in machinic decision-making. By doing so, they aid in unpacking dominant ADM imaginaries and in seeking their alternatives. With the aid of concrete cases, we are better equipped to study how ADM integrates into everyday practices and infrastructures, and to identify individual and societal implications of ADM systems. The final, integrative phase of the project concentrates on thinking creatively how to move beyond the dominant logics of automation.

The project collaborates closely with the non-profit research and advocacy organization AlgorithmWatch (see Automating Society reports 2019 and 2020), the ADM Nordic research network and the international Re-humanizing ADM research network.

Everyday AI

(Foundation for Economic Education 2020–2022)

The project is a collaboration with the strategic consultancy firm Alice Labs and adopts a cross-cultural perspective studying everyday AI in and outside of Europe. We seek to challenge the prevalent narratives and discussions of AI, often focusing on the hopes or dystopias of technologized futures. The project approaches artificial intelligence systems, including voice assistants and recommender systems, as part of a wider ensemble of digital applications, infrastructures, platforms, algorithms, and data, constantly evolving through various human-machine associations. 

By studying the practices, infrastructures, and imaginaries of everyday AI in different contexts, the project aims to uncover benefits and limits of current algorithmic logics. With this approach, the project seeks to challenge prevalent AI discussions and ethics by grounding them on the existing systems and their emotional, social, and political everyday life effects. Instead of focusing on technological, future-oriented solutions, the project proposes suggestions of how AI applications could be better positioned to support individual and societal aims.