Abstract:

This abstract aims at developing a future theoretical and conceptual paper that will argue for the need for algorithmic competences. In so doing, the abstract will outline an argument over three parts. The first part will describe the rationale for algorithmic competence. Algorithmic competence is foremost required because humans and organizations are relationally interacting in a redefined space and social contexts which is shaped by the powers and governance of algorithms and Artificial Intelligence (AI). In other words, algorithms brew stronger agentic action capabilities than before on human perceptions and actions. For example, for several years, large social media platforms like Facebook and YouTube employ algorithms for content moderation to prevent hateful speech and copyright infringement. Also, small and large organizations across the global are replacing traditional services for internal and external communication and work processes with automated tracking systems and chatbot technologies, as an approach to become more “effective”. Consequently, algorithms become an active resource that humans and organizations relationally interact with, which furthermore, learns and adapt from data generated by interaction. This changing context of course raises the important question on what type of competence frameworks are needed. In the second part, the abstract aims at discussing how the outlined context challenges us to rethink traditional approaches used to frame competences such as digital competence. The second part is nevertheless two-folded. A sociomaterial connectivist approach will be developed as a model of explanation to conceive algorithmic competence. Sociomateriality is an Actor-Theory-Network inspired research umbrella agenda which acknowledges that humans and technology are not distinguished by two self-contained entities that shape each other by deterministic effect but are equal and relational. Connectivism is a much-discussed learning theory for the digital age which acknowledges the importance of new technologies and that learning happens in networked and distributed contexts. These approaches are then applied to discuss if notions of digital literacy and digital competence are relevant to understand the outlined context in part one. For example, it can be less need for generic knowledge and skills when interacting relationally with algorithms. In the third part, the abstract will discuss examples and contexts where algorithmic competence might be relevant. Four examples will be examined. Algorithmic competences require advanced and reviewed contextual literacy skills as people will be challenged to use reading and writing skills to relationally interact with a digital technology that needs ongoing requires input. Another case can be the need for an understanding for rules and formal approaches as algorithmic based technologies operate according to operant conditionings and logics. The abstract will also be looking at example where people are challenged to perform advanced problem-solving approaches. Such might be the case when people relationally interact with algorithm IT-system that fail to work and do not provide the necessary outcome for a service to work properly.

Keywords:

Algorithms, Artificial Intelligence, competence, sociomateriality, connectivism.