Advait Sarkar’s “Constructivist Design for Interactive Machine Learning” review

[Illustration IDEO —]
  • Task ownership - IML systems should facilitate end-user tasks and real-world problems, as they can intrinsically motivate users and make them goal-oriented in their resolution. This principle is quite straightforward and necessary to all task-supporting systems;
  • Ill-defined problem - Sarkar affirms that IML systems can facilitate the engagement with the ill-defined nature of model-building and analytics tasks. Ill-defined problems “allow aspects of the problem to be emergent and have users making defensible judgments”. IML systems should assist users with ill-defined questions to make defensible judgments, (e.g., related to model accuracy, overfit, concept acquisition and evolution, etc.), support the user to take reasonable actions in assessing and managing them (e.g., by providing effective data wrangling and labelling techniques), and enabling the negotiation of meaning and understanding (e.g., is this a reasonable accuracy/error, has the model learned the concept, etc.). Sarkar makes interaction design incumbent of providing effective metaphors and techniques for mixing objectivist requirements (e.g., workflow, algorithm and parameter configuration, labelling, etc.) with the open-ended and constructivist nature of the tasks (i.e., model-building and data analytics) to enable the user to form gradually stable notions of learning concepts.
  • Perturbation - Sarkar refers to perturbation as a stimulus that “gently subverts” the user’s expectations or mental model. IML system should use these stimuli to encourage the user to address and explore errors strategically. However, he notes that designers should be aware of “the impact of errors on learners’ motivations, and the potential for the misattribution of poor instructional outcomes”. It’s not clear to the reader whether the cause for misattribution relates to shortcomings in the user’s instructional efforts to train the model, or to shortcomings of the system to enable the users to do so.
  • Reflexivity - IML systems as constructivist environments should support critical awareness and reflection about the process of knowledge building. This includes accounting for knowledge provenance and its manipulation in the historical space. How to design interaction in a IML system for capturing, making accessible and displaying the interaction history? How use and design this to promote critical reflection?
  • Collaboration - how can the design of IML systems incorporate collaborative activities that either to capture the social construction of meaning and collaborative analytics for making sense of the process?
  • Task in context - how should the design of IML systems account for different types of context — social, historical, technical, professional, institutional, etc. —in the process of knowledge construction?
  • Tool mediation - tools can influence and make a transformational impact on the practice and culture they emerge from. The set of assumptions that are built into IML systems — from epistemological, to ontological, to data, through to ideologic— should be made explicit and clear to the user.



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Francisco Bernardo

Francisco Bernardo


Human-centred software engineer; Postdoctoral Research Fellow in Computer Science at University College London