There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

/pdf/using-social-and-behavioural-science-to-support-covid-19-25vr5kyvxt.pdf

Using social and behavioural science to support COVID-19 pandemic response.

Traditional approaches to human information processing tend to deal with perception and action planning in isolation, so that an adequate account of the perception-action interface is still missing On the perceptual side, the dominant cognitive view largely underestimates, and thus fails to account for, the impact of action-related processes on both the processing of perceptual information and on perceptual learning On the action side, most approaches conceive of action planning as a mere continuation of stimulus processing, thus failing to account for the goal-directedness of even the simplest reaction in an experimental task We propose a new framework for a more adequate theoretical treatment of perception and action planning, in which perceptual contents and action plans are coded in a common representational medium by feature codes with distal reference Perceived events (perceptions) and to-be-produced events (actions) are equally represented by integrated, task-tuned networks of feature codes – cognitive structures we call event codes We give an overview of evidence from a wide variety of empirical domains, such as spatial stimulus-response compatibility, sensorimotor synchronization, and ideomotor action, showing that our main assumptions are well supported by the data

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0140525X01000103

The Theory of Event Coding (TEC): a framework for perception and action planning.

Doing Qualitative Research

In conventional software development, the boundary between user experience design and engineering is well defined: designers create specifications based on end-user needs, then engineers build to those specifications. However, AI application design challenges this “separation of concerns (SoC).” Our analysis of Human-Centered AI (HAI) guidelines shows that design extends beyond the user interface into the design of AI sub-components and training data, thus ‘puncturing’ this separation. We interviewed 21 professionals (UX researchers, AI engineers, data scientists, and managers) across 14 organizations to understand how they operationalize HAI guidelines in practice. We find that hidden information encapsulated by SoC challenges collaboration across design and engineering concerns. Practitioners describe inventing leaky abstractions—ad-hoc representations exposing low-level design and implementation details—to share information across expertise boundaries. We identify how leaky abstractions are employed to collaborate at the AI-UX boundary and formalize the process of creating and using leaky abstractions.

Human-AI Guidelines in Practice: The Power of Leaky Abstractions in Cross-Disciplinary Teams

Design Heuristics: A Tool for Innovation in Product Design

Extending design heuristics from mechanical engineering to a biomedical projects course

The central insight that led to the field of Case-Based Reasoning was that human memory appears to be organized around individual episodic experiences (Schank, 1982; Kolodner, 1980). At the time, there were few empirical findings available that shed light on how humans encode, retrieve, and reason about complex experiences. In the twenty years since then, researchers in cognitive science have investigated both everyday autobiographical memory and the performance of human experts who process many individual cases within a domain, such as medical diagnosis. The results identify some important features of the case-based reasoning process in humans, and suggest new approaches to building computational models that may display similar capabilities.

Cased-Based reasoning by human experts

Western cultures focus on salient objects and use categorization for purposes of organizing the environment (an analytic view), whereas, East Asians cultures focus more holistically on relationship...

Colleen M. Seifert

Papers

Human-AI Guidelines in Practice: The Power of Leaky Abstractions in Cross-Disciplinary Teams

Design Heuristics: A Tool for Innovation in Product Design

Extending design heuristics from mechanical engineering to a biomedical projects course

Cased-Based reasoning by human experts

Cultural Differences in Aesthetic Preferences: Does Product-to-Context Match Matter?