Attention and agency
Experimental psychology
Experimental research begins in Wundt’s Leipzig laboratory
Wilhelm Wundt’s Leipzig laboratory helps establish systematic experimental study of mental processes.
AN INTERACTIVE HISTORY
From early psychology to AI, explore the ideas and tools behind how we focus, find meaning and make choices.
Reading the connections
Cognitive psychology is unscatter’s primary scientific reference: the study of mental processes such as attention, memory and thinking. Cognitive ergonomics and human–computer interaction (HCI) connect that research with the design of tools, tasks and interfaces.
These tracks are interconnected histories, rather than competing measures of progress. Cognitive science already includes both psychology and AI. Technology can create new capabilities and introduce new demands; its effects depend on the design, the task and the person.
Language, meaning and motivation add a third perspective: how people describe experience, form goals and understand what matters to them.
Follow the threads
Three connected histories. Select a milestone to explore it, or follow a connection between the histories.
Drag the graph, or scroll or swipe right. Select a milestone to explore it. Key milestone
Dates mark selected milestones, not the origins of whole disciplines. Spacing groups ideas for reading and is not proportional to elapsed time. Lines indicate sequence only. Image credits
1870–1950
Experimental psychology develops alongside behavioural, Gestalt and developmental approaches. Formal computation, information theory and cybernetics emerge as language, meaning and human needs are studied through distinct traditions.
Attention and agency
Experimental research begins in Wundt’s Leipzig laboratory
Wilhelm Wundt’s Leipzig laboratory helps establish systematic experimental study of mental processes.
Attention and agency
William James, The Principles of Psychology
William James describes how attending to something means selecting it from other possible experiences.
Language, meaning and motivation
Hermann Rorschach, Psychodiagnostik
Psychodiagnostik introduced an inkblot-based assessment using ten plates and people’s interpretations of ambiguous forms.
Language, meaning and motivation
Ludwig Wittgenstein, Tractatus Logico-Philosophicus
Ludwig Wittgenstein examines how language can represent the world within a philosophical account of logic.
Attention and agency
Stroop’s color–word interference experiments
J. Ridley Stroop finds that conflicting written colour names interfere with naming the ink colour.
Technology and AI
Turing’s model of a general computing machine
Alan Turing formalises calculation through a machine operating on symbols and examines limits on what can be computed.
Language, meaning and motivation
Abraham Maslow, A Theory of Human Motivation
Abraham Maslow proposes an account of human motivation organized around basic needs.
Technology and AI
McCulloch and Pitts’ logical model of neural networks
McCulloch and Pitts use simplified all-or-none units and propositional logic to model networks of neural activity.
Language, meaning and motivation
Viktor Frankl’s memoir and account of meaning
Viktor Frankl reflects on imprisonment, human response and the search for meaning.
Technology and AI
Norbert Wiener’s study of feedback, control and communication
Norbert Wiener brings feedback and communication into a shared study of control in animals and machines.
Technology and AI
Claude Shannon, A Mathematical Theory of Communication
Claude Shannon develops a mathematical account of information, noise and the capacity of communication channels.
1950–1970
Information-processing models of attention and memory gain influence alongside early AI and interactive computing. Generative grammar, language in use, media and human motivation broaden the questions being explored.
Language, meaning and motivation
Philosophical Investigations
Ludwig Wittgenstein examines language through its uses in shared activities and varied contexts.
Technology and AI
AI research proposal and Dartmouth summer meeting
A proposal by McCarthy, Minsky, Rochester and Shannon names artificial intelligence; the following summer’s Dartmouth project helps establish a research community.
Attention and agency
George Miller, The Magical Number Seven, Plus or Minus Two
George Miller examines limits in particular judgement and immediate-memory tasks, and the role of grouping information.
Language, meaning and motivation
Noam Chomsky, Syntactic Structures
Noam Chomsky models language through rules that generate grammatical sentence structures.
Attention and agency
Broadbent’s filter model, with later attenuation research
Donald Broadbent’s Perception and Communication develops an information-processing account of selective attention.
Technology and AI
J. C. R. Licklider, Man-Computer Symbiosis
J. C. R. Licklider proposes close cooperation between people and computers in Man-Computer Symbiosis.
Language, meaning and motivation
Austin’s How to Do Things with Words
J. L. Austin examines how speaking can perform acts such as promising, requesting and warning.
Technology and AI
Augmentation framework and NLS demonstration
Douglas Engelbart links people, methods, language and tools in an augmentation framework, later demonstrated through NLS.
Language, meaning and motivation
Marshall McLuhan, Understanding Media: The Extensions of Man
Marshall McLuhan argues that the form of a medium changes perception and social life alongside its content.
Technology and AI
E. A. Johnson’s published touch-display research
E. A. Johnson describes a capacitive touch display as an input/output device for computers.
Technology and AI
Weizenbaum’s ELIZA paper
ELIZA uses keyword-triggered decomposition and reassembly rules to produce certain kinds of typed conversation.
Attention and agency
Ulric Neisser’s synthesis of perception, attention and memory
Ulric Neisser brings perception, attention and memory together in an influential account of mental processing.
1970–1990
Working memory, metacognition and cognitive load become design concerns as personal computing and interactive tools develop. Research on language, goals and psychological needs continues alongside these changes.
Attention and agency
Herbert Simon’s design argument about information-rich organisations
Herbert Simon argues that information systems should consider the attention required from their recipients.
Language, meaning and motivation
Deci’s experiments on externally mediated rewards
Edward Deci studies how different external rewards affect people’s interest in activities they already find engaging.
Attention and agency
Baddeley and Hitch’s model; later episodic-buffer refinement
Alan Baddeley and Graham Hitch develop an account of working memory: temporarily holding and using information.
Attention and agency
Tversky and Kahneman’s heuristics-and-biases synthesis
Amos Tversky and Daniel Kahneman describe how useful judgement shortcuts can also produce systematic errors.
Attention and agency
John Flavell’s synthesis of metacognition and cognitive monitoring
John Flavell sets out a framework for metacognition: knowledge and monitoring of one’s own thinking.
Technology and AI
Card, Moran and Newell, The Psychology of Human-Computer Interaction
Card, Moran and Newell apply information-processing psychology to people using interactive computer systems.
Where the histories meet Research application
Information-processing psychology becomes a practical tool for analysing interaction.
Technology and AI
Lisanne Bainbridge, Ironies of Automation
Lisanne Bainbridge examines how automating routine work can leave people with demanding oversight and exception handling.
Language, meaning and motivation
Deci and Ryan’s Intrinsic Motivation and Self-Determination in Human Behavior
Edward Deci and Richard Ryan develop self-determination theory, linking motivation with psychological needs and social conditions.
Technology and AI
Rumelhart, Hinton and Williams’ backpropagation paper
David Rumelhart, Geoffrey Hinton and Ronald Williams show how neural networks can learn internal representations by propagating errors backwards.
Attention and agency
John Sweller’s problem-solving and learning research
John Sweller investigates how some problem-solving demands can compete with the processes needed to learn.
Technology and AI
World Wide Web proposal, implementation and open release
The Web develops at CERN from a 1989 information-management proposal into working software and a 1993 public-domain release.
1990–2010
The Web, platforms and smartphones expand connected everyday life while research examines agency, interruptions and goal pursuit. Flow, psychological needs and meaning in life offer complementary perspectives on experience.
Language, meaning and motivation
Csikszentmihalyi’s synthesis of research on optimal experience
Mihaly Csikszentmihalyi describes flow as deep involvement in an activity that is rewarding in itself.
Attention and agency
Gollwitzer’s implementation-intentions synthesis
Peter Gollwitzer describes plans that link a specified situation to a goal-directed action.
Attention and agency
Albert Bandura’s agentic perspective in social cognitive theory
Albert Bandura describes agency through intentions, forethought, self-regulation and reflection, within social conditions.
Where the histories meet unscatter interpretation
Augmentation and agency offer complementary questions about what a tool helps a person do.
Technology and AI
Facebook’s News Feed feature launch
Facebook introduces News Feed, bringing friends’ activity into a stream on the home page.
Where the histories meet unscatter interpretation
A social feed and an account of agency bring the intentions behind an interaction into view.
Technology and AI
Smartphone interfaces, apps and measured US adoption
Smartphone touch interfaces, an app marketplace and growing ownership form a changing mobile ecosystem.
Attention and agency
Workplace observation and a later controlled interruption study
Gloria Mark, Daniela Gudith and Ulrich Klocke study how interruptions affect work speed and experienced demands.
Attention and agency
Sophie Leroy’s experiments on switching between work tasks
Sophie Leroy studies attention residue: thoughts about one task persisting after a switch to another.
2010–2026
Deep learning, generative systems and agents renew questions about cognitive effort, human control, language understanding, meaning and motivation. Emerging research remains distinct from established historical landmarks.
Technology and AI
Krizhevsky, Sutskever and Hinton’s ImageNet research
Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton train a deep network for large-scale ImageNet classification.
Technology and AI
Covington, Adams and Sargin’s YouTube system paper
YouTube researchers describe deep neural networks for selecting candidate videos and ranking recommendations.
Where the histories meet unscatter interpretation
Opening access and ranking what is available address different sides of information abundance.
Language, meaning and motivation
Martela and Steger distinguish coherence, purpose and significance
Frank Martela and Michael Steger distinguish making sense of life, having direction and experiencing life as valuable.
Attention and agency
Risko and Gilbert’s integrative review
Evan Risko and Sam Gilbert review how actions and external tools can change a task’s cognitive demands.
Technology and AI
Vaswani and colleagues, Attention Is All You Need
Attention Is All You Need introduces a neural-network architecture built around computational attention mechanisms.
Technology and AI
Google Digital Wellbeing and Apple Screen Time introductions
Google and Apple announce controls for viewing device use, managing notifications and setting application limits.
Technology and AI
Amershi and colleagues’ published interaction guidelines
Amershi and colleagues propose 18 guidelines for human-AI interaction, including feedback, correction and user control.
Where the histories meet Research application
Human-AI interaction extends the design question from completing a task to handling uncertainty and mistakes.
Language, meaning and motivation
Bender and Koller’s position paper; Mahowald and colleagues’ later review
Researchers distinguish success with linguistic form from broader questions about meaning, grounding and language use.
Technology and AI
Conversational and multimodal generative AI
OpenAI’s ChatGPT research preview makes a conversational language-model interface public; later releases add multimodal capabilities.
Where the histories meet unscatter interpretation
Delegating routine work can leave people with the difficult task of checking exceptions.
Technology and AI
ChatGPT agent’s announced integration of conversation and tool use
OpenAI introduces ChatGPT agent, combining research and action through a virtual computer and connected tools.
This timeline brings together three perspectives on attention and human agency. The overview maps broader historical developments; the graph explores selected research, ideas and technologies.
| Period | Attention and agency | Technology and AI | Language, meaning and motivation |
|---|---|---|---|
| Early foundations1870–1950 | Experimental psychology becomes established, with structuralist and functional approaches investigating experience, attention, memory and learning. Behaviourism, Gestalt psychology and developmental approaches later investigate learning, perception and the organisation of mental activity through differing methods. [8] | Formal logic, electromechanical tabulation and electrical communication lay groundwork for information processing. Formal computation, early electronic computers, neural models, information theory and cybernetics establish foundations for computing and AI. [11][3][4] | Historical and comparative linguistics develop alongside semantics, semiotics and philosophical accounts of meaning. Structural linguistics and analytic philosophy gain influence, while cultural-historical, needs-based and existential approaches explore human experience. [6][7] |
| The cognitive turn1950–1970 | The cognitive revolution advances information-processing models of attention, memory and reasoning, alongside continuing behavioural and developmental research traditions. [2] | Electronic computing expands as symbolic and neural AI, time-sharing, interactive systems and early touch interfaces develop in research and industry. [4][3] | Generative grammar, psycholinguistics, language-in-use and speech-act approaches expand; humanistic psychology and research on intrinsic motivation gain influence. [6][7] |
| Cognition and interactive tools1970–1990 | Working-memory models, metacognition, cognitive load and social cognitive theory develop, while cognitive neuroscience and alternative accounts of cognition expand. [1] | Personal computing, graphical interfaces and networks spread; expert systems and renewed connectionist learning become influential in computing and AI. [3][4] | Pragmatics, discourse and cognitive linguistics expand; self-efficacy, goal pursuit and self-determination theories develop alongside other approaches to motivation. [6][7] |
| Connected everyday life1990–2010 | Cognitive neuroscience and attention-control research expand; situated and distributed cognition, self-regulation, interruptions and cognitive offloading receive increasing attention. [1] | The Web and open-source software expand networked computing; search, social platforms, smartphones and statistical machine learning gain influence. [5][4] | Usage-based and social approaches complement other linguistic theories; narrative meaning, psychological needs, belonging and meaning-in-life research continue to develop. [6][7] |
| Contemporary AI2010–2026 | Research examines cognition in connected environments and human–AI collaboration, including attention, learning, cognitive effort, reliance and the exercise of control. [1][13] | Deep learning, Transformers and generative AI expand capabilities; recommendation systems, multimodal interfaces and AI agents become prominent in research and deployment. [4][10][12][14] | Language models renew debates about meaning, grounding and understanding, while research on motivation, purpose and social context continues. [9][7] |
The question running through it all

Human agency is our capacity to act intentionally and influence what happens. It depends on our circumstances and the support available to us, as well as our skills.
For unscatter, this raises a practical question: how can technology support people’s own goals and choices?