Human–computer interaction

Last updated
A computer monitor provides a visual interface between the machine and the user. Computer monitor screen image simulated.jpg
A computer monitor provides a visual interface between the machine and the user.

Human-computer interaction (HCI) is a field based in the design and the use of computer technology, which focuses on the interfaces between people (users) and computers. HCI researchers observe the ways humans interact with computers, and they design technologies that let humans interact with computers in novel ways.

Contents

As a field of research, human-computer interaction is situated at the intersection of computer science, behavioural sciences, design, media studies, and several other fields of study. The term was popularized by Stuart K. Card, Allen Newell, and Thomas P. Moran in their seminal 1983 book, The Psychology of Human-Computer Interaction, although the authors first used the term in 1980 [1] and the first known use was in 1975. [2] The term is intended to convey that, unlike other tools with specific and limited uses, computers have many uses and their use often involves an open-ended dialog between the user and the computer. The notion of dialog likens human-computer interaction to human-to-human interaction, an analogy that is crucial to theoretical considerations in the field. [3] [4]

Introduction

Humans interact with computers in many ways; the interface between humans and computers is crucial to facilitate this interaction. HCI is also sometimes termed human–machine interaction (HMI), man-machine interaction (MMI) or computer-human interaction (CHI). Desktop applications, internet browsers, handheld computers, ERP, and computer kiosks make use of the prevalent graphical user interfaces (GUI) of today. [5] Voice user interfaces (VUI) are used for speech recognition and synthesizing systems, and the emerging multi-modal and Graphical user interfaces (GUI) allow humans to engage with embodied character agents in a way that cannot be achieved with other interface paradigms. The growth in human–computer interaction field has led to increase in the quality of interaction, and in different branching in its history. Instead of designing regular interfaces, the different research branches have had a different focus on the concepts of multimodality [6] rather than unimodality, intelligent adaptive interfaces rather than command/action based ones, and finally active rather than passive interfaces.[ citation needed ]

The Association for Computing Machinery (ACM) defines human-computer interaction as "a discipline that is concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them". [5] An important facet of HCI is user satisfaction (or simply End-User Computing Satisfaction). "Because human-computer interaction studies a human and a machine in communication, it draws from supporting knowledge on both the machine and the human side. On the machine side, techniques in computer graphics, operating systems, programming languages, and development environments are relevant. On the human side, communication theory, graphic and industrial design disciplines, linguistics, social sciences, cognitive psychology, social psychology, and human factors such as computer user satisfaction are relevant. And, of course, engineering and design methods are relevant." [5] Due to the multidisciplinary nature of HCI, people with different backgrounds contribute to its success.

Poorly designed human-machine interfaces can lead to many unexpected problems. A classic example is the Three Mile Island accident, a nuclear meltdown accident, where investigations concluded that the design of the human-machine interface was at least partly responsible for the disaster. [7] [8] [9] Similarly, accidents in aviation have resulted from manufacturers' decisions to use non-standard flight instruments or throttle quadrant layouts: even though the new designs were proposed to be superior in basic human-machine interaction, pilots had already ingrained the "standard" layout and thus the conceptually good idea actually had undesirable results.

Human–computer interface

The human-computer interface can be described as the point of communication between the human user and the computer. The flow of information between the human and computer is defined as the loop of interaction. The loop of interaction has several aspects to it, including:

Goals for computers

Human–computer interaction studies the ways in which humans make—or do not make—use of computational artifacts, systems and infrastructures. Much of the research in this field seeks to improve the human–computer interaction by improving the usability of computer interfaces. [10] How usability is to be precisely understood, how it relates to other social and cultural values and when it is, and when it may not be a desirable property of computer interfaces is increasingly debated. [11] [12]

Much of the research in the field of human-computer interaction takes an interest in:

Visions of what researchers in the field seek to achieve might vary. When pursuing a cognitivist perspective, researchers of HCI may seek to align computer interfaces with the mental model that humans have of their activities. When pursuing a post-cognitivist perspective, researchers of HCI may seek to align computer interfaces with existing social practices or existing sociocultural values.

Researchers in HCI are interested in developing design methodologies, experimenting with devices, prototyping software and hardware systems, exploring interaction paradigms, and developing models and theories of interaction.

Design

Principles

The user interacts directly with hardware for the human input and output such as displays, e.g. through a graphical user interface. The user interacts with the computer over this software interface using the given input and output (I/O) hardware.
Software and hardware are matched so that the processing of the user input is fast enough, and the latency of the computer output is not disruptive to the workflow. Linux kernel INPUT OUPUT evdev gem USB framebuffer.svg
The user interacts directly with hardware for the human input and output such as displays, e.g. through a graphical user interface. The user interacts with the computer over this software interface using the given input and output (I/O) hardware.
Software and hardware are matched so that the processing of the user input is fast enough, and the latency of the computer output is not disruptive to the workflow.

The following experimental design principles are considered, when evaluating a current user interface, or designing a new user interface:

The iterative design process is repeated until a sensible, user-friendly interface is created. [15]

Methodologies

Various different strategies delineating methods for human–PC interaction design have developed since the ascent of the field during the 1980s. Most plan philosophies come from a model for how clients, originators, and specialized frameworks interface. Early techniques treated clients' psychological procedures as unsurprising and quantifiable and urged plan specialists to look at subjective science to establish zones, (for example, memory and consideration) when structuring UIs. Present-day models, in general, center around a steady input and discussion between clients, creators, and specialists and push for specialized frameworks to be folded with the sorts of encounters clients need to have, as opposed to wrapping user experience around a finished framework.

Display designs

Displays are human-made artifacts designed to support the perception of relevant system variables and to facilitate further processing of that information. Before a display is designed, the task that the display is intended to support must be defined (e.g. navigating, controlling, decision making, learning, entertaining, etc.). A user or operator must be able to process whatever information that a system generates and displays; therefore, the information must be displayed according to principles in a manner that will support perception, situation awareness, and understanding.

Thirteen principles of display design

Christopher Wickens et al. defined 13 principles of display design in their book An Introduction to Human Factors Engineering. [19]

These principles of human perception and information processing can be utilized to create an effective display design. A reduction in errors, a reduction in required training time, an increase in the efficiency, and an increase in user satisfaction are a few of the many potential benefits that can be achieved through the utilization of these principles.

Certain principles may not be applicable to different displays or situations. Some principles may also appear to be conflicting, and there is no simple solution to say that one principle is more important than another. The principles may be tailored to a specific design or situation. Striking a functional balance among the principles is critical for an effective design. [20]

Perceptual principles

1. Make displays legible (or audible). A display's legibility is critical and necessary for designing a usable display. If the characters or objects being displayed cannot be discernible, then the operator cannot effectively make use of them.

2. Avoid absolute judgment limits. Do not ask the user to determine the level of a variable on the basis of a single sensory variable (e.g. color, size, loudness). These sensory variables can contain many possible levels.

3. Top-down processing. Signals are likely perceived and interpreted in accordance with what is expected based on a user's experience. If a signal is presented contrary to the user's expectation, more physical evidence of that signal may need to be presented to assure that it is understood correctly.

4. Redundancy gain. If a signal is presented more than once, it is more likely that it will be understood correctly. This can be done by presenting the signal in alternative physical forms (e.g. color and shape, voice and print, etc.), as redundancy does not imply repetition. A traffic light is a good example of redundancy, as color and position are redundant.

5. Similarity causes confusion: Use distinguishable elements. Signals that appear to be similar will likely be confused. The ratio of similar features to different features causes signals to be similar. For example, A423B9 is more similar to A423B8 than 92 is to 93. Unnecessarily similar features should be removed and dissimilar features should be highlighted.

Mental model principles

6. Principle of pictorial realism. A display should look like the variable that it represents (e.g. high temperature on a thermometer shown as a higher vertical level). If there are multiple elements, they can be configured in a manner that looks like they would in the represented environment.

7. Principle of the moving part. Moving elements should move in a pattern and direction compatible with the user's mental model of how it actually moves in the system. For example, the moving element on an altimeter should move upward with increasing altitude.

Principles based on attention

8. Minimizing information access cost or interaction cost. When the user's attention is diverted from one location to another to access necessary information, there is an associated cost in time or effort. A display design should minimize this cost by allowing for frequently accessed sources to be located at the nearest possible position. However, adequate legibility should not be sacrificed to reduce this cost.

9. Proximity compatibility principle. Divided attention between two information sources may be necessary for the completion of one task. These sources must be mentally integrated and are defined to have close mental proximity. Information access costs should be low, which can be achieved in many ways (e.g. proximity, linkage by common colors, patterns, shapes, etc.). However, close display proximity can be harmful by causing too much clutter.

10. Principle of multiple resources. A user can more easily process information across different resources. For example, visual and auditory information can be presented simultaneously rather than presenting all visual or all auditory information.

Memory principles

11. Replace memory with visual information: knowledge in the world. A user should not need to retain important information solely in working memory or retrieve it from long-term memory. A menu, checklist, or another display can aid the user by easing the use of their memory. However, the use of memory may sometimes benefit the user by eliminating the need to reference some type of knowledge in the world (e.g., an expert computer operator would rather use direct commands from memory than refer to a manual). The use of knowledge in a user's head and knowledge in the world must be balanced for an effective design.

12. Principle of predictive aiding. Proactive actions are usually more effective than reactive actions. A display should attempt to eliminate resource-demanding cognitive tasks and replace them with simpler perceptual tasks to reduce the use of the user's mental resources. This will allow the user to focus on current conditions, and to consider possible future conditions. An example of a predictive aid is a road sign displaying the distance to a certain destination.

13. Principle of consistency. Old habits from other displays will easily transfer to support the processing of new displays if they are designed consistently. A user's long-term memory will trigger actions that are expected to be appropriate. A design must accept this fact and utilize consistency among different displays.

Current research

Topics in human-computer interaction include the following:

Social computing

Social computing is basically an interactive and collaborative behavior considered between technology and people. In recent years, there has been an explosion of social science research focusing on interactions as the unit of analysis. As there are a lot of social computing technologies that include blogs, emails, social networking, quick messaging, and various others. Much of this research draws from psychology, social psychology, and sociology. For example, one study found out that people expected a computer with a man's name to cost more than a machine with a woman's name. [21] Other research finds that individuals perceive their interactions with computers more negatively than humans, despite behaving the same way towards these machines. [22]

Knowledge-driven human–computer interaction

In human and computer interactions, a semantic gap usually exists between human and computer's understandings towards mutual behaviors. Ontology, as a formal representation of domain-specific knowledge, can be used to address this problem through solving the semantic ambiguities between the two parties. [23]

Emotions and human-computer interaction

In the interaction of humans and computers, research has studied how computers can detect, process and react to human emotions to develop emotionally intelligent information systems. Researchers have suggested several 'affect-detection channels'. [24] The potential of telling human emotions in an automated and digital fashion lies in improvements to the effectiveness of human-computer interaction. [25] The influence of emotions in human-computer interaction has been studied in fields such as financial decision making using ECG [26] [27] and organisational knowledge sharing using eye tracking and face readers as affect-detection channels. [28] In these fields it has been shown that affect-detection channels have the potential to detect human emotions and that information systems can incorporate the data obtained from affect-detection channels to improve decision models.

Brain–computer interfaces

A brain–computer interface (BCI), is a direct communication pathway between an enhanced or wired brain and an external device. BCI differs from neuromodulation in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions. [29]

Factors of change

Traditionally, computer use was modeled as a human-computer dyad in which the two were connected by a narrow explicit communication channel, such as text-based terminals. Much work has been done to make the interaction between a computing system and a human more reflective of the multidimensional nature of everyday communication. Because of potential issues, human-computer interaction shifted focus beyond the interface to respond to observations as articulated by D. Engelbart: "If ease of use was the only valid criterion, people would stick to tricycles and never try bicycles." [30]

The means by which humans interact with computers continue to evolve rapidly. Human-computer interaction is affected by developments in computing. These forces include:

As of 2010 the future for HCI is expected [31] to include the following characteristics:

Scientific conferences

One of the main conferences for new research in human-computer interaction is the annually held Association for Computing Machinery's (ACM) Conference on Human Factors in Computing Systems , usually referred to by its short name CHI (pronounced kai, or khai). CHI is organized by ACM Special Interest Group on Computer-Human Interaction (SIGCHI). CHI is a large conference, with thousands of attendants, and is quite broad in scope. It is attended by academics, practitioners, and industry people, with company sponsors such as Google, Microsoft, and PayPal.

There are also dozens of other smaller, regional, or specialized HCI-related conferences held around the world each year, including: [32]

See also

Footnotes

  1. Card, Stuart K.; Thomas P. Moran; Allen Newell (July 1980). "The keystroke-level model for user performance time with interactive systems". Communications of the ACM. 23 (7): 396–410. doi:10.1145/358886.358895. S2CID   5918086.
  2. Carlisle, James H. (June 1976). "Evaluating the impact of office automation on top management communication". Proceedings of the June 7-10, 1976, national computer conference and exposition on - AFIPS '76. Proceedings of the June 7–10, 1976, National Computer Conference and Exposition. pp. 611–616. doi:10.1145/1499799.1499885. S2CID   18471644. Use of 'human–computer interaction' appears in references
  3. Suchman, Lucy (1987). Plans and Situated Action. The Problem of Human-Machine Communication. New York, Cambridge: Cambridge University Press. ISBN   9780521337397 . Retrieved 7 March 2015.
  4. Dourish, Paul (2001). Where the Action Is: The Foundations of Embodied Interaction. Cambridge, MA: MIT Press. ISBN   9780262541787.
  5. 1 2 3 Hewett; Baecker; Card; Carey; Gasen; Mantei; Perlman; Strong; Verplank. "ACM SIGCHI Curricula for Human–Computer Interaction". ACM SIGCHI. Archived from the original on 17 August 2014. Retrieved 15 July 2014.
  6. "Multimodality", Wikipedia, 2019-01-02, retrieved 2019-01-03
  7. Ergoweb. "What is Cognitive Ergonomics?". Ergoweb.com. Archived from the original on September 28, 2011. Retrieved August 29, 2011.
  8. "NRC: Backgrounder on the Three Mile Island Accident". Nrc.gov. Retrieved August 29, 2011.
  9. "Report of the President's Commission on the Accident at Three Miles Island" (PDF). 2019-03-14. Archived from the original (PDF) on 2011-04-09. Retrieved 2011-08-17.
  10. Grudin, Jonathan (1992). "Utility and usability: research issues and development contexts". Interacting with Computers. 4 (2): 209–217. doi:10.1016/0953-5438(92)90005-z.
  11. Chalmers, Matthew; Galani, Areti (2004). Seamful interweaving: heterogeneity in the theory and design of interactive systems (PDF). Proceedings of the 5th Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques. pp. 243–252. doi:10.1145/1013115.1013149. ISBN   978-1581137873. S2CID   12500442.
  12. Barkhuus, Louise; Polichar, Valerie E. (2011). "Empowerment through seamfulness: smart phones in everyday life". Personal and Ubiquitous Computing. 15 (6): 629–639. doi: 10.1007/s00779-010-0342-4 .
  13. Rogers, Yvonne (2012). "HCI Theory: Classical, Modern, and Contemporary". Synthesis Lectures on Human-Centered Informatics. 5 (2): 1–129. doi:10.2200/S00418ED1V01Y201205HCI014.
  14. Sengers, Phoebe; Boehner, Kirsten; David, Shay; Joseph, Kaye (2005). Reflective Design. CC '05 Proceedings of the 4th Decennial Conference on Critical Computing: Between Sense and Sensibility. 5. pp. 49–58. doi:10.1145/1094562.1094569. ISBN   978-1595932037. S2CID   9029682.
  15. Green, Paul (2008). Iterative Design. Lecture presented in Industrial and Operations Engineering 436 (Human Factors in Computer Systems, University of Michigan, Ann Arbor, MI, February 4, 2008.
  16. Kaptelinin, Victor (2012): Activity Theory. In: Soegaard, Mads and Dam, Rikke Friis (eds.). "Encyclopedia of Human-Computer Interaction". The Interaction-Design.org Foundation. Available online at http://www.interaction-design.org/encyclopedia/activity_theory.html
  17. "The Case for HCI Design Patterns".
  18. Friedman, B., Kahn Jr, P. H., Borning, A., & Kahn, P. H. (2006). Value Sensitive Design and information systems. Human-Computer Interaction and Management Information Systems: Foundations. ME Sharpe, New York, 348–372.
  19. Wickens, Christopher D., John D. Lee, Yili Liu, and Sallie E. Gordon Becker. An Introduction to Human Factors Engineering. Second ed. Upper Saddle River, NJ: Pearson Prentice Hall, 2004. 185–193.
  20. Brown, C. Marlin. Human-Computer Interface Design Guidelines. Intellect Books, 1998. 2–3.
  21. Posard, Marek (2014). "Status processes in human-computer interactions: Does gender matter?". Computers in Human Behavior. 37 (37): 189–195. doi:10.1016/j.chb.2014.04.025.
  22. Posard, Marek; Rinderknecht, R. Gordon (2015). "Do people like working with computers more than human beings?". Computers in Human Behavior. 51: 232–238. doi: 10.1016/j.chb.2015.04.057 .
  23. Dong, Hai; Hussain, Farookh; Elizabeth, Chang (2010). "A human-centered semantic service platform for the digital ecosystems environment". World Wide Web. 13 (1–2): 75–103. doi:10.1007/s11280-009-0081-5. hdl: 20.500.11937/29660 . S2CID   10746264.
  24. Calvo, R., & D'Mello S. (2010). "Affect detection: An interdisciplinary review of models, methods, and their applications". IEEE Transactions on Affective Computing. 1 (1): 18–37. doi:10.1109/T-AFFC.2010.1. S2CID   753606.CS1 maint: multiple names: authors list (link)
  25. Cowie, R., Douglas-Cowie, E., Tsapatsoulis, N., Votsis, G., Kollias, S., Fellenz, W., & Taylor, J. G. (2001). "Emotion recognition in human-computer interaction". IEEE Signal Processing Magazine. 18 (1): 32–80. Bibcode:2001ISPM...18...32C. doi:10.1109/79.911197.CS1 maint: multiple names: authors list (link)
  26. Astor, Philipp J.; Adam, Marc T. P.; Jerčić, Petar; Schaaff, Kristina; Weinhardt, Christof (December 2013). "Integrating Biosignals into Information Systems: A NeuroIS Tool for Improving Emotion Regulation". Journal of Management Information Systems. 30 (3): 247–278. doi:10.2753/mis0742-1222300309. ISSN   0742-1222. S2CID   42644671.
  27. Adam, Marc T. P.; Krämer, Jan; Weinhardt, Christof (December 2012). "Excitement Up! Price Down! Measuring Emotions in Dutch Auctions". International Journal of Electronic Commerce. 17 (2): 7–40. doi:10.2753/jec1086-4415170201. ISSN   1086-4415. S2CID   31932319.
  28. Fehrenbacher, Dennis D (2017). "Affect Infusion and Detection through Faces in Computer-mediated Knowledge-sharing Decisions". Journal of the Association for Information Systems. 18 (10): 703–726. doi:10.17705/1jais.00470. ISSN   1536-9323.
  29. Krucoff, Max O.; Rahimpour, Shervin; Slutzky, Marc W.; Edgerton, V. Reggie; Turner, Dennis A. (2016-01-01). "Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation". Frontiers in Neuroscience. 10: 584. doi:10.3389/fnins.2016.00584. PMC   5186786 . PMID   28082858.
  30. Fischer, Gerhard (1 May 2000). "User Modeling in Human-Computer Interaction". User Modeling and User-Adapted Interaction. 11 (1–2): 65–86. doi: 10.1023/A:1011145532042 .
  31. SINHA, Gaurav; SHAHI, Rahul; SHANKAR, Mani. Human-Computer Interaction. In: Emerging Trends in Engineering and Technology (ICETET), 2010 3rd International Conference on. IEEE, 2010. p. 1-4.
  32. "Conference Search: hci". www.confsearch.org.

Further reading

Academic overviews of the field
Historically important classic[ citation needed ]
Overviews of history of the field
Social science and HCI
Academic journals
Collection of papers
Treatments by one or few authors, often aimed at a more general audience
Textbooks

Related Research Articles

The term computer-supported cooperative work (CSCW) was first coined by Irene Greif and Paul M. Cashman in 1984, at a workshop attended by individuals interested in using technology to support people in their work. At about this same time, in 1987, Dr. Charles Findley presented the concept of Collaborative Learning-Work. According to Carstensen and Schmidt, CSCW addresses "how collaborative activities and their coordination can be supported by means of computer systems". On the one hand, many authors consider that CSCW and groupware are synonyms. On the other hand, different authors claim that while groupware refers to real computer-based systems, CSCW focuses on the study of tools and techniques of groupware as well as their psychological, social, and organizational effects. The definition of Wilson (1991) expresses the difference between these two concepts:

CSCW [is] a generic term, which combines the understanding of the way people work in groups with the enabling technologies of computer networking, and associated hardware, software, services and techniques.

WIMP (computing)

In human–computer interaction, WIMP stands for "windows, icons, menus, pointer", denoting a style of interaction using these elements of the user interface. Other expansions are sometimes used, such as substituting "mouse" and "mice" for menus, or "pull-down menu" and "pointing" for pointer.

Interactivity

Across the many fields concerned with interactivity, including information science, computer science, human-computer interaction, communication, and industrial design, there is little agreement over the meaning of the term "interactivity", but most definitions are related to interaction between users and computers and other machines through a user interface. Interactivity can however also refer to interaction between people. It nevertheless usually refers to interaction between people and computers – and sometimes to interaction between computers – through software, hardware, and networks.

The following outline is provided as an overview of and topical guide to human–computer interaction:

Human-centered computing (HCC) studies the design, development, and deployment of mixed-initiative human-computer systems. It is emerged from the convergence of multiple disciplines that are concerned both with understanding human beings and with the design of computational artifacts. Human-centered computing is closely related to human-computer interaction and information science. Human-centered computing is usually concerned with systems and practices of technology use while human-computer interaction is more focused on ergonomics and the usability of computing artifacts and information science is focused on practices surrounding the collection, manipulation, and use of information.

Ben Shneiderman

Ben Shneiderman is an American computer scientist, a Distinguished University Professor in the University of Maryland Department of Computer Science, which is part of the University of Maryland College of Computer, Mathematical, and Natural Sciences at the University of Maryland, College Park, and the founding director (1983-2000) of the University of Maryland Human-Computer Interaction Lab. He conducted fundamental research in the field of human–computer interaction, developing new ideas, methods, and tools such as the direct manipulation interface, and his eight rules of design.

Multimodal interaction provides the user with multiple modes of interacting with a system. A multimodal interface provides several distinct tools for input and output of data.

In artificial intelligence, an embodied agent, also sometimes referred to as an interface agent, is an intelligent agent that interacts with the environment through a physical body within that environment. Agents that are represented graphically with a body, for example a human or a cartoon animal, are also called embodied agents, although they have only virtual, not physical, embodiment. A branch of artificial intelligence focuses on empowering such agents to interact autonomously with human beings and the environment. Mobile robots are one example of physically embodied agents; Ananova and Microsoft Agent are examples of graphically embodied agents. Embodied conversational agents are embodied agents that are capable of engaging in conversation with one another and with humans employing the same verbal and nonverbal means that humans do.

Andrew Sears is an American computer scientist. He is Professor and Dean of the College of Information Sciences and Technology (IST) at The Pennsylvania State University.

Gender HCI is a subfield of human-computer interaction that focuses on the design and evaluation of interactive systems for humans. The specific emphasis in gender HCI is on variations in how people of different genders interact with computers.

Fabio Paternò is Research Director and Head of the Laboratory on Human Interfaces in Information Systems at Istituto di Scienza e Tecnologie dell'Informazione, Consiglio Nazionale delle Ricerche in Pisa, Italy.

Robert E. Kraut American social psychologist

Robert E. Kraut is an American social psychologist who studies human-computer interaction, online communities, internet use, group coordination, computers in organizations, and the role of visual elements in interpersonal communication. He is a Herbert Simon Professor of Human-computer Interaction at the Human-Computer Interaction Institute at Carnegie Mellon University.

DiamondTouch Multiple person interface device

The DiamondTouch table is a multi-touch, interactive PC interface product from Circle Twelve Inc. It is a human interface device that has the capability of allowing multiple people to interact simultaneously while identifying which person is touching where. The technology was originally developed at Mitsubishi Electric Research Laboratories (MERL) in 2001 and later licensed to Circle Twelve Inc in 2008. The DiamondTouch table is used to facilitate face-to-face collaboration, brainstorming, and decision-making, and users include construction management company Parsons Brinckerhoff, the Methodist Hospital, and the US National Geospatial-Intelligence Agency (NGA).

Animal-computer interaction (ACI) is a field of research for the design and use of technology with, for and by animals covering different kinds of animals from wildlife to domesticated animals in different roles. It emerged from, and was heavily influenced by, the discipline of human-computer interaction (HCI). As the field expanded, it has become increasingly multi-disciplinary, incorporating techniques and research from disciplines such as Artificial Intelligence (AI), Requirements Engineering (RE), and Veterinary Science.

Feminist HCI is a subfield of human-computer interaction that focuses on helping the field of HCI build interactions that pay attention to gender, equity, and social justice in research and in the design process.

Wendy Mackay Computer Scientist

Wendy Elizabeth Mackay is a Canadian researcher specializing in human-computer interaction. She has served in all of the roles on the SIGCHI committee, including Chair. She is a member of the CHI Academy and a recipient of a European Research Council Advanced grant. She has been a visiting professor in Stanford University between 2010 and 2012, and received the ACM SIGCHI Lifetime Service Award in 2014.

Yves Guiard is a French cognitive neuroscientist and researcher best known for his work in human laterality and stimulus-response compatibility in the field of human-computer interaction. He is the director of research at French National Center for Scientific Research and a member of CHI Academy since 2016. He is also an associate editor of ACM Transactions on Computer-Human Interaction and member of the advisory council of the International Association for the Study of Attention and Performance.

Joëlle Coutaz is a French computer scientist, specializing in human-computer interaction (HCI). Her career includes research in the fields of operating systems and HCI, as well as being a professor at the University of Grenoble. Coutaz is considered a pioneer in HCI in France, and in 2007, she was awarded membership to SIGCHI. She was also involved in organizing CHI conferences and was a member on the editorial board of ACM Transactions on Computer-Human Interaction. She has authored over 130 publications, including two books, in the domain of human-computer interaction.

Susanne Bødker is a Danish computer scientist known for her contributions to human–computer interaction, computer-supported cooperative work, and participatory design, including the introduction of activity theory to human–computer interaction. She is a professor of computer science at Aarhus University, and a member of the CHI Academy.

Shumin Zhai Human-computer interaction research scientist

Shumin Zhai is an American-Canadian-Chinese human-computer interaction (HCI) research scientist and inventor. He is known for his research specifically on input devices and interaction methods, swipe-gesture-based touchscreen keyboards, eye-tracking interfaces, and models of human performance in human-computer interaction. His studies have contributed to both foundational models and understandings of HCI and practical user interface designs and flagship products. He previously worked at IBM where he invented the ShapeWriter text entry method for smartphones, which is a predecessor to the modern Swype keyboard. Dr. Zhai's publications have won the ACM UIST Lasting Impact Award and the IEEE Computer Society Best Paper Award, among others, and he is most known for his research specifically on input devices and interaction methods, swipe-gesture-based touchscreen keyboards, eye-tracking interfaces, and models of human performance in human-computer interaction. Dr. Zhai is currently a Principal Scientist at Google where he leads and directs research, design, and development of human-device input methods and haptics systems.