In 1993, researchers from different backgrounds jointly discussed the challenges and benefits in the field of human-computer collaboration. They define collaboration as the process of two or more agents working together to achieve a common goal, while human-machine collaboration is defined as a collaboration involving at least one person and a computing agent. The field of visual analysis is deeply rooted in human-machine collaboration. That is, Visual Analytics attempts to leverage analyst intelligence and machine computing power in collaborations that analyze complex problems. The author has studied thousands of papers from many top conferences such as visual analysis, human-computer interaction and visualization. Provides a comprehensive overview of the latest technologies and provides a general framework based on the authors’ research. The author of this framework calls it “Affordance,” pointing out that there is a heuristic between humans and machines, which exists independently of each other instead of the other.
From reading the article, we learned that the word “Affordance” was first proposed by American psychologist J.J. Gibson. It means that the object and the environment provide the opportunity for action. When the word is used in human-computer collaboration, it means that both human and machine provide partners with opportunities for action. In this two-way relationship, it must be effectively perceived, By using it, we can achieve better human-machine collaboration. In this two-way relationship, people and computers have different abilities.
First of all, this kind of Affordance behaves differently for different human abilities. These different abilities mainly include visual perception, visuospatial thinking, audio linguistic ability, sociocultural awareness, creativity, and domain knowledge. Among them, the first three abilities belong to human strengths, especially visual abilities. Humans have powerful visual perception abilities and can easily distinguish color, shape, and even the texture and motion of the images, human have unparalleled advantages in this aspect of the machine, so it is very reasonable for people to work instead of computers in this respect. The latter three abilities require years of systematic learning and are difficult to fully embed in the computer, so using manual analysis and personnel experience as part of collaboration can greatly improve efficiency.
On the contrary, machines also have the abilities that humans do not have, large-scale data manipulation, collecting and storing large amounts of data, efficient data movement. These capabilities are not possessed by human beings, people cannot complete this series of tasks, and people cannot completely give up subjective thinking and realize unbiased analysis. There are other ways of revelation.
All in all, the author analyzed a large number of papers and finally got a general model, which can lay the foundation for future work, so it can well solve the problems encountered in previous research, and can judge whether it can be based on the “Affordance” idea. Collaborative technologies solve problems, when tasks are assigned to one party, and the ability to develop common languages. And I think that the middle frame is also very reasonable, and it can achieve the mutual cooperation between human and machine, and the inspiration effect. The integration of problems and the convergence of their solutions should also be the direction of development.
What are the disadvantages of the previous framework?
What characteristics of people and computers correspond to the “affordance” of human and computers?
How to make humans and machines play nicely for the extensions mentioned in the article?
How to make humans and machines play nicely for the extensions mentioned in the article?
I think that communication is key to this. When a human and an AI are working to together, the AI must clearly tell the human what part of the job that it is doing and what it needs from the human. The human should also be asked questions by the AI so the AI knows what progress the human has made and what is still left to do. Much like in human-human relationships, I think that communication is key.