The author proposed that currently much developers and researchers are too optimistic as they do not see human labor under automated services. This kind of long-standing focus on only the AI side results in the lack of researches about the interaction between AI and humans. The author proposed that it is better to let AI enrich human’s intellectual work rather than let AI replace human. The author introduced interactive systems in three areas, which are data wrangling, exploratory analysis, and natural language translation. The author integrated integrate proactive computational support into these systems and described the performance of these hybrid systems using predictive models. In conclusion, he proposed that only a fluent interleaving of both automated suggestions and direct manipulation can enable more productive and flexible work.
Reflections:
As a student who had only one class about human-computer interaction before attending this course, I kept the wrong view that we should focus on the AI side of the data analytic side. Instead, there is a huge improvement in user experience if the system has a good design of human-computer interaction. The author of this paper reminds me of the importance of the interface and how AI can do for human works.
It is not correct to let a human do what they can do, let AI do want they can do and combine both sides of work simply. Instead, the interaction between humans and AI can be designed to leverage the strength of both sides and make the whole system have better performance. I like the idea about let AI to suggest for human when human is dealing with some work. This can let the results to be highly accurate and let the processing speed to decrease. Human does not need to search for information online and AI does not need to predict what is human thinking. They can just cooperate to let humans ensure accuracy while AI provides quick background searching and complex calculation. They reached harmony in the designed system.
Additionally, the author mentioned that it is not always efficient to let AI support human. For some simple job, AI can complete on itself. In these cases, it would be more efficient to let AI do the task on itself without asking advice from human workers. For a simple job, for example, some simple labeling, even human gives no advice, AI can still reach high accuracy. If we let AI wait for human response, time would be wasted. As a result, a fluent interleaving of both automated suggestions and direct manipulation can reach the highest performance of a system. We should consider both suggestion and automatic operations in our system designs.
Questions:
The author proposed that systems should have a fluent interleaving of both automated suggestions and direct manipulation. Is there any situation in which AI assistants would decrease the performance of humans and humans should complete the tasks on themselves?
What’re the criteria for determining whether the AI should make suggestions to human or it should direct manipulation?
Compared with letting humans correct AI results, what’re the advantages of letting AI suggest humans?
Hi, For question 2. I think it depends on how well the machine can complete a task. If the machine can do a good job without people, it is very feasible for the machine to complete the task directly, and it can save a lot of human resources. But when the machine can’t finish well, it can improve efficiency by making suggestion.