Guidelines for Human-AI Interaction
In this paper, the authors focus on the problem that human-AI interaction researches need the light of advances in this growing technology. According to this, the authors propose 18 generally applicable design guidelines for the designs and studies for human-AI interactions. Based on a 49-participant involved user study, writers test the validation of these guidelines. These 18 guidelines are: 1) make clear what the system can do, 2) make clear how well the system can do what it can do, 3) time services based on context, 4) show contextually relevant information, 5) match relevant social norms, 6) mitigate social biases, 7) support efficient invocation, 8) support efficient dismissal, 9) support efficient correction, 10) scope services when in doubt, 11) make clear why the system did what it did, 12) remember recent interaction, 13) learn from user behavior, 14) update and adapt cautiously 15) encourage granular feedback, 16) convey the consequences of user actions, 17) provide global controls and 18) Notify users about changes. After the user study,
After reading this paper, I am kind of surprised that authors can purpose 18 guidelines for human-AI interaction designing. I am most interested in the category of “During interaction”. This discussion focus factors about time, context, personal data and social norms. In my opinion, providing users with specific services that can assist their interactions should also be considered in this part. For example, accessible and assistant. In addition, considering social norms is a great idea. Individuals who use the AI system have many kinds of background, abilities, and ethics. We cannot treat every person with the same design of the applications and systems. Allowing users to design their preferred user interfaces, features, and functions in one general system is a promising but challenging research question. I think this is a promising topic in the future. At present, many applications and systems allow users to customize their own features with the provided default settings. Players can design their own models for games, like the Steam platform. For Google Chrome, users can design their own theme based on their motivations and goals. I believe this feature can be achieved by multiple human-AI interaction systems later.
Among these 18 different guidelines, I notice that an AI application does not have to require all these guidelines. Hence, do some of the guidelines have high majorities than others? Or, in the process of designing, researchers should treat each of them equally?
In your opinion, which guidelines do you consider are more important and will focus on them in the future? Or which guidelines you might have ignored in the previous researches?
In this paper, the authors mentioned the tradeoff between generality and specialization. How do you think to solve this problem?
Will these guidelines become useless due to the increase of specialization in various kinds of applications and systems in the future?
“Will these guidelines become useless due to the increase of specialization in various kinds of applications and systems in the future?” – That’s an interesting question. It’s hard to imagine considering that most of these principles are pretty fundamental and can generalize well. Also, if we consider historical context, a lot of these principles actually have roots in the ‘Principles of Mixed-Initiatives User Interfaces’ paper, which was published 20 years back and they still hold true today. Moreover, these guidelines, or versions of it, are being adopted by major tech companies like Google with their guidebook https://pair.withgoogle.com/ or Apple with their guidelines. I am guessing these guidelines will implicitly dictate how apps are gonna be designed in the years to come and so it’s hard to see them becoming useless. Even if they do, the updated version of these guidelines may still share the same roots.
“do some of the guidelines have high majorities than others? Or, in the process of designing, researchers should treat each of them equally?” – I am not sure about the global applicability of such guidelines. As AI evolves, the guidelines will evolve too. Hence, I believe its not the guidelines that are major or minor but rather a subset of them are applicable to a particular feature. For example, in a recommender system, the user doesn’t necessarily need to know the process of getting the recommendations but for image detection or medical imaging, the users need to be absolutely sure of the algorithm’s shortcomings.