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Dec 10, 2019

AI in focus: Positive experiences in human-AI interaction

It's the talk of the day: artificial intelligence (AI). If you want to join in the conversations, you shouldn't miss our series "AI in focus" on this groundbreaking topic. In the fourth part, Michael Burmester looks into the question of how UX designers can create positive human-AI interaction. Which existing methods and principles can be remodeled to fit this new technology? And where do we need new tools and methods?

UX is not the same as usability. If you want to design a product with a positive UX you have to take a different approach than somebody who optimizes its usability. Before looking into AI, we will therefore recollect what we have already discussed about the core aspects of UX.

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Positive emotions

In contrast to usability, UX doesn’t deal with helping the users reach their goals effectively and efficiently. UX deals with positive emotions. Every human being has psychological needs such as striving for autonomy, competence and relatedness. And this isn’t based on specific requirements or necessities – these needs are much more basic. If they are fulfilled when using a product, positive emotions and ultimately positive experiences develop. Good usability can prevent negative emotions but doesn’t provide positive experiences.

Positive experiences

In general, technology is considered as a tool to solve a particular problem a user has. When designing products with a positive UX, the goal is to provide positive experiences for the user of the product. A GPS device, for example, unerringly guides us through an unknown town – it solves a specific problem. Geocaching, however, doesn’t. It is all about fun and the joy of searching and finding hidden items using GPS.

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UX Models

In order to develop products with good usability, experts ask users what they want to do with these products and what problems they have in using them. Three scientifically proven UX models for developing positive experiences have become established. They describe and categorize different needs, emotions and experiences. Marc Hassenzahl, for example, identified stimulation, popularity, security and meaning in addition to the three above-mentioned needs competency, autonomy and belonging. Pieter Desmet defined 25 positive emotions and divided them into nine groups such as affection (e.g. love), gratification (e.g. satisfaction), empathy (e.g. kindness), interest (e.g. inspiration), assurance (e.g. pride), enjoyment (e.g. joy), aspiration (e.g. desire) and animation (e.g. surprise).

A third UX model are the so-called experience categories, which are based on several hundred interviews in which users reported about situations in their work life that they experienced as being positive. These experiences were summarized in 17 experience categories and divided into six groups: resonance (e.g. receiving feedback), social support (e.g. helping others), challenge (e.g. rising to a challenge), engagement (e.g. experiencing creativity), organization (e.g. finishing a task), communication and new experiences (e.g. creating something together).

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Cards as design aids

The needs, emotions and experiences are available in the form of cards detailing their respective characteristics. Marc Hassenzahl’s need cards, for example, describe the emotions related to the need, impressions of products that meet the need and typical quotes from users when their needs are fulfilled. These cards enable designers to develop a deeper understanding of needs, emotions and experiences and to come up with UX ideas.

They can also use these cards in workshops to analyze which needs, emotions or types of experiences could be met in their specific context of use. These insights can form the basis for initial design ideas. In general, this approach is ideally suited to create positive UX. But AI above all provides ideal conditions for creating positive emotions and experiences for users. Why? Let’s illustrate this in the following examples:

Evaluating and using data

Companies dispose of large amounts of data about what their individual employees worked on at any given time. Using AI, such data can be employed to create positive experiences for the staff – for example by giving the individual team member a feeling of self-efficacy. To achieve this, the algorithm could derive certain information and give feedback, e.g. “You worked on seven contracts today. That’s two more than the average of the past two weeks.” For reasons of data protection it is important to remember, however, that only the respective employee should see such information. Moreover, the team members should not be compared – this would be counterproductive.

Networked data

Often, team members enjoy contributing to “a higher cause”: How do others benefit from my work? What effects do the results of my work have on our company and our clients? Networked data can provide answers, giving meaning to every employee’s work.

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Cooperating with AI

Working as a team and getting things done together also provides positive emotions. This doesn’t only apply to the cooperation between people but also to the cooperation with an AI system (see also “Human-robot interaction – turning tools into companions”). It is important to know that AI can build knowledge about this and illustrate how the cooperation between the user and the AI can contribute to a joint result.

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Conclusion

AI is not a new technology. However, it is currently reliving its youth. And the research on positive UX, too, is still in its infancy but is constantly progressing. If you try to combine both, it becomes evident that many ideas and approaches are needed to gain sufficient evidence of its effects and efficacy. However, the above-mentioned tools and examples illustrate what direction the development will go from here: They will enable UX designers to create positive human-AI interaction.

The author

Prof. Dr. Michael Burmester is UID’s Principal Scientific Advisor. Since 2002, Dr. Michael Burmester has been holding a chair as professor for ergonomics and usability in the information design course at the HdM Media University in Stuttgart. His research work deals with methods of human-centered design and positive user experience. The main focus of his current research projects is positive user experience in modern working environments including current technological developments such as artificial intelligence, virtual reality, augmented reality, etc. At the HdM he heads the User Experience Research Labs (UXL) and the Information Experience and Design Research Group (IXD). He also acts as a coordinator of a project financed by the German Ministry of Economics that supports SMEs in designing digital technologies with positive usability and user experience (Mittelstand 4.0 – Kompetenzzentrum Usability).

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