The Need for an Aix Design System - Part 2

The previous article, covered why the deliberate design of the experience of artificial intelligence is so important. This follow up article focuses on how to approach the challenges: We need to develop a design system with a special focus on the conditions of AI-technologies – an AiX Design System.

Systems to Design Products

The */dxg Product Design System successfully tackles general issues in user interface (UI) and product design we see ourselves increasingly confronted with:

• Products and services are getting more sophisticated but are also expected to become easier to use, leading to design problems growing more complex.
• Lean and agile product development demand faster turn-around.
• Teams are getting more distributed.
• Design teams are growing.

An AiX Design System addresses similar issues while focusing less on UI solutions but on wider principles and patterns concerning AI-technologies. There is the opportunity to collect the expertise in this field as we build it. Applied to our product development cycle, an AiX Design System can help during the Discovery phase by providing a framework and tools to identify valuable use cases and to understand constraints; during the Design phase by sharing best practices and design patterns to solve common problems (e.g., with uncertainty in presented data); and after the Delivery phase in providing a framework on how to measure and improve the quality of the AI from a customer’s perspective.

Opportunities and Challenges

• Guided exploration (e.g., conversational interfaces)
• Alternative input (e.g., voice, natural language, gestural, facial expression)
• Contextualized output (e.g., text generation, precise answers)
• Customization and personalization (e.g., proactive shortcuts)
• Monitoring (e.g., proactive agents)
• Service integration
• Social relations between user and application

and an AiX Design System will help to meet new challenges and constraints that arise from the use of AI-technologies:

• Transparency and trust (“What data is used and how is it processed?”)
• Uncertainty (“How much can I trust this prediction?”)
• Failure and accountability (“This result seems complete nonsense ..”)
• Bias, inclusion and ethical considerations (“Why are all virtual assistants gendered female?”)
• Dynamicity (“Why are the results different now, even with the same query?”)
• Discoverability (“How smart is this application?”) Social interaction (“This chatbot is rude …”)
• Privacy (“What can they learn about me?”)

Strategy

For Wolters Kluwer, this initiative also has a strategic relevance. Not only are global markets related to AI-technologies projected to grow rapidly, but we also aim to derive 65% of our revenue from “expert solutions,” which we should expect to employ AI-technologies as their core value drivers.

A shared knowledge base of insights, guidelines, best practices, and usage patterns at the intersection of business/design and technology to optimally embed AI into product ideation, design and development will generate value across the three aspects of our corporate strategy:

1. Grow Expert Solutions

Expecting AI-technologies to be an important value driver of expert solutions, an AiX Design System will support understanding opportunities and challenges during discovery and design.

2. Advance Deep Domain Expertise

Providing best practices, an AiX Design System will help subject matter experts to apply their expertise most effectively according to the technological requirements.

3. Drive Operation Agility

Providing guidelines, principles, and reusable solutions, based on reliable expertise, an AiX Design System will accelerate the design and development of AI-enabled products producing faster turn-around in innovation.

Now is the right time to invest in an AiX Design System!

We are currently in the process of shaping a clear vision for the Wolters Kluwer AiX Design System. If you have questions or comments or want to exchange insights – please do not hesitate to reach out!