Fundamentals

When looking for ways to apply this cutting-edge, revolutionary technology, AI can not only dazzle, but can blind us as well. The more buzz and hype, the greater the pressure becomes to rush to create something using whatever new capabilities are presented to us. The benefit of moments like this is the opportunity to discover, experiment, and learn.

We must focus our design talents upon a new type relationship with machines - machines that can draw from vast stores of human knowledge, hold a conversation, and increase human understanding. What should these relationships look like? Designing for AI requires new considerations and new ways of thinking.

When we find ourselves in such unfamiliar territory, the best way to begin is by reminding ourselves of the true purpose for any innovation: to improve the quality of human life.

Consider what we’ve learned living through the past few major technological innovations. The internet brought the world’s information to our beck and call and taught us that whatever we want, whenever we want it is always a finger-length away. Mobile tech enabled humanity to take that information with us at all times. Social computing and messaging changed the foundations of how we communicate with each other and language itself.

Each innovation provided a new context for communication and expanded (or changed) our understanding of the relationships we have with machines. AI requires us to take notice of new contexts yet again. This time, designers must account for a system that can understand, reason, learn, and interact.

As a result, this changes the nature of our design considerations, some of which we take for granted based on the last 40+ years of software design. If we’ve moved past typing into a text field and pressing “submit,” what does it mean to design for human/machine relationships?

As Jared Spool says, design is the rendering of intent. This intent drives our outcomes. It’s the “why” behind what we do and the cause for us to affect change. Intentions require us to identify purposes and values for our efforts. Outcomes require going beyond ideas and create meaningful, trusted solutions for the people we serve.

Design is more than a job or role—it’s an essential part of what makes us human. The value of design is to improve lives and leave the world better than we found it. When designing for AI, our core intents are always rendered through the following lenses:

AI is the simulation of human thought processes in a computerized model. AI involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works.

These systems learn at scale, reason with purpose and interact with humans naturally. What search is to information retrieval, AI is to better, more-informed decision-making. In short, they help human experts make better decisions. We characterize AI as having four main qualities:

When it comes to designing for AI, our focus must be unwavering in providing experiences that put the user above all else.

AI isn’t about data, it’s about insights. Data is the fuel for the car, insights are the destinations. This is what people care about.

AI is capable of delivering more human-like interactions with people — based on the mode, form, and quality each person prefers. It reasons through the sum total of structured and unstructured data to find what really matters but this isn’t the full picture. Our solutions must primarily address user needs instead of being force-fit to accommodate technical capabilities or requirements.

Philosophically and psychologically, we find purpose, value and trust in others when we can perceive intended meaning, consider this meaning from differing points of view, and acquire knowledge so that we can act to have an effect on one another. If a system has the capability to understand, reason, learn, and interact then it has the basis to form a relationship with a human.

For AI to truly amplify humanity we must have and maintain meaningful relationships between humans and machines.

To design authentic AI-based relationships requires us, as designers, to consciously understand ourselves before anything else. The more we understand of ourselves, the better we will be able to teach machines how to help our users be better.

At this point, you might be asking yourself, “how do I design a relationship?” You wouldn’t be alone in this. For most people, forming and maintaining relationships is an autonomic process. We hardly give it a second thought. If you take a deeper look at the psychology behind relationships, you’ll probably find Knapp’s Relational Development Model.

Mark Knapp is a teaching professor at the University of Texas and is known for his works in nonverbal communication research. His relationship model explains how relationships grow and last and also how they end. This model is categorized into ten different stages which come under two interrelating stages “coming together” and “coming apart.” This helps to understand how a relationship progresses and deteriorates. For the purposes of our work with AI, we will focus on the “coming together” stages exclusively.

So what do we need to consider when one person in a relationship is replaced by a machine? By establishing tone and personality first, the system will have the means to endear itself to the user. As these systems are like “digital toddlers,” the means to make an emotional connection with its users will be essential.

Artificial intelligences are probabilistic systems. This means that they are taught instead of being programmed. Since they are being taught, they must have context to be able to utilize their learnings. An AI needs this context to understand its place and provide value.