Designing challenges in the AI era and how to overcome them

Design is an ever-changing field. So much so that it is difficult to keep track of design job titles. Initially, product designers designed industrial products while graphic designers focused on printing as a support.

As a creative field, Design has found its analogy with architecture; it had to be functional, usable and predictable, but also beautiful, emotional and innovative. The designers took into account business priorities, user needs and material constraints among other factors and designed the solutions. These factors (or requirements) remained constant while the designers channeled their creativity to find innovative and perfectionist solutions for the target market.

In the digital world, Design borrowed principles from the previous era, but with one fundamental difference: the solution has become a living entity. Today's digital "Product" constantly learns about the user's understanding of himself and evolves as he learns. The requirement comes in batch and is continuously based on the existing solution.

The markers in the product provide a quantitative assessment of user behavior; We track metrics such as number of sessions, frequency of sessions, time of day in which the sessions occur, activation via notification vs organic, duration of the session, most used buttons (or features), order of clicks per screen, elapsed time per screen, scrolling per screen, number of list items consumed per screen, etc. Now, in a data-driven environment, these numbers guide decisions and experiments on products and projects. 

These numbers affect the product, the product affects the user behavior, the user behavior affects the numbers and therefore the evolution of the product is always a continuous exercise.Since we identify high-level models through these metrics, we are essentially designing ad Personas. For example, if many users log in online after 22:00 regularly, we will notice that the behavior will likely include a night function. 

These users are likely to be teenagers (hypothetically), so in this case we are planning for the teen person.Furthermore, even before we start designing a product, our ethnographic studies focus on users. So both our qualitative and quantitative indicators of the day help us design for these personalities.

The future: creating for individuals

Some features, some texts or some graphic elements that really made you feel like the product really won you over. I remember that Google Home chose the 10 best restaurants in my area for my anniversary.

Content customization is omnipresent these days. Netflix, TikTok, Instagram, Youtube, Facebook, LinkedIn and all spooky Internet ads are examples of personalized interest-based content. But now, we are about to elevate it to the product itself. For example, as far as visual design is concerned,  here is an artificial intelligence  that produces 400 million visual design permutations.

The goal of design has always been to design for users aka User-Centric-Design. Techniques such as ethnographic studies, maps of customer journeys, validation exercises, surveys, product metrics, etc. These are all measures to better understand the user. However, the qualitative ones do not diminish and the quantitative ones allow models at medium (or percentile) level and not individuals.

In a world  based on artificial intelligence , we can scale Empathy down. We can understand people in the data and truly design user-centered solutions   .

How AI changes things:

Understanding people on a large scale: artificial intelligence gives data analysts better and more in-depth information. We are able to understand more complex data and at a more micro level. We can profile users more accurately based on demonstrated behavior. Instead of focusing on users as a% of metrics (or funnel), we can reliably analyze overlapping journeys (click flows) through the product.

Identify opportunities: AI also transforms the field from a reinforcement tool, that is, a response to what is asked, to be generative, or highlighting the patterns and aberrations themselves. Think of it as if conducting ethnographic research rather than a feedback survey, the former is more inclined to identify new ideas and open up new possibilities.

Predict and customize features: if we better understand and combine user travel on a large scale, we can predict user behavior and consequently prioritize functionality. This is similar to how we personalize a content feed like Netflix. For example, users who are scheduled for the transaction may see the shopping cart as the main feature of a product and users who are expected to interact may see the content / community as a priority function.

Optimize permutations: for the functions that are provided to users, experimentation with flows will become automated. For example, if we have a purchase flow, say that we have the option of using a single long form screen   , or  step-by-step  full screen flow, or a lower sheet flow; experimenting and matching options to user profiles will be easier.

New interfaces: AI will allow for newer ways to interact with users. At the moment, conversational interfaces such as voice assistants and chatbots are the best examples.

How designers can adapt:

Think system-wide: only data cannot do the job, interpreting it in the context of the user's environment makes it relevant for users. Think system-wide and identify key issues. Recent design titles as a system designer and customer experience designer already reflect this change.

Design the architecture: imagine that each user has their own version of a product but it is always the same product inside. For example, the "stories" as a product are architecturally the same for WhatsApp, Facebook, Snapchat and Insta. Although it varies in detail on various platforms, it is different from other content entities such as a post, message or movie. Focusing on the design of architecture suited to product flexibility will be the key to a designer's success.

Designing a linguistic system with flows: we have evolved from visual style guides to linguistic design systems. While the former focuses on creating options for visual artifacts, the latter focuses on creating UX components (and their encoding). In the near future, we should include more options for end-to-end flows and design systems. For example, a search flow can start by typing one option, listing it in another. Artificial intelligence can help us choose an option based on the user profile and insert it into the architecture defined above.

Designing for pleasure: the better we understand the user profile, the easier it will be to combine delicious features with users. In the ideation phase, it will be good to fully understand the users' people and the travel maps and then find myopic but delicious solutions. Artificial intelligence can help us scale the same as we become more personalized with features.

Integration with technology: a deeper understanding of technology and product analysis will be necessary to fully utilize the technological capabilities and correctly analyze the infinite permutations in real time of a product. Designers will gain by acquiring coding and instrumentation skills.

Set ethics:  think of AI as a person  , it can be good or bad. At the moment, there are enough examples of dark UX  nowadays  , none more infamous than  Privacy-Zuckering  . Artificial intelligence is more susceptible to exploitation than any other technology. It is up to us to establish the personality and ethics of the system. Digital trust will be the main engine for retaining new users, especially in emerging markets. It is our responsibility, as owners of the experience, to keep it as transparent, honest and predictable as possible. Once broken, trust cannot be restored. Design for long term relationships, not for short term earnings.

The data will always be reactive and research (ethnographic) will always be proactive. Use research to innovate and data to amplify.

Can artificial intelligence replace designers? I believe that as long as humans are the users, we will also need the human dimension on the creation side. As mentioned at the beginning, design is an evolving field, and it is stubborn enough to find creative ways to stay relevant. Maybe we can expect a new title soon: AIXD!