IA Summit 2017: Designing for Humans

The first day of the 2017 IA Summit overwhelmed me in the best way possible. I attended a variety of sessions, talks and discussions about how machines and humans are meant to work together, as a team, to solve the different challenges people face today. In keeping with the theme of “Designing for Humans,” some talks expanded on the role of the information architect and how they can enhance their own skills and add value with the aid of artificial intelligence—and not the other way around.

Here’s a quick overview of what I saw, and how we can use AI to enhance our own abilities.

Keep in mind, “it’s not our fault, but it’s our responsibility”

As information architects from all over the world gathered at the Hyatt Regency in Vancouver, keynote speaker Alan Cooper, co-founder of Cooper, shared his “Ranch Stories” and described how software and interaction design should be built the same way a farmer takes care of its land.

There should be “responsible craftsmanship” in the way product developers and companies design their products, keeping the user at the core of all decisions. Cooper stressed the concept of nurturing products so that they become sustainable, and not just fast-growing money machines, as current practices encourage. Creating and building products should be a long-term goal, where the value generated for the people and society trumps the desire to make money and earn profit. Cooper wants us to understand that “profit is the by-product of quality” and quality will only come when designers, like all of us here at IA summit, take on the responsibility of helping to solve challenges that make the life of users better in the long run.
 

Nurture machines using our IA skills

In AI for IA’s: Machine Learning Demystified, Carol Smith used her expertise as a Sr. Designer at IBM to give an overview on artificial intelligence. She showed us how information architects are central in helping nurture and develop systems that are in turn helpful for the people that use them.

At its core, AI is but a tool to save time for decision making. However, it needs to be designed with ethics, standards and techniques that align with our own values. Furthermore, Smith texplained how training these systems takes the time and expertise of various people to mitigate gaps in knowledge and implicit biases that arise in the design phase. As an example, she explained how information architecture is incorporated into chatbots as the means of creating relevant questions and the answers to be provided. In other words, we need language, hierarchies and the ability to know when to escalate to human participation to make these intelligent systems effective.

In another example, the lovable robot that beat the most successful contestants at Jeopardy, Watson, was used to show how AI is designed with specific purposes, but is only as good as the information we provide to it and the purpose we give it. As the session continued, Smith asked us to “trust machines as much as we trust humans” and have confidence that the machines are built to enhance our lives and not control it. To conclude, Smith recommended checking out Don’t Fear Super intelligent AI, a ted talk by Grady Booch and The Optimist’s Guide to the Robot Apocalypse by Sarah Kessler to get more insight into why we shouldn’t fear AI, as we can always unplug the machines.
 

Robots can help you, not replace you

Michael McLeod, VP of Design Development and Support at Eli Review, shared his experience in developing assistive learning tools that maximize teacher’s coaching abilities to help their students become better writers. He used this case study as an example on how, even though technology has evolved enough to make machines capable of providing feedback on grammar or directly write articles, humans are better at determining specific ways to help individual needs and curating beneficial information. He claimed that technology is not meant to replace people, but to assist them in becoming better, in taking away the workload that may impede them from doing their tasks or jobs easier or more effective.

McLeod explained how IA’s possess a particular set of skills that make them the best candidates to bridge the relationship gap between man and machine. They can uncover the correct indicators that are most reflective to the learning style of users, and create interfaces or designs that lead to better feedback mechanisms and holistic views of the information needed to assist this learning. As the session ended, McLeod suggested that information architects should work with subject matter experts to research and discover the specific indicators that will lead to the development of better AI assisted tools.
 
 

A Tale as Old as the First Computer Interfaces

Susan Kare walked us through her 30+ years designing interface elements for multiple companies, including Apple, Microsoft and currently Pinterest, by presenting a visual journey of the pixelated icons that are so pervasive today. Tying to the theme of the IA Summit, she quoted a 1984 Macintosh advertisment saying how we need to “teach computers about people instead of teaching people about computers” which shows how the user has, for a long time, been one of the most important factors in designing the machines that they use.

Kare reflected on the biggest takeaways that she learned as her career progressed, and how she carried these concepts with each subsequent project she worked on. She urged us to have confidence in our skill mix, and to not fear constraints that might be set on our work, as these constraints may spark creative solutions and lead to better designs. Kare also encourageed us to use iteration as a friend and to acknowledge that everything that may exist is already here, so we just need to work towards discovering it and making it applicable to the solutions we’re trying to design.

One of the biggest takeaways I had from this talk was the impact that human knowledge and user input have on the development of technologies and innovation. She explained how users at Pinterest have been able to describe certain concepts in ways that were not apparent to the creators and curators of the information, thus giving things new and diverse meanings. This further supports how artificial intelligence will know as much as we teach it and so we want to make sure that human factors are not taken out of the equation, so that we can keep uncovering more than we think is available.

Come back tomorrow and see more live blogging from our on-the-scene author, Julieta Sanchez!