Bold Insight team talks about artificial intelligence, how to embed a UX culture at UX Masterclass in South Africa

Bold Insight team talks about artificial intelligence, how to embed a UX culture at UX Masterclass in South Africa

The 15th installment of the UX Masterclass, an annual conference that brings together experts from the field of user experience (UX), innovation, and customer research, will focus on how to ensure success and adoption when humanizing digital transformations. Bold Insight Managing Directors Bob Schumacher and Gavin Lew will share insights on building a UX culture within an organization and how to increase adoption of artificial intelligence (AI) driven endeavors.

The full-day event on April 4 in Johannesburg, South Africa will offer a unique opportunity to engage and network with UX thought-leaders as well as innovators and technologists, all coming together to share their experiences.

A frequent presenter on the integration of business priorities and UX benefits, Schumacher will present, UX means business, where he will identify the impact of UX on the brand, enterprise value, and organization culture.

“As a founding partner of the conference host, the UXalliance, I’m thrilled to be a part of this dynamic event,” said Schumacher. “The global focus of the event is what keeps attendees coming back. No other conference brings this caliber of UX experts together.”

In his talk, Successful digital transformation with AI needs UX, Lew will discuss how to integrate UX into AI-infused products to increase adoption. He will illustrate how to incorporate the UX principles of context, interaction, and trust into this technology to build user acceptance.

The UX Masterclass is hosted by members of UXalliance, a network of 25 leading UX companies around the world. For more information about the event, visit

About Bold Insight

Bold Insight is user experience (UX) research agency based in Chicago. Our team offers clients the expertise and professionalism of a large agency, with the imagination and agility of a startup; specializing in medical device research, human factors validation, and large-scale global testing.

6 UX trends for 2019

6 UX trends for 2019



As industries undergo massive change, there’s a tension; new players will disrupt old market structures and the UX is going to play a critical if not defining the role in the success or failure of these transformations.

The bold future of UX: How new tech will shape the industry

Part 6  6 UX trends for 2019

There are reasons to be both optimistic and somewhat cautious about what’s coming in 2019 for the UX industry. Walking through the expansive halls of CES, as I have done every year for the last 10 years, usually leaves me with a solid understanding of where certain industries are headed, both in technology evolution and investment, and the role user experience (UX) research and design will play in that process.

Here are my thoughts on which UX considerations will take center stage in the coming year:

1. The complexity and need for speed-to-market in healthcare will drive user experiences to new and interesting levels.

In 2019, we will see a greater focus on the user experience in healthcare. Healthcare has been slow to move in the past in large part because it’s highly regulated and obsessed with safety (as it should be!). But as consumer-oriented digital applications begin to raise the awareness of what user interfaces can be to health-care professionals, users will demand better experiences.  We see this in electronic medical records, where many user interfaces are effectively mired in 1990s-style UI designs.  Further, as more nimble startups see the business opportunity in healthcare, there will be more consumer-facing applications to support a wide variety of areas (e.g., sleep, nutrition, pregnancy, etc.).  There is growing need among these companies to do human factors testing of digital products prior to FDA submission, and a painful lack of awareness of that process.


2. As payments go digital, there is a knock-on effect across the entire commercial fabric making understanding user experience essential.

In the past, many financial services that customers required demanded an intermediary financial institution, e.g., currency exchange. It’s now possible to set up an account where dollars can be moved between euros, pounds, and yen without ever having to incur any intermediary. Through a simple app, accounts can be kept in one currency and withdrawn.  The user experience is greatly simplified.  There is also a fast push to cashless societies, such as in Sweden.  (Even homeless people in Sweden can take credit cards!). Companies will have to understand their customers’ needs and lead the way with user experiences that provide systemic, safe, private, and convenient ways of interacting. Again, like in healthcare, smaller, aggressive and well-funded startups will challenge established players; the point of competition, where customers will be gained or lost, will be at the customer’s experience.

3. Mobility provides both macro and micro challenges to the user experience.

Mobility is morphing. We are all incredibly aware of how Uber, Lyft, Didi and other ridesharing services are transforming how we think about transportation and mobility. How we get around today and how goods are moved (i.e., in trucking) is changing fast. In fact, the whole notion of ownership of vehicles is changing – in the next 15 years the idea of an individual owning one or more vehicles is becoming obsolete.  Fractional ownership of multiple vehicles by cooperatives of people will be the norm. There will likely be increased mobility by drone services (CES has several examples of this.)  How users and customers will engage will be of increasing importance for the success of the business models.


4. AI needs UX.

This was the year of AI at CES. It seemed every other booth had the letters “AI” on their signage. However, most of the AI applications cannot succeed without proper data that is human tagged. In fact, over the last couple of years, I’ve been involved in several projects to just collect data to train AI algorithms. This is not traditional UX by any means.  But UX professionals and psychologists have research and logistical skills to be able to collect data that will allow us to train AI algorithms.


5. UX will grow increasingly more important in the developing world.

2019 will see the need to increase understanding of the skills, knowledge, capabilities, needs and desires of the users in the developing world. All one must do is to look at the public record to see that Google, Facebook, Amazon and others are heavily invested in moving into places like Africa, Indonesia, India, and Brazil. These next billion users are the ones that the companies are targeting. There will be enormous investment put into the user experience research needed to serve these markets because of the wide language, and cultural diversity. The technological capabilities in these locations are vast and unknown to international manufacturers trying to design user tech. To be successful in this market these companies must develop products and services that would be a value to the users and of value to them as suppliers. UX research is global! (Shameless plug for my book) And global UX research partnerships like the UXalliance can help companies be successful in these markets with on-the-ground resources steeped in local knowledge.


6. Transformations in user security and privacy will demand attention.

The increasing spate of data breaches and identify theft create an opportunity for improved user experience. (If you want to understand, and be horrified as to what you sign up for when you hit ‘Accept’, I strongly recommend watching Terms and Conditions May Apply on Netflix.)  Scott McNealy of Sun Microsystems famously said in 1999(!) “You have zero privacy anyway. Get over it.”  The digital world has become much scarier since then; the bloom has come off the rose.  With all the upside in technology, there is a huge risk.  Companies that help us manage all the risks are going to be in higher demand – and UX will be at the forefront of this.  There should be better ways to protect and control who sees what about each of us.  Anyone who has had their identify stolen or been a subject of credit card theft knows how tedious it is to manage this.


Large dominant players, who once had a comfortable existence for decades, will find themselves under intense pressure from smaller start-ups who have learned how to care for the customer.  These small players are also not burdened by legacy systems that will continue to drag them down. Successful companies in the market, whether start up or established, must learn about: who the customers are, what the customers’ needs are, and how to design for those needs.

What are your thoughts on 2019 UX trends? Comment below and let’s get a dialogue started!

This blog post is part six of a series, The bold future of UX: How new tech will shape the industry, that discusses future technologies and some of the issues and challenges that will face the user and the UX community. Read Part 1 that discussed Singularity and the associated challenges with UX design , Part 2 that provided an overview of focus areas for AI to be successful ,  Part 3 that dug further into the concept of context in AI, Part 4 that proposed UX design principles for robot design, and Part 5  that highlighted Africa’s role in building next gen fintech


UX principles for robot design: Have we begun to baseline?

UX principles for robot design: Have we begun to baseline?



As the robotics industry continues to find its way into our lives, we can begin to identify UX design principles to apply to this tech to increase the acceptance of robots and improve the human-robot interaction experience.

The bold future of UX: How new tech will shape the industry

Part 4  UX principles for robot design: Have we begun to baseline?

In a previous post, I discussed the challenges of designing a user experience for AI and how it needs three components to truly deliver on the promise of the technology: context, interaction, and trust. These three elements allow for a good user experience with an AI. Today, we’re taking AI to a related area: robotics. A robot is essentially an AI that has been given a corporeal form. But the addition of a physical form, whether or not it’s vaguely humanoid, creates further challenges. How do users properly interact with a fully autonomous mechanical being? Since this fully autonomous mechanical being can, by definition, act on its own, the flipside to this question is just as important, how does a robot interact with the user?

Before we dive into these questions, let’s all get on the same page about what a robot is. A ‘robot’ must be able to perform tasks automatically based on stimulus from either the surrounding environment or another agent (e.g., a person, a pet, another robot, etc.). When people think of robots, they often think of something like Honda’s ASIMO or their more recent line of 3E robots. This definition would also include less conventional robots, such as autonomous vehicles and machines that can perform surgery.

A research team at the University of Salzburg has done extensive research on human-robot interaction by testing a human-sized robot in public in various situations. One finding I found particularly interesting is that people prefer robots that approach from the left or right but not head-on.

In San Francisco, a public-facing robot that works at a café knows to double-check how much coffee is left in the coffee machines and gives each cup of coffee a little swirl before handing to the customer.

While a robot in Austria approaching from the left and a robot in San Francisco swirling a cup of coffee might not seem related, it points to UX principles that should be kept in mind as public-facing robots become more ubiquitous:

  • A robot should be aware that it is a robot and take efforts to gain the trust of an untrusting public (evidenced by people’s preferences for robots to not approach head-on and to always remain visible to the user)
  • A robot should be designed with the knowledge in mind that people like to anthropomorphize objects (evidenced by people preferring the coffee-serving robot to do the same things a barista might do even if it’s something the robot doesn’t necessarily need to do)

As with all design principles, these are likely to evolve. Once robots become more ubiquitous in our lives and people become accustomed to seeing them everywhere, different preferences for how humans and robots interact may become the norm.
This may already be the case in Japan, where robots have been working in public-facing roles for several years. While anthropomorphic robots are still the dominant type of bot in Japan, there is now a hotel in Tokyo staffed entirely by dinosaur robots. The future is now, and it is a weird and wild place.

What are your thoughts on all of this? Comment below and let’s get a dialogue started!

This blog post is part four of a series, The bold future of UX: How new tech will shape the industry, that discusses future technologies and some of the issues and challenges that will face the user and the UX community. Read Part 1 that discussed Singularity and the associated challenges with UX design , Part 2 which provided an overview of focus areas for AI to be successful , and Part 3 which dug further into the concept of context in AI

AI benefits from GPU, not CPU advancements

AI benefits from GPU, not CPU advancements

A quick follow-up to our blog posts about AI

The name of the game is no longer Moore’s Law where we see processors getting exponentially faster. AI technology is driven not by computing processes of the past, but from an evolution beyond central processing unit (CPU) advances to graphics processing unit (GPU)-based processors. These graphics chips used by gamers are being used by AI for their massively parallel-processing capability. As Talla commented, “We now have the equivalent of a super computer on a single chip. This allows image recognition to make a huge leap forward.”

Now, with AI, deep-thinking image identification is faster and more ubiquitous. By 2020, NVIDIA estimates there will be 1 billion cameras deployed for surveillance worldwide. But why do we build them? For public safety, parking, or customer experience of Disneyland? Where do we store this data, and how do we use the data?

What do you think? Join the discussion and comment below!

The critical component missing from AI technology

The critical component missing from AI technology



The first step when developing AI is to understand the user need; but just as critical, is knowing the context in which the data is being collected.

The bold future of UX: How new tech will shape the industry

Part 3  The critical component missing from AI technology

In our last post on artificial intelligence (AI) , we discussed the three pillars that AI needs to consider to be successful: context, interaction, and trust. In this post, we will dive deeper into the idea of context.

It’s no secret that AI is a hot topic in virtually every industry; how to apply it, how it will advance the industry, how it will improve the experience for the customer. It was a major topic at the 2018 Consumer Electronics Show (CES), and articles that either expound the virtues of AI or predict that it will be humankind’s downfall are in the popular press on a regular basis. It’s clear that while the opportunities are seemingly endless, there is a critical component missing from much of the AI technology out there: In what context is the data (that allows AI to learn) being collected?

Don’t build it just because you can

When we think of the buzz around AI, we must pause to ensure we are “not building AI just because we can.” While the opportunity is great for efficiency, people will hear this statement and immediately fear for their jobs. But successful manufacturing companies know that the key is striking the right balance between robots and people. The first step is to understand what user need is addressed with the robots. Some examples of this include:

What’s missing, and is currently doing a disservice to AI, is context. Around Valentine’s Day, a story came out where AI was asked to come up with new Valentine’s Day candy heart messages. But without context, it produced quite a few messages that would confuse (and possibly anger) anyone that received them. (I know I wouldn’t want to receive a heart that said “Sweat Poo” or “Stank love”.)

When we build AI tech, there are three stages where context must be considered:

  1. Before it’s built: Beyond uncovering the user need that the tech will address, we must make sure that the context in which it will be used gets into the AI process. This will ensure we collect the right data.
  2. During: When the data goes in, it must have context. For example, if you are collecting data on behavior in a car compared to a bedroom or kitchen, it’s clear that the context would be important.
  3. Using the collected data: Currently, AI is a ‘black box’ – you throw in data and see what comes out. But the user must use AI to do something. If we take a user-centered design approach to how the insight might be used, this is when we will really see how powerful AI can be.

The potential for AI is astounding, and it will likely be one of the defining technologies of the 21st century. However, AI is only going to be as good as the data and information that we feed to it. By providing AI with the proper context for it to advance properly, we are helping to ensure that AI is delivering on its promise of simplifying life for the end users.

What are your thoughts on the idea of context in AI? Start the discussion by leaving a comment below!

The next post in our future tech blog series will move from software to hardware with a discussion around robotics.

This blog post is part three of a series, The bold future of UX: How new tech will shape the industry, that discusses future technologies and some of the issues and challenges that will face the user and the UX community. Read Part 1 that discussed Singularity and the associated challenges with UX design and Part 2 which provided an overview of focus areas for AI to be successful.

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