In the fifth episode of the AI Experience series, we look closer at the importance of contextual understanding in the advancement of AI. For more on this topic, visit www.AIXexchange.com. Developers and potential partners interested in LG’s ThinQ Platform should check out thinq.developer.lge.com.

From AI speaker that recommend movie and TV shows matched to our personal tastes, AI is helping to make daily life more convenient in numerous ways. But we’ve all had that experience when Siri or Alexa responds with the wrong information or doesn’t understand the question. For AI to improve, it needs to better understand context.

“These limitations have inspired the call for a new phase of AI, which will create a more collaborative partnership between humans and machines,” said David Foster, head of Lyft Transit, Bikes and Scooters. “Contextual AI is technology embedded, understands human context and is capable of interacting with humans.”

When the “Age of Contextual AI” arrives, human-AI relationship will take a giant leap forward. Machines and services that can understand context in terms of physical space, the end user’s personality and style of communication – as well as myriad other factors that we take for granted, but are central to our ability to comprehend how society and personal interactions work – will become more like partners and more integrated than ever into the way we live.

Let’s take a look at five different areas that, if successfully navigated, will go a long way toward ensuring that the concept of contextual AI comes to its full fruition.

Spaces

Different kinds of spaces come with different sets of rules – some written and some unwritten. Based on those rules, we might dress and act in a certain way and also interpret what someone is saying, or what is going on around us, through a space-specific lens. One could argue that the pandemic has made environmental context even more difficult to discern for AI, with our homes now doubling as offices, classrooms, gyms, movie theaters, etc. This shift raises the importance of creating AI that can not only partially determine meaning or motive through reference to the specific type of space, but also from the nature of the interactions taking place within that space.

“We have to assume that AI is going to operate in a heterogeneous world with a lot of non AI-friendly consumers and devices or vehicles,” said Foster. “So the ability to be adaptive, predictive and context-aware is going to be key.”

When AI systems designed for different spaces and areas of our lives eventually converge, there will be serious implications around the exchange of personal data, including the way it is shared, when it is shared and for what purpose. To prevent or reduce risk, it is crucial to include end users in the development process, and to have both developers and policymakers work collaboratively to consider and uncover as many of the consequences as possible of a more integrated and contextually-aware AI network.

Values

With any new technology comes new moral considerations. Given the speed at which AI is developing, it is challenging for humans to evaluate whether each action is being performed in a responsible or ethical manner. Therefore, the task of imbuing AI with a set of values that informs its behavior has become particularly pressing.

While it is ultimately the developers who will ensure that core human values are built into AI systems, the task of choosing what those values are should be not be the domain of any one group. A broad collective that encompasses the full diversity of the modern human experience should be enlisted for this task, as this will help to establish a value set that is more representative of society as a whole and not geared to the interests or beliefs of any single segment.

Purpose

To engineer an AI that understands context, including distinctly human principles and patterns of behavior, demands the collection and analysis of significantly more user data. Increasing concerns around privacy in the digital age will undoubtedly result in users opting out of providing potentially sensitive personal information, which will unfortunately hinder AI from reaching its full potential, and individual AI solutions from rendering full value.

By transparently declaring and detailing the purpose and need for the collection of each data point, companies developing AI can help foster trust in their technologies and in their ethics as a business. If users can see the need for granting access to certain data and a clear benefit from doing so – such as the collection of home appliance usage data to help them achieve a greener, more cost-effective household – they will be more likely to share that information and to perceive the company as an ally in helping them reach their goals.

Creativity

AI is already being used in the creative sphere in a variety of interesting ways, from helping to write pop ballads to suggesting creative ideas in filmmaking when IBM’s AI platform, Watson, created the first-ever AI-made movie trailer for 20th Century Fox’s horror film, Morgan.^* While such usages represent considerable advancements in AI’s capabilities, experts question the extent to which the technology can develop its own sense of creativity.

“You can give AI a bunch of training data that says, ‘I consider this beautiful. I don’t consider this beautiful,’” says Arvind Krishna, senior vice president of hybrid cloud and director of IBM Research. “Now, if you ask it to create something beautiful from scratch, I think that’s certainly a more distant and challenging frontier.”

However, the idea that AI will one day be able to develop its own sense of creativity is essential to the unlocking of its full potential – specifically, the ability to go beyond the input data to develop new ideas and come to new contextual understandings that will enrich our lives and allow us to accelerate towards a brighter future.

Personality

Non-verbal cues such as a speaker’s facial expressions, tone of voice and body language play an important role in interpersonal communication and are factors that AI will need to be able to recognize if it is to provide better, more advanced services. However, because non-verbal cues can differ from person to person, the challenge of designing AI systems that can perceive such differences and respond accordingly, is considerable.

With the development of contextual understanding, AI will become more natural to interact with and more reliable in its ability to provide the information – or perform the tasks – we require of it. As it learns to infer meaning from the situation and surroundings, and the communication style of the end user, artificial intelligence will come closer than ever to being a genuine partner to humankind.

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^* https://www.ibm.com/watson/advantage-reports/future-of-artificial-intelligence/ai-creativity.html

In this fourth episode of AI Experience, we deep dive into how UX is evolving to better address users’ needs. Go to www.AIXexchange.com to learn even more from AI experts and leaders in various fields such as design, anthropology, policy, consumer and employee advocacy. Developers and potential partners are encouraged to explore the ThinQ Platform at thinq.developer.lge.com to experience what’s possible with LG.

From smart homes to virtual assistants to the first-ever image of a black hole, recent advances in AI are changing how we live and expanding our understanding of the universe around us. And we’ve only just scratched the surface.

But for AI to scale the heights we think it will ultimately be capable of, it is important that those developing the technology today get the user experience right. Delivering enjoyable experiences through human-centric design, especially in the arena of consumer AI products and services, will create the necessary buy-in and help fuel the technology’s growth enroute to achieving its full potential.

The term user experience refers to the overall experience a device, system or piece of software provides its user. The easier, more intuitive and pleasing the experience, the more likely it is that the user will recommend the technology in question to others, which typically drives popularity and increases uptake. For AI, as for many other products and services, convenience and efficiency are the cornerstones of a quality user experience.

“For AI to be consumable, for it to be usable, for it to be something that consumers can trust, design is actually the deal maker in that process,” said Sri Shivananda, senior vice president and CTO of PayPal. “Good design makes the product convenient and makes the customer want to engage more, come back more and be loyal to the product as well.”

Let’s take a look at five components that are material to the construction and provision of a better AI user experience: feedback and articulation, intuitive design, purpose, presence and interface.

Feedback and Articulation
To create more and better AI features and functionalities, both passive data collection and active user feedback are required. One of the most recognizable forms of active user feedback is the “like” button found on Facebook, Instagram and other social media platforms. AI algorithms record this data and use it to discern users’ preferences – and customize their feed accordingly – and to determine what is popular and trending across the platform and to help the platforms’ developers create new features that are relevant to their user base.

“I think AI will be used to help aggregate many different inputs that a human might make into a vehicle for mobility,” said David Foster, head of Lyft Transit, Bikes and Scooters, highlighting the value of AI in collecting and analyzing a variety of feedback. “Combine those with inputs that the vehicle itself is sensing around road conditions and traffic hazards, and then turn those into meaningful outputs that either give feedback to the humans through a different piece of output technology or direct the vehicle or another vehicle to take a different action.”

Intuitive Design
In basic terms, an intuitive design is one that is easy to use, where the method of control and operation seems obvious and completely natural to the vast majority of users. Integrating AI into products and services presents designers with a relatively new challenge, especially given AI’s unique ability to learn and adapt. Providing the space to do just that, while still delivering convenience to the user at all times, requires a fine balance. Yet, consumers have shown an understanding that AI applications need time to learn. This, to some extent, affords designers the opportunity to work towards more intuitive designs without the burden of having to attain perfection at the outset.

According to Alexandra Zafiroglu, deputy director at Australia’s 3A Institute (3AI), the solutions that we build “do not have to be perfect the first time that we put them out, but they have to be learning over time and providing value over time like a puppy.”

Purpose

 

A clearly defined purpose is essential to the success and effectiveness of any human-centric, commercial AI solution. And that purpose must be based on an in-depth understanding of customers’ needs and of the context within which those needs have arisen. Additionally, the transparent communication of purpose can be beneficial in building trust between the manufacturer or provider and the end user.

By clarifying intention and offering some insight into the design process (such as the time and consideration given to possible unintended consequences) and the measures put in place to prevent misuse, companies can show consumers their commitment to protecting their data security and to the ethical development of AI.

Presence

AI can provide value through active user engagement, such as voice-activated virtual assistants, and through passive means, such as the automation of smart home systems. Deciding which is the appropriate mode of control or management for each available feature or function is the cornerstone of successful AI design. But for every decision that developers have to make, there must first be a thorough examination of the potential consequences of their choices.

This decision-making process is a part of the broader human-centric design conversation, which demands that the consumer is viewed and valued as a complete person, rather than merely a source of revenue or data. Respect for the user as an individual must be factored into every decision, whether it is concerning the user experience or the very foundation of the technology itself.

Helena Leurent, director general of Consumers International, suggests that companies invite experts from different fields to share their knowledge and viewpoints, as this will help them to not only build successful AI systems, but to foster trust that any choices made are in the users’ best interests.

 

Interface

The interface of an AI product or service acts as a bridge between artificial and human intelligence, allowing the one to communicate with the other. Unsurprisingly, consumers have thus far shown a preference for AI that feels more natural and instinctive to use and interact with.

This is by no means an easy feat for designers to achieve and involves many questions that must be answered, such as, is it better to employ a touchscreen or physical buttons? Should an avatar or human voice be used to give personality to the technology? Does virtual or augmented reality provide the best conditions for relating to and engaging with AI? And of course, knowing and understanding people’s preferences and needs is also a crucial part of the equation.

Whatever design decisions are made, an interface should ultimately feel as natural as possible to as many users as possible and be suitable for use within a diverse range of scenarios. It should also be engineered with an eye on potential future integrations as AI continues to evolve and gain new capabilities.

Following human-centric design means better AI user experiences for everyone – from the consumers who use and benefit from the technology on a daily basis to the developers seeking to improve and expand on their creations and the technical support teams charged with remedying any issues that might emerge. With its ability to learn and adapt to the needs of the user, AI is already ushering in an era of unprecedented personalization and unique value. The continued refinement of the user experience will help attract more and more consumers to AI solutions and assist in securing the long-term growth of the technology itself.

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