The age of reasoning

In order for consumers to appreciate the true benefits of artificial intelligence, it is imperative that developers embrace the contextual side of the equation. But what exactly does that mean?

To be sure, it is at this stage where AI goes beyond surface level interactions to actively perform not only the basic requirements, but also make recommendations such as what you should eat before a pending business meeting that could end up being stressful or suggesting the perfect restaurant with friends later that night.

What needs to be stressed here is that there are two distinct thought processes when it comes to defining artificial intelligence and context.

In a blog written last year, Oliver Brdiczka, an artificial intelligence and machine learning architect working with Adobe Sensei, the company’s AI and machine learning technology that connects to the company’s cloud and helps marketing professionals make more informed decisions, zeroed in on two fundamentally different scenarios – what now exists and what soon could be possible.

AI, he wrote, is powering more and more services and devices that we use daily such as personal voice assistants, movie recommendation services and driving assistance systems.

“And while AI has become a lot more sophisticated, we all have those moments where we wonder: Why did I get this weird recommendation? or Why did the assistant do this? Often after a restart and some trial and error, we get our AI systems back on track, but we never completely and blindly trust our AI-powered future.

Source: Austin Neill

Interview: David Foster

Head of Lyft Transit,
Bikes and Scooters

“What worries me is AI-based systems that are controlling critical things and are thrown into the market before they are fully either developed or regulated.”

David Foster

Head of Lyft Transit, Bikes and Scooters

“These limitations have inspired the call for a new phase of AI, which will create a more collaborative partnership between humans and machines. Dubbed “Contextual AI,” it is technology that is embedded, understands human context and is capable of interacting with humans.”

What it represents is a description for a more advanced and complex system, but the problem is it misses a step. In order to ultimately arrive at the Contextual AI Age, it is first imperative that AI understands context.

Sri Shivananda, Senior Vice President and Chief Technology Officer at PayPal, likens the emergence of context in AI to the influence mobile communications has had on society.

“We've just seen over the last decade how mobile has played a significant role in changing payment behavior and payment experiences,” he says. “As we go forward, design and user experiences will continue to play a critical role in how these experiences come about.

“Commerce is going to become contextual. It is going to be surrounding us where we are. It may be through a smart speaker interaction or a continued interaction with a desktop laptop or a mobile device, or for that matter with the car that you're driving in. As commerce becomes contextual, AI has to become contextual as well.”

According to the Levels of AIX Framework, contextual AI will truly come to fruition in Level 3, when AI understands the patterns and principles across systems, using reasoning to predict and promote positive outcomes for users. This is termed, ‘causality learning’ and in order for AI to achieve this, it must be designed with end-users in mind and the many contextual components that shape our own experiences, as humans, namely the spaces, personalities and values that underpin the common-sense rules of our society.

Context can be defined in many ways, but at the end of the day it is about ensuring that AI can read all of the signs, be it the need to understand its environment or behave in appropriate ways depending on the situation.


Drawing the line between work and home life

How people behave at home is fundamentally different than how they behave at the grocery store, at work or at the nightclub. We dress appropriately, act appropriately and experience differently based on certain assumptions and knowledge about the unwritten rules that are attached to these spaces.

COVID-19 has created a new normal where our homes now are also our office, our doctors’ clinic, our movie theatre and our bank. What are the implications of this? How should we be designing these separate AI systems in a way that they share, but do not share too much?

How spaces are used and utilized have changed because of the onset of the pandemic and AI developers and designers must reassess their assumptions. With the lines blurred between home life and work life, a great deal of thought must now be put into AIX design ensuring end-users are part of the process in defining how AI not only understands, but also acts to provide optimal user experiences based on their environment.

What needs to be considered as both AI-enabled services evolve is where will the line drawn between a home and work AI offering. Will they be mutually separate entities or somehow merge and contain the ability to communicate with each other? It may be a dilemma for some and an opportunity for others, but worth discussing now as we re-establish commonly held assumptions about our spaces.

David Foster, Head of Lyft Transit, Bikes and Scooters, believes Interoperability is key.

“AI is typically evolving today in isolated islands – most of our cars aren't talking directly to our home and certainly aren't talking to our home without our explicit inputs to that AI in the vehicle. I think ultimately that will happen, because we have to assume that AI is going to operate in a heterogeneous world with a lot of non AI-driven consumers or other devices or vehicles … so interoperability is going to be key. The ability to be adaptive and predictive and context aware is also going to be key.

  • “People might be nervous about AI, talking unaided let's say from our car to our home or to our work because of concerns around security or identity or intent. But using AI so that I can ask my car to turn on the lights or the heat, my house on the way home … I'm showing intent and I'm showing context. I think many people would be comfortable with that type of approach today.”

    As we design new artificial intelligence experiences for end-users, it is going to be evermore important to ensure we consider our environment and the contextual realities that we assume as humans within different spaces. But even more important will be the challenge of codifying our very human understanding of the world based on our sense of place and the behaviours and especially the information that we share between those spaces.

When our work AI and home AI converge with our entertainment AI and our healthcare AI, there are some very serious implications about how data is shared across the systems, when it is shared and for what purpose. Developers and policymakers will need to consider the firewalls and handshakes that will need to happen, and end-users should be part of this process every step of the way.

Interview: Alex Zafiroglu

Deputy Director,
3A Institute (3Ai)

“As an anthropologist and as someone that has worked in an advanced R&D technology company and worked on product teams, I would say, no, you're never going to get a solution that works for all people at all times.”

Alex Zafiroglu

Deputy Director, 3A Institute (3Ai)


AI systems must align with human ideals

Source: Analuisa Gamboa


Without trust from a human there is nothing

A principal theme in Level 3 of the AIX Framework revolves around understanding. AI, at this point, understands the patterns and principles across systems to meet predefined missions.

Of note, AI shares learning outcomes to achieve a broader mission. Whatever that mission is. It could mean interpreting the mood of an individual at one end of the spectrum or helping society as a whole grow and learn at the other.

An example of a value defined as a purpose for AI occurred recently when EU consumer group Euroconsumers, published a white paper on how AI can be leveraged by consumers to accelerate Europe’s sustainability agenda.

Two key recommendations came from the report:
• AI driven tools and complementary technologies can help power the sustainability transition in different industries including household utilities, food, mobility and retail
• There is currently a significant lack of trust and satisfaction in the consumer AI experience.

Companies developing consumer-facing AI services for the green and digital transition have a perfect opportunity to help people achieve their sustainability goals and demonstrate they can deliver on trustworthy AI at the same time.

There was also a stark warning for all AI developers: Trust is paramount.

“Without trust from the consumer, AI will not be able to achieve its true potential,” said spokesperson Marco Pierani. “It would only be detrimental. More now than ever, tech companies should maximize their efforts to create AI that would not only improve the lives of consumers, but society as a whole.”

For Alex Zafiroglu, Deputy Director at the 3A Institute, purpose speaks to the underlying problem that the AI is solving for the end-user. This purpose must align with our goals and this is the context that needs to underpin the AI’s understanding and functioning.

  • “We need to have a usage roadmaps or experience roadmaps, particularly for thinking about an AI experience framework, such as the [AIX Framework]. And in that case, you need to think very critically about those humans, who are at the far end of the solution who are basically what the industry would call end-users. You also need to think about the value that is being generated by the application of artificial intelligence solutions in a particular context, because context is incredibly important. You need to think about, to what ends are you building solutions, both for those end-users and for your direct customer.”

Source: Blake Wisz


Onus is on both the developer and end-user

Source: Heidi Fin

Creativity, says IBM may be the ultimate moonshot for artificial intelligence: “Already AI has helped write pop ballads, mimicked the styles of great painters and informed creative decisions in filmmaking.”

Experts, it states in a blog, “contend that we have barely scratched the surface of what is possible. While advancements in AI mean that computers can be coached on some parameters of creativity, experts question the extent to which AI can develop its own sense of creativity. Can AI be taught how to create without guidance?”

“Just a few years ago, who would have thought we would be able to teach a computer what is or is not cancer?” asks Arvind Krishna, senior vice president of hybrid cloud and director of IBM Research. “I think teaching AI what’s melodic or beautiful is a challenge of a different kind since it is more subjective, but likely can be achieved.

“You can give AI a bunch of training data that says, ‘I consider this beautiful. I don’t consider this beautiful.’ And even though the concept of beauty may differ among humans, I believe the computer will be able to find a good range. Now, if you ask it to create something beautiful from scratch, I think that’s certainly a more distant and challenging frontier.”

More purpose-driven AI, say when your personal AI starts mashing up with data from your fridge, your smart stove and the Uber Eats recommendations to provide creative ideas for lunch, are maybe a little way away. However, the idea that AI will be able to look beyond the obvious context of certain inputs and generate novel combinations and juxtapositions that create new contextual meaning for the end-user, is something that could be quite valuable, since it is already how we problem solve as humans.

How should developers consider the kind of creativity that sparks unexpected joy? Creativity that makes the type of predictions and unique insights that end-users find useful? Plenty that can be interesting that can be done just by changing what parameters the developers use and the way the end-user plays with them.

The interesting juxtaposition will be in the context that we see around AI creations. By playing with the context AI is able to understand we may see more interesting intentional creations across more dimensions of context.

The onus will be on the developer and the end-user to get it right.


More a case of personalization

Source: Alex Knight

Context is Queen

A.I. Around the World

It can sometimes seem like the world’s AI advancements come from experts concentrated in only a few major countries, but AI is a truly global endeavor with amazing talents applying themselves to furthering the field. Here are five examples of organizations driving the future of AI from around the world:


Next Einstein Forum

Africa’s youth and women the voices of global science leaders are making a big impact on the global scientific community and the world. Interconnectedness & Inclusivity is the way forward.


Black in AI

A progressive network offering academic programs that support black junior researchers and provides initiatives to increase the presence of black people in the field of AI.


Alef Education

Recognized for best AI application in education. This brave award winning global education technology company in the Middle East transformed education by using AI for tailored and personalized learning experiences without traditional tools.



A private organisation owned by the Singapore Government that helps scientists build Deep Tech startups to solve difficult problems affecting the world by leveraging the city state's advanced smart city ecosystem.


AI for Accessibility Hackathon

The HACKATHON had to go digital because of Covid-19, but the event was successful at bringing to life creative AI solutions to amplify human capability in Eastern Europe. This year’s focus was to create inclusiveness through the use of AI in the retail industry.

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This report is sponsored by LG Electronics and Element AI and produced by the BriteBirch Collective.

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