In the first part of this series, we looked at the evolution of technology as an attempt to demystify AI and frame it as simply another innovation in human history. In this section we explore how to make AI more human by thinking beyond users of technology and instead focusing on the deep psychological needs of people by fostering positive human-centric innovation.


Given the complexity and ambiguity of AI, there is a lot of misunderstanding around the potential impact this technology will have and this raises fears in many people who cautious about a future with machines. Automation does indeed threaten to alter significantly or replace entirely some jobs, but scaremongering headlines exacerbate the threat and demonise the technology. To be human is often to be risk-adverse and skeptical of change and throughout history, our fear of technological innovation has repeated itself.

“Cybergeddon” is cancelled

The truth of the matter is that the robot apocalypse and “Cybergeddon” is not coming anytime soon. Paul Daughtery, Chief Technology Officer at Accenture suggests we are at the “pre-game stage” of AI. Before any robot apocalypse — we must develop an AGI — artificial general intelligence. This is the intelligence of a machine that could successfully perform any intellectual task that a human being can. This is an incredible complicated task and some of the largest AI projects in the world are geared towards developing an AGI and they aren’t progressing too quickly. Although deep neural networks are very good at recognizing patterns — they are not that brilliant as explanation or many of the cognitive capabilities humans have such as empathy.

The other important element to consider is the non-deterministic nature of technology. Technology alone is neither good nor evil but rather it is how we, as humans use and design it, that has the greatest impact. Ultimately it is about building and using AI responsibly with humans at the core.

We have recently been exposed to an example of non human-centric AI through the Cambridge Analytica data misuse scandal earlier this year. There have also been a number of examples of bias in data sets which imbues algorithms with racist or sexist prejudice from the humans that build them. Even though Cambridge Analytica gained access to almost 100 million Facebook users in a major breath of personal information, the impact this had was relatively small. However, as digital “fake” content gets worse as AI gets smarter and with the misuse of algorithms on the rise we are at an important watershed where we need to seriously think about how to optimize our lives in an AI future. How can we bring human-centricity to AI?

Human-Centric AI

At Brand Genetics we believe the Future is Human. When we see people in human-terms we can start to spot core opportunities to enhance their lives. This is true of new technologies throughout history. At first people are skeptical of innovation but then end up loving it when it demonstrably improves the way they live and/or work. For example, when AI is used to make more produce available in food deserts, eliminate waste supply chains and treat patients with depression — AI is attractive! What unites all of these? Human-centricity. Human-centric means understanding human behaviour with psychology, anthropology and neuroscience and looking to address real human needs in the use of AI products and services. Too often we think simply about ‘users’ of technology rather than about humans — with emotions, feelings and needs.

So how do we build human-centric AI? Think positive innovation

Many AI experts suggest that the best way to build human-centric AI is to think about collective or applied intelligence. In other words, humans and machines working together. Accenture CTO Daughtery is an advocate of this approach as it allows us to use both the best of human intelligence and cognitive processing and the best of machine intelligence to work towards an augmented and enhanced humanity.

While we wholeheartedly support this approach, and are increasingly seeking to work with machines to increase efficiencies, we believe the best potential for human-centric AI is using evidence-based behavioural science to innovate for the future. This is why we are very excited by the concept of positive innovation, a term that puts positive human experience at the heart of the innovation process to help people thrive, both online and offline. With so many anxieties and ambiguities surrounding the use of algorithms, we believe there is an opportunity to mitigate these fears and design technologies by fostering positive innovation that facilitates human wellbeing.

In the final part of this series we explore some of the ways brands and businesses are already doing this: by combining behavioural science and data analytics companies like McDonalds and JP Morgan are successfully creating innovations enhancing human wellbeing which are as good for people as they are profit!

Clemmie Prendergast is a consultant at Brand Genetics, an insight and innovation agency specialising in human-centred insight and innovation. With a background in anthropology, she has a wealth of experience in behavioural science and psychology and has worked in strategy, insight and behaviour change.

Human-Centered Insight, Innovation and Trends from Brand Genetics www.brandgenetics.com

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