Human-centred AI is focused on creating an ethically designed algorithm, which has learnt from human input and collaboration.
With recent developments in the space, such as Google's LaMDA being labelled 'sentient' by an (ex) Google engineer, it is important to define how the future of AI will develop, and how it can best aid humanity.
AI discussions in recent years have taken one of two pathways:
- The human-centred approach. The view that AI will never be able to replace the creativity and intelligence of humans,.
- The machine autonomy approach. This sees humans as unable to think as logically or quickly as AI. This makes AI far more efficient, and free from the biases humans have. In theory at least.
But which one is better for your business? Which can help marketers the most? Which flag should you be flying? Who's jersey should you be wearing? Who are you fighting for in the punch-up at halftime?
By developing machine intelligence with the goal of understanding emotion, behaviour, and human language, human-centred AI bridges the gap between machine and human beings. This is pretty darn good news for your customer experience.
I know, I know. This all sounds a bit sci-fi. A bit utopian. Or dystopian, whether you're a glass-full or glass-empty type of marketer. But it could be a game-changer.
Human-centred AI responds to the autonomous theory by suggesting that machines can't replicate human-ness accurately enough to be impactful, missing out on the nuances of creativity. Therefore, humans have to resist allowing algorithms to take full control, and instead allow them to complement and strengthen activities instead. Sounds good to me, a writer. Please don't steal my job, robots.
So, a human-centred approach advocates for a more effective experience between machines and humans, which keeps the experience, safety, and health of humans and users in mind.
And with the global AI market predicted to reach $190.61B market value by 2025, the primary intent of ML and AI needs to be established ASAP.
Right, back to businesses, brands, and marketers. This human-centred AI can help you in many ways. It can scrutinise data through the lens of human behaviour. It can help you understand your customer base in a more effective manner.
It can even mean freeing up employees for more complex, creative, and fulfilling tasks. It basically takes everything you're doing now, adding ease, whilst still keeping the humanity needed for great CX at the forefront.
In fact, AI augmentation is predicted to have created $2T in business value by 2021. This value is equal to 6B hours of worker productivity globally. And by 2023, 40% of infrastructure and operations (I&O) teams will use AI-augmented automation in large enterprises, freeing up IT personnel’s time for strategic work.
“Businesses are needing a deeper understanding of customer activity and the life events that are happening for them, such as purchasing a home or car or having a child, that is consistent with the privacy rights and expectations of their customers yet allows for better and more proactive customer service,” explains Luis Chiang, Salesforce Innovation Unit leader for IBM EMEA.
“It's about starting with a ‘design thinking’ user-centric process that gives IBM real empathy for what our client is trying to do for their businesses, how they're trying to do it, and then building the technology around their interactions. This can help them serve their customers in more immediate ways with a lot deeper intelligence and personalisation.”
This approach to AI means delivering solutions which meet evolving employee and customer needs and expectations.
But let's take a deeper look into some of the benefits, shall we?
Improved Software and Products
One benefit to human-centred AI is the ability to develop more successful software and improve product building. By applying the principles of behavioural science to technology through human-centred AI, there is an opportunity for developers and product designers to develop advanced products, i.e. products and experiences which are exactly what your customers want and need
They'll be able to use data and insights to determine user behaviour, preferences, and subconscious patterns to develop products which are more informed, and therefore are more satisfying and enriching. The user experience is placed in the foreground, with rewarding experiences being identifiable and easier to apply.
CX at scale
So, as we've mentioned above, human-centred AI provides the potential to develop next-level human and customer-centred marketing and business models.
Though, with 65% of customers say a positive brand experience is more influential than great advertising, providing this great CX is vital.
However, it is easy for marketing to become intrusive, which can damage customer and user experiences. In fact, 32% of customers say they will walk away from a brand they love after just one negative experience.
This is where human-centric AI can step in. It can allow marketers to deliver the best customer experience to each distinct client and then allow you to scale this experience.
First up, it shows you whom to target. This means gaining insights into how to segment customers, and knowing where they are in their self-directed customer journey. Then, you can gain information on what to say in your messages, and whether you need to include an offer.
Then it's all about when to engage. When will someone be responsive to your messaging? What digital channels should you be connecting with them on? With the amount of offline and online channels, it's often difficult to decide. Human-centred AI helps with all of these insights and decisions.
This AI also helps when developing personalised customer experiences. When customers are provided with a good technological experience, such as a helpful chatbot, a personalised email, or a website feature which works perfectly, they'll associate positive feelings with the brand which provided it. Or they'll not notice. But they definitely will notice when something doesn't work.
However, personalisation can only happen in this way when human needs, wants, emotions, and behaviours are taken into account during the development of technology. So, basing AI development on human psychology and behaviour leads to products which offer a satisfying, enriching, and fulfilling customer experience.
Human-centred AI leverages the strengths of human insight and machine learning to take the best, and remove the worst, from each side's abilities. The result is easier and quicker processes, and more precise algorithms, all built from human values.
So, businesses will benefit from being able to make highly informed decisions that have the potential to deliver effective outcomes, using applications of predictive analytics in important use cases.
The goal of human-centred AI is not to replace human decision-making, but to enhance our abilities by way of intelligent, human-informed technology. This leads to more informed decisions, clearer strategies, and better solutions to challenges.
Reliability and Scalability
This AI takes human thinking abilities and allows our ideas to scale to serve much larger data needs.
Without the input of human intervention, AI can only help so much. So, taking a human-centric AI approach takes some of the weight from the shoulders of the human users. It can give some of the computational heavy liftings to the AI, while still implementing the emotional and cognitive input from the human beings. This allows for the expansion of data and processes on a larger scale, whilst not compromising data integrity or increasing spending on human resources.
This basically offers a more dependable solution to being reliant on one or the other. Whilst we've been through the idea that algorithms are seen to be the more reliable choice, combining the two is far more effective.
If humans become reliant on fully automated algorithms, it can be easy to lose the ability to handle situations when those algorithms don't work. So, people should always be present in order to be an alternative for an edge case, when the AI is unsure how to respond or responds incorrectly. By keeping humanity centred in AI, we don't have to be fully reliant on algorithms that will sometimes fail.
Shock horror: algorithms might not be the answer to solving the problems of human bias. In fact, algorithms can actually perpetuate and amplify biases through feedback loops. It took less than 24 hours for Twitter to corrupt an AI chatbot introduced by the site, leading it to parrot back racist, misogynistic, and offensive content.
So, unchecked a biased algorithm won't provide objective, neutral decisions, which can be especially dangerous if the algorithm is being used to make important decisions, for cases like loans, job candidates, and parole.
This is made even worse when the AI is considered 'unbiased', with these biased opinions and other issues coming to be seen as objective, computer-decided facts.
The human approach, therefore, keeps humans in the loop when building AI, so they can monitor for bias in algorithmic decisions. The approach enables a checks and balances system which means neither the humans nor the AI have complete control, and are autonomous, meaning it is easier to identify ways to make outcomes more inclusive.