How can we meet customer concerns with facial and body recognition?
New Zealand's contact-tracing app is one of the first national tech efforts against COVID-19. As with other facial and body recognition tech though, questions of privacy will inevitably arise.
The potential of biometric data is starting to be realised, Accenture and Fjord report, with several world-leading organisations readily adopting facial and body recognition systems.
In China Alibaba’s Smile to Pay facial recognition payment simply scans a smile. Governments are using it too, with India planning the world’s largest facial recognition system and the Pentagon investing in technology that identifies people by their unique heartbeat.
It is important to approach these innovations with caution.. There’s the real risk biometric apps could make us, and our customers, feel like a human barcode – scanned and transacted upon.
5G and personalisation of the future
Speeding things up, 5G mobile will go mainstream in 2020. Predicted to generate the majority of global media revenues by 2025, Accenture’s latest Fjord report foresees that the impact of biometric data will go far beyond just faster data connection.
Industries will be transformed. Annual mobile media revenues are predicted to double in the next ten years to US$420 billion, the report says.
There’ll be new possibilities for personalised real-time experience from biometric data within physical spaces. We’ll move away from kiosk-type transactions, and toward new service designs that make invisible data transactions more valuable.
We’re not far off, the Fjord report says, from a world where a person can wear an internet-connected glove, and have their movements mimicked in real-time by a robot in another geographic location.
New organisational models, such as bundling of packages and more effective advertising to supercharge businesses to work in real-time, are likely to also arise.
Customer-first with privacy concerns
With technology more integrated in our daily lives, there are opportunities for closer relationships between business and consumer – but questions about privacy must be heard. Fjord recommends three ways to manage your biometric strategy in a customer friendly manner:
1.Unlock services with biometrics.
Have you audited your customer interaction recently?
Is it as frictionless as it could be? Examine questions of convenience, consent and communications to create new service opportunities.
2. Advocate for data minimalism.
Data breaching in biometrics are more severe than past ways of drawing insight. Both business staff and customer should be made aware of and in alignment with this.
3. Make the invisible visible.
Customers of the future want to be curators of their own personalised experiences – so build a platform in line with what they want.
Ensure customers understand where – and when – a scan, transaction or consent has occurred.
Data, AI, BI & ML
Artificial Intelligence and Machine Learning are the terms of computer science. Artificial Intelligence : The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”. Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think. There is a misconception that Artificial Intelligence is a system, but it is not a system. AI is implemented in the system. There can be so many definition of AI, one definition can be “It is the study of how to train the computers so that computers can do things which at present human can do better.” Therefore it is an intelligence where we want to add all the capabilities to machine that human contain. Machine Learning : Machine Learning is the learning in which machine can learn by its own without being explicitly programmed. It is an application of AI that provide system the ability to automatically learn and improve from experience. Here we can generate a program by integrating input and output of that program. One of the simple definition of the Machine Learning is “Machine Learning is said to learn from experience E w.r.t some class of task T and a performance measure P if learners performance at the task in the class as measured by P improves with experiences.”