May 17, 2020

LG’s AI washing machine latest step on smart device march

AI
IoT
William Smith
2 min
The integration of smart technologies into everyday items continues at pace
The integration of smart technologies into everyday items continues at pace, with any and every domestic item seemingly ripe for the application of the...

The integration of smart technologies into everyday items continues at pace, with any and every domestic item seemingly ripe for the application of the “smart” prefix. The latest example comes from South Korea’s LG Electronics, and its newly announced AI powered washing machines.

Coming to European markets by the end of the year under the company’s smart device brand, ThinQ, the machines incorporate so-called Direct Drive technology. In its press release, the company said that 20,000 data points were tracked by the technology in order to optimise the washing cycle. The machine also accepts commands from connected smart speakers and mobile apps.

“The combination of ThinQ AI with LG’s proven Direct Drive technology delivers customer benefits that are more significant than anything in the evolution of washing machines in the past century,” said Song Dae-hyun, president of LG Electronics Home Appliance and Air Solution Company.

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The devices represent the consumer end of the IoT space, demonstrating the applicability of the technology to the home environment. As much as they might add convenience for consumers however, it is businesses who are able to reap the biggest rewards.

Smart appliances are big business, with PwC estimating that £10.8bn will be spent on smart home devices in the UK alone in 2019. One of the key sticking points for consumers, and one of the key drivers for business, is the data that such technologies are able to gather. While consumers might fear the security risk, businesses are able to collect an unprecedented amount of data on the use of their products, allowing them to refine, tailor and improve their offerings and potentially revolutionise the ways that they do business.

Rob Holston, EY’s Global Consumer Products Commercial Analytics Leader, was quoted in a company blog post as saying: “While connected devices and the rise of availability of customer data can lead to some obvious insights and ways to improve products in the short-term, businesses need to step back and rethink their fundamental assumptions about their industries.”

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Jun 21, 2021

ICO warns of privacy concerns on the use of LFR technology

Technology
ICO
LFR
cameras
3 min
Organisations need to justify their use of live facial recognition (LFR) is fair, necessary, and proportionate, says the Information Commissioner’s Office

Live facial recognition (LFR) technology should not be used simply because it is available and must be used for a specific purpose, the Information Commissioner’s Office (ICO) has warned.

“I am deeply concerned about the potential for live facial recognition (LFR) technology to be used inappropriately, excessively, or even recklessly. When sensitive personal data is collected on a mass scale without people’s knowledge, choice or control, the impacts could be significant,” said Elizabeth Denham, the UK’s Information Commissioner.

Denham explained that with any new technology, building public trust and confidence in the way people’s information is used is crucial so the benefits derived from the technology can be fully realised.

“It is not my role to endorse or ban a technology but, while this technology is developing and not widely deployed, we have an opportunity to ensure it does not expand without due regard for data protection,” Denham added.

The Information Commissioner’s Office has said it will work with organisations to ensure that the use of LFR is lawful, and that a fair balance is struck between their own purposes and the interests and rights of the public. They will also engage with Government, regulators and industry, as well as international colleagues to make sure data protection and innovation can continue to work hand in hand.
 

What is live facial recognition? 

Facial recognition is the process by which a person can be identified or recognised from a digital facial image. Cameras are used to capture these images and FRT software measures and analyses facial features to produce a biometric template. This typically enables the user to identify, authenticate or verify, or categorise individuals. 

Live facial recognition (LFR) is a type of FRT that allows this process to take place automatically and in real-time. LFR is typically deployed in a similar way to traditional CCTV in that it is directed towards everyone in a particular area rather than specific individuals. It can capture the biometric data of all individuals passing within range of the camera indiscriminately, as opposed to more targeted “one-to-one” data processing. This can involve the collection of biometric data on a mass scale and there is often a lack of awareness, choice or control for the individual in this process. 

 

Why is biometric data particularly sensitive?

Biometrics are physical or behavioural human characteristics that can be used to digitally identify a person to grant access to systems, devices, or data. Biometric data extracted from a facial image can be used to uniquely identify an individual in a range of different contexts. It can also be used to estimate or infer other characteristics, such as their age, sex, gender, or ethnicity.

The security of the biometric authentication data is vitally important, even more than the security of passwords, since passwords can be easily changed if they are exposed. A fingerprint or retinal scan, however, is immutable. 

The UK courts have concluded that “like fingerprints and DNA [a facial biometric template] is information of an “intrinsically private” character.” LFR can collect this data without any direct engagement with the individual. Given that LFR relies on the use of sensitive personal data, the public must have confidence that its use is lawful, fair, transparent, and meets the other standards set out in data protection legislation.

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