Data Protection Day - Key developments and trends for 2023

28 January 2023 is Data Protection Day (or Data Privacy Day outside of Europe), which marks the anniversary of the Council of Europe’s Convention 108.

To mark Data Protection Day 2023, Baker McKenzie’s Global Data Privacy and Security Team is pleased to present this special edition update of key data protection and privacy developments and trends across the globe, as well summarising future legislative changes, predictions, and enforcement priorities to look out for during 2023.

International data transfers continue to be a significant area of focus, particularly from an EU perspective. The practical implications of the Schrems II judgment are still being felt by organisations and grappled with by data protection authorities, and related developments are on the horizon with the recently published draft adequacy decision for the EU-US Data Privacy Framework (you can read more in our update here). There are emerging trends in enforcement action from EU data protection authorities shining a light on issues such as transparency and privacy notice information, as well as the legal basis for processing personal data, particularly in the context of online behavioural advertising.

Outside of the EU, there is a proliferation of new privacy laws and amendments to existing privacy laws to keep up with. These range from new laws (or amendments to existing laws) which have now come into force, laws or amendments that are expected to come into force this year, as well as discussions or proposals for future reforms. In particular, there are developments to be aware of in Australia, Japan, Taiwan, Vietnam, India, Qatar, UAE, Saudi Arabia, Türkiye, Canada, Argentina, Vietnam, Switzerland, several US states and the UK. Almost half of these are G20 economies so we except such changes will be important given the inextricable link between information driven trade ecosystems.

Children’s personal data continues to be high up on the agenda across the globe. In the UK, this is reflected in the ICO’s Age Appropriate Design Code, and in the US, with the California Age-Appropriate Design Code Act (you can read more in our update here). Children’s online safety is also an important topic of wider focus in addition to data protection, and you can read more about this in our specially commissioned report “Online child safety: an opportunity to get it right” led by Elizabeth Denham of Baker McKenzie and produced jointly with Milltown Partners (available here).

You can find more information on these developments and trends and many others in our summary below. You can also jump to specific country overviews using the links below.

If you have any specific questions, please do not hesitate to get in touch with your usual Baker McKenzie Data Privacy and Security contacts.

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Pandemic awakens demand for data-driven automation

 

Supply chain disruptions from COVID-19 drive Samsung, LGES, Hyundai Motor toward 'lighthouse manufacturing'

By Kim Yoo-chul

The COVID-19 pandemic was an opportunity for manufacturers in global supply chain systems to embrace significant challenges. Korean conglomerates like Samsung, LG and SK groups also had to adjust to the crisis by revamping their supply chains and embracing more innovative manufacturing processes.

Steps taken by advanced and emerging economies to control their coronavirus infection spikes resulted in national lockdowns and temporary halts in the flow of raw materials and subsidiary products, which as a consequence disrupted manufacturing processes.

The pandemic itself didn't necessarily bring about any new challenges in supply chains because in some business areas it merely shone a light on earlier unseen vulnerabilities, including increased inventory levels due to closures, and resultant profit losses. Executives at Korea's leading exporters noted that the pandemic accelerated the identification of problems that already existed in supply chains.

Sources and executives at Samsung, LG and SK groups' technology units told The Korea Times that COVID forced them to make their supply chain strategies more sustainable, resilient and even collaborative with key stakeholders such as suppliers and customers.

"Companies usually scale back their investments in a crisis, however, during the pandemic, Samsung didn't stop investing in technology improvements, highlighting the company's focus on the value of a digitally-connected supply chain to help the firm respond quickly to volatile supply and demand situations," an official at one the conglomerates said.

Last year, Samsung Electronics, the world's top manufacturer of TVs, smartphones and memory chips, said it planned to spend 450 trillion won on "focus areas," specifically artificial intelligence (AI) and application semiconductors. Company representatives said Samsung is also working on advanced robots and AI.

In January, Samsung invested $46 million in domestic robot maker Rainbow Robotics. This move, which gave it a 10.3 percent stake in the firm, was seen as showing its commitment towards advancing supply chain technologies such as AI, data analytics, and robotic process automation and control towers, while retaining its current staffing system. "Maintaining a high-performing supply chain in terms of both efficiency and visibility has become a competitive necessity," another company official said.

Transitional path, Foxconn model

However, officials at the country's leading exporters said while they have no questions about the necessity of updating supply chains for resilience and operational excellence, it's highly unlikely that manufacturers will see any visible progress in the smart factory concept in the near future.

"Data acquisition and analysis, and factory automation are required for a smart factory because it is more about a high level of customization and how factories operate," said Jeong Hong-beom, an executive in charge of handling smart factory-oriented strategies at Hyundai Motor, the country's top automaker. Crucial to a smart factory is the technology that makes data collection possible, which includes sensors, motors and robotics on actual production and assembly lines.

Because the basic structure of a smart factory includes the integration of information, communication and production technologies, with the potential for integration across manufacturing supply chains made possible via the internet-of-things (IoT), a presidential aide handling industrial policies under the former Moon Jae-in administration said it should be possible for Korean firms to pursue hybrid models according to different production bases as part of efforts to initiate smart factories.

"Simply put, smart factories require a shift in mindset because they are about data management and not just factory automation. Smart factory initiatives are complex to execute and require the backing of employees and business units. Such initiatives could also face resistance to change and cause confusion inside an organization. Given the regulatory risk in terms of data transparency, auditability and labor-centric business structures, Korean manufacturers will remain in the early stages of this for a considerable period of time," the unnamed aide said.

LG Energy Solution (LGES), for example, has recently created a chief data officer (CDO) position, as part of efforts to establish a data-driven smart factory structure. A spokesman at the top battery supplier for Tesla, said it is still in the process of hiring specialists, and classifying data for specific purposes. As a long-term strategy, the spokesman said LGES aims to get potential clients to think more about smart manufacturing utilizing robotics, data analytics and AI.

Min Kyeong-do, an executive at Gaon Partners, a consulting company, said what is happening inside Taiwan's Foxconn is worth watching for Korean manufacturers, which have substantial overseas exposure, as the world's top maker of electronic components is taking steps to build data-driven lighthouse manufacturing networks in the wake of supply chain disruptions.

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Consumer Robotics: How Artificial Intelligence Is Changing The Game

 

The future of consumer robotics is bright and full of possibilities. As technology advances, robots are becoming more and more integrated into our daily lives, performing tasks that were once considered the exclusive domain of humans. From vacuum cleaners and lawnmowers to personal assistants and healthcare workers, robots are increasingly becoming a common sight in homes and businesses worldwide.


One area where consumer robotics will soon be making a huge impact is in the home. With the rise of smart homes and the Internet of Things (IoT), robots can interact with other devices and systems in the home to automate tasks and make life easier for homeowners. For example, a robotic vacuum cleaner could automatically be programmed to clean the house every day. At the same time, a smart thermostat could adjust the temperature based on the homeowner's preferences.

When Consumer Robots Get A Brain

Artificial intelligence (AI) is revolutionizing the field of consumer robotics by enabling robots to perform tasks more efficiently, accurately and independently. With its ability to process large amounts of data and make decisions based on that data, AI is being used to enhance consumer robots' capabilities in various ways.


One of the primary ways that AI is being used in consumer robotics is to improve the ability of robots to interact with their environment and perform tasks. A robot vacuum cleaner equipped with AI will be able to learn the layout of a home over time, allowing it to clean more effectively and efficiently, becoming more personalized over time.

AI is also being used to improve consumer robots' communication and social skills. For example, AI can be used to enable robots to recognize and respond to human emotions, as well as to engage in conversation and interact with people in more natural and human-like ways. This can be useful in applications such as personal assistants or home healthcare robots, where the ability to communicate and interact with people is critical.
The Future Of Play
Robotics can be used in smart toys to provide children with an interactive and engaging learning experience. These toys often incorporate sensors, motors and other electronic components that allow them to move, respond to stimuli and perform various tasks.

more info : https://www.forbes.com/sites/forbestechcouncil/2023/01/27/consumer-robotics-how-artificial-intelligence-is-changing-the-game/?sh=6abddd205b93

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UAE lunar rover will test 1st artificial intelligence on the moon with Canada

The moon is about to host one giant leap in artificial intelligence (AI).


A Canadian machine learning system will make its way to the moon's surface onboard a United Arab Emirates rover that launched with SpaceX Dec. 11.

The Rashid rover, hosted on the Japanese ispace lander, is expected to touch down this spring in search of minerals and other items of interest on the lunar surface. Canada's system will inform the rover's decision-making in a big first for AI: No AI has ever reached beyond low Earth orbit before, company officials say.

If this works, the tech will be big for NASA's moon push, Mission Control Space Services (MCSS) CEO Ewan Reid told Space.com. "AI will be a critical enabling tool to making decisions on board spacecraft," Reid said. That work not only extends to seeking out water on the moon, which NASA plans to do with its Artemis missions, but also to making Earth observation more efficient. And MCSS, a company of just 40 people so far, aims to be in the driver's seat.

When most people think of Canadian tech in space, they think of flashy projects like Canadarm: The robotic arm series that has served the shuttle, the International Space Station and soon, NASA's Gateway lunar station. More astute observers may also cite space medicine or even rocketry as tech fields in which Canada has expertise.

MCSS represents what many small space Canadian companies do, however: provide essential software or components that fly in the background, fueling missions all over the world. The company doesn't advertise all of its work; often MCSS customers want media attention on their own mission, Reid said.

"That's why this [AI] demonstration with the Canadian Space Agency is nice, because it's very much in the public domain and we're allowed to talk about it," Reid said.

If all goes to plan, Rashid will run for approximately one lunar day (29 Earth days) on the surface. It is not expected to last the lunar night, but as a demonstration mission that's just fine for MCSS. It has plans to leverage a lot from a few precious days on the moon.

more info :https://space.com/moon-artificial-intelligence-system-first-solar-system

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Doctors, Get Ready for Your AI Assistants

In 2023, radiologists in hospitals around the world will increasingly use medical images—which include x-rays and CT, MRI, and PET scans—that have been first read and evaluated by AI machines. Gastroenterologists will also be relying on machine vision during colonoscopies and endoscopies to pick up polyps that would otherwise be missed.

This progress has been made possible by the extensive validation of “machine eyes”—deep neural networks trained with hundreds of thousands of images that can accurately pick up things human experts can’t. One of the most exciting new capabilities of AI is to instruct untrained and uninitiated people to acquire medical-grade images through a smartphone. Someone without any medical knowledge will be able to pop an ultrasound transducer into a smartphone’s base and, with a little gel on its tip, instantly acquire high-quality images. The AI algorithm instructs the person to move the transducer up or down, clock- or counterclockwise, and it will automatically capture the image when it meets the objective standard. This will extend the ability to perform medical imaging of most parts of the body (except the brain), anywhere, anytime, and by anyone. Concurrently, algorithms are also being developed for automated accurate interpretations. In 2023, we will see more of this in remote parts of the world, perhaps best exemplifying the potential for AI to reduce health inequities.

The same deep-learning democratization is progressively taking hold for patients as well, who can already be notified by their smartwatch’s algorithm that they have an abnormal heart rhythm (such as atrial fibrillation). In 2023, this will extend to preliminary diagnosis of all skin lesions, urinary tract infections, children’s ear infections, and an increasing number of common conditions that are not life-threatening.

These are the early steps towards a virtual health coach to ideally prevent conditions that a person is at increased risk for manifesting, which in 2023 will be used for managing specific conditions such as diabetes, hypertension, or even depression, with the help of chatbots and human coaches in the background when necessary.


In 2023, clinicians will also be aided by AI in their daily tasks—particularly by being liberated from the job of painstakingly typing medical data into the computer. This burden not only contributes to burnout among physicians, but markedly detracts from the patient interactions. Natural language processing and machine learning now enable synthetic notes to be created automatically from the conversation between doctors and patients at the visit or bedside.

We have seen the beginning of use of AI for remote monitoring, which is already preempting the need for hospitalization for patients with Covid-19 by real-time data capture from wearable sensors. That will only increase in 2023. We still need more validation trials to show that algorithms can accurately anticipate early signs of clinical deterioration and intervene, but the implication for avoiding a large proportion of hospital stays looms large.

Nevertheless, there remains a dire need to reduce bias and promote privacy and security in the application of medical AI. Privacy AI computing is starting to take off with the use of federated and swarm learning, as well as with the increasing application of edge computing, which uses algorithms fully operating on the smartphone. In 2023, these strategies will be explored more fully, in a much-needed effort to not only fully investigate the potential for AI in health and medicine but also to address its potential flaws and pitfalls.

 more info : https://www.wired.co.uk/article/artificial-intelligence-medicine-machine-vision

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Analysts Offer Predictions for Automatic Data Processing, Inc.'s Q1 2024 Earnings (NASDAQ:ADP)

Automatic Data Processing, Inc. (NASDAQ:ADP - Get Rating) - Equities research analysts at Jefferies Financial Group issued their Q1 2024 EPS estimates for shares of Automatic Data Processing in a research note issued on Wednesday, January 25th. Jefferies Financial Group analyst S. Samana expects that the business services provider will earn $2.08 per share for the quarter. The consensus estimate for Automatic Data Processing's current full-year earnings is $8.12 per share. Jefferies Financial Group also issued estimates for Automatic Data Processing's Q2 2024 earnings at $2.20 EPS, Q3 2024 earnings at $2.68 EPS, Q4 2024 earnings at $2.04 EPS and FY2025 earnings at $9.78 EPS.

A number of other brokerages also recently weighed in on ADP. Robert W. Baird increased their price target on shares of Automatic Data Processing to $251.00 in a research report on Tuesday, November 1st. Morgan Stanley raised their target price on shares of Automatic Data Processing from $245.00 to $250.00 and gave the stock an "equal weight" rating in a report on Thursday, October 27th. Mizuho dropped their target price on shares of Automatic Data Processing from $285.00 to $275.00 and set a "buy" rating on the stock in a report on Thursday. Wolfe Research raised their price target on shares of Automatic Data Processing from $220.00 to $225.00 in a research note on Thursday, January 5th. Finally, Cowen raised their price target on shares of Automatic Data Processing to $237.00 in a research note on Thursday, October 27th. One analyst has rated the stock with a sell rating, four have issued a hold rating and three have issued a buy rating to the company. According to data from MarketBeat, Automatic Data Processing presently has an average rating of "Hold" and an average target price of $243.67.

more info :https://www.marketbeat.com/instant-alerts/nasdaq-adp-analyst-earnings-estimates-2023-01-27/

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