Artificial Intelligence in China: Shanghai Skyline with Historical Waibaidu Bridge – A symbol of China’s blend of history and modern AI innovation.
China’s rise as a global leader in the field of Artificial Intelligence (AI) is monumental, with aspirations that reach beyond mere technological advancements. As I highlighted in my previous post, China’s AI innovations aim to tackle the challenges posed by the one-child policy, which has aged its population significantly.
This leads to an imbalance of assets and liabilities that AI, with its practical applications, can help to resolve. The stakes of AI in China signify a major shift in technological advancements and economic development.
AI and China’s Economic Growth: A Strategic Alignment
The development of AI in China is not merely about technological innovation. It’s about creating real-world solutions that align with the nation’s demographic and economic needs. Whether it’s healthcare, transportation, or financial services, Artificial Intelligence in China is changing the game.
Practical Applications of Artificial Intelligence in China: Transforming Various Sectors
From healthcare to transportation, AI is revolutionizing various sectors in China. The nation’s focus on AI innovation and its potential for practical applications are part of a broader strategy to sustain economic growth.
Artificial Intelligence in China: Learning from China’s AI Strategy
What can we learn from China’s AI endeavors? The answer lies in understanding their approach towards innovation, collaboration, and long-term planning. My book Visual Analytics with Tableau (Amazon) explores how visual analytics plays a vital role in understanding complex data structures and emerging trends, including those related to AI.
Don’t miss out on the latest insights related to AI, digital transformation, and more. Follow me on Twitter and LinkedIn to stay in the loop.
#China is one of the largest #AI markets in the world: the stakes of AI are very important for China as they represent the future of economic development. With the one-child policy, China has greatly aged its population, which will soon be in an imbalance of assets & liabilities. pic.twitter.com/Eh44EUGd1O
4 day workweek Microsoft experiment: performance boost by 40%
The 4 day workweek Microsoft experiment is a groundbreaking initiative that has captured global attention. By embracing a four-day workweek in Japan, Microsoft achieved a 40% boost in productivity. This article explores the details of the experiment, its implications, and how it aligns with the broader trends in automation and work efficiency.
The Future of Work and Automation
The 4th industrial revolution is upon us, and with it comes a new era of efficiency and productivity. Automation is transforming nearly all areas of our lives, allowing us to achieve superior results in less time. This evolution is not only reshaping our work but also improving our work–life balance. A century ago, a six-day workweek was the norm. The industrial revolution then ushered in the five-day workweek. Now, the 4-day workweek is not just a possibility but an inevitability, driven by technological advancements.
The 4-Day Workweek: A Historical Perspective
The concept of a 4-day workweek is not new, but it has gained traction in recent years. Companies like Microsoft are leading the way, recognizing that reduced working hours can lead to increased efficiency and happier employees. This shift is more than a trend; it’s a response to the changing nature of work in the digital age.
Microsoft’s Experiment: A 4-Day Workweek
In a bold move, Microsoft tested a four-day workweek in Japan, allowing employees to enjoy a three-day weekend. By limiting meetings to 30 minutes and promoting remote communication, they achieved a 40% boost in productivity, measured as sales revenue per employee. This experiment proved that a shorter workweek doesn’t mean cutting salaries; it means working smarter.
Key Observations from the 4 Day Workweek Microsoft Experiment
Productivity Boost: Sales revenue per employee increased by 39.9%.
Adoption of Short Meetings: 30-minute meeting adoption rate rose by 46%.
Remote Work Success: Remote meeting adoption rate increased by 21%.
Energy Efficiency: Power consumption decreased by 23.1%.
Positive Impact on Work and Life: Changes and effects on consciousness/behavior were observed at 96.5% for work and 97.1% for life.
Ready to embrace the future of work? Explore the 4-day workweek and other innovative strategies in Decisively Digital (Amazon). Follow me on Twitter and LinkedIn for more insights on digital transformation, artificial intelligence, and business analytics.
Everyone has experienced days that are almost completely filled with meetings. Since business trips have become redundant due to the Covid-19 pandemic and you no longer need to plan in any travel time, it is very tempting to fill in the remaining gaps in your schedule with new tasks – and in the worst case, there is no time for lunch.
Is this the type of modern work we want to experience? Below we have put together some ideas and suggestions that can help to make your working day more pleasant.
1. 5-minute breaks after meetings
A 5-minute break after a meeting can be incredibly revitalizing – especially when meetings are often back-to-back. Outlook gives you the option to automatically schedule meetings 5 minutes shorter:
Once you have shortened your meetings by 5 minutes, you need to make sure that everyone sticks to it.
2. Blocker for lunch breaks, daycare, etc.
To make sure nobody schedules a meeting during your lunch break, a lunch blocker can help you here. Just create an appointment series:
If all the colleagues in your team create a lunch blocker for the same time, it’s (almost) like having lunch together.
If you also have children who need to be taken to daycare, kindergarten, or school, an appointment series can serve the same purpose here. As it is usually possible to make calls while in the car, you can also leave a note with your phone number in the appointment series so that your colleagues know how to reach you when you’re on the road.
3. Chat und Call Etiquette
When pinging colleagues on Teams, don’t simply write “Hello”, as each message distracts them from their current task. While you are typing the remaining message, your colleague is very likely to wait until you have sent it. Even though it might seem impolite or even rushed at first, it is easier for your colleagues if you get right to the point. It is therefore a good idea to type the whole message and send it in one go.
The same goes for calls. Instead of pinging a colleague before calling them and typing “Hello” or “Hello, are you free for a quick call?” it’s better to give them some information beforehand, such as the topic and the estimated duration of the call. For example, you could write “Hello, do you have 3 minutes to discuss topic XYZ with me?” That allows your counterpart to estimate whether they can take the time for this particular call.
For more information on chat and call etiquette, check out this link: aka.ms/NoHello
4. Reduce meetings
To reduce the number of meetings you need to attend, it is helpful to ask yourself the following questions before sending out meeting invites:
Can the question be clarified by chat or email?
Is this matter urgent or can it wait until the next regular team meeting?
Do we really need to involve everyone or are fewer participants enough?
Each meeting should be critically questioned and the most important meetings prioritized. Before attending a meeting, it helps to ask yourself the question: Do I have an active contribution to make to the meeting, or do I only need to read the meeting minutes?
5. Using AI-based technologies
Do not hesitate to actively leverage AI-based technologies. MyAnalytics gives you the option to automatically block focus times. With just one click, not only dedicated times can be blocked for you, but these blockers also automatically change your status on Teams to “Don’t Disturb”. Thus you can simulate, for example, your travel times. More information about the features of MyAnalytics can be found by following this link.
Outlook also gives you various options that can help you save time and focus on the essentials. You can use email rules to automatically move mail to different Outlook folders. For example, you can determine that all cc messages are placed in a separate folder. That allows you to dedicate time to reading these messages as required. The goal is that at the end of the day your inbox is empty (zero-inbox policy) so that you can start afresh the next day. You can also deactivate Outlook push notifications so that you are not distracted by pop up notifications during important activities.
What are your ideas for a more productive workday? We’d like to read your suggestions in the comments below.
AI has to potential to save millions of lives by applying complex algorithms | Photo Credit: via Brother UK
Good health is a fundamental need for all of us. Hence, it’s no surprise that the total market size of healthcare is huge. Developed countries typically spend between 9% and 14% of their total GDP on healthcare.
The digital transformation in the healthcare sector is still in its early stages. A prominent example is the Electronic Health Record (EHR) in particular, and, in general poor quality of data. Other obstacles include data privacy concerns, risk of bias, lack of transparency, as well as legal and regulatory risks. Although all these matters have to be addressed in a Digital Strategy, the implementation of Artificial Intelligence (AI) should not hesitate!
AI has to potential to save millions of lives by applying complex algorithms to emulate human cognition in the analysis of complicated medical data. AI furthermore simplifies the lives of patients, doctors, and hospital administrators by performing or supporting tasks that are typically done by humans, but more efficiently, more quickly and at a fraction of the cost. The applications for AI in healthcare are wide-ranging. Whether it’s being used to discover links between genetic codes, to power surgical robots or even to maximize hospital efficiency, AI is reinventing modern healthcare through machines that can predict, comprehend, learn and act.
Let’s have a look at ten of the most straightforward use cases for AI in healthcare that should be considered for any Digital Strategy:
1. Predictive Care Guidance:
AI can mine demographic, geographic, laboratory and doctor visits, and historic claims data to predict an individual patient’s likelihood of developing a condition. Using this data predictive models can suggest the best possible treatment regimens and success rate of certain procedures.
2. Medical Image Intelligence:
AI brings in advanced insights into the medical imagery specifically the radiological images. Using AI providers can gain insights and conduct automatic, quantitative analysis such as identification of tumors, fast radiotherapy planning, precise surgery planning, and navigation, etc.
3. Behavior Analytics:
AI helps to solve patient registry mapping issues for and help the Human Genome Project map complicated genomic sequences to identify the link to diseases like Alzheimer’s.
4. Virtual Nursing Assistants:
Conversational-AI-powered nurse assistants can provide support patients and deliver answers with a 24/7 availability. Mobile apps keep the patients and healthcare providers connected between visits. Such AI-powered apps are also able to detect certain patterns and alert a doctor or medical staff.
5. Research and Innovation:
AI helps to identify patterns in treatments such as what treatments are better suited and efficient for certain patient demography, and this can be used to develop innovative care techniques. Deep Learning can be used to classify large amounts of research data that is available in the community at large and develop meaningful reports that can be easily consumed.
6. Population Health:
AI helps to learn why and when something happened, and then predict when it will happen again. Machine Learning (ML) applied to large data sets will help healthcare organizations find trends in their patients and populations to see adverse events such as heart attacks coming.
7. Readmissions Management:
By analyzing the historical data and the treatment data, AI models can predict, flag the causes of readmissions, patterns, etc. This can be used to reduce the hospital readmission rates and for better regulatory compliance by developing mitigating strategies for the identified causes.
8. Staffing Management:
Predictive models can be developed by analyzing various factors such as historical demand, seasonality, weather conditions, disease outbreak, etc. to forecast the demand for health care services at any given point of time. This would enable better staff management and resource planning.
9. Claims Management:
AI detects any aberrations such as – duplicate claims, policy exceptions, fictitious claims or fraud. Machine learning algorithms recognize patterns in data looking at trends, non-conformance to Benford’s law, etc. to flag suspicious claims.
10. Cost Management:
AI automates the cost management through RPA, cognitive services, which will help in faster cost adjudication. It will also enable analysis, optimization, and detection by identifying patterns in cost and flagging any anomalies.
Conclusion:
As these examples show, the wide range of possible AI use cases can improve healthcare quality and healthcare access while addressing the massive cost pressure in the healthcare sector. Strategic sequencing of use cases is mandatory to avoid implementation bottlenecks due to the scarcity of specialized talent.
Which use cases for AI in healthcare would you add to this list?
Share your favorite AI use case in the blog post comments or reply to this tweet:
China AI: The impressive Alibaba Campus in Hangzhou, a hub of innovation and intrapreneurship.
China’s AI revolution is taking the world by storm. In this journey across cities like Hangzhou, discover how China is leading the AI industry, inspiring innovation, and shaping the future.
Currently, I’m on a 4-week China trip, visiting many cities. In Hangzhou, I met CEIBS peers who work for Alibaba. While the Alibaba campus is quite impressive, I got even more impressed by Alibaba’s leadership culture, which is encouraging its employees to innovate as intrapreneurs.
Intrapreneurship at Alibaba: The China AI Model for Success
At the impressive Alibaba Campus in Hangzhou, I discovered the power of intrapreneurship. If you start your own project (a new mobile app, a patent, a scientific paper, etc.), you’re doing it at your own pace. Employees are encouraged to innovate at their own pace, without being micro-managed. Success is rewarded with bonuses. Truly, this is where we can learn from China in the „China AI“ landscape!
China’s AI Ambitions: Leading the New World Order
Yue and me, Hangzhou West Lake
While traveling in China I was reading AI Superpowers: China Silicon Valley, and the New World Order by Kai-Fu Lee, a book that is a must-read to get an idea of where China’s AI ambitions are heading to. What matters most for AI innovation these days, the author argues, is access to vast quantities of data—where China’s advantage is overwhelming.
Visualizing the Journey: Exploring my Tableau Public Viz
Which other cities in China did I visit? Check out my Tableau Public viz:
A visualization of my 2019 China Visit, exploring the cities and experiences.
Interested in Visual Analytics? Grab a copy of my latest book, Visual Analytics with Tableau (Amazon), for a comprehensive guide to mastering data visualization.
Stay Connected and Explore More on China AI
China’s AI is reshaping the global landscape. From Alibaba to the nation’s strategies, China AI inspires and challenges the world. It’s a blend of technology, culture, and energy driving China’s AI revolution.
The experiences and insights from this trip have been truly enlightening. I invite you to join me as I continue to explore the fascinating world of China AI, digital transformation, and visual analytics. Follow me on Twitter and LinkedIn, and let’s continue learning together.
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