Category Archives: Artificial Intelligence
The Impending Artificial Intelligence Revolution in Healthcare – Op-Ed – HIT Consultant
Harjinder Sandhu, CEO of Saykara
For at least a decade, healthcare luminaries have been predicting the coming AI revolution. In other fields, AI has evolved beyond the hype and has begun to showcase real and transformative applications: autonomous vehicles, fraud detection, personalized shopping, virtual assistants, and so on. The list is long and impressive. But in healthcare, despite the expectations and the tremendous potential in improving the delivery of care, the AI revolution is just getting started. There have been definite advancements in areas such as diagnostic imaging, logistics within healthcare, and speech recognition for documentation. Still, the realm of AI technologies that impact the cost and quality of patient care continues to be rather narrow today.
Why has AI been slow in delivering change in the care processes of healthcare? With a wealth of new AI algorithms and computing power ready to take on new challenges, the limiting function in AIs successful application has been the availability of meaningful data sets to train on. This is surprising to many, given that EHRs were supposed to have solved the data barrier.
The promise of EHRs was that they would create a wealth of actionable data that could be leveraged for better patient care. Unfortunately, this promise never fully materialized. Most of the interesting information that can be captured in the course of patient care either is not or is captured minimally or inconsistently. Often, just enough information is recorded in the EHR to support billing and is in plain text (not actionable) form. Worse, documentation requirements have had a serious impact on physicians, to whom it ultimately fell to input much of that data. Burnout and job dissatisfaction among physicians have become endemic.
EHRs didnt create the documentation challenge. But using an EHR in the exam room can significantly detract from patient care. Speech recognition has come a long way since then, although it hasnt changed that fundamental dynamic of the screen interaction that takes away from the patient. Indeed, using speech recognition, physicians stare at the screen even more intently as they must be mindful of mistakes that the speech recognition system may generate.
Having been involved in the advancement of speech recognition in the healthcare domain and been witness to its successes and failures, I continue to believe that the next stage in the evolution of this technology would be to free physicians from the tyranny of the screen. To evolve from speech recognition systems to AI-based virtual scribes that listen to doctor-patient conversations, creating notes, and entering orders.
Using a human scribe solves a significant part of the problem for physicians scribes relieve the physician of having to enter data manually. For many physicians, a scribe has allowed them to reclaim their work lives (they can focus on patients rather than computers) as well as their personal lives (fewer evening hours completing patient notes). However, the inherent cost of both training and then employing a scribe has led to many efforts to build digital counterparts, AI-based scribes that can replicate the work of a human scribe.
Building an AI scribe is hard. It requires a substantially more sophisticated system than the current generation of speech recognition systems. Interpreting natural language conversation is one of the next major frontiers for AI in any domain. The current generation of virtual assistants, like Alexa and Siri, simplify the challenge by putting boundaries on speech, forcing a user, for example, to express a single idea at a time, within a few seconds and within the boundaries of a list of skills that these systems know how to interpret.
In contrast, an AI system that is listening to doctor-patient conversations must deal with the complexity of human speech and narrative. A patient visit could last five minutes or an hour, the speech involves at least two parties (the doctor and the patient), and a patients visit can meander to irrelevant details and branches that dont necessarily contribute to a physician making their diagnosis.
As a result of the complexity of conversational speech, it is still quite early for fully autonomous AI scribes. In the meantime, augmented AI scribes, AI systems augmented by human power, are filling in the gaps of AI competency and allowing these systems to succeed while incrementally chipping away at the goal of making these systems fully autonomous. These systems are beginning to do more than simply relieve doctors of the burden of documentation, though that is obviously important. The real transformative impact will be from capturing a comprehensive set of data about a patient journey in a structured and consistent fashion and putting that into the medical records, thereby building a base for all other AI applications to come.
About Harjinder Sandhu
Harjinder Sandhu, CEO of Saykara, a company leveraging the power and simplicity of the human voice to make delivering great care easier while streamlining physician workflow
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The Impending Artificial Intelligence Revolution in Healthcare - Op-Ed - HIT Consultant
Intuality Inc.’s Artificial Intelligence Making Accurate Predictions of Coronavirus Cases and Deaths – PRNewswire
WINSTON SALEM, N.C., May 5, 2020 /PRNewswire/ --Grant Renier, Chairman of IntualityInc., and Dr. Howard Rankin have been presenting, during weekly YouTube podcasts, the results of the system's cases and deaths for each of 120 days into the future since March, for the USA, Canada, UK, and 5 major EU countries.IntualityAI is tracking and predicting in real-time 500+ countries and governmental districts worldwide, as a free public service during this world-wide crisis.
"The numbers have been pretty accurate so far," says Grant Renier.So, what does IntualityAI predict about the future?
"We see a slight flattening of the curve by early July, but a second spike appearing in August. The system predicts the cumulative number of deaths in the US up to 103,000 by August 24," Grant continued.
Similar patterns are charted for the UK and Canada. By August 24, the system predicts a cumulative total of 6,800 deaths in Canada, and slightly over 38,000 deaths in the UK.
IntualityAI, the behavioral economics-based technology, has had success in forecasting in money markets, elections, sports, health and technology applications. It is the product of more than 30 years of research and development.
Dr. Howard Rankin, an expert in cognitive bias and author of "I Think Therefore I Am Wrong: A Guide to Bias, Political Correctness, Fake News and the Future of Mankind," along with Mr. Renier, hasbeen running IntualityAI podcasts related to COVID-19 atleast once a week.Accessthem on YouTube under"IntualityAI"and onitswebsite at http://www.intualityai.com.
Contact: GrantRenierPhone: 207.370.1330Email: [emailprotected]
Alt Contact: Dr. Howard RankinPhone: 843.247.2980Email: [emailprotected]
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intualityai-covid-19-prediction.png IntualityAI COVID-19 Prediction Accuracy AI prediction engine continues to predict daily COVID-19 cases and deaths within 2% of actual, since April 10, 2020.
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Company website
SOURCE Intuality Inc
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Intuality Inc.'s Artificial Intelligence Making Accurate Predictions of Coronavirus Cases and Deaths - PRNewswire
How is Artificial Intelligence Disrupting the Media and Entertainment Sector? | Head to Quantzig’s Recent Article for Comprehensive Insights -…
LONDON--(BUSINESS WIRE)--Quantzig, a global data analytics and advisory firm, that delivers actionable analytics solutions to resolve complex business problems has announced the completion of its latest article that explains how artificial intelligence is transforming the media and entertainment industry.
AI and analytics is crucial from a business perspective and plays a pivotal role in driving outcomes in the media and entertainment industry. Request a FREE proposal to learn more about the business benefits of predictive analytics.
Amid the rising demand for OTT and online streaming services, media and entertainment companies face multiple challenges that can be attributed to factors such as demand fluctuations, unpredictable traffic, and personalization of services. Companies in the media and entertainment sector are investing a significant portion of their budget to improve bandwidth for streaming content seamlessly, unaware of the benefits they can obtain by using artificial intelligence to personalize user experience and search optimization while improving content-creation and production processes. Additionally, media companies can leverage artificial intelligence to automate operations and drive decision-making. In this article, we have highlighted a few benefits of artificial intelligence in the media and entertainment industry that can help companies to gather data at scale and improve the consumer experience.
Talk to our analytics experts for comprehensive insights on how our analytics can help you navigate the crisis by making better, well-informed business decisions.
According to Quantzigs advanced analytics experts, Artificial intelligence enables media and entertainment companies to precisely target audiences based on their media consumption patterns, increasing the chance of a conversion.
Benefits of Leveraging Artificial Intelligence in the Media and Entertainment Sector
At Quantzig, we understand the challenges faced by media service providers amid the crisis. To help them emerge successfully, our advanced analytics experts analyze the role of AI and analytics in driving better outcomes by shedding light on its benefits:
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About Quantzig
Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. For more than 15 years, we have assisted our clients across the globe with end-to-end data modeling capabilities to leverage analytics for prudent decision making. Today, our firm consists of 120+ clients, including 45 Fortune 500 companies. For more information on our engagement policies and pricing plans, visit: https://www.quantzig.com/request-for-proposal
How Artificial Intelligence could help Wales prevent the spread of Covid-19 – Nation.Cymru
Photo by engin akyurt on Unsplash
Keith Darlington, AI consultant and author
As most of the world has now gone into lockdown, the entire scientific research community has gone into overdrive trying to understand the nature of the COVID-19 virus.
Technology, including Artificial Intelligence (AI), is helping with this task. From the beginning, AI applications have been working behind the scenes assisting the limitations of human knowledge in this massive endeavour. In this article, I briefly describe examples of different ways that this is happening.
Machine learning, as it is known, is the main driving force behind AI. In essence, what machine learning does is to take large amounts of data called Big Data and learns to detect patterns in the data. Future outcomes can be predicted, and other useful insights about the data can sometimes be revealed.
But having access to large amounts of data is essential to ensure that a high confidence level can be assigned to these predictions. The machine learning methods can be applied to many problems, as described below.
Tracking
AI has played a role since the very earliest stages of this virus. A Canadian AI company called BlueDot developed an AI program that alerted the world to the virus after the first case was detected in China on December 31st.
This program was designed to predict infectious diseases and locate and track their spread. It works by combining AI with the knowledge of epidemiologists who identify how and where to look for evidence of emerging diseases.
BlueDot analyses over 100,000 reports daily in many languages and then sends out regular alerts to health care, government, business, and public health clients. The alerts provide brief synopses of anomalous disease outbreaks that its AI program has discovered and the risks they may pose.
But other AI applications have rapidly appeared to monitor not only the spread of information about COVID-19 but also the spread of humans infected and detect humans carrying symptoms. For example, contact tracing smartphone apps were first used in Wuhan to track and trace possible carriers of the virus (see later).
Another AI program is being used in cities in China to detect symptoms of people in bus and train stations as well as other public places where there is a high concentration of people. In this application, AI is combined with sensor detecting temperature measurement technology using computer vision. This technology makes it possible to take body temperature, a key symptom of COVID-19, in a contactless way without affecting normal behaviour.
With this technology in place, those whose body temperatures exceeded the threshold could be located. Doing this manually would be time-consuming and could increase the risk of cross-infection.
Scanning
Testing has become a key issue in the fight against COVID-19. Countries like South Korea and Germany have been seen as successful in handling the virus because of the amount of testing that is done in those countries. Health authorities are keen to increase the numbers being tested but the main testing methods are labour intensive and time-consuming.
But AI is now assisting with other forms of testing, such as x-ray scanning. Various AI programs are now available for chest screening that can highlight lung abnormalities in a chest X-ray scan and provide a COVID-19 risk evaluation much faster than human radiologists.
Resistance
AI has been used in healthcare systems for many years for a range of applications and has encountered some resistance particularly with regard to use of medical patient data. Having access to medical data raises many sensitive issues of privacy and confidentiality.
This became a contentious matter when the British NHS system failed to comply withdata protection rules when it provided 1.6 million patient records to a Google-owned company in 2017 for machine learning analysis.
This, in part, explains the concern with the use of contact-tracing apps, which are already in widespread use in Asia in countries like China, Hong Kong, Singapore and South Korea. They are also now being used in other parts of the world such as India, Italy, and Israel and development in other nation-states continue apace.
Contact-tracing apps vary in the way they work but generally use the fact that smartphone users whereabouts are detectable and therefore, can monitor close contact with other users. AI algorithms can then determine the risk of cross infection and then alert users of such risks by learning from the data collected.
In the last few days, it has been announced that an app has been proposed by the UK government for use in England, that may also be rolled out in Wales. This app is now being trialled in the Isle of Wight.
Mark Drakeford said on the 4th May, that there are some difficulties that need to be resolved because of the differences between NHS England and NHS Wales. As Drakeford said at his daily press conference: At the moment we are working with the UK government on that app to see if we could make use of it here in Wales.
It works by using the Bluetooth protocol to identify other smartphone owners who are in close proximity to each other. Thus, if someone develops Covid-19 symptoms, he or she can notify the app of these symptoms. This data can then be uploaded onto the NHS server and people who have been in contact with this person can be notified and possibly given advice such as requesting self-isolation.
There have been concerns about privacy and the possibility of government surveillance of individuals i.e., the emergence of the Big Brother State particularly with using this app because of its access to centralised data. However, the proposed app will only require participants to enter part of their postcode and will not ask them to enter their names. This offers some level of anonymity because the data will be stored under an anonymous ID.
An important distinction between this contact-tracing app and others is that the data will be centralised and stored on the NHS servers unlike some apps used in other countries which work on individual phones rather than collected centrally. The advantages of doing this is that the hotspots are in the country can be detected. And even if there is a low participation rate in the project, of around 20%, then some important insights may be gained into how the virus is spreading.
For all the privacy concerns, many will feel its a price worth paying particularly if assurances are given that this data will be used for this purpose only. Mark Drakeford thought people would be willing to part with some personal freedoms to take part in the project, and many experts believe that having access to track and trace data is essential.
For example, Dirk Brockmann, an epidemiologist who leads a project tackling the coronavirus pandemic at the Robert Koch Institute in Germany says: There is a simple way that people can help the fight against coronavirus, beyond washing their hands donate their data.
Most people now own smartphones and, if they can be persuaded that it is used for the good of all and used anonymously, then individuals may be persuaded to submit data voluntarily. This is vitally important because according to the University of Oxfords Big Data Institute, a contact-tracing app could help stop this pandemic, but 80% of smartphone owners would need to use it.
Another concern with contact-tracing is that the data may not be a good reflection of the population because the elderly are less likely to use smartphones. But as Mathew Gould, the head of the NHS unit that developed the app, says: Im conscious that smartphone use goes down with the more elderly population. This is part of a strategy, so were making sure were not just relying on the app.
Conclusions
Fighting this pandemic has been helped by AI adoption from its inception. The use contact-tracing is likely to begin a new phase which we hear a great deal about in the coming months.
Its use is controversial but may turn out to be crucial in our battle with COVID-19.
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How Artificial Intelligence could help Wales prevent the spread of Covid-19 - Nation.Cymru
FTC Provides Guidance on Using Artificial Intelligence and Algorithms – JD Supra
Updated: May 25, 2018:
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FTC Provides Guidance on Using Artificial Intelligence and Algorithms - JD Supra
Boosted.ai Raises $8 Million in Series A Funding to Bring Artificial Intelligence in Investment Management to the Mainstream – Financial Post
AI Platform Offers Machine Learning Techniques to Global Financial Industry
NEW YORK & TORONTO Boosted.ai, the leading distributed machine learning platform for global investment professionals, today announced the closing of an $8 million USD Series A financing round, led by Portag3 Ventures. Dunamu & Partners and Polar Equity Partners also participated in the round. Inclusive of seed capital, Boosted.ais total funding now stands at $11 million.
Boosted.ai will use the funding to continue enhancing Boosted Insights, its proprietary machine learning platform that empowers portfolio managers, analysts and chief investment officers to augment their existing investment processes, source new ideas and manage risks. Boosted Insights is a first-to-market AI platform for investment professionals, supporting idea generation, portfolio construction and portfolio monitoring without requiring users to be coders, software engineers or data scientists. The platform also allows investment professionals to find value in alternative datasets that otherwise require extensive quantitative experience to unlock.
Co-founded in 2017 by Joshua Pantony, Jon Dorando and Nicholas Abe, Boosted.ai currently has more than a dozen active clients and services the full spectrum of asset managers, including long-only mutual funds, long-short hedge funds, family offices and the investment arms of commercial banks. Combined assets under management managed by the Boosted.ai client base is in excess of $500 billion.
According to the CFA Institute, there are five main hurdles to using artificial intelligence within investment management: cost, talent, technology, vision and time. Boosted Insights solves all five hurdles for managers, said Joshua Pantony, CEO of Boosted.ai. Our mission is to bring elements of quantitative management to the finance industry at large as data becomes the difference between winning and losing for investors globally.
Quantitative overlays, factors and stand-alone strategies are no longer options for the investment management industry they are a requirement to compete. The challenge the industry faces is systematically and efficiently implementing them, alongside unique data sources, to stay ahead of the competition, said Adam Felesky, CEO of Portag3 Ventures. The Boosted.ai platform enables asset managers of any sophistication to do this by tapping into the most advanced machine learning tools available, augmenting their existing investment process through a user-friendly interface that does not require coding expertise.
Funding will also be used to hire additional talent in Toronto and New York City, as well as enhance marketing and sales processes.
In conjunction with the funding round, Adam Felesky from Portag3 Ventures has joined Boosted.ais Board of Directors.
To learn more or schedule a demo of Boosted Insights, visit here.
About Boosted.ai
Boosted.ai is an artificial intelligence company that enhances portfolio management outcomes for the global financial industry through distributed machine learning. Co-founded by Joshua Pantony, Jon Dorando and Nicholas Abe in 2017, the company and its proprietary web-based platform, Boosted Insights, bring advanced quantitative investing techniques to portfolio managers, without requiring any coding or data science background. Headquartered in Toronto and New York City, Boosted.ai is backed by Portag3 Ventures, Dunamu & Partners and Polar Equity Partners. Learn more at boosted.ai and follow us on LinkedIn.
About Portag3 Ventures
Portag3 Ventures is an early-stage investor supporting the worlds most innovative financial technology companies. Its team has deep entrepreneurial and industry experience and provides its founders with full access to the firms partners, in-house experts, and broader global ecosystem. Portag3 alongside Diagram Ventures, a fintech venture builder is a part of the venture capital strategy of Sagard Holdings, a multi-strategy alternative investment platform. Portag3 has a presence in Toronto, Montreal, New York, San Francisco, Europe and Southeast Asia. To learn more, visit p3vc.com.
About Dunamu & Partners
Dunamu & Partners invests in disruptive tech companies in diverse geographies, including North America, East and Southeast Asia. It has mainly backed innovative AI-empowered, data-driven fintech companies. Dunamu & Partners is an investment arm of Dunamu, Inc., an operator of #1 digital asset exchange Upbit and Stockplus (a.k.a. Kakao Stock), a leading multi-asset trading platform in South Korea. With deep experience in investment management and entrepreneurship, the teams leaders act as supportive confidants to founders around the world. To learn more, visit Dunamu & Partners.
View source version on businesswire.com: https://www.businesswire.com/news/home/20200505005225/en/
Contacts
Matthew Luongo Prosek Partners for Boosted.ai mluongo@prosek.com +1 (646) 818-9279
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Artificial intelligence is predicting coronavirus outbreaks before they start – TechRepublic
Artificial intelligence has played a central role in the fight against the coronavirus. Cotiviti has leveraged AI to predict COVID-19 hot spots around the country before an outbreak happens.
As the coronavirus continues to spread around the globe, we've seen a surge in the use of cutting edge technologies to track and control the pandemic, especially artificial intelligence. It seems like only a distant memory when artificial intelligence (AI) was being discussed as an emergent "existential threat" to humanity. However, with the rise of a pandemic, we've quickly embraced the ever-expanding capabilities of AI as a part of our first line of defense.
Recently, an AI platform fed mountains of pharmaceutical data and research studies journals determined that a rheumatoid arthritis medication could potentially be used to treat COVID-19 patients. As we reported earlier this month, some companies are deploying surveillance systems harnessing AI to pinpoint potential infections and mitigate the spread of the pandemic.
SEE: Coronavirus: Critical IT policies and tools every business needs (TechRepublic Premium)
One of the tremendous advantages of AI is the ability to absorb databases of information at warp speed. It's simply too labor-intensive (if not virtually impossible) for a human being to review every single study and every clinical trial directly or indirectly related to a medical phenomenon.
"That's how I spend my time between 2 o'clock in the morning and 4 o'clock in the morning, trying to catch up on a lot of the clinical information," explained Dr. Emad Rizk, chairman, president and CEO of Cotiviti.
The healthcare analytics and solution company Cotiviti is now using AI and a mass of health data to predict future coronavirus hot spots around the US before these clusters emerge. During our interview, Rizk expressed his belief that AI and deep learning can greatly benefit mankind, from accelerating treatment to potentially improving current pharmaceuticals, but he does reiterate a sense of caution about the data being fed to the algorithms.
"You have to be careful that the algorithms are not using a small window of data. In other words, using just two to three data elements to come to a conclusion is a lot different than using 100 data elements," Rizk said.
Cotiviti processes patient screening information and medical claims in its Caspian Insights Platform and uses this information to identify trends. The platform leverages machine learning alongside a wide spectrum of healthcare data to illustrate a "longitudinal" view of patient treatment and care outcomes over time.
The platform plays a central role in Cotiviti's recently unveiled COVID-19 Outbreak Tracker. The interactive map provides weekly predictions about potentially hidden hot spots around the US. The map also highlights areas where coronavirus mitigation efforts may be working, illustrating a decreased probability of a hidden outbreak. Cotiviti uses a vast array of medical information including chest X-rays, emergency department visits, CPT codes, ICD-9 codes, and more to pinpoint hotbeds.
For more on mapping, check out our Flipboard magazine, Coronavirus maps
"We're not looking at confirmed cases only, we're looking at leading indicators by using our technology and comprehensive database [to] potentially see anything that might be occurring so we can raise the flag and say [these] ZIP codes look suspicious," Rizk said.
In early March, the company used Caspian data to pinpoint nearly 2 dozen states with signs indicating a potential future coronavirus outbreak. Within two weeks, 80 percent of these predicted hot spots became a reality, according to Cotiviti. Since then the company has refined its algorithm and pinpointed future hot spots with up to 91% accuracy, per Rizk.
New clinical data is available around the clock, and this information can be applied to advance the model as the virus spreads and other hot spots contract. The data will also be closely monitored when it comes to seasonal flu trends and using this information to pinpoint anomalies indicative of potential coronavirus cases. In the coming weeks and months, there will be interesting predictive indicator updates to gauge as cities and states slowly begin to reopen for business.
"When we go to ZIP code X-Y-Z, we can use our model to hone in and begin to see if there was any correlation with opening up that ZIP code to an increase in amplitude and volume of flu-like symptoms using our deep machine learning and our AI incidence," Rizk said.
For this particular crisis, feeding an algorithm the appropriate information to do its task is one challenge. People are also struggling to glean useful insights amid a deluge of seemingly never-ending coronavirus news coverage and, at times, conflicting reports. Rizk concluded our conversation touching on his colleagues and comrades at the forefront of this pandemic and reiterating the importance of taking a comprehensive 360-degree approach to information.
"I have many friends out on the front line serving and doing everything that they can. And we are all trying to get through the bombardment of information out there. Everyone is trying to help. But again, everybody is coming at it from a different lens," he said.
"One angle, you'll only see one angle, not the whole picture," he continued.
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Image: Cotiviti
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Artificial intelligence is predicting coronavirus outbreaks before they start - TechRepublic
How China used robots, drones and artificial intelligence to control the spread of the coronavirus – MarketWatch
While most countries in the world are fighting exponential growth of coronavirus infections, China seems to have gotten the situation under control.
Thats been largely due to the Chinese governments ability to enforce preventive measures more successfully than Western democracies. Individualism, a patchwork approach and fear of stopping economic growth backfired in the U.S. and some European countries.
An overlooked factor that helped flatten the curve in China: Technology.
Social distancing, contactless transactions, cleaning and gathering diagnostic data have been made possible by automated technologies developed at Chinese companies.
Pudu Technology from Shenzhen employed its repurposed catering robots in more than 40 hospitals across the country. The robots help medical staff deliver supplies and medicine to patients and limit health-care workers exposure.
Another company from Shenzhen, MMC (MicroMultiCopter), used megaphone-equipped drones to patrol the streets, warning groups of people who failed to wear masks to disperse. The drones are capable of spraying disinfectants in public places and measuring individual thermal signatures, helping to reduce the spread of the virus. In addition, the MMC drones monitored traffic, enabling uncongested vehicle movement and faster response rates in case of medical emergencies.
Other technologies have been employed as well. Chengdu city in Sichuan Province armed epidemic-control personnel with high-tech smart helmets that can automatically measure peoples temperature when they enter a five-meter range. The helmet sounds an alarm if anyone has a fever.
If you think that something is missing, youre right. We havent mentioned AI artificial intelligence. Alibaba BABA, +0.07%, the Chinese tech and e-commerce multinational company, has developed AI that allegedly can detect coronavirus infections with 96% accuracy.
Finally, Chinas vast surveillance system is finally being put to a good use: Facial-recognition cameras come equipped with thermal sensors that can detect people with fevers and those not wearing masks.
Mobile apps also play a big role here Tencent TCEHY, +0.74% and Alipay have developed apps that inform users if theyve been in contact with a virus carrier and whether they should stay at home or be allowed in public spaces.
For these apps to work, however, additional personal data need to be provided by the user. Alipays app, which is in use in over 200 cities, classifies people by color codes: Red is for supervised quarantine, yellow is for self-quarantine and green means unrestricted movement.
The lack of transparency of how these codes are generated has already led to much confusion and frustration, which is only amplified by the fact that the data entered in the app are shared with the government and police. The same is true of the surveillance. Privacy was never a big topic in the Peoples Republic of China (PRC), and now the last shreds are being obliterated in the name of public safety. The country may eventually subdue the coronavirus infection, but at what cost?
Still, there are things that we Westerners could learn from the Chinese. Seeing empty streets of European and American cities on the news gives me hope that people are finally realizing this isnt just a flu and that we need to take things seriously.
Tech can help, but this time it plays second fiddle to staying home and abiding by protective measures against the virus. Until a vaccine is approved, this is the best way the curve can be flattened and the burden on health-care professionals can be reduced to a sustainable level. So, until further notice, stay home and stay safe.
Jurica Dujmovic is a MarketWatch columnist.
Customer experience, innovation, artificial intelligence, culture.a look inside Amazon Interview with Claire Whitaker – Customer Think
Todays interview is with Claire Whitaker, a product and artificial intelligence (AI) consultant, who over the last nine years has worked in lean innovation, customer experience (CX), product management and technology including AI teams at top companies across industries, including Amazon. Claire joins me today to share some insights from her experience and, particularly, from her time at Amazon.
This interview follows on from my recent interview The nature of service and how weve grown up with a service economy which is now finding it very hard to actually serve customers Interview with Joel Bailey of EY Seren and is number 340 in the series of interviews with authors and business leaders that are doing great things, providing valuable insights, helping businesses innovate and delivering great service and experience to both their customers and their employees.
Heres the highlights of my chat with Claire:
About Claire
Claire is a product and AI consultant. Over the last nine years, she has worked in innovation and CX teams at top companies across industries, including Amazon. She has been involved in a variety of projects looking at how to use advanced technologies like AI and AR to improve customer experience. Now as a certified SME consultant, she helps tech companies move from feeling overwhelmed in your business unable to scale, to have a product roadmap the team is excited about delivering.
You can found out more about Claire at Artificially Intelligent Consulting, say Hi to her on Twitter @ElizabetClaire and do connect with her on LinkedIn here.
Image by 272447 from Pixabay
Artificial Intelligence in BFSI Market Latest State Of Affairs On Innovation, Revolutionary Opportunities Customers 2026 – Cole of Duty
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Artificial Intelligence in BFSI Market Latest State Of Affairs On Innovation, Revolutionary Opportunities Customers 2026 - Cole of Duty