Category Archives: Artificial Intelligence
Southern California Adult-Serving University Taps Artificial Intelligence to Boost Student Success – National University News
National University rolls out chatbot NUton, developed in partnership with AdmitHub, to help adult students balance the complexity of college with family, work, and personal commitments
LA JOLLA, CALIF. (May 6, 2021) National University, a nonprofit university celebrating its rich 50-year history of serving working adult learners, educators, and veterans, today announced initial results from its successful launch of a new behaviorally intelligent chatbot that is helping to boost persistence and retention among its unique student population. Designed in partnership with AdmitHub, the conversational artificial intelligence chatbot, called NUton, offers proactive, personalized guidance to help all enrolled students navigate their way to and through college.
So many of the factors that influence student success are related to the complex and delicate balance among work, family, personal, and academic life, particularly for the population of working adults, parent learners, and veterans that we serve, said Dr. David Andrews, president of National University and a developmental psychologist by training. This is about offering anywhere, anytime communication to help students access the wide variety of supports and services available to help students overcome everyday challengesfrom financial aid and course registration to academic advising and wellness.
The chatbot offers 24/7 communication via text message and directs students in need of additional support to targeted academic and student support resources designed to support the needs of the highly-diverse student population at National University. The average age of National students is 33 years old, and students from underrepresented communities make up about half of enrolled students.
National University and AdmitHub began their new partnership in 2019, and NUton was originally introduced to students through a grant-funded initiative with the universitys Veteran Center, focused on increasing the quality of student support for the more than 25 percent of students who are veterans or active-duty servicemembers. In its early days, the university observed that students used the platform, often after normal business hours, to access information about academic planning and advising, financial aid, health and wellness, and other campus services.
In response to the successful launch with the military-affiliated student population, the university scaled the chatbot initiative to serve its entire population in the Fall of 2020, especially in light of the challenges presented to students during COVID quarantines and modifications to on-site education. Today, approximately 20,000 students engage with the chatbot each month.
Preliminary outcomes data suggest the chatbot is helping to boost academic success for Nationals students and save university staff and faculty valuable time to focus on individual student concerns. For instance, retention increased by 17 percent among students who were enrolled in classes in April and who were provided personalized engagement and communication. In addition, students have overwhelmingly embraced NUton with an engagement rate of nearly 50 percent, much higher than other means of university communication, and an average staff and faculty time savings of approximately 500 hours per month.
Even more interesting is how NUton is allowing university staff and faculty to learn more about the unique needs of online learners than ever before. With every text message received, NUton provides a previously unavailable window into student preference, school-work-life balance, and academic challenges for which the university can now take action, said Dr. Brandon Jouganatos, Vice President for Enrollment Management and Student Success. A major concern of adult learners remains flexibility in scheduling and commitments as their many responsibilities shift, and NUton has allowed students the ability to express enrollment preferences, reschedule courses, and otherwise create academic program flexibility with a simple text.
Drew Magilozzi, co-founder and CEO of AdmitHub, also applauded NUtons unique approach. In many cases, students are more inclined to ask a chatbot than a financial advisor about how to navigate financial aid or tap into scholarship opportunities, which enables advisors to focus on the questions and challenges that require more hands-on support, Magliozzi said. Through the combined efforts of caring educators, staff and advisors with support from artificial intelligence chatbots, National University is helping to address the unique needs of a highly-diverse student populationwith a greater degree of empathy and precision and even at a very large scale.
NUton was developed using artificial intelligence and natural language processing technology from pioneering develope AdmitHub. AdmitHubs conversational chatbots are used by a growing number of colleges and nonprofit organizations to help boost enrollment, improve persistence, and advance student success. Research conducted in partnership with Georgia State University found AdmitHubs technology reduced so-called summer melt by more than 20 percent among incoming students, and further studies suggest the technology can increase FAFSA completion rates and fall registration rates for returning students.
National University (NU), a veteran-founded nonprofit, has been dedicated to meeting the needs of hard-working adults by providing accessible, affordable, achievable higher education opportunities since 1971. As San Diegos largest private nonprofit university, NU offers over 75 online and on-campus programs and flexible four-week classes designed to help students reach their goals while balancing busy lives. Since its founding, the NU community has grown to over 25,000 students and 175,000 alumni around the globe, many of whom serve in helping industries such as business, education, health care, cybersecurity, and law and criminal justice. Learn more at NU.edu
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Southern California Adult-Serving University Taps Artificial Intelligence to Boost Student Success - National University News
Artificial Intelligence Identifies Netflix And Facebook Among Top Stocks For The Month – Forbes
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April was a mixed bag between economic strength, inflation scares, and corporate earnings, but on the whole, the stock market has behaved relatively well in 2021. And while there is always uncertainty in the market, a case for strong diversification has never been clearer. Whether sell in May and go away will come to fruition this month or not will remain to be seen, but with vaccinations rolling out across the country and states opening up, there is surely some pent-up demand for consumer spending, the largest part of the American economy. With that being said, if you need some help deciding on what stocks to buy our Artificial Intelligence ("AI") algorithms at Q.ai have identified some standout stocks to consider for this month to help you out. Our AI systems have picked Top Tech Stocks, Top Consumer Stocks, Top Quality Value Stocks, Top Growth Stocks, and Top Dividend Stocks to assist you.
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Netflix is our first Top Tech Stock for the month of May. The streaming media giant continues to impress overall, but competition is heating up and is putting the brakes on new all-time highs. Netflix is rated a Top Buy this month and our AI systems rated Netflix C in Technicals, A in Growth, B in Low Volatility Momentum, and C in Quality Value. The stock closed down 1.41% to $496.08 on volume of 3,129,366 vs its 10-day price average of $506.75 and its 22-day price average of $528.37, and is down 5.12% for the year. Revenue grew by 5.58% in the last fiscal year, and grew by 67.1% over the last three fiscal years, whereas Operating Income grew by 21.84% in the last fiscal year, and grew by 248.04% over the last three fiscal years. EPS grew by 35.91% in the last fiscal year, and grew by 208.34% over the last three fiscal years. Revenue was $24996.06M in the last fiscal year compared to $15794.34M three years ago, Operating Income was $4585.29M in the last fiscal year compared to $1605.23M three years ago, EPS was $6.08 in the last fiscal year compared to $2.68 three years ago, and ROE was 29.62% in the last year compared to 27.46% three years ago. The stock is also trading with a Forward 12M P/E of 47.83.
Simple moving average of Netflix (NFLX)
Facebook is our next Top Tech stock this month. Facebook recently made headlines with its supreme court oversight board ruling on whether or not to uphold its suspension of the former President. However, it is still a big tech staple with a strong future outlook and earnings power from ad revenues that are hard to replicate. Facebook is rated a Top Buy this month and our AI systems rated Facebook C in Technicals, A in Growth, C in Low Volatility Momentum, and B in Quality Value. The stock closed down 1.05% to $315.02 on volume of 15,577,605 vs its 10-day price average of $312.19 and its 22-day price average of $309.6, and is up 17.13% for the year. Revenue grew by 9.81% in the last fiscal year, and grew by 69.06% over the last three fiscal years. Operating Income grew by 16.79% in the last fiscal year, and grew by 53.16% over the last three fiscal years. EPS grew by 15.67% in the last fiscal year, and grew by 54.17% over the last three fiscal years. Revenue was $85965.0M in the last fiscal year compared to $55838.0M three years ago, Operating Income was $32671.0M in the last fiscal year compared to to $24913.0M three years ago, EPS was $10.09 in the last fiscal year compared to $7.57 three years ago, and ROE was 25.42% in the last year compared to to 27.91% three years ago. The stock is also trading with a Forward 12M P/E of 24.13.
Simple moving average of Facebook (FB)
USANA Health Sciences Inc our first Top Consumer Stock for the month. The company is a U.S.-based company that is principally engaged in developing, manufacturing, and selling science-based nutritional and personal-care products. The company operates through direct selling. USANA is rated a Top Buy this month and our AI systems rated USANA a C in Technicals, C in Growth, B in Low Volatility Momentum, and B in Quality Value. The stock closed up 4.29% to $94.6 on volume of 98,218 vs its 10-day price average of $93.34 and its 22-day price average of $97.07, and is up 21.36% for the year. Revenue grew by 3.64% in the last fiscal year and Operating Income grew by 2.94% over the same period. EPS grew by 3.83% in the last fiscal year and grew by 18.84% over the last three fiscal years. Revenue was $1134.64M in the last fiscal year compared to $1189.25M three years ago, Operating Income was $176.49M in the last fiscal year compared to $188.35M three years ago, EPS was $5.86 in the last fiscal year compared to $5.12 three years ago, and ROE was 31.43% in the last year compared to 33.47% three years ago. Forward 12M Revenue is expected to grow by 0.81% over the next 12 months, and the stock is trading with a Forward 12M P/E of 14.69.
Simple moving average of USANA Health Sciences Inc (USNA)
Asbury Automotive Group Inc is also a Top Consumer Stock for the month of May. Asbury is a regional collection of automobile dealerships that went public in March 2002. The company operates over 90 stores with associated parts and service departments and 25 collision centers. Asbury is rated a Top Buy this month and our AI systems rated General Motors B in Technicals, A in Growth, B in Low Volatility Momentum, and C in Quality Value. The stock closed up 0.08% to $205.59 on volume of 76,628 vs its 10-day price average of $205.06 and its 22-day price average of $203.59, and is up 44.07% for the year. Revenue grew by 8.21% in the last fiscal year, and grew by 12.26% over the last three fiscal years, while Operating Income grew by 16.24% in the last fiscal year, and grew by 50.03% over the last three fiscal years. EPS grew by 28.63% in the last fiscal year, and grew by 104.74% over the last three fiscal years. Revenue was $7131.8M in the last fiscal year compared to $6874.4M three years ago, Operating Income was $406.3M in the last fiscal year compared to $314.8M three years ago, EPS was $13.18 in the last fiscal year compared to $8.28 three years ago, and ROE was 32.79% in the last year compared to 38.74% three years ago. Forward 12M Revenue is expected to grow by 1.69% over the next 12 months and the stock is also trading with a Forward 12M P/E of 12.39.
Simple moving average of Asbury Automotive Group Inc (ABG)
Cinco de Mayo has passed but Chipotle Mexican Grill Inc is still our first Top Growth Stock. The stock has been on an absolute tear over the last few years, and is the largest player in the $16 billion domestic fast-casual Mexican restaurant category. Chipotle is rated Attractive this month and our AI systems rated Chipotle C in Technicals, A in Growth, B in Low Volatility Momentum, and C in Quality Value. The stock closed down 1.62% to $1426.5 on volume of 127,655 vs its 10-day price average of $1468.8 and its 22-day price average of $1499.64, and is up 8.14% for the year. Revenue grew by 5.53% in the last fiscal year, and grew by 29.81% over the last three fiscal years. Operating Income grew by 26.49% in the last fiscal year, and grew by 17.54% over the last three fiscal years. EPS grew by 14.0% in the last fiscal year, and grew by 126.19% over the last three fiscal years. Revenue was $5984.63M in the last fiscal year compared to $4864.98M three years ago, Operating Income was $327.13M in the last fiscal year compared to $352.06M three years ago, EPS was $12.52 in the last fiscal year compared to $6.31 three years ago, and ROE was 19.21% in the last year compared to 12.58% three years ago. Forward 12M Revenue is expected to grow by 2.96% over the next 12 months and the stock is also trading with a Forward 12M P/E of 54.3.
Simple moving average of Chipotle Mexican Grill Inc (CMG)
Our second Top Growth stock this month is Fiserv Inc. Fiserv Inc is a leading provider of core processing and complementary services, such as electronic funds transfer, payment processing, and loan processing, for U.S. banks and credit unions, with a focus on small and midsize banks. Fiserv is rated a Top Buy this month and our AI systems rated the company B in Technicals, A in Growth, C in Low Volatility Momentum, and A in Quality Value. The stock closed down 1.23% to $116.59 on volume of 3,896,209 vs its 10-day price average of $121.94 and its 22-day price average of $123.28, and is up 4.17% for the year. Revenue grew by 154.82% over the last three fiscal years. Operating Income grew by 17.36% in the last fiscal year, and grew by 25.36% over the last three fiscal years. Revenue was $14852.0M in the last fiscal year compared to $5823.0M three years ago, Operating Income was $1630.0M in the last fiscal year compared to $1526.0M three years ago, EPS was $1.40 in the last fiscal year compared to $2.87 three years ago, and ROE was 2.86% in the last year compared to 47.25% three years ago. Forward 12M Revenue is expected to grow by 2.04% over the next 12 months and the stock is also trading with a Forward 12M P/E of 20.62.
Simple moving average of Fiserv Inc (FISV)
Crocs Inc is our first Top Quality Value Stock for the month, a truly impressive rebound for a company that had a 99% drawdown in the 2008 financial crisis to hit new all-time highs today. The company is engaged in the design, development, marketing, distribution, and sale of casual lifestyle footwear accessories for men, women, and children. Crocs is rated a Top Buy this month and our AI systems rated Crocs C in Technicals, A in Growth, C in Low Volatility Momentum, and A in Quality Value. The stock closed up 2.57% to $106.36 on volume of 1,593,795 vs its 10-day price average of $95.66 and its 22-day price average of $86.97, and is up 72.77% for the year. Revenue grew by 12.91% in the last fiscal year and grew by 43.8% over the last three fiscal years, Operating Income grew by 41.61% in the last fiscal year and grew by 375.58% over the last three fiscal years, and EPS grew by 29.01% in the last fiscal year and grew by -681.53% over the last three fiscal years. Revenue was $1385.95M in the last fiscal year compared to $1088.2M three years ago, Operating Income was $249.66.6M in the last fiscal year compared to $74.34M three years ago, EPS was $4.56 in the last fiscal year compared to $(1.01) three years ago, and ROE was 148.09% in the last year compared to 19.45% three years ago. Forward 12M Revenue is expected to grow by 1.98% over the next 12 months and the stock is also trading with a Forward 12M P/E of 18.27.
Simple moving average of Crocs Inc (CROX)
eBay Inc. is our next Top Quality Value Stock. With $100 billion in marketplace gross merchandise volume, or GMV, generated in 2020, eBay's Marketplace facilitated more than 2% of the $4.3 trillion global online commerce market. eBay is rated Attractive this month and our AI systems rated eBay C in Technicals, C in Growth, B in Low Volatility Momentum, and A in Quality Value. The stock closed up 0.95% to $58.24 on volume of 7,002,822 vs its 10-day price average of $59.32 and its 22-day price average of $61.27, and is up 13.44% for the year. Revenue grew by 8.7% in the last fiscal year, and grew by 29.08% over the last three fiscal years. Operating Income grew by 11.15% in the last fiscal year, and grew by 65.84% over the last three fiscal years. EPS grew by 61.34% over the last three fiscal years. Revenue was $10271.0M in the last fiscal year compared to $8650.0M three years ago, Operating Income was $2717.0M in the last fiscal year compared to $1821.0M three years ago, EPS was $7.89 in the last fiscal year compared to $2.56 three years ago, and ROE was 79.05% in the last year compared to 29.7% three years ago. Forward 12M Revenue is expected to grow by 0.67% over the next 12 months, and the stock is trading with a Forward 12M P/E of 14.39.
Simple moving average of eBay Inc (EBAY)
Broadcom Inc is our first Top Dividend Stock for the month. The company boasts a highly diverse product portfolio across an array of end markets. Broadcom is rated Neutral this month and our AI systems rated Broadcom D in Technicals, C in Growth, C in Low Volatility Momentum, and A in Quality Value. The stock closed down 0.16% to $443.83 on volume of 1,638,981 vs its 10-day price average of $457.96 and its 22-day price average of $468.2, and is up 4.38% for the year. Revenue grew by 3.34% in the last fiscal year and grew by 18.4% over the last three fiscal years, Operating Income grew by 26.92% in the last fiscal year, and EPS grew by 36.6% in the last fiscal year. Revenue was $23888.0M in the last fiscal year compared to $20848.0M three years ago, Operating Income was $4250.0Min the last fiscal year compared to $5487.0M three years ago, EPS was $6.33 in the last fiscal year compared to $28.44 three years ago, and ROE was 12.12% in the last year compared to 50.68% three years ago. Forward 12M Revenue is expected to grow by 1.05% over the next 12 months and the stock is also trading with a Forward 12M P/E of 16.19.
Simple moving average of Broadcom Inc (AVGO)
Bank Of America Corp is our final Top Dividend Stock this month. The company is one of the largest financial institutions in the United States, with more than $2.5 trillion in assets. Our AI systems rated Bank of America Neutral this month and gave it a C in Technicals, C in Growth, B in Low Volatility Momentum, and A in Quality Value. The stock closed up 0.95% to $41.39 on volume of 23,266,920 vs its 10-day price average of $40.15 and its 22-day price average of $39.73 and is up 37.83% for the year. Revenue grew by 8.99% in the last fiscal year, Operating Income grew by 24.4% in the last fiscal year, and EPS grew by24.6% over the last fiscal year. Revenue was $74208.0M in the last fiscal year compared to $87738.0M three years ago, Operating Income was $18995.0M in the last fiscal year compared to $34584.0M three years ago, EPS was $1.87 in the last fiscal year compared to $2.61 three years ago, and ROE was 6.66% in the last year compared to 10.57% three years ago. The stock is trading with a Forward 12M P/E of 13.82.
Simple moving average of Bank of America Corp (BAC)
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Artificial Intelligence Identifies Netflix And Facebook Among Top Stocks For The Month - Forbes
Hill International and Everguard.ai Partner to Advance Artificial Intelligence (AI) in Improving Construction Jobsite Safety – PRNewswire
IRVINE, Calif., May 6, 2021 /PRNewswire/ --Hill International and Everguard.ai announced today they are bringing best-in-class technologies including artificial intelligence (AI) and sensor fusion to construction companies focused on improving worker health and safety. This collaboration, enabled through the Qualcomm Smart Cities Accelerator Program and Qualcomm IoT Services Suite, will bring Everguard's Sentri360 platform and ecosystem to Hill International customers, creating a paradigm shift from a reactive to a proactive approach to prevent jobsite injuries and accidents.
Everguard has been recognized as a unique solution for prioritizing construction safety and digital management of construction sites, focusing on worker safety. Combined with Hill's dedication to construction management, cost engineering and estimating, quality assurance, and risk management, these three companies are leading the way for the next generation of safe and efficient construction jobsites.
Initial efforts will focus on using the power of AI, computer vision (CV), and real-time location services (RTLS) to enhance safety protocols already in place on construction jobsites for initiatives such as personal protective equipment (PPE) compliance, geofencing of restricted areas, anti-collision, and fall detection. The use of heavy machinery and working at height along with the interaction of workers, drivers, and equipment on a construction site creates significant safety concerns across the industry.
"We believe this technology will reduce and prevent injuries and accidents," said Mike Smith, President, Americas, of Hill International. "We strive to partner with only the top organizations in making certain our customers have the right tools and technologies to elevate their construction sites to the highest level when it comes to health and safety. This partnership with Everguard will help us continue to be on the forefront of deploying technology to help our clients reduce their risks, avoid injuries, and save lives."
By connecting members looking for smart city solutions, the Qualcomm Smart Cities Accelerator Program aims to enrich lives through the accelerated transformation of city infrastructure and services. The Qualcomm IoT Services Suite delivers comprehensive, end-to-end, IoT as a Service (IoTaaS) solutions to enable the digital transformation of smart cities and smart connected spaces globally. Smart solutions and technologies are at the forefront of driving the next generation of smart spaces and construction sites.
"We are excited that Everguard.ai and Hill International have chosen the Qualcomm IoT Services Suite to deliver smart solutions via Construction-Management-as-a-Service because prioritizing construction safety and digital management of construction sites allows businesses and municipalities the ability to focus on worker safety," said Sanjeet Pandit, senior director, business development and head of Smart Cities, Qualcomm Technologies, Inc. "Construction-Management-as-a-Service will continue to accelerate the transformation of city infrastructure and services to help enrich communities' lives."
Everguard's Sentri360 is the only platform and interface construction contractors need to create and manage a proactive safety and productivity program. The technology-agnostic platform collects inputs from disparate industrial sensor technologies, allowing them to interact in ways not possible independently. Millions of sensor data pieces are fed into edge computers for AI analysis and processing in much the same way that humans process information gathered by their senses. Sentri360 does not just make sensor technologies work together, it makes them work smarter together.
The platform and ecosystem provide near-real-time alerts and outputs to managers and workers, notifying them of safety threats before accidents occur and identifying opportunities for additional employee training. It creates a Sensor Fusion Safety Zone that surrounds workers as it learns dynamically "on the job", improving safety and productivity for every worker as it lowers incidents and injuries, and their corresponding costs.
"Hill International and Everguard share a dedication to being technology and safety leaders in our respective fields," said Sanjay Pandya, vice president and general manager of construction at Everguard. "Their dedication to safety is unmatched. We couldn't be more thrilled to be working with the Hill team."
About Hill International
Hill International,with more than 2,700 professionals in 69 offices worldwide, provides program management, project management, construction management, facilities management, and other consulting services to clients in a variety of market sectors. Engineering News-Record magazine recently ranked Hill as the eighth-largest construction management firm in the United States. For more information on Hill, please visit our website at http://www.hillintl.com.
About Everguard.ai
Everguard'smission is to protect companies' most important assets their people with the first truly proactive solution dedicated to industrial safety. Their Industrial Health and Safety platform and ecosystem is the only interface industrial workplaces need to create and manage a proactive safety and productivity program. The technology-agnostic platform and ecosystem ties together disparate industrial sensor technologies allowing them to interact in ways not possible independently. Artificial intelligence (AI) and sensor fusion combine inputs from edge computing, computer vision (CV), real-time location system (RTLS), wearables and others to enable proactive interventions, helping prevent industrial accidents and the billions of dollars in fees and lost-time incidents they cause.
Qualcomm is a trademark or registered trademark of Qualcomm Incorporated.
Qualcomm Smart Cities Accelerator Program is a program of Qualcomm Technologies, Inc. and/or its subsidiaries.
Qualcomm IoT Services Suite is a product of Qualcomm Technologies, Inc. and/or its subsidiaries.
SOURCE Everguard.ai
The Use of Artificial Intelligence in Healthcare Accelerated During the Pandemic. It’s Here to Stay. – Entrepreneur
May5, 20215 min read
Opinions expressed by Entrepreneur contributors are their own.
Artificial intelligence (AI) hasdisrupted numerous industriesand promptedtheaddition of the suffix -tech to many of them:insurtech, fintech,agritech. Healthcare, in particular, has flourished because of AI, even before the pandemic, as machine intelligence makes scanning large populations for diseases feasible and drivesa proactive approach to healthcare keepingpeople healthy instead ofwaiting for them to get sick.
As the name suggests, population health focuses on cohorts over individuals, but there is more to it than that. For researchers in healthcare, population health relies onkeeping track of the incidence of diseases in a variety of groups of people. For example, they mightcompareCovid-19 outbreaks among individuals of different demographics who reside in a range of ZIP codes. It focuses on the prevention or early detection of disease in large populations through screening.
This is different from the more generalized public health, which examines the health condition of a whole population of individuals. Catering to public health calls for an analysis of pollutants in the air and water. Tending to population health requires the examination of disease incidence in groups according to criteria such as age, genderor location.
Related:Ai-Da, the First Robot Artist To Exhibit Herself
When it comes to AI in healthcare, its safe to say technology cannot replace human doctors' informed judgment and experience treating members of the public nor does anyone intend for it to do so. Withrespectto population health, which has become even more importantsince the pandemic, AI is needed more than ever to provide diagnosis and treatment statisticsand other informationto specialists and public-health researchers.
Population-health management software typically integrates patient data across healthcare IT systems for analysis. The data is used to better predict and manage illnesses and diseases. The software is also used to facilitate care delivery across populations based on need. In some ways, it caterstowards clusters of people, but it ultimately helps improve the quality of individualized patient care. After all, the analysis of population data leads to better prediction of individual-health risksand a more accurate big-picture representation of health trends within different communities.
Related:The Future ofHealthcareIs in the Cloud
Hospitals and associated clinics have turned to AI solutions over the course of the pandemic to improve resource efficiency, strengthen diagnosticsand manage patient volumes. This is particularly critical in preventative care, especially with orthopedic surgery. Orthopedic surgeries are expected to rise from 22.3 million in 2017 to 28.3 million in 2022 worldwide. When factoring in the scarcity of resources, that places pressure on surgeons, cliniciansand radiologists.
Deep-learning-based technologies like Zebra Medical Visionease the burdenby providing radiologists medical imaging analytics for scans and automatically analyzing them for various clinical findings. Such findings can be passed onto doctors, who can take the reports into consideration when making a diagnosis.
Looking at the intersection of population-health management and healthcare-data analytics could be interesting, as each market is set to become s $40 billionmarket within a couple of years. If were examining the genomic space alone, the tipping point is around the corner with an affordable cost of $600 for full genome sequencing today, on track for $100 sequencing in just a few years. As genomic data becomes financially plausible and the data generated from genomics doubles every year, expected to reach 20 exabytes by 2025, the 5,000 geneticists worldwide won't be able to process a significant fraction of it. Healthcare-data analytics in population health will be essential.
Precision medicine must rely on proper data processing and analysis. The AI models are already powerful enough they just need the data to work with. Genetic-interpretation company Emedgene developed the concept of cognitive genomic intelligence an inclusive, ever-growing platform that automatically produces insights from genomic data, reducing the time and cost of its interpretation, which traditionally requires hours of manual review and yields limited insights when solely relying on human intelligence.
H2O.AI is another solution that uses AI to analyze data throughout healthcare systems to mine, automate and predict processes. The ever-popular IBM Watson Health uses AI to provide value-based-care solutions for population-health management, directly benefiting providers, health plans, employers and pharmaceutical and biotech organizations.
Related:Healthtech Is the NewHealthcare
AI is raising the standards of population health, ultimately making it easier for doctors to make more informed decisions as they come up with optimized care regimens. The tech itself is widely consideredan administrative luxury, which it may have been at first, but it has gone on to become aliteral life-saver.
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The Use of Artificial Intelligence in Healthcare Accelerated During the Pandemic. It's Here to Stay. - Entrepreneur
How Artificial Intelligence Is Revolutionizing the Advertising Industry – BBN Times
The implementation of artificial intelligence (AI) in advertising has transformed the industry by curating content, automating online bidding, displaying data driven ads and maximizing broadcast and streaming revenues.
Advertising the communicative efforts undertaken by businesses to draw the attention of the masses towards their offerings has come a long way from where it started. Although the roots of this practice can be found deep in antiquity, the more substantially vehement instances of advertising emerged roughly around a century ago and will most likely continue far into the future, as long as there are products to sell and people who can buy them. And meanwhile, the way advertising content is conceived, created, and delivered will also undergo massive changes to keep up with the market trends and technological innovations, as it has been always doing. And the latest addition in the never-ending cycle of change that the advertising industry has adopted is artificial intelligence. After theadvertising industry gained its lost robustness with big data, the advent of AI in advertising is another milestone in the gradual shift of the industry from being mainly a creative initiative depending solely on human behavior to the primarily data-driven endeavor it has become today. With increased access to data, not just regarding broad market-wide trends but also pertaining individual behavior, the use of AI in advertising is set to make brand interactions more personalized, informative, and immersive.
While printed ads have existed long before the late nineteenth century, it was only during that period that they saw an explosive growth. As a result of industrialization in the late 1800s, manufacturers found themselves producing goods in unprecedented volumes, and at unprecedented rates. That is when they felt the need to have more consumers for their products, who they contrived to create through mass advertising campaigns. In this period, between 1880 and 1920,advertising volume in America rose from $200 million to $3 billion. Advertisements in this period populated newspapers, magazines, and other forms of printed media, which were produced and circulated to the general public. With the advent of newer media of mass communication such as radio in the early 20th century and later, television, advertisements also spilled over into these media. Until this period, advertisements were produced to target large groups of people.
By the mid 20th century, advertisement became a major global industry, and this is when segmentation of the audience came about, with advertising becoming more scientific and research-based than before. This is also when advertisement took to television. By the end of the twentieth century, the internet had already planted its roots across the globe and grew explosively in the first decade of the new millennium.
The internet offered a new medium of advertising and more tools to be able to segment audiences. This led to more targeted advertising campaigns over the internet. The second decade of the 21st century saw the emergence of social media and data analytics which made the collection of more detailed information possible. However, the emergence of social media and the internet has alsoelevated the importance of segmentation, personalization, and relevance. Unlike TV or print media, where ads are unavoidable for the readers or viewers, the internet makes it possible for consumers to tune irrelevant communications out. Sensing this need, the modern advertising industry is investing in tools and technology to make advertising more effective by learning as much about their audience as possible. And as it has done in every other industry it has been used in, the use of AI in advertising is revolutionizing the way ads are created and delivered to the audience.
Modern day advertising, especially on the digital stage, requires a high degree of personalization,as it is a known fact that people prefer personalized marketing communications. A survey reported that88% of US marketers experienced a noticeable improvement in business resultsdue to the implementation of personalization programs. Thus, providing greater personalization is on the agenda for most marketing and advertising leaders. Providing personalized content and offers to a vast number of individual customers requires the analysis of vast volumes of data, and then using the inferences from the analysis to determine the kind of ads to show for each customer. This makes the use of machine learning and AI in advertising the perfect solution. Artificially intelligent tools, due to their ability to process vast amounts of data quickly and act on it automatically. This ability allows these tools to create a detailed profile of every member of the audience based on their browsing data, social media activity, and other data such as demographic information that the individual provide voluntarily. Using these profiles the AI determines what ads the user is more likely to respond to, and displays those ads to them at opportune instances.
These ads are displayed through a process calledreal-time bidding (RTB), where multiple parties bid for displaying their specific ads when a user visits a page. Since this process takes place within the time it takes to load a page, it requires a high level of data processing capability to make the right bid quickly at the right time. A wrong decision in such instances may lead to a missed opportunity to get noticed or a wasted investment since, if the ad does make it to the page, the company gets charged even if the user doesnt click on the ad. Thus, bidding must be undertaken by determining the right value while also determining the right time to display ads, for maximizing the likelihood of getting a response (a click). This process is carried out by AI algorithms using the data collected from each individual.
Similar to print media and print ads, another relic from the history of advertisement that is extant today is the billboard, and other signages. Theglobal digital signage industry is, in fact, thriving and is expected to reach a market value of over$31 billion by the year 2025. AI billboards are capable ofshowing ads and messages to the audience based on how they reactto them. The efficacy of these smart, digital billboards is undeniable as a brand awareness boosting tool, since even normal billboards have been found out to be effective in engaging passing people.
Broadcast and streaming services are among the biggest attractors of worldwide audiences of varied demographics and hence, present the perfect stage for displaying advertisements. Sporting events and popular TV shows made by broadcasters draw millions of viewers. Media planning and Ad sales are activities that have been conventionally done by humans, but now, as the demand for the attention of audiences grows among brands, the competition for displaying ads is becoming cut-throat. Just like ad bidding for social media platforms, AI can be used for buying ad slots from broadcast and streaming services. AI can analyze large volumes of viewership data to optimize media schedules and maximizead sales revenuesfor advertisers.
These cases mark just the beginning when it comes to the potential applications of AI in advertising. As AI systems become more capable and gain wider adoption, they can have a greater influence over the advertising cycle from creation to delivery. By using AI in conjunction with other technologies like augmented and virtual reality, advertising can be made more immersive and personalized.
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How Artificial Intelligence Is Revolutionizing the Advertising Industry - BBN Times
Did you know these 10 everyday services rely on AI? – World Economic Forum
Artificial intelligence (AI) has transformed many aspects of our lives for the better. It even played a role in developing vaccines against COVID-19. But you may be surprised just how many things we take for granted that rely on AI.
As IBM explain, "at its simplest form, artificial intelligence is a field, which combines computer science and robust datasets to enable problem-solving." It includes the sub-fields of machine learning and deep learning. These two fields use algorithms that are designed to make predictions or classifications based on input data.
This is how AI is used in our everyday lives.
Image: European Parliament
Of course, as technology becomes more sophisticated, literally millions of decisions need to be made every day and AI speeds things up and takes the burden off humans. The World Economic Forum describes AI as a key driver of the Fourth Industrial Revolution.
Forecasted shipments of edge artificial intelligence (AI) chips worldwide in 2020 and 2024, by device.
Image: Statista
The Forums platform, Shaping the Future of Technology Governance: Artificial Intelligence and Machine Learning, is bringing together key stakeholders to design and test policy frameworks that accelerate the benefits and mitigate the risks of AI and machine learning.
Here are 10 examples of AI we encounter every day.
Your email provider almost certainly uses AI algorithms to filter mail into your spam folder. Quite helpful when you consider that 77% of global email traffic is spam. Google says less than 0.1% of spam makes it past its AI-powered filters.
But there are concerns that algorithms that read content to target advertising are invading our privacy.
AI automates a host of functions on your smartphone, from predictive text that learns the words you commonly use to voice-activated personal assistants which listen to the world around them and try to learn your keywords.
The way your phone screen adjusts to ambient light or the battery life is optimized is also down to AI. But if the personal assistant absorbs everything you say, whether youre on the phone or not, some critics say it creates opportunities for surveillance, however benign the intention.
In many parts of the world, online and app-based banking are the norm. From onboarding new customers and checking their identity to countering fraud and money laundering, AI is in charge. Want a loan? An AI-powered system will assess your creditworthiness and decide.
This is how AI is used in banking.
Image: Business Insider
AI also monitors transactions and AI chatbots can answer questions about your account. More than two-thirds of banks in a recent survey by SAS Institute say they use AI chatbots and almost 63% said they used AI for fraud detection.
Going for an x-ray? Forget the idea of a clinician in a white coat studying the results. The initial analysis is most likely to be done by an AI algorithm. In fact they turn out to be rather good at diagnosing problems.
In a trial, an AI algorithm called DLAD beat 17 out of a panel of 18 doctors in detecting potential cancers in chest x-rays.
However, critics say AI diagnosis must not become an impenetrable black box. Doctors need to know how they work in order to trust them. Issues around privacy, data protection and fairness have also been raised.
As in banking, chatbots are also being deployed in healthcare to engage with patients - for example, to book an appointment - or even as virtual assistants to physicians. This presents numerous issues though, from miscommunication to wrong diagnoses.
The World Economic Forum's Chatbots RESET programme brings together stakeholders from multiple areas to explore these opportunities and challenges to govern the use of chatbots.
AI is at the heart of the drive towards autonomous vehicles, adoption of which has accelerated due to the pandemic. Delivery services are one area being targeted, while China now has a robotaxi fleet operating in Shanghai.
There are still safety issues to be ironed out, however. There have been accidents involving self-driving cars, some of them fatal.
The Netherlands is the best prepared for autonomous cars.
Image: Statista
Conventional trackside railway signals are being replaced by AI-powered in-cab signalling systems which automatically control trains. The European Train Control System allows more trains to use the same stretch of track while maintaining safe distances between them.
To date, the use of AI in controlling aircraft has been limited to drones, although flying taxis that use AI to navigate have already been flight-tested. Experts say a human is still better at flying an airliner but AI is widely used in route planning, optimizing schedules and managing bookings.
7. Ride sharing and travel apps
Ride sharing apps use AI to resolve the conflicting needs of drivers and passengers. The latter want a ride immediately, while drivers value their freedom to start and stop working when they choose. Learning how these patterns interact, AI can send you a ride when you ask for it.
Travel apps use AI to personalize what they offer users as algorithms learn our preferences. Hotel search engine Trivago even bought an AI platform that customizes search results based on the users social media likes.
Uncanny how social media seems to know what you like, isnt it? Of course, its all down to AI. Facebooks machine learning can recognize your face in pictures posted on the platform, as well as everyday objects to target content and advertising that interests and engages you.
Job seekers using LinkedIn benefit from AI which analyzes their profile and engagement with other users to offer job recommendations. The platform says AI is woven into the fabric of everything that we do.
Unexpected breakdowns are every factory managers nightmare. So AI is playing a key role in monitoring machine performance, enabling maintenance to be planned rather than reactive. Experts say its cutting the time machines are offline by 75% and repair costs by almost a third.
AI can also predict changes in demand for products, optimizing production capacity. AI is currently used in about 9% of factories worldwide but Deloitte says 93% of companies believe AI will be a pivotal technology to drive growth and innovation in the sector.
Google says AI can enhance the value of wind power by 20%.
Image: Pixabay/enriquelopezgarre
10. Regulating power supply
Wind and solar power may be green but what happens when the wind doesnt blow and the sky is cloudy? AI-powered smart technology can balance supply and demand, controlling devices like water heaters to ensure they only draw power when demand is low and supply plentiful.
Googles DeepMind created an AI neural network trained using weather forecasts and turbine data to predict the output from a wind farm 36 hours ahead. By making output to the power grid more predictable, Google says it increased the value of its wind energy by 20%.
The views expressed in this article are those of the author alone and not the World Economic Forum.
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Did you know these 10 everyday services rely on AI? - World Economic Forum
How US cities are using artificial intelligence to boost vaccine uptake – Cities Today
US President Joe Biden yesterday announced a goal for 70 percent of the adult US population to have received at least one COVID-19 vaccine shot by July 4.
Cities are playing a key role in this historic vaccination effort, not only in terms of logistics and administration but also with respect to the critical component of resident engagement.
To maximise vaccine uptake, local governments are working to mitigate any resident concerns; to counter misinformation and distrust; and to clear up confusion about practicalities. To do this effectively they need to understand in close to real-time and at scale how citizens are feeling about vaccines.
Thats why nineteen US cities and counties, including Los Angeles, Philadelphia, New Orleans and Newark, are using advanced sentiment analysis to help shape and scale their vaccine programmes.
The initiative is a collaboration between Israeli start-up Zencity and the Harvard Kennedy Schools Ash Center, with funding from the Robert Wood Johnson Foundation and support from Bennet Midland.
Through the programme, the cities and counties are using Zencitys tools to collect and analyse organic feedback from publicly available sources such as social media posts, online channels and local news sites, alongside proactive resident input from community surveys.
Zencity uses artificial intelligence (AI) to classify and sort the data to identify key topics, trends, anomalies, and sentiment.
Each city will receive a report including insights on how opinions about the vaccine break down across demographic groups; trends and themes in community sentiment toward vaccination; misinformation that might need to be addressed; and recommendations for how to communicate about vaccines. Each citys results are benchmarked against the average results from the cohort.
Assaf Frances, Director of Urban Policy, Zencity,said: These results will enable cities to make data-informed decisions as they continue to navigate vaccine rollout. This could mean anything from making the appointment scheduling process more accessible if the results show that logistical hurdles have been a major barrier to mass vaccination, to providing more education around vaccine safety and efficacy to a particular segment of the population where the data is showing more hesitancy.
Deana Gamble, Communications Director, City of Philadelphia, told Cities Today: Were currently in a pivotal moment where vaccine supply has never been greater yet there is still a significant amount of vaccine hesitancy, especially among communities of colour. We need to provide accurate and up-to-date information to those who are still unsure about the benefits of getting the vaccine and how to do so.
With this in mind, Philadelphia has launched the six-month #VaxUpPhilly marketing campaign.
Gamble said one key insight from Zencity was that Philadelphia residents report similar levels of intention to get the vaccine as the cohort average, but they are more likely to wait longer.
This speaks to intention to get vaccinated yet less urgency with residents indicating that they require more information or evidence, specifically by seeing more people they know get the vaccine, Gamble commented. This shows us that the education efforts of our #VaxUpPhilly campaign including use of myth busters and trusted, credible messengers are critical.
Philadelphia faced controversy early in its vaccine rollout. In January, the city cut ties with Philly Fighting COVID, a young start-up which was running the citys largest vaccination site, after it emerged the company had cancelled testing efforts and become a for-profit entity, and concerns were raised about its privacy policy. Philly Fighting COVID said it had the best intentions and had not sold or shared any data but the incident was still damaging for the city.
Gamble said: We certainly acknowledge the mistakes the administration made working with the group which has necessitated rebuilding trust with the public about our vaccination programme. The insights gleaned from Zencity can help us better communicate with residents, which can help us overcome the challenges caused by Philly Fighting COVID.
Liana Elliott, Deputy Chief of Staff for New Orleans Mayor LaToya Cantrell, said that although New Orleans vaccine rollout is going well, we also are hitting our plateau a little bit earlier than we thought.
Understanding nuances around vaccine sentiment can help the city push through this.
Generally, the hesitancy that we thought we were going to find was not nearly as prevalent in the communities that we expected, Elliott commented, noting lower levels of concern than anticipated in communities of colour and more of a tendency for conservative white men to have reservations.
Further, as in Philadelphia, while many people are willing to get vaccinated, some dont want to go first.
Elliott said: We worked really hard to make sure that we are working with our community partners and getting proactive about talking to people about the vaccine and bringing vaccine events into communities.
This includes encouraging people to share when they have been vaccinated on social media, urging hospitality businesses to incentivise and support staff vaccinations and making the inoculation process a positive one. For example, a brass band played to mark the opening of the vaccination site at the Ernest N. Morial Convention Center and local bars hosted shots for shots events, which Elliott described as very New Orleans.
These approaches have really encouraged people to go check it out and just go get [their vaccination] done, she said.
The Zencity analysis has also helped New Orleans to shape vaccine messages and understand who are the trusted ambassadors best placed to deliver them.
Research published in March by global communications company Edelmanfound that US residents most trust doctors, scientists and public health officials about vaccine information and are more likely to trust someone like themselves or their organisations CEO than a government official. However, Zencity data showed that New Orleans Mayor LaToya Cantrell is one of the most trusted messengers for residents.
Feedback also highlighted some ways the city needed to simplify appointment booking. It then analysed sentiment to check the improvements were working, and this is a continuous process.
If we start seeing more chatter about [something being] hard or [people not knowing] when or where to go, then that means something is broken in that chain of communication we have got to go back and fix it, Elliott said.
She added that a key benefit of the programme with Zencity is: It really helps us confirm that what we are seeing and experiencing anecdotally and locally as staff is in fact holding up across not only our city but across the country and across all the other cohort cities as well.
Sometimes its not necessarily that it informs or changes how were doing things but it affirms that were going the right way and that what were doing is working, she said.
A national report on getting residents on board with vaccinations will be published by Zencity, Harvard Kennedy Schools Ash Center, the Robert Wood Johnson Foundation and Bennett Midlandlater this month.
Image: City of New Orleans
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How US cities are using artificial intelligence to boost vaccine uptake - Cities Today
Adoption of Artificial Intelligence to Have Strong Impact on Cutlery and Handtool Manufacturing Businesses | Discover Company Insights on BizVibe -…
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Artificial Intelligence is the Most Disruptive Technology of the Century – Analytics Insight
Artificial intelligence seems to be the next big thing in many industries today. The technology is infiltrating every sector and transforming the tasks that computers perform into a lot of hype. Starting from fitness-focused smartphone apps that adapt to womens menstrual cycle to autonomous vehicles that use sensors and software to dodge at stray animals, artificial intelligence has influenced every part of human life. It has evolved from being just a trend to a core ingredient virtually across every aspect of computing. In the modern world, businesses across diverse sectors use artificial intelligence as a tool to meet their goals, be it customer service through an intuitive chatbot or streamlining video production through synthetic voiceovers. For a term that dates back to 1956 and celebrates its 65th birthday this year, artificial intelligence has performed and revolutionized more than how anybody imagined.
As years passed, humans gained great faith in technology and machines, which eventually accelerated artificial intelligence adoption. Today, the role of artificial intelligence in an enterprise has become so important that it has touched every facet of business, and its crucial place will significantly grow over the coming years. Artificial intelligence, though revolutionary in itself, is an enabler that needs to be used effectively to achieve business objectives. Businesses are using AI agents to engage customers, rapidly create content, analyze transactions and detect fraud. Even though it comes with a lot of flaws, the speediness, customized content, and target recommendations, overweigh the cons.
AI-driven technologies have the potential to enhance our lives as both learners and workers. Researchers and developers are continuously improving them to mimic human behaviors in routines like learning, problem-solving, and processing language. While they are growing to be strong imitators of humans, they still lack essential human traits such as wisdom, insight, humor, and empathy. Fortunately, the next generations AI will carry all the objectives that humans think are essential for machines to cope up with them. The technological capabilities will attempt to solve real-world issues, moving beyond doing repetitive and routine works.
While big guys like Amazon, Apple, Google, and Microsoft scramble to infuse their products with artificial intelligence, other companies are hard at work developing their own intelligent technologies and services. The rise of digitization and the thirst for automation are fuelling the demand for AI solutions. Not just companies, even the governments are focusing on deep research in the field of finding, investing, and growing local talent to make their country the AI hub. Artificial intelligence companies are also initiating to deliver a robust service to their customers by using sub-technologies like machine learning, deep learning, edge computing, business intelligence, etc. as their prominent business principle. In a nutshell, artificial intelligence is used as a tool to integrate multiple sources of data or a vast amount of data, data security, real-world applications, predictions, cloud operations, etc. With the arena of AI technologies at the beginning, the world has experienced so much so far. The future is anticipated to be more sophisticated and personalized with the help of artificial intelligence.
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Artificial Intelligence is the Most Disruptive Technology of the Century - Analytics Insight
The EU Proposal for Regulation of Artificial Intelligence: meaningful steps toward grasping the medico-legal nettle? – Lexology
On 21 April, the European Commission published its bold proposal1 for a regulation laying down harmonised rules governing artificial intelligence.
As stated in the firms wider article on the significance of this move, in doing so the Commission has placed the EU at the forefront of the global debate on when and how risks arising from AI should be captured and regulated. Although the UK is no longer directly subject to EU regulations, the AI market is global. From a medical devices perspective, AI providers cannot ignore the regulations, especially if they wish to provide their products within the EU.
Overcoming tensions
Ever present within the proposed regulations is the familiar tension between, on the one hand, the desire to avoid encroaching on freedom to research and swiftly exploit new technologies bringing wide ranging expected benefits and, on the other, the need to protect the public. The proposals seek to bring the attendant risks within a workable legal framework.
Whilst some in tech have already signalled concern, the Commissions stated aims in producing the proposal are difficult to argue with. Taking a long term view, innovation only stands to benefit from legal certainty. Such certainty can only enhance the prospect of those working with AI securing confident investment, and build public trust and buy in - public confidence being key to the continued uptake of AI-based solutions. It will also help prevent the market fragmentation across the EU that might have come with a less comprehensive legal instrument.
The challenges AI presents to the legal orthodoxy are myriad, whether one considers the medical device regulatory regime, the common law fault-based liability framework injured patients traditionally navigate in clinical negligence cases in the United Kingdom, or the strict liability defect-based product liability framework.
Against this complex background, we go on to consider the key aspects of the Commissions proposal with a particular focus on what it could mean for stakeholders in the health sector.
The Commissions proposal in more detail
The proposal seeks to impose on high-risk AI systems an adjusted form of the regime governing medical devices (and indeed a range of other products). AI systems qualifying as high risk are expected to go through a conformity assessment process and be CE-marked before being placed on the market or put into service. Certain AI systems are entirely prohibited, and those that are not high-risk are subject to more limited obligations, but the focus for those in the health sector will overwhelmingly, for reasons set out below, be on the provisions relating to high-risk AI systems.
AI system is defined very broadly, and includes software developed by machine learning using a wide variety of methods, including deep learning; logic- and knowledge-based approaches; and finally statistical approaches, Bayesian estimation, search and optimisation methods. Any such software that can, for a given set of human-defined objectives, generate outputs such as content, predictions, recommendations or decisions influencing the environments it interacts with, will fall within the definition. From a medical devices perspective, Article 6 of the proposed regulation confirms that an AI system is high-risk where it is intended to be used as a safety component for a product, or is itself a product, covered by the Union harmonisation legislation at Annex II and would be required to undergo a third-party conformity assessment pursuant to that legislation. Annex II includes the EU Regulations on Medical Devices (MDR)2 and In Vitro Diagnostic Medical Devices (IVDR)3). The classification rules and conformity assessment procedures under the MDR mean that most software qualifying as a medical device will require the involvement of a notified body before CE marking, so will qualify as high-risk AI systems where they include an AI element. Specific systems deemed high risk may also appear in Annex III.
The proposed regulation provides that high-risk AI systems must be subject to an extensive risk management and quality management system and a technical file must be produced before being CE marked. Notified bodies will be enabled to assess conformity. Of interest to those in the UK, conformity assessment bodies in third countries may be authorised to carry out the activities of notified bodies under the regulation, so long as the Union has concluded an agreement with them. Some requirements are of interest both for their own sake and for the ways they seek to resolve some of the more vexed questions on how a liability system can navigate the challenges of AI. For example, Articles 10-14 of the proposal make provision for high-risk AI systems to:
The Commission states that the proposed minimum requirements are already state-of-the-art for many diligent operators and the result of two years of preparatory work, derived from the Ethics Guidelines of the High Level Expert Group on Artificial Intelligence (Ethics Guidelines for Trustworthy AI), piloted by more than 350 organisations. It goes on to state that they are largely consistent with other international recommendations and principles, which ensures that the proposed AI framework is compatible with those adopted by the EUs international trade partners. The precise technical solutions to achieve compliance with those requirements may be provided by standards or by other technical specifications or otherwise be developed in accordance with general engineering or scientific knowledge at the discretion of the provider of the AI system. This flexibility is particularly important, because it allows providers of AI systems to choose the way to meet their requirements, taking into account the state-of-the-art and technological and scientific progress in this field.
Article 60 envisages an EU database for stand-alone high risk AI systems, with providers under an obligation to register their systems and enter various pieces of information about them that will be accessible to the public.
As regards enforcement, for persistent non-compliance Member States are expected to take all appropriate measures to restrict or prohibit the high-risk AI system being made available on the market or ensure that it is recalled or withdrawn from the market. Non-compliance with the data and data governance requirements in Article 10 should not be taken lightly. It can lead to fines of up to a maximum of EUR30,000,000 or up to 6% of a companys total worldwide annual turnover for the preceding financial year if greater. Lesser penalties are envisaged for other instances of non-compliance and the supply of incorrect, incomplete or misleading information to notified bodies or national competent authorities.
One issue the proposal does not directly address is civil liability, though the explanatory memorandum states that initiatives that address liability issues related to AI are in the pipeline and will build on and complement the approach taken. It is worth taking a brief look at what might be expected in that regard.
EU initiatives on liability
Turning to the question of liability, medical device manufacturers and other stakeholders in the sector should be mindful of the European Parliaments resolution of 20 October 20204. In this resolution, the EU Parliament made recommendations to the Commission on a civil liability regime for AI. This will form a key strand in the blocs approach to grappling with AI.
The recommendations included revision of the Product Liability Directive5 to adapt to the digital world, including clarification of the definition of product, damage, defect, and producer. The recommendations acknowledge that by its very nature AI could present significant difficulties to injured parties wishing to prove their case and seek redress. In order to address what could be seen as an inequality of arms, they made various proposals, including that in certain clearly defined cases the burden of proof should be reversed.
In common with the Commissions proposal, the Parliaments liability recommendation also made reference to high-risk AI systems, singling them out as suitable candidates for a standalone strict liability, compulsory insurance-backed compensation system. Under that system, the front- and/or back-end operator of a high-risk AI system would be jointly and severally liable to compensate any party up to EUR2,000,000 where they had been caused injury by a physical or virtual activity, device or process driven by that AI system. The operator could not exonerate themselves with a due diligence defence only a force majeure type defence would be available and once the injured party had been compensated, the paying party could seek proportional redress from other operators based on the degree of control they exercised over the risk. In other words, apportionment would be dealt with between defendants later, once liability and any consequent compensation had been worked out with the injured Claimant.
Through the Consumer Protection Act (the legislation implementing the Product Liability Directive in the UK), a strict liability regime covering defective products has of course operated in this jurisdiction for many years. Clearly there is much debate over whether that framework will remain fit for purpose as AI based products evolve and proliferate in ever more varied and complex healthcare settings in future. Absent a contractual relationship between the patient and those responsible for the product incorporating AI, it also remains to be seen whether product liability claims will come to be viewed by claimants as a viable alternative to actions in tort. That said, adjustments to the core principles of negligence have of course been made before by the Courts, if with some reluctance, to meet novel challenges that arise in a complex litigation environment6.
Stakeholders will watch with interest how the Commissions proposal meshes with any forthcoming instruments tackling liability.
Welcome first steps
The Commissions proposal is a welcome development and the passage of the proposed regulation through the legislative process will be keenly observed globally. Notwithstanding that it will be a long time before a future iteration of the proposal becomes law, it provides a concrete starting point to begin to answer some of the many other questions posed by AI in a legal sense.
In tandem with the Parliaments recommendations, the question, for example, of legal personality for AI would appear to have been effectively sidestepped by instead looking at AI systems and operators. The proportionate approach of isolating high-risk AI systems for the greatest scrutiny is also a step in the right direction.
In the Medicines and Medical Devices Act 20217, the Secretary of State has at their disposal an enabling piece of primary legislation under which there are extensive powers to make regulations fit for the digital age.
When making regulations under the relevant subsection, the Secretary of State must have in mind the overarching objective of safeguarding public health. As part of this, consideration must be given to whether or not regulations would affect the likelihood of the United Kingdom being seen as a favourable place in which to carry out research, develop, manufacture or supply medical devices8.
With that in mind, all UK stakeholders will be keen to see sooner rather than later where they stand relative to those in the EU.