Theres no shortage of promises when it comes to AI. Some say it will solve all problems while others warn it will bring about the end of the world as we know it. Both positions regularly play out in Hollywood plotlines like Westworld, Carbon Black, Minority Report, Her, and Ex Machina. Those stories are compelling because they require us as creators and consumers of AI technology to decide whether we trust an AI system or, more precisely, trust what the system is doing with the information it has been given.

This content was produced by Nuance. It was not written by MIT Technology Review's editorial staff.

Joe Petro is CTO at Nuance.

Those stories also provide an important lesson for those of us who spend our days designing and building AI applications: trust is a critical factor for determining the success of an AI application. Who wants to interact with a system they dont trust?

Even as a nascent technology AI is incredibly complex and powerful, delivering benefits by performing computations and detecting patterns in huge data sets with speed and efficiency. But that power, combined with black box perceptions of AI and its appetite for user data, introduces a lot of variables, unknowns, and possible unintended consequences. Hidden within practical applications of AI is the fact that trust can have a profound effect on the users perception of the system, as well as the associated companies, vendors, and brands that bring these applications to market.

Advancements such as ubiquitous cloud and edge computational power make AI more capable and effective while making it easier and faster to build and deploy applications. Historically, the focus has been on software development and user-experience design. But its no longer a case of simply designing a system that solves for x. It is our responsibility to create an engaging, personalized, frictionless, and trustworthy experience for each user.

The ability to do this successfully is largely dependent on user data. System performance, reliability, and user confidence in AI model output is affected as much by the quality of the model design as the data going into it. Data is the fuel that powers the AI engine that virtually converts the potential energy of user data into kinetic energy in the form of actionable insights and intelligent output. Just as filling a Formula 1 race car with poor or tainted fuel would diminish performance, and the drivers ability to compete, an AI system trained with incorrect or inadequate data can produce inaccurate or unpredictable results that break user trust. Once broken, trust is hard to regain. That is why rigorous data stewardship practices by AI developers and vendors are critical for building effective AI models as well as creating customer acceptance, satisfaction, and retention.

Responsible data stewardship establishes a chain of trust that extends from consumers to the companies collecting user data and those of us building AI-powered systems. Its our responsibility to know and understand privacy laws and policies and consider security and compliance during the primary design phase. We must have a deep understanding of how the data is used and who has access to it. We also need to detect and eliminate hidden biases in the data through comprehensive testing.

Treat user data as sensitive intellectual property (IP). It is the proprietary source code used to build AI models that solve specific problems, create bespoke experiences, and achieve targeted desired outcomes. This data is derived from personal user interactions, such as conversations between consumers and call agents, doctors and patients, and banks and customers. It is sensitive because it creates intimate, highly detailed digital user profiles based on private financial, health, biometric, and other information.

User data needs to be protected and used as carefully as any other IP, especially for AI systems in highly regulated industries such as health care and financial services. Doctors use AI speech, natural-language understanding, and conversational virtual agents created with patient health data to document care and access diagnostic guidance in real time. In banking and financial services, AI systems process millions of customer transactions and use biometric voiceprint, eye movement, and behavioral data (for example, how fast you type, the words you use, which hand you swipe with) to detect possible fraud or authenticate user identities.

Health-care providers and businesses alike are creating their own branded digital front door that provides efficient, personalized user experiences through SMS, web, phone, video, apps, and other channels. Consumers also are opting for time-saving real-time digital interactions. Health-care and commercial organizations rightfully want to control and safeguard their patient and customer relationships and data in each method of digital engagement to build brand awareness, personalized interactions, and loyalty.

Every AI vendor and developer not only needs to be aware of the inherently sensitive nature of user data but also of the need to operate with high ethical standards to build and maintain the required chain of trust.

Here are key questions to consider:

Who has access to the data? Have a clear and transparent policy that includes strict protections such as limiting access to certain types of data, and prohibiting resale or third-party sharing. The same policies should apply to cloud providers or other development partners.

Where is the data stored, and for how long? Ask where the data lives (cloud, edge, device) and how long it will be kept. The implementation of the European Unions General Data Protection Regulation, the California Consumer Privacy Act, and the prospect of additional state and federal privacy protections should make data storage and retention practices top of mind during AI development.

How are benefits defined and shared? AI applications must also be tested with diverse data sets to reflect the intended real-world applications, eliminate unintentional bias, and ensure reliable results.

How does the data manifest within the system? Understand how data will flow through the system. Is sensitive data accessed and essentially processed by a neural net as a series of 0s and 1s, or is it stored in its original form with medical or personally identifying information? Establish and follow appropriate data retention and deletion policies for each type of sensitive data.

Who can realize commercial value from user data? Consider the potential consequences of data-sharing for purposes outside the original scope or source of the data. Account for possible mergers and acquisitions, possible follow-on products, and other factors.

Is the system secure and compliant? Design and build for privacy and security first. Consider how transparency, user consent, and system performance could be affected throughout the product or service lifecycle.

Biometric applications help prevent fraud and simplify authentication. HSBCs VoiceID voice biometrics system has successfully prevented the theft of nearly 400 million (about $493 million) by phone scammers in the UK. It compares a persons voiceprint with thousands of individual speech characteristics in an established voice record to confirm a users identity. Other companies use voice biometrics to validate the identities of remote call center employees before they can access proprietary systems and data. The need for such measures is growing as consumers conduct more digital and phone-based interactions.

Intelligent applications deliver secure, personalized, digital-first customer service. A global telecommunications company is using conversational AI to create consistent, secure, and personalized customer experiences across its large and diverse brand portfolio. With customers increasingly engaging across digital channels, the company looked to technology partners to expand its own in-house expertise while ensuring it would retain control of its data in deploying a virtual assistant for customer service.

A top-three retailer uses voice-powered virtual assistant technology to let shoppers upload photos of items theyve seen offline, then presents items for them to consider buying based on those images.

Ambient AI-powered clinical applications improve health-care experiences while alleviating physician burnout. EmergeOrtho in North Carolina is using the Nuance Dragon Ambient eXperience (DAX) application to transform how its orthopedic practices across the state can engage with patients and document care. The ambient clinical intelligence telehealth application accurately captures each doctor-patient interaction in the exam room or on a telehealth call, then automatically updates the patient's health record. Patients have the doctors full attention while streamlining the burnout-causing electronic paperwork physicians need to complete to get paid for delivering care.

AI-driven diagnostic imaging systems ensure that patients receive necessary follow-up care. Radiologists at multiple hospitals use AI and natural language processing to automatically identify and extract recommendations for follow-up exams for suspected cancers and other diseases seen in X-rays and other images. The same technology can help manage a surge of backlogged and follow-up imaging as covid-19 restrictions ease, allowing providers to schedule procedures, begin revenue recovery, and maintain patient care.

As digital transformation accelerates, we must solve the challenges we face today while preparing for an abundance of future opportunities. At the heart of that effort is the commitment to building trust and data stewardship into our AI development projects and organizations.

See more here:

Beyond the AI hype cycle: Trust and the future of AI - MIT Technology Review

When governments the world over announced lockdowns, the hunt for best collaboration and video-calling apps had begun for most users. There were video calling apps for funHousepartyand then there were business apps. But competition in the space was limited. Zoom captured a large share of the market with its user interface and accessible features. The disaster that followed in terms of the company trying to keep up with demand and buying Chinese servers gave space to the likes of Microsoft and Google to add more users. But as work from home becomes a norm, and people get attuned to living with video calling apps, companies are incorporating more features to keep their userbase. One of the biggest highlights for all apps has been the use of artificial intelligence and machine learning to attract users. The latest addition to this is Microsoft.

What has Microsoft introduced?Microsoft last week announced features that will help users enable team mode, where they can sit together in a different environment. So, with a virtual background, you can see everyone sitting right in front of you in a classroom, library or coffee house setting, thereby making the whole experience more personal. Microsoft is also trying to incorporate a feature which allows you to adjust brightness and other parameters of the video.

How is it different from virtual backgrounds?Zoom has had virtual backgrounds for long now. Microsoft is a late entrant, but the concept is the same. When Zoom uses virtual background, it often renders the depth of the image to superimpose other backgrounds on it. The machine-learning algorithm then identifies the human component and changes the rest. The technology is not perfect, adjust the camera too fast, and it will not work. In this case, Microsoft is using the same technology to extract you from the image and put you in the same room along with friends and colleagues sitting behind a desk or a table. That way you can see all the participants in one window.

What is Google Meet doing?Google is using AI differently. Instead of using it for video, it is using the technology to cut out background noise. This active noise filtering means that you can only hear the sound of the speaker, and every other sound gets muzzled.

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Teaming with AI: How Microsoft is taking on Zoom on virtual background front - The Financial Express

Lead author Ernest Lee, MD, PhD, and colleagues found many studies in the recent literature focused on image analysis and classification of skin lesionsno surprise since digital photography is by now ubiquitous in the field.

Here they comment that machine learning is a natural fit for translation into dermatology because dermatology is a specialty that is heavily reliant on visual evaluation and pattern recognition.

However, the researchers also found machine learning is being applied to everything from studying the genetic basis of skin diseases to identifying associations between comorbidities, and to designing and predicting patient responses to drug therapies.

The simultaneous rise of machine learning and next-generation sequencing in particular represents a golden opportunity to advance precision dermatology, and multidisciplinary collaborations between machine learning experts, biologists and dermatologists will be required to expand the scope of this research, Lee and co-authors write.

Read the original post:

Dermatology researchers: AI tools soon to be 'tightly integrated into daily clinical practice' - AI in Healthcare

The photo has been used for illustrative purpose.

It has been oft-quoted albeit humouredly that the ideal of medicine is the elimination of the physician. The emergence and encroachment of artificial intelligence (AI) on the field of medicine, however, puts an inconvenient truth on the aforementioned witticism. Over the span of their professional lives, a pathologist may review 100,000 specimens, a radiologist more so; AI can perform this undertaking in days rather than decades.

Visualise your last trip to an NHS hospital, the experience was either one of romanticism or repudiation: the hustle and bustle in the corridors, or the agonising waiting time in A&E; the empathic human touch, or the dissatisfaction of a rushed consultation; a seamless referral or delays and cancellations.

Contrary to this, our experience of hospitals in the future will be slick and uniform; the human touch all but erased and cleansed, in favour of complete and utter digitalisation. Envisage an almost automated hospital: cleaning droids, self-portered beds, medical robotics. Fiction of today is the fact of tomorrow, doesnt quite apply in this situation, since all of the above-mentioned AI currently exists in some form or the other. But then, what comes of the antiquated, human doctor in our future world? Well, they can take consolation, their unemployment status would be part of a global trend: the creation displacing the creator. Mechanisation of the workforce leading to mass unemployment. This analogy of our friend, the doctor, speaks volumes; medicine is cherished for championing human empathy if doctors arent safe, nobody is. The solution: socialism.

Open revolt against machinery seems a novel concept set in some futuristic dystopian land, though, the reality can be found in history: the Luddites of Nottinghamshire. A radical faction of skilled textile workers protecting their employment through machine destruction and riots, during the industrial revolution of the 18th century. The now satirised term Luddite, may be more appropriately directed to your fathers fumbled attempt at unlocking his iPhone, as opposed to a militia.

What lessons are to be learnt from the Luddites? Much. Firstly, the much-fictionalised fight for dominance between man and machine is just that: fictionalised. The real fight is within mankind. The Luddites fight was always against the manufacturer, not the machine; machine destruction simply acted as the receptacle of dissidence. Secondly, government feeling towards the Luddites is exemplified through 12,000 British soldiers being deployed against the Luddites, far exceeding the personnel deployed against Napoleons forces in the Iberian Peninsula in the same year.

Though providing clues, the future struggle against AI and its wielders will be tangibly different from that of the Luddite struggle of the 18th century, next; its personal, its about soul. Our higher cognitive faculties will be replaced: the diagnostic expertise of the doctor, decision-making ability of the manager, and (if were lucky) political matters too.

The monopolising of AI will lead to mass unemployment and mass welfare, reverberating globally. AI efficiency and efficacy will soon replace the error-prone human. It must be the case that AI is to be socialised and the means of production, the AI, redistributed: in other words, brought under public ownership. Perhaps, the emergence of co-operative groups made up of experienced individuals will arise to undertake managerial functions in their previous, now automated, workplace. Whatever the structure, such an undertaking will require the full intervention of the state; on a moral basis not realised in the Luddite struggle.

Envisaging an economic system of nationalised labour of AI machinery performing laborious as well as lively tasks shant be feared. This economic model, one of abundance, provides a platform of the fullest of creative expression and artistic flair for mankind. Humans can pursue leisurely passions. Imagine the doctor dedicating superfluous amounts of time on the golfing course, the manager pursuing artistic talents. And what of the politician? Well, thats anyones guess

An abundance economy is one of sustenance rather than subsistence; initiating an old form of socialism fit for a futuristic age. AI will transform the labour market by destroying it; along with the feudalistic structure inherent to it.

Thought-provoking questions do arise: what is to become of human aspiration? What exactly will it mean to be human in this world of AI?

Ironically; perhaps it will be the machine revolution that gives us the resolution to age-old problems in society.

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AI technology will soon replace error-prone humans all over the world but here's why it could set us all free - Gulf Today

A new study from West Virginia University (WVU) Rockefeller Neuroscience Institute (RNI) uses a wearable device and artificial intelligence (AI) to predict COVID-19 up to 3 days before symptoms occur. The study has been an impressive undertaking involving over 1000 health care workers and frontline workers in hospitals across New York, Philadelphia, Nashville, and other critical COVID-19 hotspots.

The implementation of the digital health platform uses a custom smartphone application coupled with an ura smart ring to monitor biometric signals such as respiration and temperature. The platform also assesses psychological, cognitive, and behavioral data through surveys administered through a smartphone application.

We know that wearables tend to suffer from a lack of accuracy, particularly during activity. However, the ura ring appears to take measurements while the user is very still, especially during sleep. This presents an advantage as the accuracy of wearable devices greatly improves when the user isnt moving. RNI noted that the ura ring has been the most accurate device they have tested.

Given some of the early warning signals for COVID-19 are fever and respiratory distress, it would make sense that a device able to measure respiration and temperature could be used as an early detector of COVID-19. In fact, weve seen a few wearable device companies attempt much of what RNI is doingas well as a few DIY attempts. RNIs study has probably been the most thorough work released so far, but were sure that many more are upcoming.

The initial phase of the study was deployed among healthcare and frontline workers but is now open to the general public. Meanwhile the National Basketball Association (NBA) is coordinating its re-opening efforts using uras technology.

We hope to see more results emerge from RNIs very important work. Until then, stay safe Hackaday.

See the original post here:

Detect COVID-19 Symptoms Using Wearable Device And AI - Hackaday

Many electric vehicle companies are enabling modern technologies like Artificial Intelligence and IoT in their vehicles

AI and IoT have transformed the entire delivery services especially with the electric vehicles

The implication of AI and IoT in electric vehicles ensure efficiency and safety

Urban logistics and delivery services are one of the main issues of every big and small city. From grocery to food items to everything, the delivery market has grown rapidly with the growth of technology and the Internet. It moves vehicles in rush hours and on roads which are already congested by private traffic.

According to the data of MDS Transmodal Limited, the impact of delivery services is that they represent between 8 and 18% of urban traffic flows and they decrease by 30% the road capacity because of pick-up and deliveries operations and it continues to grow in the coming years. Delivery operations have a high impact on congestion and urban environmental quality. They are responsible for about 25% of CO2 mobility emissions in urban areas.

A new venture that has joined the delivery services is that Electric Vehicles. The electric vehicle industry is growing rapidly to combat pollution. Electric vehicles (EVs) is seen as a catalyst to the reduction of CO2 emissions and more intelligent mode of transportation systems. The Government of India is also pushing for a shift towards electric vehicles for every purpose. The Indian government has claimed that India will move to 30% electric vehicles by 2030.

The Government of India has the vision of making the country electrically mobile. The government of India has encouraged mainstream electric mobility by dedicating INR 10,000 Cr to boost EV usage under Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) II scheme and a 5% reduction of GST on electric vehicles.

As the technology is growing and many industries are adopting the changes, many electric vehicle companies are enabling modern technologies like Artificial Intelligence and IoT in their vehicles. They are providing these e-scooters for many purposes, from personal use to now in the smart delivery ecosystem.

Use of e-bikes, e-cargo bikes and e-scooters is extremely positive for the enhancement of Corporate Social Responsibility (CSR), visibility and green image among customers and clients, cost savings because it consumes low energy and it is low maintenance and performances are very good. It is easy to access any location in urban areas and reliability is too high with these e-vehicles. This is the reason, nowadays more delivery giants are opting for e-scooters instead of petrol or diesel scooters.

Some problems are related to the usage of electric vehicles like the lack of adequate charging stations, limited autonomy especially in hilly areas and some technical malfunctions of engines and batteries. But the AI and IoT technologies have even come with the solution to all these problems.

AI and IoT have transformed the entire delivery services especially with the electric vehicles (EVs). Now, the electric scooters of the delivery executives are AI and IoT enabled. So that the drivers behaviour can be monitored for safe and timely delivery of goods. Companies have started using Telematics devices for tracking & monitoring vehicle movement during the delivery. These technologies will not only monitor the movement of vehicles but also ensure the safety of drivers in case of any kind of road accidents.

Using AI and IoT, it will be easy to contact the driver and a consumer in case of an emergency. These scooters can be controlled by a mobile application, GPS which are installed on the vehicles and an accelerometer can tell the company every single movement of a scooter during the delivery of the goods.

Using the AI and IoT, e-scooters which are equipped with cellular, GPS, and accelerometer technology, they use machine learning to interpret the habits of their riders and either notify dangerous habits of the drivers or alter their machines to produce safer conditions. Artificial Intelligence has now made it possible for the driver to look at the app after delivery and see where they went, how fast they drove, if they made any dangerous moves, and also give tips for a safer delivery next time.

Attachment of an accelerometer to a scooter with AI and IoT, also made it possible for the company or consumer to see when a rider accelerates too quickly or brakes too sharply. Electric vehicles also come with features like navigation assist, ride statistics, remote diagnostics, voice-enabled app, anti-theft alarm and lock, speedometer call alerts, ride behaviour-based artificial intelligence suggestions, which can be used in case of emergency. AI and IoT have helped the electric scooter to connect the drivers smartphone and store all vehicle-related data on the cloud.

Next level of tech revolution can be seen in the electric vehicle sector. There is 247 connectivity to a cloud server which allows a user to monitor the performance of the vehicle even when the driver is not around. Data analytic algorithms employed by the server analyses the data and notifies the user about possible service needs.

Modern technologies like AI and IoT have also improved the battery charging technology of Electric Vehicles (EV) and reduced the time it takes to stop at a gas station. It is the result of that Electric Vehicles companies are using artificial intelligence to monitor the state of the battery as it is charging. This improvement in battery technology has not only made delivery services faster but also safe for the consumers as well as delivery companies.

See the rest here:

Implication Of AI And IoT Enabled Electric Scooters For Smart Delivery Services - Inc42 Media

This detailed and well synchronized research report about the AI Governance market is the most significant, up-to-date, ready-to-refer research analysis that allows readers to draw substantial market specific cues that eventually remain crucial growth influencers in the AI Governance market , more specifically under the influence of COVID-19 implications that have visibly impacted normal industry process in multiple ways, leaving a trail of tangible implications.

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Market segment by Type, the product can be split into SoftwareServiceOther

Market segment by Application, split into BFSIHealthcare and Life SciencesGovernment and DefenseRetail and Car

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Some Major TOC Points:1 Report Overview2 Global Growth Trends3 Market Share by Key Players4 Breakdown Data by Type and ApplicationContinued

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Global AI Governance Market is accounted for xx USD million in 2019 and is expected to reach xx USD million by 2025 growing at a CAGR of xx% : IBM,...

Swedish supermarket Coop Sweden has a retail grocery assistant on its websites. Cooper, as the assistant is called, can help you with dietary requirements, suggest recipes and provide nutritional information. The idea behind Cooper is to increase interaction with consumers while providing a seamless shopping experience.

As consumers move online, implementing the technologies of the fourth industrial revolution (4IR) is becoming more crucial. Cooper is an example of the 4IR in practice. These technologies are changing the way we work, commute, communicate and, as Cooper will tell you, even shop. The 4IR is based on high-level technology such as artificial intelligence, automation, biotechnology, nanotechnology and communication technologies that permeates society. It is a combination of various technologies that can communicate with humans and interact with other devices and programs.

The lockdown necessitated by the Covid-19 pandemic has been an important yardstick for understanding behavioural changes in consumers as online options become more commonplace. A recent Nielsen study found that 37% of South Africans say they are shopping more online in this period. As Gareth Paterson, a lead retail analyst at Nielsen South Africa, put it, Amid the strange new world of Covid-19, online grocery shopping has been a lifeline for many South African consumers who have desperately sought out safe and secure shopping alternatives amidst the uncertainty of lockdown living. As a result, available online shopping platforms, especially for groceries, medicines, and other necessary items, have seen a surge in usage over the last few weeks as consumers prefer not to venture into stores and have increasingly opted for these reduced touchpoint alternatives.

According to data from the survey, Nielsen is anticipating that options such as click and collect and online personal shopping will grow exponentially, resulting in prolonged behavioural changes. Retailers have been quick to cotton on to this shift and have responded in innovative and effective ways. For instance, Checkers has launched an app called Checkers Sixty60, which has groceries delivered to you in 60 minutes. There are 5 000 groceries to choose from and options to substitute products if your first choice is not available.

In various industries, the coronavirus has been an important lesson where we are well equipped to deal with the 4IR and where we still have gaps. This will undoubtedly signal a shift in consumer behaviour and many will not return to traditional brick-and-mortar retail. We will increasingly see more retailers adapt to this way of operating. In fact, a report by global management consultancy Accenture last year suggested that South African retailers would see a knock to a business if they did not embrace e-commerce. The emphasis on traditional stores, Accenture argues, means that many retailers are losing out on the potential profits that come with online offerings. Yet, interestingly enough, the current pandemic may subvert this.

This is not to say that online shopping has not had somewhat of a watershed moment in recent years. Perhaps the best example that provides a holistic user experience is the Mr Price app. With it, you can shop online, find the stock in stores and even upload a picture of something you like for it to suggest similar items available on the app through the snap and shop feature. For instance, I could either take or upload a picture of a pair of brown formal shoes that I saw a colleague wear. The app will then pull any stock available at Mr Price that looks similar and provide a list of suggestions accompanied by pictures.

The starkest instance of the popularity of online retail is Black Friday, which has gained popularity in South Africa in the last few years. It is probably the biggest day of the year for retailers, particularly online retailers. In the week leading up to it, consumers receive hordes of massive Black Friday discounts. Some of them may have put together wish lists to check out at the stroke of midnight while others may have used their phones to search for discounts.

AI is tailoring the online experience and it is determining prices, inventory and making distribution far more efficient for your favourite retailers. Another example of this on Instagram is the move to online shopping with a new AR shopping feature that is being rolled out, which allows consumers to try on products digitally before buying them. For example, using your phone you could try on the latest shade of Mac lipstick to see how you would look. This followed a rollout of a checkout feature that allowed you to buy products directly on Instagram without ever leaving the app.

The try-on feature is limited to certain brands and is still in a trial phase, but it is as easy to use as the filters when you create a story that could give you dog ears and a tongue or freckles and blue eyes. The long-term vision is to roll this out with all retail, so, for example, you could see what a couch looks like in your living room. This is not the only technology Instagram has adopted. AI influencers have been introduced, which have been surprisingly popular.

According to consumer insight website LendEDU, three years ago 52.9% of millennials said Instagram has the most influence on them when making shopping decisions. For instance, many followers use the website LIKEtoKNOW.it, which sends a direct link to a product after a shopper likes a post. Creating completely digital influencers is a whole new avenue. Miquela is an AI influencer with 2.4-million followers. Just like any other influencer, her posts are perfectly planned, she has a themed feed, has sponsored content and gives her followers useful advice and brand recommendations. But she does not actually exist she is run with AI technology. This has not stopped her career from taking off.

Last year, she collaborated with Prada for Milan Fashion Week by posting 3D-generated gifs of herself at the Milan show venue wearing the spring/summer 2018 collection. On Pradas Instagram account, she gave their followers a mini-tour of the space, just like any influencer would for a brand. She is not an outlier there are many more like her. Balmain recently announced a Balmain Army made up entirely of computer-generated imagery (CGI) models. There is also a dedicated modelling agency for digital models called The Digital.

Amazon, the largest online retailer by revenue, has 45 000 robots at its warehouses to fulfil orders and a fleet of airborne drones into service for fast deliveries. It is not just online that retail is transforming with the 4IR. There is room to implement this kind of technology at brick-and-mortar level. The introduction of robotics has streamlined checkout processes, for instance. In the United Kingdom, you can self-checkout at grocery stores that weigh your goods to prevent theft. Similarly, there are robots akin to sales assistants in stores in the United States they can help you find an item either verbally or through the touch screen. Some robots can perform real-time inventory tracking.

Best Buy, the US-based electronics store, has an automated system much like the claw machine at the arcade that can retrieve products from shelves. There is scope to streamline and automate processes that will prove to be cost-effective for retailers in the long run. Accelerated adoption of technology will be a key strategic move that could lift retailers margins significantly. Retailers can introduce digital technologies and automation into their operations to reduce costs and enhance the customer experience. They can turn e-commerce from a threat to a growth opportunity, a McKinsey and Company report on the future of work in South Africa reads.

One of the grim realities of this era we are moving into is that there will be knock-on employment, particularly of low-skill workers. The caveat is that there will be demand for graduates and employees with higher skills levels, and we need to meet the demand for graduates not to fall into an even deeper unemployment crisis.

From a retail perspective, there is so much to be done that can augment consumers experiences. As industries vie to be a step ahead in the ever-changing context, consumers and business owners have to be open to these experiences and shifts. As physicist William Pollard once said: Without change there is no innovation, creativity, or incentive for improvement. Those who initiate change will have a better opportunity to manage the change that is inevitable.

Professor Tshilidzi Marwala is the vice-chancellor and principal of the University of Johannesburg and deputy chair of the Presidential Commission on the Fourth Industrial Revolution

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Cooper, the grocery assistant with AI, gives concierge service - Mail and Guardian

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Artificial Intelligence (AI) Software Market Size by End-user Application:

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Artificial Intelligence (AI) Software Market Size By Product Analysis, Application, End-Users, Regional Outlook, Competitive Strategies And Forecast...

SALT LAKE CITY, July 10, 2020 (GLOBE NEWSWIRE) -- In a release issued under the same headline on June 1, 2020 by OMNIQ, Inc. (OTCQB:OMQS), please be advised that the second paragraph as originally issued contained certain inaccuracies, not related to financial results or projections, which have been corrected below.

OMNIQ, Inc. (OTCQB:OMQS) (OMNIQ or the Company), announces that it has been selected to deploy its Quest Shield campus safety solution at the Talmudical Academy of Baltimore in Maryland.

The Quest Shield security package uses the Companys AI-based SeeCube technology platform, a ground-breaking cloud-based/on-premise security solution for Safe Campus/School applications. The platform provides unique AI-based computer vision technology and software to gather real-time vehicle data, enabling the Quest Shield to identify and record images of approaching vehicles including color, make and license plate information. The license plate is then compared against the schools internal watch list to provide immediate notifications of unauthorized vehicles to security and administrative personnel. In addition to providing a vehicle identification and recognition solution to the Talmudical Academy, the Quest Shield comprehensive security platform addresses other security concerns including controlling access to the buildings and visitor management as well as the ability to pre-register guests for school activities.

Additionally, as part of COVID-19 mitigation, parents in Maryland will be asked to take and record their childs temperature each day before they leave for school. Quest Shield will automate this process, by providing parents an online form where they may record the temperature. All Talmud Academy students will be equipped with an ID tag that will have a QR code that can be read with a barcode scanner. As students enter campus, faculty equipped with Quest handheld scanners will read the barcode to confirm that the students temperature has been taken that day; if the form has not been filled in, faculty will check temperatures before allowing students inside.

Shai Lustgarten, CEO of OMNIQ, commented: It is our privilege to work with the Talmudical Academy to provide our solution to enhance safety at their Baltimore campus. Quest Shield is an extension of the homeland security solution we designed for the Israeli authorities to fight terrorism and save lives.

Rabbi Yaacov Cohen, Executive Director, Talmudical Academy of Baltimore, commented:Concern about campus safety and the safety of our students and faculty drove the Talmudical Academy to seek ways to implement new strategies aimed at preventing crimes and violence that may be committed on the school grounds. The unfortunate reality today is that situations we could never imagine just a few years ago are happening now with increasing regularity. Most security systems that are currently being deployed on other campuses are good at recording events subsequent to crimes being committed. With Quest Shield, we have an opportunity to alert personnel and Law Enforcement ahead of any sign of violence.

Mr. Lustgarten added: The Quest Shield has been tailored to provide a proactive solution to improve security and safety in schools and on campuses as well as community centers and places of worship in the U.S. that have unfortunately become a target for ruthless attacks. Were pleased to work with a forward-thinking organization like the Talmudical Academy, it is gratifying that the Academy selected the Quest Shield platform to strengthen its security precautions.

Additionally, many schools and communities are expressing concern around children returning to school in the fall due to COVID-19. With that in mind, Talmudical Academy will also employ the Quest Shield to provide an automated screening process to confirm that students have had their temperatures checked, per Maryland regulation, upon their arrival on campus and prior to them entering the school facilities.

Mr. Lustgarten concluded, We are proud to be able to improve student safety in the U.S., as well as in other vulnerable communities. Quest Shield has previously been implemented by a pre-K through Grade 12 school in Florida and at a Jewish Community Center in Salt Lake City. We look forward to working closely with the Academy and other institutions to promote the health and safety of students, faculty and support personnel.

About OMNIQ, Corp.OMNIQ Corp. (OMQS) provides computerized and machine vision image processing solutions that use patented and proprietary AI technology to deliver data collection, real time surveillance and monitoring for supply chain management, homeland security, public safety, traffic & parking management and access control applications. The technology and services provided by the Company help clients move people, assets and data safely and securely through airports, warehouses, schools, national borders, and many other applications and environments.

OMNIQs customers include government agencies and leading Fortune 500 companies from several sectors, including manufacturing, retail, distribution, food and beverage, transportation and logistics, healthcare, and oil, gas, and chemicals. Since 2014, annual revenues have grown to more than $50 million from clients in the USA and abroad.

The Company currently addresses several billion-dollar markets, including the Global Safe City market, forecast to grow to $29 billion by 2022, and the Ticketless Safe Parking market, forecast to grow to $5.2 billion by 2023.

Information about Forward-Looking StatementsSafe Harbor Statement under the Private Securities Litigation Reform Act of 1995. Statements in this press release relating to plans, strategies, economic performance and trends, projections of results of specific activities or investments, and other statements that are not descriptions of historical facts may be forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934.

This release contains forward-looking statements that include information relating to future events and future financial and operating performance. The words anticipate, may, would, will, expect, estimate, can, believe, potential and similar expressions and variations thereof are intended to identify forward-looking statements. Forward-looking statements should not be read as a guarantee of future performance or results, and will not necessarily be accurate indications of the times at, or by, which that performance or those results will be achieved. Forward-looking statements are based on information available at the time they are made and/or managements good faith belief as of that time with respect to future events, and are subject to risks and uncertainties that could cause actual performance or results to differ materially from those expressed in or suggested by the forward-looking statements. Important factors that could cause these differences include, but are not limited to: fluctuations in demand for the Companys products particularly during the current health crisis, the introduction of new products, the Companys ability to maintain customer and strategic business relationships, the impact of competitive products and pricing, growth in targeted markets, the adequacy of the Companys liquidity and financial strength to support its growth, the Companys ability to manage credit and debt structures from vendors, debt holders and secured lenders, the Companys ability to successfully integrate its acquisitions, and other information that may be detailed from time-to-time in OMNIQ Corp.s filings with the United States Securities and Exchange Commission. Examples of such forward looking statements in this release include, among others, statements regarding revenue growth, driving sales, operational and financial initiatives, cost reduction and profitability, and simplification of operations. For a more detailed description of the risk factors and uncertainties affecting OMNIQ Corp., please refer to the Companys recent Securities and Exchange Commission filings, which are available at http://www.sec.gov. OMNIQ Corp. undertakes no obligation to publicly update or revise any forward-looking statements, whether as a result of new information, future events or otherwise, unless otherwise required by law.

Investor Contact: John Nesbett/Jen BelodeauIMS Investor Relations203.972.9200jnesbett@institutionalms.com

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CORRECTION - OMNIQ's Artificial Intelligence-Based Quest Shield Solution Selected by the Talmudical Academy of Baltimore - GlobeNewswire

By Balakrishna DR

Globally, the financial services industry has proved to be an enthusiastic adopter of Artificial Intelligence (AI) driven by the availability of data and investment appetite. Creative implementation of AI by start-ups and fintechs has helped further this trend. From personalisation to customer service, fraud detection and prevention to compliance, and risk monitoring to intelligent contract documents, AI has helped banks gain better control and predictability.

Today, customers expect faster, personal, and meaningful services and interactions with their banks and little tolerance for generic unsolicited messages. Therefore, banks must leverage AI to balance the need for privacy and security with personalisation and engagement. That said, the Indian banking sector has some amount of catching up to do.

While Indian banks have explored the use of AI, it has primarily been used to improve customer experience by adding chatbots as an additional interface for customers like SIA by State Bank of India, Eva by HDFC and iPal by ICICI. State-owned banks have been slow to leverage AI, largely because AI implementation requires banks to operate outside of the traditional privacy framework. India still does not have robust data protection and privacy policy. Reserve Bank of India (RBI) needs to take a commanding and dynamic role in framing regulations on emerging technologies, data privacy and ensuring the business interests of the banks.

Banks must adopt new business models simultaneously to integrate AI into their strategic plans and explore the use of AI for analytics and to improve customer experience. However, reliance on legacy systems, lack of data science talent, and cost constraints have impeded seamless adoption of AI. They must focus on three key aspects:

Fraud detection: AI plays a vital role in fraud detection, given the heightened threat of cyberattacks. As per the 2019 RBI annual report, losses due to banking frauds have risen by a whopping 73.8% despite the Governments efforts to curb them. What is more alarming is that banks took an average of 22 months between the occurrence of fraud and its detection, as per RBI data. Considering RBIs zero-liability safety net in the event of cyber frauds, it is imperative banks adopt best-fit practices and technology levers to mitigate these risks. With adoption of real-time payments, there has also been rapid innovation in the digital fraud landscape.

Set against this backdrop, banks must deploy context-sensitive AI solutions to enable advanced and adaptive real-time monitoring of their payment networks. These AI solutions additionally leverage relevant data points to assess transaction risk, true identity-matching, and identification of complex typologies and patterns.

Digitisation of processes: The tremendous proliferation of mobile devices and the internet can be leveraged to enable the superior user experience and analytics-based functionalities that give consumers an insight into their spending patterns and provide recommendations on investment and risk profiles. For instance, digitising the KYC process to eliminate the need for physical document submission and verification is something that traditional banks still do not offer. This can be simplified by utilising AI-based computer vision technology to verify documents, Optical/Intelligent Character Recognition (OCR/ICR) technologies to digitise scanned documents, and Natural Language Processing (NLP) to make sense of them.

Decision making: AI is a great fit in areas where decisions are based on available structured and unstructured data. For example, it can help predict potential loan defaulters and offer loss mitigation strategies that will work for them. It can help determine the best time to approach a customer to sell a new product. AI-based smart environments can collate data from multiple sources and drive an inference and enable SMEs to take decisions. AI can also improve straight-through processing using Intelligent Automation to automate repetitive processes that need decision making.

Given the magnitude of the challenge, it might make sense for banks to come together to establish a consortium for knowledge sharing on AI. This would also help Indias numerous regional and cooperative banks that are behind on the technology curve. A consortium could help uplift these small banks and enable them to be integrated seamlessly into a broader nationwide secure banking network. Whichever way it happens, AI in Indian banking is only set to grow.

The author is Senior VP, Service Offering Head Energy, Communications, Services and AI & Automation Services, Infosys

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Banking on AI: The time is ripe for Indian banks to embrace artificial intelligence - The Financial Express