College and University Campuses can Combat COVID-19

It’s graduation season around the world and for what seems like the first time, graduation will not commence per usual. The celebratory hustle and bustle of college campuses at this time of year is now replaced with empty classrooms, haunted hallways and desperate hopes that students will return in the Fall. The truth is, nobody knows what will happen in the Fall semester, but students aren’t the only ones feeling the immediate impacts of campus closures. Colleges and Universities are now scrambling to address not only the concerns of parents, students, and staff but also the significant impacts on endowments, revenues and their budgets going forward.

An Inside Higher Ed survey of 172 campus leaders shows that the number one concern remains bringing the students back to campus safely and continuing their high standards for education off campus. However, the financial focus is right up there, “more presidents citing a desire for financial health and operational planning support (60 percent) than for anything else.” Artificial Intelligence can address operational concerns while freeing up financial resources for other concerns such as faculty training and instructional technology.

Source: Inside Higher Ed

While revenues are experiencing immediate impact, the need to protect buildings and assets, ensure environmental compliance is met, and reduce building baseloads becomes more critical as staff and services are less present. After all, students need a campus to return to. Artificial Intelligence, and Maestro specifically, is primed to not only address these impacts in the immediate term but provide long-term stability and digital transformation.

At an operational level, buildings have been closed but the need to maintain them to prevent asset degradation and compliance requirements still need to be met. With fewer people onsite to identify and manage issues and IT stretched with online learning, now more than ever AI and autonomous or remote adoption of solutions need to be applied. At this point, it is likely that there are already significant maintenance backlogs, which AI can address and mitigate future negative impacts of.

The short-term, mid-term and long-term impacts can all be addressed through Maestro artificial intelligence in the following ways:


Short Term: Reduce costs, ensure compliance and protect assets through improved approach to managing assets with limited onsite staff. Optimize baseloads. Identify and prioritize critical failures. Iron out inconsistencies in data. Move to PPM.

Mid Term: Significant cost savings in resource efficiency, maintenance, increase asset life use, reduced capital expenditure.

Long Term: Enhanced scenario modelling for space optimization and asset acquisition ROI assessments.

Benefits like this can be achieved through Maestro’s artificial intelligence and neural network computing capabilities to target significant energy and maintenance cost reduction opportunities through automated, no-cost measures across the campus, eliminating the need for direct human interaction with the on campus assets. A run-rate to deliver a benefit of >$20m annually could easily be achieved in as little as 60 days through a rapid deployment of the technology and the prioritization of the highest energy cost consuming facilities.

In an effort to focus on creating a stable environment for students to come back to, Higher Education Institutions must turn to AI as a remedy for immediate negative financial and operational impacts caused by COVID-19. To learn more about how AI can turn your business operations around, stay tuned for our COVID-19 & AI series or contact our team today to learn more.


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AI & COVID-19: Stabilize & Survive

In the midst of the COVID-19 pandemic, why are corporations accelerating rather than delaying their digital transformation initiatives? The pandemic’s unprecedented impact on demand, workforce, supply chain, short-term costs and liquidity has forced corporations to take immediate, strategic action to maintain operations. In exploring their means of stabilization and survival, corporations found that Artificial Intelligence is uniquely positioned to ensure business continuity in the short-term, with its proven value in improving employee safety & security, short-term costs and liquidity.

While no industry has proven immune to the pandemic, the depth and breadth of its disruption in the manufacturing vertical clearly demonstrates why corporations have adopted transformational technologies over traditional solutions to beat COVID-19. Manufacturers have felt the acute pressure of COVID-19 in their plants and across their value chains.

  • Demand: Sharp declines in demand across non-essential product segments have disrupted each step of the value chain, driving significant earnings adjustments; essential goods producers are struggling to continue operations with heightened risk, and to satiate demand with unprecedented operating and supply chain limitations.
  • Supply Chain: Despite the geographic diversity of supplier networks, sudden overseas supplier shutdowns and domestic fulfillment delays have disrupted if not halted downstream activity, depleting on-hand inventory, prompting a rapid search for market alternatives, and driving material and part shortages, price increases, and an expected spike in upstream transportation costs as restrictions lift.
  • Workforce: Rapid adoption of new distancing protocols, shift structures and offsite resourcing arrangements have ensured employee safety & security, but constrained operating efficiency, quality, throughput and yield; deferred critical asset maintenance and replacement have increased downtime risk and may increase mid-term CAPEX obligations.
  • Short-Term Costs: Essential and non-essential product manufacturers have made significant adjustments to minimize variable costs, maintain business operations, and operate in an environment of significant macroeconomic and trade policy uncertainty, including layoffs, furloughs and temporary plant closures.
  • Liquidity: With strong macroeconomic headwinds, demand and supply side disruption, and constrained operational agility, liquidity is a principal concern of manufacturers that will not be alleviated at the moment restrictions are lifted, but gradually as the supply chain and broader economy rebound.

How is Artificial Intelligence empowering corporations with substantial value chain disruption to act fast and weather the storm?

Elutions’ highly-automated and autonomous Artificial Intelligence solution, Maestro, leverages historical data, deploys rapidly and delivers immediate improvements in safety & security, short-term costs and liquidity. The following Artificial Intelligence use cases are paramount to ensuring business continuity in manufacturing.

  • Remote Operability, Operational Automation & BEP Adherence: By enabling remote asset and process control, visualization and planning, and automated system-driven asset and process optimization, corporations ensure operational continuity, resilience and efficiency, improving employee safety & security, reducing labor requirements and operating costs, and increasing cash-on-hand.
  • In-Line Quality Assurance & Scrap Reduction: By enabling automated quality prediction and dynamic operating parameter adjustment at each stage of production, manufacturers autonomously ensure end-product quality, minimize scrap and rework, and optimize the Unit Cost of Production as conditions change, improving operating margins, yield (revenue), and liquidity through minimized waste.
  • Dynamic Downtime Prevention & Predictive Preventative Maintenance: By enabling dynamic, system-driven alternate control sequencing in the event of a sensor, asset or process failure, corporations autonomously avoid unplanned downtime, associated repair and replacement costs, and foregone revenue. With system-driven Predictive Preventative Maintenance and automated Work Order creation, corporations minimize downtime and production risk, extend asset use life, generate significant savings through right-time, right-size maintenance, and improve safety & security through truck-roll consolidation.
  • Market, Demand & Capacity Driven Procurement & Inventory Management: By continuously predicting raw material costs, sales and capacity alongside the live environment, and enabling automated procurement and IM directives, corporations optimize operating productivity, inventory levels, and the margin value of Inventory on-hand. Similarly, by continuously predicting replacement part costs, process demand alongside forecasted utilization, and automating replacement part purchasing, corporations optimize part inventory levels, reduce short-term costs and improve liquidity.

Beyond short-term survival, corporations have placed their bets on Artificial Intelligence to thrive in the mid-to-long-term. Stay tuned for more market intelligence on how AI is helping corporations build resilience and optimize operations.


Up Next: AI & COVID-19: Transformation


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Preparing for Landing: AI, Airports & COVID-19

An industry that felt a near immediate and drastic impact from COVID-19 was the air-travel industry. With the COVID-19 measures and bans, a large part of air traffic, mostly passenger but also cargo, has come to a near standstill across the globe. Air traffic has historically been cyclical, closely following the regional and global economic growth metrics, and it had experienced unexpected downturns during or after tragic events like 9/11. However, it has never been hit by an incident of this magnitude that led to reports by TSA of less than 1% of the amount of travelers going through airport security year over year from this time in 2019 to now.

Take Atlanta’s Hartsfield-Jackson a once bustling airport and one of the world’s largest and busiest hubs has now reported massive losses. According to the airport’s general manager, John Selden, “Revenue is probably down, off the top of my head, 50 to 60%,” he also added, “we usually have 2,600 flights a day here, fully loaded. In other words, almost no seats available. Right now, we’re down to 1,200 flights and they’re mostly empty.” The airport is down 85% in passengers.

While there is no clear picture on when air traffic will recover, looking at the TSA reports there is a clear increase in travel during the month of May thus far, at least in the US. Domestic markets are expected to be opened first, following the example in China. However, consumer confidence and regaining the trust of travelers will be integral to the timing and speed of industry recovery.

According an IATA-commissioned survey, 40% of passengers say they will wait 6 months or more before traveling. The recovery will also depend on the financial outlook as a prolonged global recession will dampen demand for air traffic further.


The uncertainty surrounding travel is leaving many leaders to wonder,

“How can we ever recover from this?” 

The answer lies in the application of Artificial Intelligence.


Artificial Intelligence-led initiatives will provide a helpful remedy to the negative impacts of the COVID-19-led disruption and will also inform post-COVID-19 operating models as they are developed and tested. As for many other industries, it is imperative to recovery for airports to fast-track AI-led initiatives in these times of increased operational uncertainty and unforeseen structural changes.

In the short to medium term, AI will help airports minimize their operational costs by increasing resource efficiency according to operational demand and reducing maintenance costs through predictive preventative maintenance, and maintain, possibly even enhance, their standards of operations with a reduced workforce through its autonomous application. In turn, greater flexibility will be provided to airports which had been forced to suspend terminal and runway capacity and reduce workforce as an immediate response to the loss of air traffic, particularly as some of the travel demand returns over the next few months.

In the medium to long term, AI will inform future operating models as airports will develop and test new ways to run every bit of their operations from car parks to passenger gates. Insights gained by AI will add a strategic value to airports as they plan for their future.

Businesses that successfully and swiftly adopt to automated, autonomous applications of AI and rethink their business models will be the ones realizing a competitive advantage once we return to normalcy. Contact our team today to harness the power of Elutions’ Artificial Intelligence Solutions.


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Why In-House Artificial Intelligence Projects Fail

Companies all over the world, from giant corporations to start-ups, are keen to cash in on the vast value of Artificial Intelligence. With an intent to capture as much of that value as possible, many spend millions on in-house AI solution development rather than outsourcing to address their most critical business challenges. In a world where there’s a feasible DIY solution for almost everything, Artificial Intelligence is most often the outlier. The complexity and cost of AI solution development demands experience to reduce financial risk and ensure speed to benefit, especially in highly competitive sectors.

Think of your business as a human body, and your business challenges as illnesses of varying severity. Some challenges, like some illnesses, are treatable with over the counter medications, while others require a visit to the doctor, prescriptions, long-term treatment or intensive care. If you had an illness that required extensive medical attention, you wouldn’t hesitate to seek out the best medical team for treatment. Should you treat your business any differently?

In deciding whether to go in-house or outsource, it is important to consider how a strategic AI implementation will impact your business. If it’s done right, it will reduce costs, increase revenue and enhance competitive advantage. If it’s done wrong, to what extent is your business at risk?

Financial opportunity from AI abounds across sectors (see the figure below), and there is both margin opportunity and market share on the table for the businesses that harness AI to tackle their strategic challenges first. In other words, getting your AI implementation done fast and right matters, and you must weigh your decision to go in-house or outsource accordingly.

Artificial intelligence (Al) has the potential to create value across sectors. 
Al impact, 
$ billion 
700 
500 
400 
Healthcare systems 
and services 
Public and social sectors 
300 
Advanced electronics/ 
semiconductors 
Retail 
Transport and logistics 
Travel 
Consumer packaged goods 
Automotive and assembly 
Banking 
Basic materials 
Insurance 
Media and 
entertainment 
High tech 
O Oil and gas 
100 
20 
Telecommunications 
Pharmaceuticals 
and medical 
products 
30 
Chemicals 
Agriculture 
Aerospace and defense 
40 
50 
60 
McKinsey&Company 
Share of Al impact in total impact derived from analytics, % 
Source: McKinsey Global Institute analysis

With competitive advantage on the line and the clock ticking, corporations place their bets on whether to navigate the AI journey alone or with partners. Instinctively, they are hesitant to collaborate, tantalized by the prospect of minimizing solution costs, while building their own innovative capacity and owning the resulting IP outright.

Logically, they then look to market outcomes and learn why in-house AI solution development efforts fail more often than not, even in the Fortune100 and at tech companies.

Without experience developing and delivering AI solutions, many corporations fail understand the costs, resources, processes, stakeholders, and even the objectives involved from the onset. As a result, in-house projects often lack a clear and viable design and delivery strategy, roadmap and KPIs, dramatically reducing the speed to benefit if not inhibiting benefit delivery altogether. Program costs and timelines become a driving force for failure. With little transparency into which aspects of the solution will drive the most value, there is no clear way to prioritize spending. Costs either spiral out of control, or corners are consecutively cut in design, development, testing and delivery, resulting in piecemeal solutions that impair data quality, promote bias and diminish solution accuracy, functionality, utility and outcomes.

More often than not, successful AI adopters partner with proven providers on a combination of off-the-shelf solution tailoring, ground-up solution design and solution delivery. How do they decide to partner rather than go it alone?

First, they recognize the competitive imperative for AI—the opportunity cost of following rather than leading in their market—along with the direct costs of failure, and their lack of in-house knowledge and experience with AI solution design and delivery. Second, they find a provider with a successful track record in similar or analogous environments. Third, they develop trust with that provider by laying the groundwork for a happy marriage in contracting. Then they see it through. From the leadership level-down, they commit to the partnership and collaborate from end-to-end to ensure project success.

Strategic AI implementations are broad in scope, capturing data and impacting activities across corporate ecosystems. This complexity is readily apparent in industry, where AI not only provides data-driven direction for decision-making at every step of the value chain and in every organizational department, but directly informs control and automation strategies in production, testing, packaging, distribution and even purchasing.

In recognition of the immense value and complexity of AI in industry, and the competitive need for speed in adoption, the World Economic Forum, in collaboration with McKinsey & Company, has published a toolkit of “practical recommendations” for industrials to accelerate their AI journey at scale. Appearing in The Next Economic Growth Engine Scaling Fourth Industrial Revolution Technologies in Production, this toolkit advocates the adoption of proven AI solutions and related technologies through a partnership and acquisition approach rather than in-house development.

Figure 6: Industry toolkit for accelerating adoption of technology 
Value delivery engine 
Intelligence 
• Predictive maintenance 
• Machine learning-supported, 
root-cause problem-solving 
for quality claims 
Connectivity 
Augmented reality-guided 
assembly operations 
Real-time IOT-based 
performance management 
Flexible automation 
• Robots to automate 
challenging tasks 
• Real-time product release 
39 high-impact digital applications ready for deployment 
Scale-up engine 
Mobilize 
Mobilize the 
Organization 
Strategize 
Set the vision and the 
value to capture 
Innovate 
Spark innovation by 
demonstrating the 
value at stake 
Scale up 
Capture full value 
& Company, Fourth in With the World

With more and more data available for exploit across industries, the opportunities for its monetization through AI are greater and increasingly complex. So too is the risk of getting your implementation wrong.

Can your business afford the DIY approach?


Challenge us to solve your unsolvable business quandaries.


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Facial Recognition, Literally?

Artificial Intelligence is transforming the way consumers purchase, the way business is conducted across industries, and the multi-billion dollar beauty industry is not getting left behind. In fact, there are a multitude of companies using AI to personalize and revolutionize skincare, haircare and everything in between.  Using AI to personalize the experience may prove to be one of the best ways to differentiate in a heavily saturated market.

Is AI the answer to not only changing how consumers interact with beauty product, but also the answer to future product development?

In a market as personal as cosmetics, specifically skincare, where everyone has unique concerns and desires, the ability to use Artificial Intelligence to personalize could be truly revolutionary. Is it possible that the key to ageless, flawless skin is Artificial Intelligence? The women behind PROVEN skincare believe that it is. PROVEN uses AI, aggregating data into the world’s largest skincare database, The Skin Genome Project, 8 million consumer reviews, 100,000 skincare products, 20,000 ingredients and 4,000 academic journals, to tailor skincare products to consumers’ specific needs. Consumers go to PROVEN’s website, take a three-minute skincare quiz and are provided with a skincare routine, taking the guesswork out of which products will deliver the best results.

“Using your answers to our Skintelligence QuizTM, our database instantly sifts through this incredible amount of information to select the best ingredients for your skin. This means you won’t waste time and money trying out products that may or may not work. And if your skin changes, your skincare can evolve right along with you.”

Proven

Taking the concept of Facial Recognition quite literally, FOREO, a tech-enabled skincare and oral care corporation, has recently launched a product that uses facial mapping and artificial intelligence to up your skincare routine. The Luna Fofo analyzes your skin and produces real-time readings that in turn customize your smart facial massage and cleansing routine. The Luna Fofo doesn’t do a one time analysis, rather it continuously analyzes your skin and constantly customizes your routine to your skincare concerns, even tracking your skin’s hydration levels. All of this is stored in a user friendly app so you can track your daily skin health with ease.

These are just a few consumer product-enhanced forms of AI that are transforming the beauty industry and the way consumers interact with AI daily. Beyond customer interaction, could AI enable advanced data capture and analysis to drive product development?  Manufacturing?  Sourcing?

Where is the limit of expansion for AI technology in business?


Challenge SolvetheUnsolvable to change your industry with AI.


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Facial Recognition, Data Privacy and Your Identity

For age old reasons, the government issued ID or passport has been the official link between our facial features and our identification. And the two in combination have been the traditional way of both authenticating and identifying us on an ad-hoc and transient basis at bars, banks, airports, and so much more…

The range of how our identity and facial features can be used in both private affairs and civil procedures is virtually endless, even without our knowledge or explicit consent. The regulation of usage is a difficult topic for unanimous agreement surrounding our privacy and safety in the same world where freedom of expression, movement and liberty contribute to our livelihoods.

Then we introduce technology to the equation.

Where technology adds a level of magic, comfort and efficiency to our lives, never experienced before relieving us of the boring, mundane and impossible it also adds a level of risk to our data privacy and security. And we all know that once something has been introduced to the internet, it’s near impossible to remove.

Take Google Nest Hub Max – we entrust it to connect us to our homes when we are far away for us to track and see for ourselves key events – saving energy, ensuring comfort and convenience whilst maximising the surveillance and security of our babies, dogs and homes. But can we trust where Google is storing our most sensitive data and what they are doing with it? Nest uses Face Match, facial recognition software, which is enabled by the front facing always-on camera for security, to understand which user is using it and for video calls. If the feature is on, the detection is constant and the security of our data, how it is being processed and stored, cannot be guaranteed. The detection can however be turned off, but at the detriment to functionality.

Turn to Apple photos, Google Photos and Facebook tagging – instances where facial recognition is applied to data you provide, aka your photos. The ease of photography, the popularity of the selfie and the constant desire to update your friends, family and followers on your day-to-daymeans bulky streams consisting of hundreds if not thousands of photos. Manually organising these photos is administrative and time-consuming, in other words, something AI and automation can now do for us. So when Apple’s algorithms can identify the faces of your family and friends, even your pets, organise them and allow you to search by face, does this functionality make the security risk worth it?  

Facebook’s facial recognition feature notifies you when others upload photos of you. Whilst recent developments enable an individual to opt-out of this function, there is no guarantee that Facebook itself is not scanning and processing your image. Harnessing your identity to potentially create an online profile of you to sell to advertisers and who knows what else. Likewise with Google – which uses facial recognition and automation to autotag photos of you and your friends – you can also choose to opt out, but you have no control over what your friends may decide to do with photos of you and where that data publicly ends up.

All of these technologies and instances of applied facial recognition also enable facial mapping, providing swift and secure entry into our smart phones – deeming them impenetrable when in the wrong hands. Once unlocked, a further safeguarding layer of facial recognition is provided for mobile payments like Apple Wallet, which unlike other touch-less forms of payment, has no limit.

Whilst there is an enigma surrounding where our facial image data actually lives inside of Google, Facebook and Apple’s servers, how secure it is and how effective is the encryption?  One thing is certainly clear, the multi-purposes of our devices and their built in sensitivity to our changing environments that simplify and augment our lives  – be it Nest which knows, in real time, the occupancy of our homes and our preferred weather, or our phones which house our banking details alongside thousands of images, text and browser history – the future of our data privacy begs the question:

Is the cost of convenience and our need to publish and document our life’s moments  worth more right now than the risk of jeopardizing our privacy and possibly identify?


Up Next: AI & COVID-19: Transformation


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Enterprise Artificial Intelligence – Academic Theory or Ready for Primetime?

Solvetheunsolvable has already explored various aspects of consumer AI and products purporting to leverage AI technologies, but is AI for Enterprise ready for primetime?

Investors aren’t the only ones betting big on Artificial Intelligence, it turns out Higher Education is also investing heavily into the space. With heavy investment in research and development, enterprise level AI seems to be having a rocky start.  Earlier this month Northeastern University allocated $50 million to an Institute for Experiential Artificial Intelligence. This institute will be dedicated to uniting leading experts to solve the world’s unsolvable problems.

“This new institute, the first of its kind, will focus on enabling artificial intelligence and humans to collaborate interactively around solving problems in health, security, and sustainability. We believe that the true promise of AI lies not in its ability to replace humans, but to optimize what humans do best.”


Northeastern President Joseph E. Aoun

This isn’t Northeastern’s first step into the world of Artificial Intelligence and Automation. They already have an Institute for Experiential Robotics that is bringing together engineers, sociologists and other experts, including economists, to design and build robots with abilities to learn and execute human behaviors.  Northeastern isn’t just building Institutes for experts to conduct research, they are making it a priority to prepare their students for success in the age of artificial intelligence. They have an entire curriculum dedicated to what they call, humanics which is a key part of their strategic plan, Northeastern 2025.

Northeastern 2025 Promo Video

“We are building on substantial strengths across all colleges in the university,” said Carla Brodley, dean of the Khoury College of Computer Sciences. “Experiential AI is highly relevant to our mission.”

Though Northeastern is an example of one university betting heavily on AI, they are not alone in their quest to equip students with proper education for the AI-enabled future. In fact, government agencies are getting involved in funding AI in Education. The UK has pledged to invest £400 million in math, digital and technical education through the government’s AI sector deal to protect Britain’s technology sector amid Brexit and an additional £13 million for postgraduate education on AI. In the US, just a few days ago, the National Science Foundation announced a joint federal program to fund research focused on artificial intelligence at colleges, universities and nonprofit or nonacademic organizations focused on educational or research activities. 

The National Science Foundation is awarding $120 million to fund planning grants and support up to six institutes, but there’s a catch. Each institute must have a principal focus on at least one of six themes:

  • Trustworthy AI
  • Foundations of Machine Learning
  • AI-Driven Innovation in Agriculture and the Food System
  • AI-Augmented Learning
  • AI for Accelerating Molecular Synthesis and Manufacturing
  • AI for Discovery in Physics

As universities and governments bet big on the future of AI and education, it underscores the importance of AI on a global scale in the future, but does it call into question the current existence of AI solutions ready to take business to the next level? Utilizing AI and automation will be imperative for corporations to remain competitive and for the advancement of business, but when will the floodgates be swept open, and by who, remains a mystery.

Will you leap into the future and embrace AI now? How do you see the futuristic vision of enterprise AI transform your business? Challenge Solvetheunsolvable with your business conundrum or leave your thoughts in the comments below and let’s explore what AI can do for you. 


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Artificial Intelligence: The Future of Healthcare

What’s more important to parents than the health and well being of their children? Not much, if anything. So imagine this… your child could have a disease that an Artificial Intelligence enabled iPhone app would diagnose more than a year before doctors and all you have to do to find out is take some photos. Sound too good to be true? With the power of Artificial Intelligence, alternative health care tests, such as this one for children, could literally be in your hands right now…

A post from Government Technology explains:

“CRADLE makes use of artificial intelligence to look at baby pictures taken with a flash and pick out instances of white eye. When tested on 50,000 images of 40 children, half of whom had been diagnosed with an eye disease, the technology was able to identify white eye in pictures taken up to 1.3 years before the child was diagnosed.”

This non-intrusive, ultra- convenient Artificial Intelligence enabled technology is pushing the boundaries of digital health diagnosis, and this is just one example. In addition to convenience, your data privacy is less at risk as the app analyses the photos right on your device, reducing latency and increasing privacy by not uploading to a server. This type of technology, when developed further, could be very useful to detect a variety of health issues.

In fact, there are other apps that are already utilizing AI to address a host of mental and physical health concerns. Some of these health applications range from AI chat bots programmed to treat mental health all the way to AI-enabled apps that can help women track and predict fertility. Investors are betting big on these AI-enabled health apps with millions in funding being pumped into these companies of the future.

The future of AI-enabled apps is certainly bright. Wearable tech, like FitBit or Apple Watch, when equipped with built-in Artificial Intelligence, could one day utilize personal health data to identify diseases such as cancer in the very early stages. Apple Watch is already able to use AI to identify irregular heart beats known as paroxysmal atrial fibrillation (Afib) with 97% accuracy.

Image result for healthcare cost rising

With the continuous rise of healthcare costs, for individuals and the country as a whole, consumers are looking towards AI for more affordable self-diagnostics. This is evident in more than AI health apps, but also in many at home health kits such as, EverlyWell and QuestDirect, stay tuned for our Data Privacy Series article on at home diagnostics coming soon.

Artificial Intelligence is improving the healthcare space at rapid speed and the technology is only getting better. So the question that must be posed is:


Could AI be the key to solving the $760 billion healthcare crisis?


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Alexa, How are you using my data?

Smart Home technology is a well saturated market with technology that just a short few years ago many thought could not be possible. We have long talked about voice assistants and video enabled devices but now technology that was once thought to be futuristic has arrived, seemingly omnipresent in many households around the global. Not only are Artificial Intelligence enhanced video enabled devices now available but they come in many varieties, from home protection to two-way video chatting with your pet.


Video “chat” with a pet?….

When did animals start chatting?


With these ever present devices in so many households – cameras, digital assistants, smart TVs, smart thermostats and more – are we enhancing our physical privacy or actually putting it in jeopardy? Are the benefits, such as automation, smart phone remote capabilities and more, worth the risk of data privacy?

Are you taking advantage of Smart Tech, or is it taking advantage of you?

So what’s the big deal if your smart home has data that’s making your life easier? Amazon’s Alexa can make it easier for you to order more household items. Google Home can integrate with Google Nest to allow you to control your A/C by simply telling it to change the temperature. All great features that help make things a little bit more convenient in our day to day, but what exactly are these companies doing with our data?

Amazon is pretty transparent in regards to the voice data Alexa is storing, a quick look on their website tells us that. But what about Google, their biggest competitor in the Smart Home space? Google is fairly transparent as well, though as previously mentioned in the intro post, changing your privacy settings may impact your service. Google’s privacy policy website tells us that they are mostly using your saved data to improve searches and targeted ads, see this video below:

These are great examples of transparency from these corporations and they outline relatively mundane uses for your data but it’s still important to understand. The future consequences of these corporations having your stored data should be the biggest concern. Google’s CEO Eric Schmidt said in 2010:

“One of the things that eventually happens … is that we don’t need you to type at all,” later adding: “Because we know where you are. We know where you’ve been. We can more or less guess what you’re thinking about.”

Eric Schmidt

Adapt that quote to the Smart Home and eventually Google doesn’t need you to speak to Google Home, rather the A/C just changes to suit your pre-determined preferences when you arrive home because of patterns in your stored data combined with Artificial Intelligence. Alexa doesn’t need you to tell her to order paper towels, they just show up because all of your stored data has told them it’s time for another shipment.

While these specific examples of transparency regarding data storage are promising, consider how much you’re willing to give away and where the line is with your data privacy. Consider the fact that these devices are always listening and while the corporations behind them may be simply using this data to “train” their AI, the government or third party apps could be using this data for other reasons.

In 2018 law enforcement subpoenaed Amazon for Amazon Echo data as evidence in a criminal trial for murder. The lines between privacy, technology and criminal justice are changing daily. Amazon is not the only tech company that has had this happen, Fitbit and Apple have run into similar situations.  While most technology companies are quick to defend consumer privacy the question still stands:


How much of your personal privacy are you willing to give away?


Letting AI into our daily lives is not something to fear but maintaining control over data and privacy should be a top concern. There’s many ways to protect your privacy, or at least limit your exposure, while utilizing the benefits of Smart Home tech. Awareness is the first step in achieving enhanced privacy. Visit 101 Data Protection Tips for a comprehensive list of ways to attempt to protect your privacy.


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