AI & COVID-19: Safely Back to School

As we enter September, in one of the strangest years to date, COVID-19 has infiltrated nearly every facet of our everyday lives. When people leave their homes, it is normal to grab keys, cellphone, wallet and now a mask. For most, the changes have simply become the new routine. But one of the biggest disruptors caused by COVID-19 is in the return to campus for many college students. This results in colossal questions being asked, and one extremely important question:

How can we ensure the protection of our student-body, faculty and staff braving the return to college campuses across the globe?

Recently, the World Health Organization (WHO) released that “…current evidence suggests that COVID-19 spreads between people through direct, indirect (through contaminated objects or surfaces), or close contact with infected people via mouth and nose secretions. These are released from the mouth or nose when an infected person coughs, sneezes, speaks or sings, for example.” We recognize that the spread of COVID-19 is an Airborne illness and yet, if colleges are to re-open this fall as many already have, how can we protect the integrity of the open, constructive in-person dialogue that many classrooms thrive upon? The answer exists, partially, in making the environment on campus the healthiest for all, limiting the spread of COVID-19.

According to the WHO, many reported outbreaks of COVID-19 share their occurrence in “closed settings, such as restaurants, nightclubs, places of worship or places of work where people may be shouting, talking, or singing.” Additionally, the lack of social-distancing in practice and lack of mask wearing increased the rate of the spread and we’ve seen in many States bars and restaurants closing again to contain outbreaks. One of the most important things to pay attention to regarding these outbreaks and the future spread is this statement from the WHO,

In these outbreaks, aerosol transmission, particularly in these indoor locations where there are crowded and inadequately ventilated spaces where infected persons spend long periods of time with others, cannot be ruled out.”

The World Health Organization

Beyond wearing a mask, social distancing and lowering the capacity of contained spaces, the physical environment of the classroom and broader spaces can have a profound effect on the virus’ ability to spread. We acknowledge that this is one of the keys leading to the decreased spread of COVID-19 on the College Campuses, increasing the safety for all. In fact, we are currently working with esteemed universities to prepare their shared spaces for the return of activity on campus.

For years, our team has followed the gold star of industry standard guidelines from the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) and other international equivalents in our work on campuses and beyond. ASHRAE published a report in April of 2020 to rebut some false statements regarding HVAC and also put out a full statement with guidelines regarding the optimal HVAC conditions to decrease the spread of COVID-19.

In their reports, ASHRAE specifically stated the following, “Transmission of SARS-CoV-2 through the air is sufficiently likely that airborne exposure to the virus should be controlled. Changes to building operations, including the operation of heating, ventilating, and air-conditioning systems, can reduce airborne exposures.” This is not only pivotal to the re-opening of college campuses but in all industries where offices are re-opening for example, busy sales floors at large corporations or call centers where many people are talking all day long in close quarters.

In relation to universities and colleges specifically, our team works with facilities teams to automate implementation of the guidelines set by ASHRAE’s Epidemic Task Force. The new guidelines for COVID-19 are vast and the automated implementation by Maestro allows for facilities teams to focus on non-COVID-19 related projects. While Maestro’s core remains to reduce operational and energy spend, our team is passionate about making the working environment as safe as possible for students, faculty and staff to return to this fall.

With Maestro, it is possible to return to safer classrooms and offices, all while achieving significant energy and maintenance cost reduction opportunities through automated, no-cost measures across the campus, eliminating the need for direct human interaction with the University’s assets.

Contact us to learn how Maestro can make your campus a safer place to return to.


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Virtual CogX: The Festival of AI & Breakthrough Technology

Elutions is proud to announce their Lead Partnership of The CogX Global Leadership Summit and Festival of AI & Breakthrough Technology, June 8th- June 10th. In a world that is constantly in flux to adapt to impacts of COVID-19, CogX made the difficult decision to virtualize their event. We fully align with this decision as they themselves said,

“There are important, and in some cases urgent, topics to discuss: both the immediate challenges presented by COVID-19, and to play our part in helping restart the economy by connecting, collaborating and supporting each other.”

Relevant, now more than ever, is CogX’s 2020 Event Theme- How Do we Get the Next 10 years Right? Outlined below are the ways in which the conference aims to address this massive question:

– Move the conversation forward with concrete actions

– Reframe the climate emergency as the biggest economic opportunity in the last 200 years

–Increase understanding of the current Covid-19 pandemic and champion innovative solutions

The global pandemic has allowed many of us, corporations and individuals, to pause and re-evaluate what the next ten years will look like. It is clear now that the 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.

We will be hosting a virtual expo booth across the three days, June 8th through June 10th, where attendees can reach out to our team to learn more. We will also be hosting virtual lunch and learns, happy hours, and coffee chats. Our Managing Director of EMEA, Jamie Devlin, will also be a featured speaker on Industry 4.0 and sustainable supply chain, Monday, June 8th, 5pm BST (12pm EST).

For a limited time, we are offering our readers, interested in attending our speaking events, the chance to receive a Gold Pass, free of charge. Please click here and provide your full name, title at your company, email address and phone number to receive a Gold Pass.


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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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AI & COVID-19

Throughout modern history, several infectious diseases have spread with sufficient speed, scale and severity to be considered pandemics. Malaria, Smallpox, H1N1, and HIV/AIDS, which remains active, made the list. COVID-19, however, is in a league of its own. The last pandemic of comparable economic impact, if not on human life, was the Spanish Flu, which directly followed WWI and wrought havoc in a significantly less interconnected world than the one in which we live today.

The Global Impacts of COVID-19 have already been unprecedented. “Stay-at-home,” “social-distancing” and travel and trade restrictions imposed to protect public health have had devastating impacts on the global economy, supply chain and employment. How and when this pandemic will end remains unclear. What is certain is that businesses now face an existential threat, and their leaders must take immediate action to set and execute strategies to weather the storm and ensure they are prepared for future economic, operational or human crisis.

In a time when “non-essential” businesses have been forced to shutter operations or shift to remote collaboration, and “essential” businesses face unparalleled demand alongside novel operational and supply chain challenges, how can manufacturers, O&G companies, airports, utilities, universities and other major businesses survive?

If they adapt quickly, can they thrive?

The answer to this question for industry lies in the adoption of end-end Artificial Intelligence.

Over the next few weeks, we will dive into the major business impacts of COVID-19 and how Elutions Artificial Intelligence platform, Maestro, is addressing them across multiple verticals.  We strongly believe that businesses that successfully and swiftly adopt automated, autonomous applications of AI and rethink their business models will be the ones realizing a competitive advantage once we return to a “new normal”.

Inspired by industrial trends a multitude of sources, reports by McKinsey and many others, Elutions’ AI & COVID-19 Series will specifically address the themes of Survival, Optimization, and Transformation. 


Survival: Artificial Intelligence applied immediately to stabilize business operations.

Optimization: Artificial Intelligence’s intermediary impacts, growing and preparing for a “new normal.”

Transformation: Artificial Intelligence’s long-term impacts in a post-pandemic landscape.


Check back in with us weekly for new content on how to address the business impacts of COVID-19 through the strategic application of end-end Artificial Intelligence.


Up Next: AI & COVID-19: Transformation


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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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DNA Testing: Is knowing your heritage worth risking your privacy?

Consumer data is becoming a form of currency for most corporations. If it seems like every company is constantly trying to get you to share your data, it’s because they are. Data, especially when it’s connected to your specific demographic profile, is extremely valuable to companies to gain insights about a multitude of trends in order to target advertising and more. But what makes our personal genetic data so valuable? And why are we so willing to give it to genetic-testing companies?

Do we realize what personal rights we are forfeiting in the future when we eagerly dive into knowing about our past?

If data is so valuable, we should be protecting it the way we would protect our wallets, but often there is little care given to our personal data or meta-data. When genetic-testing companies exploded into the market, consumer response was huge. It felt like every one of our family members, friends, and co-workers were finding out more information about their genetic makeup and sending the kits out as gifts. All the hype and the benefit of having a deeper understanding of genetic history was enough for many people to jump on the trend without giving much thought to the risk.

“The key thing about your genetic data … it is uniquely yours. It identifies you, so if you are going to entrust it to a company, you should try to understand what the consequences are”

Jennifer King, director of consumer privacy at Stanford Law School’s Center for Internet and Society

The risk of giving so much genetic data to these companies, whether they are helping you learn more about your allergens or genetic makeup, may outweigh the benefits. One of the biggest risks with data privacy is when third parties get involved and both Ancestry and 23andMe have been investigated by the Federal Trade Commission over their third party policies.  Most of the third party sharing is able to be opted in or out, but many consumers choose to opt-in regardless of if they know what they are truly sharing.

Another large risk we take when using genetic- testing is the physical sample submission. With Nest or Alexa, often times we can delete our data and profile but how could our society regulate the destruction of our physical sample if we decide we no longer want companies to have it. The physical sample has also been something of major interest to law enforcement. This could definitely be viewed as a positive, considering the suspected Golden State Killer was identified due to a DNA partial match. This technology allowed a partial match to shrink the suspect pool from millions to one family tree.

But is law enforcement looking to these privatized genetic-testing companies a violation of our rights? Is the regulation of technologies quick enough to protect us?

Artificial Intelligence combined with the in-home healthcare testing industry could very well be the key to solving the global healthcare crisis, as discussed in previous articles at solvetheunsolveable, but data protection remains a key concern. Artificial Intelligence is allowing patients and doctors to connect to vast databases and learn more about their personal diagnoses in just moments, something that not too long ago could take months or years. However, the data harnessed could be used for the wrong reasons when in the hands of for profit organizations. When consumers opt-in to sharing their data under the guise of finding the cure to a disease, they believe they are making the world a better place but who really stands to profit from that data?

People do think they are helping the world, helping society, even though they may not as an individual benefit. But if your DNA helps develop a drug for a pharmaceutical company, there is nothing governing what they do. It could be a drug they sell at a high profit but doesn’t help the world become a better place.

Jennifer King, director of consumer privacy at Stanford Law School’s Center for Internet and Society

The lack of transparency is confusing to consumers and this is often an intentional strategy from companies in order to profit off of consumer data. Consumers should be very careful of releasing their most intimate data, their very own DNA. In the effort to learn more information about our history using our genetic data, we could be negatively impacting our future.


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Up Next: AI & COVID-19: Transformation

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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