Why Future-Proof Employee Training Always Includes Feedback Loops

Why Future-Proof Employee Training Always Includes Feedback Loops

training feedback loops

If you consider yourself as having a “super hardcore work ethic, talent for building things, common sense and trustworthiness,” then great news. You just met all of Elon Musk’s criteria for stellar career-building spaceships, proving it doesn’t take a rocket scientist to get a job at SpaceX.

The outspoken entrepreneur recently posted a tweet announcing a career day at the aerospace firm, in which he also promised that “the rest we can train.”

Source: https://twitter.com/elonmusk/status/1224625719659110400

It’s a significant promise and one that ensured SpaceX career day would have candidates lining up out of the door. But the fact is that making the most of employee training is an area where many companies struggle.

A 2019 training industry report stated that 37% of companies surveyed wanted to increase the effectiveness of their training programs, in a year when training budgets had also increased by nearly 42%. But, in the same way that gaining a foot in the door at SpaceX isn’t rocket science, neither is improving the quality of your employee training programs. Feedback loops exist everywhere.

Future-ready business leaders who can learn to leverage these feedback loops in the context of employee development will find it easier to implement more agile, fit-for-purpose, and engaging training programs.

Recognize the challenges

Perhaps one of the most critical challenges facing today’s talent development teams is the move to digital adoption.

A new employee joining your organization faces dozens of systems and tools, some of which may already be familiar to them, while others may be used for the first time. A report from the Cloud Security Alliance survey found that the average enterprise runs 464 applications, of which employees use around 260.

Furthermore, the shift to digital also means organizations are increasingly leveraging automation for routine tasks, using software that connects platforms, robotics, and artificial intelligence. This shift means that employees are increasingly valued for their soft skills. So much so that participants in a Workplace Learning report commissioned by LinkedIn cited soft skill training as the most critical area of focus.

Source: https://learning.linkedin.com/resources/workplace-learning-report-2018

These training demands also have to be balanced against the need for employees to become productive as soon as possible after joining.

While a structured learning program is known to be beneficial in long-term retention, there’s also the challenge of keeping employees engaged through the right balance of on-the-job versus classroom-based learning.

Feedback is a gift

In management contexts, the concept of feedback is often limited to discussions around the annual performance review. But the traditional performance review model is outdated and doesn’t work.

According to a survey by Gallup, only 14% of employees strongly agree that their performance review inspires them to improve. In general, the annual performance meeting is a one-directional feedback process that can be uncomfortable and draining – for managers and employees alike.

However, this unfortunate outcome is the result of the contrived manner in which the annual performance review mandates the delivery of feedback. It doesn’t apply to the concept of feedback itself, which works successfully in many other contexts.

Feedback loops exist everywhere.

For example, when we get cold, our bodies trigger a series of reactions, such as shivering, that tells us to move somewhere warmer. Artificial intelligence algorithms are trained using feedback loops that tell them whether their output was correct, or not. So why don’t we apply the concept more to our employee communications and development?

Introducing feedback loops to employee training models

Using feedback loops in employee training doesn’t need to involve implementing new policies or learning management systems. In fact, doing so risks the same pitfalls as the dreaded performance review.

Instead, you can incorporate feedback loops more holistically and naturally, ensuring that they become woven into the cultural fabric of your organization.

Here are a few pointers.

1. Set objectives

Every training activity should have clear objectives. What knowledge, skills, or understanding should your employees have gained at the end? How will these help them in their new roles and help achieve the goals of the company?

Use these outcomes as a way of gauging the success of the training. If the desired results aren’t there, make adjustments accordingly.

2. The structure is essential – but avoid being prescriptive

Focusing on objectives and outcomes enables you to take a more flexible approach to employee training programs. Just because an organization uses 200 different systems doesn’t mean every employee needs training in all of them. You can use a template or high-level plan to categorize various activities and maintain some structure. For example, compliance-based training is generally essential, but software training can be undertaken on a need-to-have basis.

Tailoring a structured program to an employee’s individual needs allows them to get up and running more quickly. At the same time, the organization saves on training budgets for skills the employee may already have learned elsewhere.

3. Solicit feedback on progress and engagement

Employees should be encouraged to provide feedback as an integral part of their onboarding. Feedback could be formalized, perhaps as a survey at the end of a training exercise. But there are always opportunities for informal, qualitative feedback. During training sessions, whether on the job or elsewhere, take regular breaks to check to understand, offer opportunities for questions, or ask how participants think the training is going.

Feedback doesn’t need to be formalized into performance reviews or employee satisfaction surveys to be meaningful. Creating a culture of open communication means that feedback loops become incorporated into the mindset of employees and managers. In this way, the organization becomes more resilient to feedback and more easily able to make minor adjustments on the fly.

4. Measure return on investment

There is no “one-size-fits-all” approach here. However, some metrics can help to measure the effectiveness of training programs.

Retention is the most universally popular among executives, managers, and talent developers, but performance measurements and qualitative behavior changes can also be effective.

Getting looped in on training

It’s time to consign the dismal annual performance review to the past. Feedback loops offer a way to ensure that your approach to training employees is agile enough to develop, along with the needs of the organization as a whole.

Establish an open feedback culture from day one of onboarding and create the best possible chance for enduring and fruitful employee relationships.

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Big Data in the Telecommunications Ecosystem

Big Data in the Telecommunications Ecosystem

telecommunications ecosystems

Big data analysis is the next innovative technique that the telecommunications (telecom) sector is deploying. Big data will tame the telecommunications abundance of data, and enable harvesting information “gold” from existing data storage. We know that Big data includes paper as well as innovating new ways of collecting numerous touch-points of data.

Telecoms have always created and analyzed vast quantities of data about their customers — both financial and administrative transactions and operations. Telecom service providers have always been early adopters of data-related technologies. Included in this tech are old-school statistical analysis followed by data mining, knowledge management, and business intelligence applications.

According to a MindCommerce study:

“An average telecom operator generates billions of records per day, and data should be analyzed in real or near real-time to gain maximum benefit.”

For communications service providers (CSPs) to make use of insightful knowledge, much of the data must be processed in near real-time. Traditional systems would take days, weeks, even months to process the data, not to mention the complex variety of structured and unstructured data that would trip up legacy applications.

Big data analysis is used by telecommunications service providers (telecoms) in a variety of intriguing and practical ways that even a few years ago would not have been possible.

  • CSPs monitor network traffic to identify problems to make decisions that improve service and customer satisfaction. The CSP operational diagnostic information also helps prioritize investment in the networks’ physical and technical assets.
  • Telecoms analyze the metadata of call records to pinpoint fraudulent activities that protect their customers and criminal investigations.
  • Telecoms index mountains of documents, images, and manuals within minutes to help call center agents resolve customer issues. Agents can now quickly search for information previously locked away in paper. The paper resolution reduces the call handling time, thereby reducing labor costs. For commerce, these finable documents boost efficiency, which can increase both employee and customer satisfaction — and retention.
  • CSPs evaluate usage patterns to help businesses create service plans that better suit their customers’ needs. When you take care of your customers, it cuts customers’ costs — and more importantly to telecom companies — it helps them predict and reduce churn.
  • Telecom companies even use data pouring in from social media networks to optimize the content of, and investment in marketing campaigns on the fly.

Telecom big data sources include the obvious such as phone calls, emails, and multi-media messages. The telecom big data authority also extends to geo-spatial information, transaction metadata, social media usage, log data, file downloads, sensor data, and more.

History of Big Data

Until recently, the variety and velocity of data were vexing. Disparate data being created at rapidly increasing rates presented insurmountable storage, and processing dilemmas.

It may seem like big data is a recent scourge, but data recording and ciphering its value has been going on since 7000 B.C. The earliest modern 20th-century big data problems were US federal government projects.

If only Franklin Roosevelt had known that he was a pioneer in big data. Read more about these and other intriguing big data history facts.

But it would be the 21st century, in 2005, before Roger Mougalas from O’Reilly Media named the problem of managing and processing large sets of data. All of the data produced and gathered cannot be conquered using traditional business intelligence tools.

The term “big data” came long after the knowledge that there was a plethora of information that existed. And each year, each month and each day since, the amount of data have been recognized — innovations have been critical to contain it all.

The Internet of Things (IoT) drives the unfathomable speeds and quantity of data from sensors that are used for calculations. These calculations are lightning-quick, often life-preserving. By their very nature, these calculations must result in instant decisions and actions.

Telecom’s Big Data Analytics Trends

Some of the hyped-topics in telecom technology, such as virtual reality (VR) and augmented reality (AR), and even the latest 5G feel like it fizzles to many consumers. But the misunderstanding is mostly because of emerging innovations required to make the information happen. There is a latency between possibilities, and the human mind’s ability to take it all in.

All technology can’t be understood by the layperson, as raw material is presented for the next paradigm about-face. For sure, those technologies will deliver applications, both practical and entertaining, that will exponentially accelerate the creation of data. But for all persons to “get” or understand what is happening in the telecommunications field is like asking the community to understand a booster rocket. All people are not trained engineers, and they won’t have a firm grasp on the technical aspects.

For example, Kevin Westcott, Deloitte’s VP and leader of its US Telecom practice, predicts the popularity of e-sports to skyrocket. We all get that we want the popularity and reputation of e-sports to rise. But, this prediction was before the world-altering COVID-19 pandemic.

When you send millions of individuals into isolation — with little to do but seek out streamed entertainment — something will change in our world and the world of commerce. The forced isolation of the pandemic has brought cancellations of the entire seasons of the world’s hottest sports organizations. E-sports and the big data it generates will likely heat up faster than the predicted trends.

Also, legalized sports betting is on the rise following a 2018 US Supreme Court decision lifting the federal ban on sports betting.

To follow suit — several states have already legalized sports betting. 5G’s low-latency, high-volume communications will enable real-time sports betting. With 5G already being deployed in stadiums and sports bars, betting from your seat or barstool is imminent. (Yes, we are all hoping the stadiums and sports bars will be opened soon.)

Telecoms are at the ready — as they should be — to analyze every wager. New telecom connectivity technologies like 5G fixed wireless and satellite internet will offer the backbones needed for disruptive, big-data birthing applications.

The aggressive growth of smart homes and cars, video on demand, streaming apps, gaming, and other entertainment and educational applications will continue producing even higher volumes of data. The data will then be analyzed to glean the insights for businesses and other operational decisions.

Big Data Analytics Solutions

Big data analytics technologies are evolving right along with the technologies and supporting infrastructure. These are the very structures that created the formidable volumes of data in the first place. Companies must be able to collect data from different sources, analyze them, and distribute the information to disparate databases. Data centers or data warehouses are awaiting the intelligence, and depending on the data for the specific needs of the organization.

Marketing Campaigns

The challenge with big data projects is finding skilled resources with experience to create cutting-edge architectures and supersonic data processing applications. These data processing applications must support data-driven business models and near-real-time hyper-targeted marketing campaigns.

Problem-Solving Teams

Teams for solving big data problems must have a wide variety of engineers, analysts, business experts, and system integrators. These specialized teams are rarely found in-house for most companies, even large telecom service providers.

Outsourcing

Outsourcing and staff augmentation is frequently used for big data ventures. For example, Vates, a leading big data analytics and systems integration company in Latin America, is in the center of some of the biggest telecom big data projects in the world.

Global Telecom Company

Vates was hired by a global telecom company to bring its engineering and agile project management prowess to meld with the development of a system. Engineering teams located across the US, Chile, and Argentina are working on the development.

IBM Streaming Analytics

The combined in-house and outsourced team utilized IBM Streaming Analytics to develop architecture and big data analytics solutions. These processes take and analyze the unstructured and structured metadata from multiple sources in near-real-time.

One of the resulting systems was created using IBM Streams processes. The IBM system processes 35 million CSV files or 100 terabytes of data per month. You can read about these impressive big data analytics use cases for the Telecom company.

The Vates Expertise

In a follow-on project for the same telecom, Vates utilized its expertise. Vates works with data from different formats, that originate from varied locations. The company can create solutions capable of checking network quality (NQI) in near-real-time.

Receiving XML files with measurements as detailed as the antenna position, the company can calculate its deviations. The information enables the system to gauge signal quality at a particular location. With this microscopic big data, a technician can quickly make necessary corrections.

Patterns

The insight-sifting solutions uncover hidden patterns, trends, and profound perceptions of customer behavior. Within this data is other useful business, operational, and marketing information — all bringing instantaneous business value.

As big data technologies evolve, solutions will likely be developed by blended teams. These blended teams will be using outsourcing and staff augmentation to overcome the challenges of staying on the leading edge.

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Cybersecurity, Modern Technology and  Business Threats

Cybersecurity, Modern Technology and Business Threats

cybersecurity business threats

The year 2020 is overcome with the COVID-19. But the virus isn’t the only threat to our security. 2020 is also set to revolutionize the world with advancements that will shape the future of lives and businesses, alike. We now have 5G and IoT to Artificial Intelligence, Cloud technology, and Machine Learning. These technologies will become an integral part of our daily lives in creating efficiency, saving time, reducing costs, and unlocking new opportunities.

Though this optimistic language is something you hear quite often (and it’s not untrue to a large degree), the more the world transforms towards a digital future, the higher the rise in threats of Cyberattacks.

Modern technology is set to increase the amount of data we create online, and protecting this data will be one of the defining arcs of this decade. From system security to network security, businesses will face challenges in optimizing their cybersecurity to prevent malicious attacks from being successful.

It is hard to prevent malicious attacks because these technologies are new, vulnerabilities are less known, scalability harder due to a lack of familiarity, thereby making all of these ambiguities an excellent target for bad actors to exploit.

So let’s take a look at some of these technologies, modern regulations in place, and what businesses can do to combat this threat with regards to their cybersecurity.

The Advent of 5G and It’s Cybersecurity Vulnerabilities

As 5G trials and roll-outs happen, we are entering a new era of communication and innovative consumer services. As the adoption of 5G will require companies and people to switch to all-software networks, the cycle of constant updates might result in security vulnerabilities.

These frequent updates are similar to the updates of smartphone software, but those about 5G networks can lead to security risks. Risks are something that early adopters will have to deal with since the number of 5G connected devices that send and receive information increases and remote access becomes much more commonplace, cybersecurity experts will have a huge challenge in front of them.

With increased users and use, expanding the bandwidth for 5G will present opportunities for experts looking to exploit these vulnerabilities. As enterprises and cities become 5G powered, the attack surface will become much larger, putting the burden on governments and private enterprises to pump up and revolutionize their security tools and strategies to safeguard their devices, networks, and applications against malicious attackers.

One problem that early adopters might face due to a lack of security infrastructure could be the authorization and identification of a 5G network. Access to the system can allow a significant threat to data and security, and perhaps these early users might adopt a stringent no-trust policy with regards to 5G network access.

Don’t Think Phishing Is Over

Though technology is evolving rapidly in the digital landscape, cybersecurity experts will have to deal with phishing attacks. These attacks are often targeted to penetrate a network or infect the users of the network itself.

Though phishing is a generally well-known attack, hackers and malicious actors are becoming smarter (thanks to technological evolution), and their attacks are becoming more and more sophisticated. So like 2019, security measures against Phishing will also be necessary for 2020 as well.

Exploits such as email phishing are hard to eliminate as a problem since you can’t really disable emails altogether, and hackers know that. Phishing is also an easier way to get inside a network as opposed to other modern hacks, such as exploiting a zero-day vulnerability.

Companies today have to always beware of these phishing emails since they only take one wrong click by someone with access to admin credentials on a network to open a backdoor that allows malicious actors to get in, take control, and corrupt the company’s network.

The problem that most experts face is that there is no one solution to stop phishing attacks from succeeding. At the end of the day, these attacks can boil down to a reckless click, human error, and lack of knowledge.

Blocking downloads without confirmation, assessing the email before opening any links directly, and using anti-malware and anti-spyware software to block or monitor potential malicious activities could help you mitigate the harm but not necessarily prevent it entirely.

A.I. and ML Based Cybersecurity Vulnerabilities Can’t be Ignored

As the Machine Learning and Artificial Intelligence market grow, their application in different business operations, systems, and infrastructure will be a challenge to overcome. These technologies are incredibly resource-intensive and will require significant efforts to make them secure against potential attacks.

AI and ML-based devices and software have to be trained with the help of data, and experts will have to keep a keen eye on the kind of data that is being used. Data duping to corrupt the learning process of the Machine Learning algorithm can be injected to hamper the training process.

This can lead to the algorithm working seemingly fine but producing wrong results, which could, in the case of analytical products and applications, cost businesses millions of dollars.

How experts monitor and analyze the data will play a crucial part in the future of A.I and ML since the data set being used can be a security vulnerability that will have to be dealt with.

In the current climate, this is a less severe issue due to A.I and ML operating in specialized environments, but once businesses begin to scale these processes, there are bound to be vulnerabilities.

When processes such as threat analysis and data review become completely automated, malicious actors could exploit these processes to misguide companies and manipulate results without any obviously apparent problems. Furthermore, the technology itself can be used to discover new vulnerabilities, breakthrough security measures, and tools, and penetrate systems through the same algorithm that is being used to protect networks.

California Consumer Protection Act(CCPA) Is Now In Effect.

The California Consumer Privacy Act can be considered California’s GDPR. It became active from January 1, 2020, pushing the world of business in a new direction, with more accountability measures being ensured to re-establish the lost trust between consumers and companies. A company to client relationships in these cases was and still is dependent on the sharing of personal information for better and more targeted services, something that lawmakers think has been misused.

The bill established new consumer rights relating to the access, deletion, and sharing of personal information that businesses collect from their users. If your business is collecting user information, under CCPA, your business has to provide a reason as to why you’re collecting this information, what this information is, how you will use this information, and guide users through the process of deleting that information from your database, if they choose to do so.

The concerns with regards to cybersecurity and data protection became news after the claim of Huawei’s 5g technology being a possible threat of the security that resulted in the US government banning all US businesses from dealing with the Chinese tech giants.

In such a world, the burden on Tech companies to ensure maximum data protection came into a significant highlight, with more and more people pushing for stricter regulations and demanding accountability from service providers to ensure that the data of their customers are in safe hands.

The CCPA enforces businesses to implement a process that allows them to obtain the consent of a parent or a guardian and the minor if they’re between the age of 13 and 16 to collect and share their data for the business’ purposes.

This comes with the additional “Right to Say No to Sale of Personal Information” which is to be provided through a web link on the homepage of a business’ website that redirects users to a page where they can opt-out their consent protecting their data and personal information from being sold by the business legally.

Businesses and Companies are required to update their respective privacy policies with the newly required information, including but not limited to the description of California residents’ rights

While these are the more straightforward laws that are placed within the CCPA to ensure privacy protection and data protection, another measure the CCPA takes is to ask businesses to avoid sending opt-in requests to residents who have opted out of the option for a period of 12 months.

The used terminology, which is “avoid” while does leave a gray area for businesses to use, it takes into account that business activities mainly revolve around data gathering, in the absence of which companies cannot promote specific deals or show ads, for which a 12 month mandatory waiting period could be detrimental to the functioning of the business.

The power of GDPR can be seen through the European Union’s 1.5 Billion Euro fine for anti-trust AdSense advertising. This fine, which was levied in 2019, brought the overall EU anti-trust bill to 8.2 Billion Euros. GDPR expects companies to use data responsibly and its breach weighs significant financial damage to businesses, creating a force that ensures that companies adopt the best data protection, regulation, and use policies.

CCPA is a similar force, being in effect from the beginning of the year. It expects businesses in California to adopt the best security practices and comply with the regulations set to protect consumers.

For businesses based in California, transitioning to CCPA compliance is crucial, and it has to be done as soon as possible, to limit the potential fines that might be coming their way. For businesses that are not California-based, planning to make this change and implementing it is also crucial. It’s likely that other states such as New York will most likely adopt their own version of the CCPA, even if it is not adopted by the Federal government.

Hiring security specialists, focusing on compliance, and devoting resources to ensure that there is a successful transition to a post-CCPA world is something that businesses in 2020 should be looking towards.

Microsoft and Linux – The future is Cloud

The future of Windows seems to be shifting towards a cloud-based platform. Cloud PCs will work similarly to how other cloud-based platforms and services work. Most likely, users will have to pay a subscription to gain access to a pre-set app bundle to run on the PC.

What makes Microsoft more interesting is their adoption of Linux and transitioning towards a Linux-based operating system.

Sounds confusing, right? Well, you need to grasp hold of it if you are planning to continue using any resources from Microsoft shortly.

The future of Windows might stay the same on the front-end, with cloud-based PCs providing a similar UI to the Windows OS we’ve grown up accustomed to, but on the back-end, Microsoft might deploy a full-Linux setup.

A fulltime Linux setup is happening because most VMs are now running on Linux iterations. Even Microsoft Azure has around 40% of its machines running on Linux at the moment.

There are a few substantial benefits of using on the Back-end, especially for businesses. Here are the benefits:

  1. Migration from an older PC to a new one, its updates, and patches will become easier than before. The service will upgrade the hardware, take care of the updates and release them directly, and deal with migration
  2. For businesses, Linux is a much better platform for security. Linux is a safer platform for storing sensitive data with only the admins having the root access, helping keeping system vulnerabilities in check.
  3. The service is more likely to adopt a more robust security system than you would on your own hardware, which means that you will gain access to enterprise-grade security, helping you combat the rising threat of cyber-attacks.

For businesses, it is imperative to start investing in robust security infrastructure, and at Tekrevol, we’re trying our hand with some as well.

From a security standpoint, Linux is key to OS in the next decade. If you too have a wide range of OS applicability critical to your internal systems, you really need to know how Linux can make your security more concrete.

How Will Cybersecurity Trends Impact Business strategy?

According to one study by Accenture, 68% of business leaders think that there is an increased risk of a cyber-attack on their business. The year 2020 will be one where tackling these threats will become a primary focus of business leaders and entrepreneurs.

Combating this problem will require these leaders to acquire more knowledge, skills, and tools to improve their organization’s security protocols. Protocols includes network protection and data protection against possible breaches.

We can expect an increased demand for network security specialists, ML design security specialists, and system security experts. In general, the demand for security specialists across technologies will also increase.

Businesses will have to incorporate new risk assessment models for technologies such as IoT, 5G, and AI-based products.

According to Gartner’s press release, cybersecurity risk is one of the top concerns that chief audit executives have with regards to their businesses.

In 2020, businesses will come to a tipping point where they will either develop strategies and technologies that help combat the risk of cyber vulnerability, or the lack of evolution will hurt their performance in the market.

Similarly, one can foresee big corporations acquiring digital security startups for record-high acquisitions to keep up with this rising threat.

How businesses achieve compliance with government regulations and establish strict security protocols with regards to modern tech will define their success in the year 2020. So, if you’re a business owner looking to scale, transferring your focus towards establishing a robust security infrastructure has to be a central part of your business strategy.

Wrapping Things Up:

The future is digital, there is no denying it but simply focusing on the possible benefits isn’t going to cut it. For businesses, it is crucial to realize their responsibility towards consumers and take the necessary steps to ensure data protection and other cybersecurity avenues.

It is also vital for them to focus strongly on the security of their own platforms, services, and products to ensure that the adoption of modern technology drives positive results. The technologies we’ve talked about have great potential, but the journey into the world of technology requires avid preparation to ensure security and safety.

Businesses today have to invest more into optimizing their security, create new strategies, implement new infrastructure, and leverage modern tools to ensure that they are ahead of the and ready to fight any cyber-threats that may come their way.

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We Don’t Have to Sacrifice Students’ Privacy for Campus Security

We Don’t Have to Sacrifice Students’ Privacy for Campus Security

student privacy

Colleges and universities face a distinctly modern conundrum: They want and need to keep students safe, but smart security technologies that can track and monitor students’ activities on and off campus threaten their right to privacy. Schools and technology vendors must collaborate to find solutions that increase campus security while also protecting individual privacy.

The Privacy Problem

The very nature of some of these advanced tools requires the collection and storage of sensitive personally identifiable information. The risk of a data breach is one obvious concern — but so is the destruction of the university experience as we know it.

College is a time for personal growth and learning.

Imagine how violating and restrictive it would’ve felt if the administration of your college could’ve determined where you were on campus at any time and who you were speaking with on social media.

But it’s a growing possibility that schools will overstep the fine line between student safety and individual rights.

Major Risks Accompany New Security Tools

Facial recognition technology poses a particularly acute risk to individual privacy. Schools already track students to some extent with their ID cards — it would hardly be a big stretch for them to implement facial recognition technology to increase tracking abilities.

Law enforcement has already explored this tool, but it’s proven largely ineffective and invasive. For instance, when London’s Metropolitan Police trialed the technology throughout 2018 and 2019, it stopped 42 individuals but only identified eight of them correctly.

The Danger of Social Surveillance

Advanced social surveillance is another emerging risk for student privacy. Universities already have a lot of data at their fingertips that poses a security risk for both students and staff. That danger grows when you fold in advances in data and natural language processing that make social media posts and other information easy for administrators to track and analyze.

The last thing a university should want is for these technologies to be used against its students — just imagine the public relations crisis that could occur. 

In addition, schools and universities haven’t even begun to contemplate all the data complexities that come with using these new security tools. How will the data be stored? When will it be deleted? Can law enforcement access it? If so, when? Who else can access it? These are just a few of the many concerns that must be addressed.

Privacy and Security Aren’t Mutually Exclusive

The privacy concerns accompanying new security tools are considerable. But that’s not to say that colleges and universities shouldn’t employ the latest technology to increase student safety. Campus administrators just need to do so carefully.

They should work hand in hand with security companies to strategically employ and use the technology, setting up strict rules for how and when the tool will come into play and by whom the information can be accessed and used.

If colleges and universities implement new security tools with the following three strategies in mind, they’ll be more likely to keep the privacy — and safety — of their students intact:

1. Earn stakeholder buy-in. 

This includes faculty, staff, and students. Inform each stakeholder audience of the key security concerns and threats of any technology you’re considering.

Open a dialogue about how people feel about security on campus and crime-prevention measures before you implement anything.

You may find people feel comfortable with some security technologies but not others.

The University of Washington Bothell provides a solid framework for accomplishing this. The school surveyed students, faculty, and staff on campus security to understand where people felt safe and what areas needed additional security. The survey found that more than half of the participants were either moderately or highly concerned about a campus shooter, and the majority agreed that security cameras would make them feel safer.

2. Enact specific solutions to specific problems. 

Tools like facial recognition and social media monitoring promise a lot but are hard to implement at scale to target specific problems.

Instead of relying on one solution to solve all your problems, start with the problem first.

Determine a specific problem you want to solve, then adopt a specific technology solution to solve it.

Luckily, the security industry is flooded with new technologies that can address virtually any problem that colleges and universities might encounter — without invading privacy.

From threat-detection technology, which can detect threats without invading privacy, to systems that detect intruders to help schools respond to theft, there are plenty of options that beef up security without requiring the collection and storage of students’ PII.

For example, a handful of universities, including Temple University and Duke University, recently replaced ID cards with students’ phones. While this method requires students to relinquish a similar amount of PII, it’s both more convenient and a step toward advanced security across campus. It helps limit the possibility of intruders picking up a dropped ID card and gaining access to residence halls and labs.

3. Plan security holistically.

No security solution should be considered in isolation. You must consider a number of “side effects,” such as the data it requires and creates and the extra processing it needs. You should also consider how the new solution will work with existing security processes and personnel. 

Before launching ahead full speed, design a trial period that will reveal how the new technology will work and what processes will be required.

Campus security and student privacy are not mutually exclusive. By approaching security smartly and working together with security firms to implement specific solutions to specific problems, colleges and universities can advance security without transforming the campus into a surveillance state.

Image credit: Ameer Basheer — Unsplash

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Physical vs Digital Health: What You Need to Know About Privacy and HealthTech

Physical vs Digital Health: What You Need to Know About Privacy and HealthTech

physical vs digital health

In November of 2019, news broke around Google’s $2.1 billion acquisition of Fitbit continuing the search giant’s push into the health market. Here is physical versus digital health and what you need to know about privacy and healthtech.

In December, we learned that the US Justice Department is now investigating the deal after many, including watchdog groups Public Citizen and Center for Digital Democracy, expressed concerns about giving Google access to even more data on American consumers.

What’s going on in privacy and healthtech?

It seems like big tech acquisitions happen on a daily bases – so what’s so significant about Google’s big FitBit purchase to warrant attention from the DOJ and what does this mean for healthtech? It all boils down to privacy and the ongoing debate around data ownership.

While healthtech companies and the innovations that they bring to help motivate, manage and improve our physical health are extremely valuable, we can’t lose sight of other factors. It’s unfortunate that people often ignore their digital health. Mainly — which companies have access to our incredibly personal and valuable health data? What they’re doing with it?

From the increase in major health data breaches and hacks to key considerations of using the latest healthtech – here’s what consumers need to know in order to optimize for both physical and digital health.

Health Data is Valuable — Hackers Would Agree

The number of medical records hacked during the first half of 2019 reached 32 million, doubling the previous record set in 2018. This includes the largest breach to date, in which 19 million medical records were stolen from clinical laboratories Quest Diagnostics and LabCorp. The numbers seem to grow every year, alongside users’ justified concern around the security measures taken to protect this sensitive data.

It’s no coincidence that more than 25% of all data breaches are related to healthcare.

Hackers are smart to identify some of the most valuable and vulnerable data, in this case, medical records. These records provide access to troves of personal information that can be sold on the dark web to enable identity theft.

Very few data resources offer such insight into people’s lives, which makes medical records and the companies holding them a highly coveted target. To put it in numbers, personal health information is considered three times more valuable to hackers compared to other types of personal data, including credit card information.

These alarming stats come at a time when healthtech solutions are on the rise and there’s a rapid (and much needed) digitization of traditional healthcare providers.

Activity trackers and other wearable devices.

As activity trackers and other wearable devices become part of our daily routine, we sometimes don’t categorize certain solutions as possible gateways to our medical information.

No, this doesn’t mean we should simply stay “off the grid” in hopes of keeping our data safe, especially given the massive benefits healthtech brings to our modern-day lives.

Rather, we need to be more vigilant about the kinds of products and companies we decide to volunteer our personal health information to.  Here are a few important considerations to take in order to protect your healthcare data.

Consider the Why — Always Focus on Value

Why should you give this specific company access to your medical data? What sort of value are you getting in return, and is it worth it? A recent study conducted by Mine.com revealed that many of us allow hundreds of online tools and services to access our data.

Even years after they’ve ceased to give any value in return, and in many cases, after a one-time use only or without so much as opening a user account.

Digging into this further, our research shows that users have over 2,500 unique health and wellness services in their digital footprints, that’s around 8 companies on average and 40% of which are from a one-time use and recommended for deletion.

The top US-based health and wellness services found in our users’ digital footprints include Headspace.com, fitbit.com, myfitnesspal.com, 23andme.com, cvs.com, skimble.com, and zocdoc.com.

We either forget about these services or feel overwhelmed by the need to manage them, which allows companies to continue collecting our data, health-related or otherwise. This is an important consideration because it allows us to separate the tools we use and need from the unnecessary data baggage.

You wouldn’t want your medical information to be deleted from the web altogether, as this might make it impossible to receive medical treatment should you need it. We must start by focusing on what truly brings you value.

Consider the Who — Trust is Crucial

Who really gains access to your healthcare data? Can they be trusted? Verifying the identity of companies that provide medical technology is crucial because it helps us understand who we’re dealing with and allows us to make informed decisions.

If possible, read the company’s privacy policy (it should be accessible to everyone but in many cases is hard to comprehend). Consider the fact that smaller startups may not have the means to properly protect your data.

Huge corporates can use your information in many different ways, some of which you might not approve of such as selling data to advertisers.

It’s also important to note that the business world is dynamic, which means that the company enjoying access to your data today may change ownership tomorrow. A couple of recent examples include the acquisition of FitBit by Google mentioned earlier.

There has also been a collaboration between the DNA-testing company 23andMe with pharmaceutical giant GlaxoSmithKline. Both news items were met with suspicion from users who were rightfully worried about the implication of such deals on their private data.

Consider You — Maintaining Physical and Digital Health is Possible

It’s very possible to continue using the latest healthtech services and tools while protecting data ownership by managing your data on a regular basis. Once the power shifts to the people to take control of their data, the above stats, questions, and considerations will no longer seem as threatening. Then the relationship between consumers and healthcare technologies will become much healthier.

While the healthtech industry is different in many aspects, one thing remains the same. Just like any other technology we interact with, there are pros and cons. The same way hackers recognize the value of healthcare technology, so must we.

New, innovative solutions can greatly improve our lives (and even safety) like never before.  A few months ago, Apple Watch’s fall detection feature saved a man’s life by automatically calling 911.

Instead of being afraid of progress or rejecting new solutions, we must ask the right questions, and make technology work for us, not against us.

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