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4 Emerging Technologies That Could Define the Future of Work

Future of Work

With COVID currently making a huge impact on how we work, it should be safe to say the future of work is bound to deviate from what we thought was the original course prior to the pandemic. Already now, after 2 years of combining remote work with traditional work practices, companies are starting to accept the fact that remote work is here to stay. This in turn has driven increased adoption of remote work-enabling technologies such as VDI DaaS, and cloud computing.

While globally disruptive events like this pandemic can certainly influence work practices, there are also emerging technologies that can have a similar effect. Here are four of them.

AR (Augmented Reality) Cloud

Augmented Reality

AR (Augmented Reality) Cloud is a blanket term referring to an amalgamation of several technologies that takes the basic tenets of AR to create a more immersive, context-aware user experience that overlays digital content on a user’s physical environment when viewed through the lens of an AR-enabled device.

Whereas today’s AR applications are usually delivered via phones and tablets, most AR Cloud applications are predicted to run on glasses and head-mounted displays (HMDs), and controlled through voice commands.

Context-awareness is critical in an AR cloud environment. Otherwise, the technology won’t be any different than current AR implementations. This means, an AR cloud application should be aware of the precise location and time the user is currently in, as well as the specific object the user wishes to retrieve information about.

For a true AR cloud solution to work, a lot of the relevant technologies need to mature first. For instance, in the case of pinpointing a user and object’s exact locations, a GPS-based solution might not support certain use cases, as GPS won’t work for sub-meter distances. AR cloud environments will rely heavily on technologies like 5G, artificial intelligence (AI), edge computing, and internet of things (IoT), some of which (e.g., 5G) need to have a lot of maturing to do.

However, assuming all relevant technologies would have already matured, AR cloud is poised to make a huge impact on the way people work.

Imagine a realtor showing a potential customer around a property. If both of them are wearing AR-cloud enabled glasses, context-aware information can add more value to whatever the realtor is talking about.

Or imagine a safety office inspecting a chemical plant. That officer can get additional information (e.g. required controls, relevant compliance provisions, potential hazards, etc.)  on a particular subject on the fly just by looking at it and perhaps issuing a few voice commands.

Lastly, imagine a new hire going through an onboarding process. A pair of AR-cloud enabled glasses can guide that new hire around and orient him/her of the various offices, equipment, and facilities onsite. The possibilities are endless.

Advanced Virtual Assistant (AVA)

Advanced Virtual Assistant

If AR Cloud can be viewed as the next generation of AR, the Advanced Virtual Assistant (AVA) can likewise be viewed as the next generation of the Virtual Personal Assistant (VPA). Imagine Alexa getting a major upgrade and turning into Jarvis.

AVA solutions are primarily built on technologies such as Natural Language Processing (NLP) and Robotic Process Automation (RPA). They respond to voice-initiated commands or questions just like Apple’s Siri, Amazon’s Alexa, Microsoft’s Cortana, and Google Assistant, but are more capable for enterprise-grade use cases.

AVA’s can be particularly useful to knowledge workers such as technical writers, researchers, programmers, system analysts, etc., who can ask questions while working on a task and get answers on the fly. This will help knowledge workers complete tasks in shorter periods of time.

Homomorphic encryption

Homomorphic encryption

Homomorphic encryption operates as a happy medium between conducting mass processing of information and safeguarding privacy. It enables the computations on and analysis of encrypted data sans decryption or loss of confidentiality. Thus, data can be outsourced and processed by external parties while maintaining security.

By leveraging homomorphic encryption, industries mindful of digital security, including banking and healthcare, can safely analyse and conduct searches on data without compromising the trust of consumers and data privacy regulators. In the past, we could only encrypt data-at-rest and data-in-motion. Now, with homomorphic encryption, it is already possible to encrypt even data-in-use.

For employees whose roles involve handling sensitive data, homomorphic encryption reduces the risk of accidental data leaks without curtailing productivity. This also means business units may now pursue projects that involve collaboration, outsourcing, and other activities that might have been deemed too risky before.

Synthetic data

Synthetic data

Trailblazer technologies such as machine learning (ML) and artificial intelligence (AI) need data, lots of data. Unfortunately, there are certain types of data that aren’t usable or need to be omitted (e.g. personal data). This is where synthetic data comes in. Synthetic data are pieces of data generated through simulations and computer algorithms, and then used as alternatives to real-world data.

AI-generated synthetic data is simulated data that virtually retains the accuracy of original datasets, by virtue of complex patterns formed by deep neural networks. Having more data, i.e., real, non-sensitive data supplemented by synthetic data, improves the accuracy of AI-driven simulations, thereby allowing companies to simulate business scenarios or user behaviour.

Through these processes, companies can minimise losses and perfect profitability. By leveraging synthetic data, scientists can cut down the time needed for data collection, in turn allowing analysts and other employees to make adjustments based on trends in record time, ahead of the competition.

Rather than recollect data after longer periods of time, data scientists can simply discard and regenerate synthetic data to reflect current situations or omit biases. Legal issues can also be avoided, as synthetic data eliminates the use of information covered by data privacy laws and regulations.

AR Cloud, AVA, homomorphic encryption, and synthetic data, along with other emerging technologies, won’t be arriving at our doorsteps any time soon. However, when they do, their impact on the workplace can be pretty substantial. It would be wise to read more about them.

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