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Thanks, COVID: Digital automation progress in workforce accelerated

(TECH NEWS) We know machines and automation are the future of the workforce – but did you know that COVID-19 is speeding up the transition?

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Man on tablet with automation tasks

If you haven’t been living under a rock, chances are you’ve heard a thing or two about the rise of AI and machines in the workforce. You’ve probably also heard phrases like “automation” and “digitization” to describe a future economy sans humans that is already well underway, especially in fields like data entry, accounting, and administrative support. If you feel nervous about whether or not you’ll have a job in this future workforce, you’re certainly not alone.

I like to focus on the more hopeful words that are floating around, such “job retraining” or “reskilling”, that imply everyday humans (like me) will still have a place in the workforce if we pivot our careers aptly. This puts emphasis on that special human-y pizazz that distinguish us from our machine competitors.

But did you know that analysts predict COVID-19 will accelerate this, giving way to a more automized work force sooner than we had anticipated?

According to The Future of Jobs Report 2020 – a report conducted by the World Economic Forum (WEF) – the number of jobs being lost right now due to the pandemic is significantly more than the number of jobs being created for a future economy (think: jobs in green energy, jobs in tech, etc.). Employers are not doing enough to account for this disparity.

Research suggests that by 2025, automation and a new division of labor between people and machines will impact 85 million jobs across 15 areas and 26 economies worldwide – and 2025 isn’t some distant future, it’s literally right around the corner.

It’s no surprise that these changes will exacerbate inequalities in the workforce, as automation disproportionally affects low-skilled workers, young people, and women.

Managing Director of the WEF Saadia Zahidi had this to say: “…accelerating automation and the fallout from the COVID-19 recession has deepened existing inequalities across labor markets and reversed employment improvements gained after the global financial crisis.”

Of all the negative fallout from the COVID-19 pandemic, a widened wealth gap is one that will persist even after the vaccine is distributed. The marginalized and disenfranchised do not always have the privilege of flexibility when it comes to career pivoting and reeducating, which I firmly believe will come back to bite employers in the bum later on.

Even if you have kept your job during this time, research shows that about 50% of you will need to reskill ASAP. So if you’re not a wealthy, educated business owner who is typically unaffected by mass struggle, chances are you’re going to have to take immediate actions to insure that come 2025 (or sooner!) you still have a way of providing for yourself and your family.

My advice? If you’re unemployed (or tied to your employer by a thread), now is the time to take matters into your own hands and reskill. Take a class on HubSpot. Complete a UX course. Develop the parts of yourself that make you human (Hint: Try spending your free time engaging with others and not scrolling on Instagram or Twitter).

Essentially, we have to learn to future-proof our jobs because no one else is going to do it for us. The only silver lining to this the period of uncertainty is the free time – so take advantage of it and become your machine competitor’s worst nightmare.

Anaïs DerSimonian is a writer, filmmaker, and educator interested in media, culture and the arts. She is Clark University Alumni with a degree in Culture Studies and Screen Studies. She has produced various documentary and narrative projects, including a profile on an NGO in Yerevan, Armenia that provides micro-loans to cottage industries and entrepreneurs based in rural regions to help create jobs, self-sufficiency, and to stimulate the post-Soviet economy. She is currently based in Boston. Besides filmmaking, Anaïs enjoys reading good fiction and watching sketch and stand-up comedy.

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3 Comments

3 Comments

  1. Ann Cummings

    November 5, 2020 at 8:44 am

    As more time went on, I began realizing just how quickly this automation was accelerating all around us. The places we went into all had plenty of self-checkout stations, little stations for self-help around a store if you couldn’t find something or needed a price, food stations, etc. And the longer this virus has gone on, the more automation has taken over so many jobs. And it definitely will continue to march on. All done in the name of safety and precautions due to the virus, but look at the difference 8-9 months has already made…..

  2. Pingback: Flying cars preparing for takeoff – in Florida? - The American Genius

  3. Pingback: Applying for a home? Robots and automation may decide your fate

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4 ways startups prove their investment in upcoming technology trends

(TECH NEWS) Want to see into the future? Just take a look at what technology the tech field is exploring and investing in today — that’s the stuff that will make up the world of tomorrow.

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Woman testing VR technology

Big companies scout like for small ones that have proven ideas and prototypes, rather than take the initial risk on themselves. So startups have to stay ahead of technology by their very nature, in order to be stand-out candidates when selling their ideas to investors.

Innovation Leader, in partnership with KPMG LLP, recently conducted a study that sheds light onto the bleeding edge of tech: The technologies that the biggest companies are most interested in building right now.

The study asked its respondents to group 16 technologies into four categorical buckets, which Innovation Leader CEO Scott Kirsner refers to as “commitment level.”

The highest commitment level, “in-market or accelerating investment,” basically means that technology is already mainstream. For optimum tech-clairvoyance, keep your eyes on the technologies which land in the middle of the ranking.

“Investing or piloting” represents the second-highest commitment level – that means they have offerings that are approaching market-readiness.

The standout in this category is Advanced Analytics. That’s a pretty vague title, but it generally refers to the automated interpretation and prediction on data sets, and has overlap with Machine learning.

Wearables, on the other hand, are self explanatory. From smart watches to location trackers for children, these devices often pick up on input from the body, such heart rate.

The “Internet of Things” is finding new and improved ways to embed sensor and network capabilities into objects within the home, the workplace, and the world at large. (Hopefully that doesn’t mean anyone’s out there trying to reinvent Juicero, though.)

Collaboration tools and cloud computing also land on this list. That’s no shock, given the continuous pandemic.

The next tier is “learning and exploring”— that represents lower commitment, but a high level of curiosity. These technologies will take a longer time to become common, but only because they have an abundance of unexplored potential.

Blockchain was the highest ranked under this category. Not surprising, considering it’s the OG of making people go “wait, what?”

Augmented & virtual reality has been hyped up particularly hard recently and is in high demand (again, due to the pandemic forcing us to seek new ways to interact without human contact.)

And notably, AI & machine learning appears on rankings for both second and third commitment levels, indicating it’s possibly in transition between these categories.

The lowest level is “not exploring or investing,” which represents little to no interest.

Quantum computing is the standout selection for this category of technology. But there’s reason to believe that it, too, is just waiting for the right breakthroughs to happen.

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Internet of Things and deep learning: How your devices are getting smarter

(TECH NEWS) The latest neural network from Massachusetts Institute of Technology shows a great bound forward for deep learning and the “Internet of Things.”

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Woman using smart phone to control other devices in home, connected to deep learning networks

The deep learning that modifies your social media and gives you Google search results is coming to your thermostat.

Researchers at the Massachusetts Institute of Technology (MIT) have developed a deep learning system of neural networks that can be used in the “Internet of Things” (IoT). Named MCUNet, the system designs small neural networks that allow for previously unseen speed and accuracy for deep learning on IoT devices. Benefits of the system include energy savings and improved data security for devices.

Created in the early 1980s, the IoT is essentially a large group of everyday household objects that have become increasingly connected through the internet. They include smart fridges, wearable heart monitors, thermostats, and other “smart” devices. These gadgets run on microcontrollers, or computer chips with no processing system, that have very little processing power and memory. This has traditionally made it hard for deep learning to occur on IoT devices.

“How do we deploy neural nets directly on these tiny devices? It’s a new research area that’s getting very hot,” said Song Han, Assistant Professor of Computer Science at MIT who is a part of the project, “Companies like Google and ARM are all working in this direction.”

In order to achieve deep learning for IoT connected machines, Han’s group designed two specific components. The first is TinyEngine, an inference engine that directs resource management similar to an operating system would. The other is Tiny NAS, a neural architecture search algorithm. For those not well-versed in such technical terms, think of these things like a mini Windows 10 and machine learning for that smart fridge you own.

The results of these new components are promising. According to Han, MCUNet could become the new industry standard, stating that “It has huge potential.” He envisions the system has one that could help smartwatches not just monitor heartbeat and blood pressure but help analyze and explain to users what that means. It could also lead to making IoT devices far more secure than they are currently.

“A key advantage is preserving privacy,” says Han. “You don’t need to transmit the data to the cloud.”

It will still be a while until we see smart devices with deep learning capabilities, but it is all but inevitable at this point—the future we’ve all heard about is definitely on the horizon.

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Google is giving back some privacy control? (You read that right)

(TECH NEWS) In a bizarre twist, Google is giving you the option to opt out of data collection – for real this time.

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Open laptop on desk, open to map privacy options

It’s strange to hear “Google” and “privacy” in the same sentence without “concerns” following along, yet here we are. In a twist that’s definitely not related to various controversies involving the tech company, Google is giving back some control over data sharing—even if it isn’t much.

Starting soon, you will be able to opt out of Google’s data-reliant “smart” features (Smart Compose and Smart Reply) across the G-Suite of pertinent products: Gmail, Chat, and Meet. Opting out would, in this case, prevent Google from using your data to formulate responses based on your previous activity; it would also turn off the “smart” features.

One might observe that users have had the option to turn off “smart” features before, but doing so didn’t disable Google’s data collection—just the features themselves. For Google to include the option to opt out of data collection completely is relatively unprecedented—and perhaps exactly what people have been clamoring for on the heels of recent lawsuits against the tech giant.

In addition to being able to close off “smart” features, Google will also allow you to opt out of data collection for things like the Google Assistant, Google Maps, and other Google-related services that lean into your Gmail Inbox, Meet, and Chat activity. Since Google knowing what your favorite restaurant is or when to recommend tickets to you can be unnerving, this is a welcome change of pace.

Keep in mind that opting out of data collection for “smart” features will automatically disable other “smart” options from Google, including those Assistant reminders and customized Maps. At the time of this writing, Google has made it clear that you can’t opt out of one and keep the other—while you can go back and toggle on data collection again, you won’t be able to use these features without Google analyzing your Meet, Chat, and Gmail contents and behavior.

It will be interesting to see what the short-term ramifications of this decision are. If Google stops collecting data for a small period of time at your request and then you turn back on the “smart” features that use said data, will the predictive text and suggestions suffer? Only time will tell. For now, keep an eye out for this updated privacy option—it should be rolling out in the next few weeks.

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