Artificial intelligence is using Automation of making Several human jobs obsolete.

At present, global AI adoption and investment are soaring. Reportedly, 37 percent of organizations have deployed AI solutions. Analysts have forecasted that global AI spending will more than double over the next three years, topping US$79 billion by 2022.

Almost two-thirds of global reports state that AI technologies are enabling their organizations to move ahead of the competition. Sixty-three percent of the leaders surveyed already view AI as “very” or “critically” important to their business success, and that number is expected to grow to 81 percent within two years.

Nature of Work

However, analysts are somewhat uncertain about how much effect AI would have on human jobs. On one hand, AI-driven automation has made most jobs obsolete and on the other hand, new designations of jobs and new territories are being discovered concerning AI operations. While AI adopters express concern about automation as an ethical risk, they emphatically believe that human workers and AI will augment each other, changing the nature of work for the better. Changing how work gets done within the organization by making operations more efficient, supporting better decision-making, and freeing up workers from repetitive tasks- is the core to what companies want to achieve with AI.

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Managing the Gap of Skills

To meet their AI aspirations, companies will likely need the right mix of talent to translate business needs into solution requirements, build and deploy AI systems. They would require to integrate AI into processes and interpret results. However, most early adopters face an AI skills gap and are looking for expertise to boost their capabilities. Reportedly, 68 percent of executives confess to a moderate-to-extreme skills gap, and more than a quarter rate their skills gap as “major” or “extreme.” The gap is evident across all countries surveyed, ranging from 51 percent reporting moderate-to-extreme gaps in China to 73 percent reporting the same in the United Kingdom. The new designations of this field are AI builders and AI translators. These AI builders refer to researchers to invent new kinds of AI algorithms and systems, software developers to architect and code AI systems, data scientists to analyze and extract meaningful insights from data, and project managers to ensure that AI projects are executed according to plan. AI translators bridge the divide between the business and technical staff—the front and back ends of building AI solutions.

Replacement or Advancement?

The desire to replace workers with new, AI-ready talent is clear, but it is not the end of human jobs at all. Reports reveal a scarcity of AI talent around the world. Canadian firm Element AI recently analysed LinkedIn profiles to gauge the size of the worldwide top-tier AI talent pool and counted 36,524 self-reported PhD-level AI experts (including data scientists and machine learning researchers and engineers). So, it is very clear that when a door is being closed in the job sector, a new, more advanced section of jobs are opening doors on the other side.

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Artificial intelligence (AI) is changing all aspects of our lives and that too at a rapid pace. This includes our professional lives, too. Experts expect that in the days ahead, AI would become a greater part of our careers as all companies are moving ahead with adopting such technology. They are using more machines that use AI technology that would affect our daily professional activities. Soon enough, we would see machine learning and deep learning in HR too. It would affect all aspects of HR (human resources) such as the way HR professionals on-board and hire people, and the way they train them.

Impact on onboarding and recruitment

These days, companies are using robotics in HR to make sure they have found the right people for particular job profiles. This means that even before you have stepped into your new office, your company already knows that you are the best person for the job thanks to such technology. They are using AI to pre-screen candidates before they invite the best candidates for interviews. This especially applies to large companies that offer thousands of new jobs each year and where millions of applicants go looking for jobs.  

Impact on training on the job

Companies are also using machine learning and deep learning in HR to help provide on-the-job training to employees. Just because you have landed a job and settled in it, it does not mean that you know it all. You need to get job-related training so you can keep getting better. This is where experts expect that AI would play a major role in the coming years. It will also help one generation of professionals in an organization transfer its skills to its successors. This will make sure that no company would ever suffer from skill gaps.

Workforce augmentation   

Robotics in HRwill play a major role in improving the people working in organizations where the management implements such technology. A major reason why people are so apprehensive about using AI in an organization is that they feel it would replace them and do all that they can do now. This will consequently lead to job losses. However, in the present scenario, AI is all about augmenting such a workforce. This means that it would help you perform your job with greater efficiency. Contrary to popular opinion, it would not replace you.

Workplace surveillance

Companies can also use machine learning and deep learning in HR to improve their workforce surveillance work. This is uncomfortable for several employees as they feel that such technology would encroach on their workplace privacy. Gartner recently did a survey where it found that more than half of the companies that had a yearly turnover over $750 million use digital tools to get data on the activities of their employees and monitor their overall performance. As part of this, they analyze their emails to find out how engaged and content they are with their work.

Usage of workplace robots

Apart from robotics in HR,companies these days are also using physical robots that can move around on their own. This is especially true for the warehousing and manufacturing companies. Experts expect that soon this would become a common feature in a lot of other workplaces too. Companies specializing in mobility are creating delivery robots that can move around the workplace and deliver items straight to your desk. Tech companies are also developing security robots. Experts believe they would become commonplace because they can assure the safety of commercial properties from trespassers. Companies are also developing software to help you park your cars in your office. 

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Leading edutech platform Coursera has raised $130 million as part of the  Series F funding round. This financing would enable Coursera to bring quality and highly contextual learning material to aspiring professionals in the forward specializations during the ongoing COVID-19 pandemic.

Yesterday, NVIDIA and UF announced a strategic alliance to develop AI and Data Science education facilities for the State of Florida. The partnership includes $70 million joint funding towards building the world’s fastest AI Supercomputer for higher education.

Coursera’s latest $130 million funding further bolsters the rapid movement towards research and education-driven approach to sustain Data Science as a key specialization in the Industrial Revolution 4.0.

The latest funding brings the company’s cash balance to more than $300 million. The round was led by NEA and joined by existing investors Kleiner Perkins, SEEK Group, Learn Capital, SuRo Capital Corp, and G Squared.

Coursera, along with its community of partners, has been at the forefront of preparing individuals and institutions for the Fourth Industrial Revolution. The ongoing pandemic has further accelerated the rate of digital transformation among companies. The jobs of the future will be powered by a highly-skilled and distributed workforce, collaborating virtually to deliver value.

Coursera remains committed toward bringing on-demand educational content and assets to millions of learners, thousands of campuses and companies, and hundreds of governments. The company understands its role of staying well-resourced to serve the world at this particularly challenging time. It confirmed using the funds to double down on our product and engineering efforts, expand our job-relevant catalog, and further grow global presence.

Coursera has witnessed a huge demand for two of their COVID-focused initiatives —

1. Campus Response Initiative to help universities teach impacted students; and
2. Workforce Recovery Initiative to help governments reskill unemployed workers.

The Digital Skillset is Missing its Mark in the Data-Driven Economy

In a recent report, NTT Data has revealed the glaring holes in the talent pool pertaining to the data science industry. Different industry verticals are plagued by complex challenges, all stemming from the lack of analytical skillset among the professionals. Industry-driven learning, traning and development platforms are an important cog in this machinery, looking at the current and future data trends.

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The world is facing unprecedented economic disruption, and the need to develop skills for a digital future is even more apparent now. Coursera and other edutech firms should continue to innovate and bring quality learning material to democratize AI education for all.

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When Albert Einstein spoke of how the human spirit must prevail over technology, little did the world know that decades later this statement would hold true for the human race trying its best to stay relevant in the world of ‘Globotics’. This interesting term has kicked up quite a storm recently when globalisation expert Richard Baldwin wrote on the fast-paced effects of digital disruption and the need for humans to adapt to the inevitable transition. In simpler terms, Globotics refers to robotics in times of globalisation. Since liberalization in the late 90s, globalisation has been opening up new avenues in different parts of the world by bringing in innovations and machines into a world that was striving to connect people and products to markets. This has expedited a lot of production, smoothened processes across industries and ensured greater development for most economies.

With artificial intelligence and machine learning ensuring greater efficiency, one can safely say it is also the era of hyper-globalisation. However, every change comes with its set of growing pains. About 25 years back, the world was not ready for social media and virtual lives, and now the world is not yet quite ready to embrace the way technology will conquer everything from our daily chores to jobs. The giant strides taken by technology have been witnessed by the software industry, which has grown by leaps and bounds since globalisation.

Software industry ushers in machine learning

Closer home, in India, globotics has brought in IT industries, software development adding a separate dimension to the way India would collaborate with the world in terms of technology. The software industry has brought in machine learning and like everything, growth and expansion of this industry is happening but at a hefty price. While our world is constantly evolving and being reshaped by technology, one also needs to focus on making digitally challenged organisations more relevant so that they do not fall out of the race. Initially, with the advent of software industries and technological innovations, white-collared people had greatly benefited from the rudimentary robotics. However, over time the pace of change and digital disruption has taken the world by surprise calling for acceptance and adaptation.

The transition

India, as a country known for its IT hubs, has been a huge contributor to the global IT industry. Therefore, the country is going to play a major role in the way the transition and evolution due to automation and machine learning is going to take place. All kinds of jobs in this sector have undergone transitions due to machines taking over human roles and easing out the entire process. For example, earlier, web development used to be a creative job but now it is done easily through simpler programming on the machines. Data analysts, on the other hand, use creativity and human intelligence and will probably never be displaced by machines as they would always be needed to feed algorithm for the machine. The entire process is a vicious cycle where the more analysts are strengthening the algorithm, the more engineers are killing their own jobs. While blue-collared jobs have seen a reasonable amount of automation, white-collared jobs are yet to see a transition into robotics displacing humans.

The transition will primarily follow three steps. Apart from the impact on the economy, the psychological impact will spell frustration among employees of different sectors. This will then take some time to initiate acceptance with automation being an inevitable part of various professions. Along with acceptance will come compliance on ways of using these machines and to know how to make the most of it when combined with human intelligence and talent. For instance, every technical industry should invest in using Artificial Intelligence and Machine Learning to do the high-risk complicated tasks that need not be done by employees. Once this balance is struck between human resources and machines in every organisation, individuals from various vocations might be better prepared to deal with the transition. It will be far easier to thrive in the new world once employees know how to upskill themselves and which faculties will be indispensable in a world of robotics. An example of this is that a therapist’s job cannot be done by a machine and even while medical science advances, doctors will still be required for a certain level of diagnosis and care. Fields of creativity and ethics like that of mental health cannot be replaced by AI algorithms and this should be kept in mind.

The way ahead

It is interesting to note that in a certain way the next generation will be going back to their roots. As the human race continuously move up the value chain in an upward moving cycle, it will be compelled to tap into its creative and emotive side again unlike before when it was upskilling to use machines and becoming mechanical. It is about working together with machines and being indispensable. The trick, therefore, lies in understanding that there will always be some jobs that machines cannot do.

Artificial Intelligence technology was conceived by the human mind and therefore there will be ways in which employees can always make themselves superior and indispensable. While IT and software professionals would need more reskilling and upskilling programmes to stay relevant and climb up the value chain, creativity and ethics will become more important than ever before. The Darwinian theory of survival of the fittest is deemed to hold true in a world where adaptation is the key to success and growth. The future of the workforce will see a paradigm shift which might seem daunting at first but in the end these are all phases of growth demanding everyone to be a stronger and better version of themselves.

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Retailers are increasingly adopting artificial intelligence and robotics, both in brick-and-mortar shops and in warehouses, and with a new robot workforce comes the need for new management methods.

That’s right: in the near future, HR departments won’t focus only on human employees, but also include a robot resources department to look after non-human workers.

According to research firm Gartner, robot resources could be a thing as early as 2025. In the next five years, predict Gartner analysts, at least two of the top ten global retailers will have reshuffled their HR departments to accommodate the needs of their new robot workers.

There is no need to start thinking about AI holidays and robot retirement parties. Rather, robot resources organizations will be procuring, maintaining, training, taxing, decommissioning and disposing of obsolete machinery.

With AI-powered robots being particularly suited to the retail industry, Gartner’s research predicts that 77% of retailers plan to deploy AI as early as 2021. Automation of tasks such as floor cleaning, data-collection or security could have promising results – and the very first use case identified by the research firm is warehouse picking.

Big retailers have already demonstrated the potential of scaling AI and robotics in the warehouse. Walmart, for example, recently unveiled Alphabot, a robotic fulfillment system implemented in the retailer’s 20,000 square-foot warehouse in New Hampshire, and which combines human labor and robot speed to pick 800 products per hour.

Similarly, US giant Kroger signed a deal in 2018 with UK company Ocado to build huge automated robot warehouses, in which dishwasher-sized robots coordinate in swarm-like behavior to pick orders before handing them over to human employees to pack into bags.

It is largely customer demand for both accuracy and speed that has boosted retailers’ interest in robotics. “The retail industry continues to transform through a period of unprecedented change, with customer experience as the new currency,” said Gartner’s research director Kelsie Marian.

“The adoption of new digital technologies and the ever-changing expectations of customers continues to challenge traditional retailers, forcing them to investigate new human-hybrid operational models.”

But just because robot resources are coming of age, that doesn’t mean that human resources are going anywhere. Quite the opposite, argued Marian: retail workers will have to work alongside new robotic colleagues, and the new paradigm will require careful planning.

She highlighted that choosing the right candidate – human or machine – for a given job will be critical for success. “Retail CIOs must provide ongoing maintenance and performance monitoring for effectiveness,” she said. “If not, the team may become counterproductive and lead to a bad customer experience.”

In that respect, Amazon may well be an example of success. The retail giant started working with robotics as early as 2012, when it purchased robot manufacturer Kiva Systems. Working in tandem with human employees, Kiva’s robots transport pallets of inventory from one location to another in Amazon’s warehouses. More recently, they have started scanning and boxing items to be sent to customers.

Amazon said that if installed in each of its 55 US fulfillment centers, the robots could eventually replace 1,300 employees. The news sound bad, but in parallel the company announced that it would pay workers up to $10,000 to quit their jobs and set up their own delivery business, in order to tackle retail’s infamous last-mile logistics challenge.

Since the initiative was announced last year, tens of thousands of workers have applied to Amazon’s new delivery service program.

According to Gartner’s analysts, such examples of human-robot collaboration will become mainstream in future retailers’ business models. “This means the robot will have to mesh with the human team – essentially meaning that both sides will need to learn how to collaborate to operate effectively together,” she said.

Hence the importance of rethinking HR departments. The good news is that those new robotic teams shouldn’t be requiring too much feedback forms and probation paperwork.

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The impact of automation in the workforce extends far beyond any individual employee, organization or even industry. As artificial intelligence advances and companies adopt this technology, we’re beginning to see an economic shift.

In 2017, JPMorgan estimated that automation has the potential to increase global gross domestic product by more than $1.1 trillion over the next 10 years. Meanwhile, according to Bloomberg (paywall), PwC predicted that AI could add up to $15.7 trillion to the worldwide economy by 2030. While there’s a huge discrepancy between these projections, I believe the underlying message is clear: Automation is a major factor in the future of global economic growth.

And yet, some experts are anticipating an “AI winter,” a period when investments and developments in AI begin to slow down or stall. Although I’ve observed some success in funding AI in various ways — such as coding boot camps and computer science degrees in an effort to close the skills gap — we haven’t seen the complete payoff we’ve expected. AI still has biasproblems; deep learning still gets stumped by simple, if unexpected, variables; neural networks are far from the point where they can be consistently leveraged strategically for business.

As a serial AI entrepreneur, I’ve made it my goal to dedicate enormous resources to research and development for machine learning and AI, and I’ve been able to build tech companies that do the same. Although some do not agree we are approaching an AI winter, from my perspective, as the economy comes to increasingly rely on more sophisticated machines, we can confront a potential plateau of AI development by training machines as an industry and providing more education to those creating the technology.

Education Reform For AI

In my experience, most of today’s AI developers are constrained by the mandate to automate. As a result, machines can become products of what I call “teaching to the test.” They can do singular tasks incredibly well, given incredibly narrow conditions.

When AI has to go off-script, so to speak, it struggles. For example, tech company DeepMind was working to develop AI that would function as a world-class Breakout player. But according to Wired, what they found in this initial brush with gaming AI was that the “seemingly supersmart AI could play only the exact style of Breakout it had spent hundreds of games mastering.” Even the smallest change to the game mechanics or layout caused the whole thing to break.

My point is that the majority of AI today doesn’t have critical thinking skills or common sense. Instead, it’s been designed to succeed through sheer rote memorization. It’s processing information to give an answer or action, but it’s not actually understanding what’s happening.

To address this, I believe tech companies need a playbook for research and development to prepare themselves for the next wave of innovation. And although there’s no canonical curriculum for training AI, there are a few key steps executives can take to ensure they are investing in AI education the right way:

Hire strategically.

Perhaps most importantly, it’s crucial that organizations hire the right people. Staffing for AI isn’t easy. Ensuring your recruits have the right technical chops can be expensive, but it’s worth it. Look for employees who have a history of dedicated curiosity. Have they published research? Are they interested in continued education? I believe AI developers who are equal parts programmers and researchers are the most valuable asset a tech company can have. Organizations that can recruit and keep this talent will find that they are suddenly the owners of valuable IP because their new AI hires are able to devote themselves to experiments and training the tech, rather than learning the skills for the job.

Enable your entire team to become more AI-literate.

Of course, as organizations seek to hire for positions that will become the bedrock of their tech strategy, I suggest that executives consider investing other company resources in support. Make your organization more competitive in its hiring by acquiring or collecting diverse and interesting data sets. There’s so much data out there, and extracting some of that data can help you determine what’s possible. For example, you might pull data from hundreds of automated bots and then synch them to create immediate, actionable insights. This means that you might have to spend more time at the collection phase, and your data sets might have to be larger as you conduct additional research to fill in any holes.

Additionally, incorporate AI training into your company’s professional development cross-departments. I believe the workforce of the future depends upon AI leadership and literacy. It’s predicated on the idea that everyone can contribute to AI’s teachings. This doesn’t mean teaching everyone in your organization to code. In fact, quite the opposite. Keep your lessons high-level and even philosophical. You’ll know you’ve succeeded if everyone in your organization can explain how AI gets trained, how it could be applied to a situation and — this is just as important — why it might fail.

The Future Of Company Success

Already, I’ve seen some companies commit the necessary resources for research and development projects in an effort to train AI to think about the challenges it’s presented with. Other companies considering doing the same should earmark resources purely for research and development in AI without the end goal being a breakthrough in automation. Make it clear that the underlying mission of your research teams is to push the bounds of your technical understanding — not push out a product. 

This shake-up in educating AI will unlock solutions we never dreamed possible. After all, the real value in AI comes from the bigger, new ways of thinking that it illuminates for us — the new patterns and wild ideas that only a machine, powered by tons of data and a healthy dose of common sense, could come up with.

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The world of AI and automatons is rapidly developing as industries use to emerging technologies to gain a competitive edge, such as in the automobile industry.

But there are concerns that such speedy innovation could have unintended and widely unforeseen effects on the human population of the world.

Some experts in the field believe a consequence of AI will be a spike in depression among workers.

It has been suggested that depression will be just one of the mental health issues that becomes more prevalent in people that find themselves losing out to robots in the jobs market.

Tech expert Charles Towers-Clark, who is CEO of cloud company Pod Group and author of “The WEIRD CEO: How to lead in a world dominated by Artificial Intelligence”, has predicted that in the future workers will become “disenfranchised and depressed” as they are pushed out of the workplace by AI.

He told Daily Star Online: “Any task that can be put into a process will be automated. If a task can be automated, it can be completed by a computer or a robot.

“For example, drivers – approximately 5% of the working population – will almost certainly be replaced by autonomous vehicles.

“Soon enough, AI will not only understand finance and law better than bookkeepers and junior lawyers but will also write better code than programmers.”

He continued: “There is every possibility that AI will destroy a huge number of jobs. Within 100 years, new jobs will be created.

“However, within the next generation or two, this won’t be the case. So, within the next 25 years, a large part of society may very well end up being unable to find employment, which will leave them disenfranchised and depressed.”

His thoughts have been echoed by other leading figures in the industry.

David Niki, the chief technology officer at Innowire Advisory, has predicted similar patterns for an unemployed human workforce.

Describing how the number of staff at most businesses will be dramatically reduced, Mr Niki said that although people will always have “the edge over AI”, it will not stop workers losing their job to technology.

“I think more than professions being lost, the number of staff will be reduced. ie. in the future, you might have a call centre having five people working instead of 100.

“People still need to be there, but their number will significantly decrease. The AI will take care of most of the parts but will need to escalate to human operators at some point.”

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