Last week, Qualcomm announced the next step in their bid to power the next generation of commercial 5G-enabled robots, with the release of the RB5 platform. Bringing high-compute power and a significant degree of modularity to the energy-constrained robotic platform market, the RB5 is an evolution on the company’s RB3 platform released in 2019, and a potential game-changer in the development of smart robotic fleets. 

Qualcomm Robotics RB5 platform is comprised of an extensive set of hardware, software and development tools. The Qualcomm Robotics RB5 platform is the first of its kind to bring together the Company’s deep expertise in 5G and AI to empower developers and manufacturers to create the next generation of high-compute, low-power robots and drones for the consumer, enterprise, defense, industrial and professional service sectors. 

The comprehensive Qualcomm Robotics RB5 Development Kit helps ensure developers have the customization and flexibility needed to commercialize robotic endeavors. To date, Qualcomm Technologies has engaged many leading companies that have endorsed the Qualcomm Robotics RB5 platform, including 20+ early adopters in the process of evaluating the platform. Additionally, 30+ ecosystem players are developing necessary hardware and software to enable various robotics applications. Beyond simple hardware, RB5 is a rich development kit with the potential to address many end-robot types from US$200-dollar social robots to autonomous haulage trucks. 

According to ABI Research, “providing a comprehensive development environment to support the integration of robotics chipset platforms is not unique to Qualcomm as we have seen other players, such as Nvidia with their ISAAC SDK, adopting the same approach. However, there are many new capabilities that differentiate RB5 from competing solutions, including the very feature-rich and highly integrated connected chipset design approach Qualcomm has traditionally used to generate scale in many markets, including smartphones, the home robots, and other IoT applications. From this perspective, RB5 represents a major addition in the toolbox for those developing the next fleet of smart robots.”  

“Qualcomm Technologies is the world’s leading wireless technology innovator with a strong foundation in AI, mobile computing and connectivity. By applying its deep-rooted mobile systems expertise to the robotics industry, Qualcomm Technologies is helping to enable the creation of more powerful, secure and intelligent robots than ever before,” said Dev Singh, senior director, business development and head of autonomous robotics, drones and intelligent machines, Qualcomm Technologies, Inc. “With the Qualcomm Robotics RB5 platform, Qualcomm Technologies will help accelerate growth in a wide array of robotics segments such as autonomous mobile robots (AMR), delivery, inspection, inventory, industrial, collaborative robots and unmanned aerial vehicles(UAVs), enabling Industry 4.0 robotics use cases, and laying the foundation for the UAV Traffic Management (UTM) space.”  

ABI Research’s Rian Whitton tells IndustryWeek, the mezzanines add a really impressive degree of customization, “making this pretty close to a comprehensive platform for any kind of mobile robot,” he says. “The partnership with AWS is also interesting. Robot developers need all the software improvements they can get to reduce autonomy exceptions when these robots are deployed.”  

To enable the next generation of robotics solutions and designs, Qualcomm Technologies has entered into a strategic collaboration with TDK to further enhance the capabilities of the Qualcomm Robotics RB5 platform. TDK has added its latest state-of-the-art sensor technologies for enhanced robotics applications as part of the Qualcomm Robotics RB5 platform and they have been instrumental in providing world class sensor solutions and motor control hardware.  

The fact that RB5 focuses on expanding 5G’s usefulness is exciting as manufacturers develop use cases. However, Whitton sees its robotic utilization occurring further down the road. “4K video streaming, massive IoT and ultra-low latency for mission critical operations are all valuable competencies 5G will bring to the robotics fleets of the future,” he says. “A lot more has to fall into place before the adoption of 5G for robotics becomes normalized however, and there’s a lot of low hanging fruit that can rely solely on WIFI and 4G /LTE.” 

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How far are we from artificial general intelligence? And if we ever see true AGI, will it operate similar to the human brain, or could there be a better path to building intelligent machines?

Since the earliest days of artificial intelligence — and computing more generally — theorists have assumed that intelligent machines would think in much the same ways as humans. After all, we know of no greater cognitive power than the human brain. In many ways, it makes sense to try to replicate it if the goal is to create a high level of cognitive processing.

However, there is a debate today over the best way of reaching true general AI. In particular, recent years’ advancements in deep learning — which is itself inspired by the human brain, though diverges from it in some important ways — have shown developers that there may be other paths.

What is artificial general intelligence?

For many, AGI is the ultimate goal of artificial intelligence development. Since the dawn of AI in the 1950s, engineers have envisioned intelligent robots that can complete all kinds of tasks — easily switching from one job to the next. AGI would be able to learn, reason, plan, understand natural human language and exhibit common sense.

In short, AGI would be a machine that is capable of thinking and learning much in the same way that a human is. It would understand situational contexts and be able to apply things it learned about completing one task to other tasks.

What is the current state of AGI?

We’re still a long way from realizing AGI. Today’s smartest machines fail completely when asked to perform new tasks. Even young children are easily able to apply things they learn in one setting to new tasks in ways that the most complex AI-powered machines can’t. 

Researchers are working on the problem. There are a host of approaches, mainly focused around deep learning, that aim to replicate some element of intelligence. Neural networks are generally considered state-of-the-art when it comes to learning correlations in sets of training data. Reinforcement learning is a powerful tool for teaching machines to independently figure out how to complete a task that has clearly prescribed rules. Generative adversarial networks allow computers to take more creative approaches to problem solving.

But there are few approaches that combine some or all of these techniques. This means today’s AI applications can only solve narrow tasks, and that leaves us far from artificial general intelligence.

How a more human-like approach to AGI might look

Gary Marcus, founder and CEO of Robust.ai, a company based in Palo Alto, Calif., that is trying to build a cognitive platform for a range of bots, is a proponent of AGI having to work more like a human mind. Speaking at the MIT Technology Review’s virtual EmTech Digital conference, he said today’s deep learning algorithms lack the ability to contextualize and generalize information, which are some of the biggest advantages to human-like thinking.

Marcus said he doesn’t specifically think machines need to replicate the human brain, neuron for neuron. But there are some aspects of human thought, like using symbolic representation of information to extrapolate knowledge to a broader set of problems, that would help achieve more general intelligence.

“[Deep learning] doesn’t work for reasoning or language understanding, which we desperately need right now,” Marcus said. “We can train a bunch of algorithms with labelled data, but what we need is deeper understanding.”

The reason why deep learning struggles to reason or generalize information is that algorithms only know what they’ve been shown. It takes thousands or even millions of labelled photos to train an image recognition model. And even after all that, the model is unable to perform different tasks like natural language understanding.

In spite of its limitations, Marcus doesn’t advocate moving away from deep learning. Instead, he says, developers should look for ways to combine deep learning with classical approaches to AI. These include more symbolic interpretations of information, like knowledge graphs. Knowledge graphs contextualize data — connecting pieces of information that are semantically related — while also using deep learning models to understand how people interact with information and make improvements over time.

“We need to stop building AI for ad tech and news feeds, and start building AI that can make a real difference,” Marcus said. “To get to that place you have to build systems that have deep understanding, not just deep learning.”

The case for deep learning

However, not everyone agrees. Speaking at the conference, Danny Lange, vice president of AI and machine learning at Unity Technologies, a video game software development company, said efforts to replicate human-like thinking could unintentionally limit what machines are capable of learning. Deep learning models operate on fundamentally different tracks than the human brain and, given enough data and compute power, there’s no telling how far they may be able to go. While we are still far from artificial general intelligence, deep learning could potentially get us there.

“What I appreciate about deep learning is that if you feed it enough data, it is able to learn abstractions that we as humans are not able to interpret,” Lange said.

One area of deep learning in particular, reinforcement learning, could be a promising path toward more general intelligence. Lange said these algorithms do operate somewhat more like natural thought when it comes to learning new tasks. And there have been examples in synthetic environments that have shown some ability to generalize learnings from one task to another.

He also believes that developers could speed up the training of deep learning models, which is currently one of the biggest hurdles. He’d like to see efforts to optimize the data sets that models train on, so that algorithms don’t need to see millions of examples of something to learn what it is. This idea is still developing, but Lange thinks it could take deep learning farther than it can currently go.

“We have limited data and compute power today,” he said. “But we haven’t gone very far with deep learning yet.”

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In his 1990 book The Age of Intelligent Machines, the American computer scientist and futurist Ray Kurzweil made an astonishing prediction. Working at the Massachusetts Institute of Technology (MIT) throughout the 1970s and 1980s and having seen firsthand the remarkable advances in artificial intelligence pioneered there by Marvin Minsky and others, he forecast that a computer would pass the Turing test – the test of a machine’s ability to match or be indistinguishable from human intelligence – between 2020 and 2050.

Kurzweil, now Google’s head of artificial intelligence, or AI (an acronym with which we’ve all now become familiar), has subsequently refined his claim. He now says this event will happen by 2029. What’s more, in 2045 we will witness what he calls “the singularity” – the point at which human and artificial intelligences merge, leading to exponential advances in technology and human capabilities.

Exciting stuff. Or is it? While Kurzweil is famously optimistic about the effect AI will have on human lives, others aren’t so sure. Part of this stems from the fear, inculcated by a thousand sci-fi movies, that “the robots will take over” – either rendering humans functionally useless or worse, becoming our masters in a dystopian role reversal.

The truth may lie somewhere in between. But what’s increasingly clear is that AI is advancing at a rapid pace. Already, it is posing profound questions about the future of work, of society and the very nature of what it means to be human.

We can get a sense for this from current innovations. Whether it’s self-driving vehicles, devices like Amazon’s Echo that can “understand” human language, or the intelligent crunching of vast medical datasets to diagnose disease more accurately, we’re moving towards a place where all manner of tasks are automated and human error – or perhaps human judgment – is obviated.

A recent report by the global consultancy McKinsey estimated that almost half (49 per cent) of the activities people are paid nearly $16 trillion in wages to do in the global economy have the potential to be automated by adapting currently demonstrated technologies.

This month I had the chance to discuss some of these implications before a House of Lords select committee in the UK’s Parliament. One issue the House of Lords committee is considering is whether to recommend the appointment of a new minister for AI to provide a coordinated response to these shifting sands across different government departments.

In this, the UK would be playing catch-up to the UAE, which, in a world-first, recently appointed 27-year-old Omar bin Sultan Al Olama to this role. Speaking to The National recently, Mr Al Olama set out his positive, practical vision for AI, saying it could offer humanity a “quick win” in helping to tackle climate change and other pressing problems.

While the UAE might be famous abroad for its glittering, futuristic cities of Dubai and Abu Dhabi, it is also situated in one of the world’s most ecologically sensitive regions and has an acute economic need to move away from fossil fuels as the main source of its wealth – so government-led nurturing of AI’s potential for sustainable ends makes a lot of sense.

Nor is the UAE alone in wanting to reap the economic benefits of AI. Indeed, across the world, it’s no exaggeration to say that something of an AI arms race has begun. China recently announced its intention to dominate the sector, creating a $150 billion industry by 2030, in direct competition with the US. China’s output of academic papers on artificial intelligence overtook the 28 EU countries combined for the first time last year.

Of course, we all hope that technological advances will continue to happen and will continue, on balance, to benefit humanity. But there’s little doubt there will be some unintended consequences, some of which are already manifesting themselves. One thing I’m particularly concerned about is the impact on job security. Sitting next to me in the House of Lords committee meeting was Olly Buston, the chief executive of the think-tank Future Advocacy, which recently published a report estimating between 22 per cent and 39 per cent of jobs in the UK are at high risk from automation by the early 2030s. With an average of about 30 per cent across the country, that represents more than 10 million livelihoods.

In London, where I work, there have been controversies recently over the way new technology-driven companies like Uber, a taxi service, and Deliveroo, a takeaway food delivery company, treat their workers. Because their businesses are built around advanced data services and smartphone apps, they have access to vast numbers of potential customers and willing recruits at the push of a button. But they have chosen, somewhat cynically, to class the people who work for them as self-employed rather than as employees. In the UK, this means they have no automatic right to sick pay, holiday or pension contributions and no opportunity for career progression.

Replicated at scale across an economy, you can imagine the effect this could have. While many workers will see their job security and welfare safety net vanish, those in control of the technology stand to benefit enormously. The question then becomes: how can we change the social contract so that we don’t just see runaway inequality and wealth polarisation? How can we make sure the increases in productivity and value-generation AI promises benefit all of society, instead of forcing millions into a precarious, hand-to-mouth existence that leaves little room for personal flourishing?

Recently, the Institute for Global Prosperity, of which I am director, put forward a radical new proposal that could help address one aspect of this challenge. Known as universal basic services, this would see many of the essentials of 21st century life – including housing, food, transport and information technologies – provided free at the point of need. This is a familiar concept in the UK, where our National Health Service has been providing needs-based healthcare for all, for the past 70 years. We have calculated that an extension of provision into these other areas could be afforded at a cost equivalent to about 2.3 per cent of the UK’s GDP. The practical effect of this would be to dramatically reduce the basic cost of living for most people, giving them greater freedom over their work and leisure choices.

We’re not saying this would be a panacea. But compared to other ideas like a universal basic income – a flat payment to all citizens – it’s far more affordable and could be one measure that helps to alleviate the worst impacts of inequality brought about by an increasingly tech-driven world.

This needs to go hand-in-hand with a much more detailed analysis of how we can upskill our populations through education to make the most of AI’s positive potential. Kurzweil said recently that AI will enhance us, not replace us. His predictions have often been right – but that doesn’t mean we shouldn’t start planning now for this radically changed future.

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For the majority of CIOs, cybersecurity and artificial intelligence (AI) will significantly change how they do their jobs in the near future, a new survey said on Tuesday. Cybersecurity continues to threaten the global landscape in 2018 and 95 percent of CIOs surveyed said they expect cyber threats to increase and impact their organisations, said the survey, presented during Gartner Symposium/ITxpo in Ontario.

“In response to these concerns, the survey found that digital security ranks high on the CIO agenda as 35 percent of respondents said they have already invested and deployed some aspect of digital security, and 36 percent are in the process of planning to implement some form of digital security,” said Andy Rowsell-Jones, Vice President and Distinguished Analyst at Gartner.

“CIOs are also increasingly adopting AI in their organisations. Predominantly, AI is being used initially, either to boost the customer experience or to fight fraud,” he added.

The “2018 Gartner CIO Agenda” survey gathered data from 3,160 CIO respondents in 98 countries and all major industries. The results showed that 95 percent of CIOs expect their jobs to change or be remixed due to digitalisation. “The CIO’s role must grow and develop as digital business spreads, and disruptive technologies, including intelligent machines and advanced analytics, reach the masses,” said Rowsell-Jones.

CIOs surveyed rank AI, followed by digital security and the IoT, as the most problematic technologies to implement. The respondents agreed that the most common pain point is the fact that these technologies, particularly AI, demand new skills, some of which can be hard to find. The survey found that CIOs are spending more time on the business executive elements of their jobs compared with three years ago.

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The concept of artificial intelligence has been fuel for science fiction since at least 1920, when the Czech writer Karel Čapek published R.U.R., his play about a mutiny led by a throng of robots. Speculation about the future of intelligent machines has run rampant in the intervening decades but recently has taken a more critical turn. Artificial intelligence (AI) is no longer imaginary, and the implications of its future development are far-reaching. As computer scientists confirm their intent to push the limits of AI capabilities, religious communities and thinkers are also debating how far AI should go—and what should happen as it becomes part of the fabric of everyday life.

“Scientists want to be at the cutting edge of research, and they want the contribution to knowledge,” says Brendan Sweetman, chair of philosophy at Rockhurst University. “But at the same time, a lot of what they do raises moral questions.”

Artificial intelligence is already pervasive. It’s embedded in iPhone’s Siri and Amazon’s Alexa, which are apps designed to answer questions (albeit in a limited way). It powers the code that translates Facebook posts into multiple languages. It’s part of the algorithm that allows Amazon to suggest products to specific users. The AI that is enmeshed in current technology is task-based, or “weak AI.” It is code written to help humans do specific jobs, using a machine as an intermediary; it’s intelligent because it can improve how it performs tasks, collecting data on its interactions. This often imperceptible process, known as machine learning, is what affords existing technologies the AI moniker.

The sensationalizing of AI is not a product of weak AI. It is, instead, a fear of “strong AI,” or what AI could someday become: artificial intelligence that is not task-based, but rather replicates human intelligence in a machine.

This strong AI, also known as artificial general intelligence (AGI), has not yet been achieved, but would, upon its arrival, require a rethinking of most qualities we associate with uniquely human life: consciousness, purpose, intelligence, the soul—in short, personhood. If a machine were to possess the ability to think like a human, or if a machine were able to make decisions autonomously, should it be considered a person?

Religious communities have a significant stake in this conversation. Various faiths hold strong opinions regarding creation and the soul. As artificial intelligence moves forward, some researchers are engaging in thought experiments to prepare for the future, and to consider how current technology should be utilized by religious groups in the meantime.

“The worst-case scenario is that we have two worlds: the technological world and the religious world.” So says Stephen Garner, author of an article on religion and technology, “Image-Bearing Cyborgs?” and head of the school of theology at Laidlaw College in New Zealand. Discouraging discourse between the two communities, he says, would prevent religion from contributing a necessary perspective to technological development—one that, if included, would augment human life and ultimately benefit religion. “If we created artificial intelligence and in doing so we somehow diminished personhood or community or our essential humanity in doing it, then I would say that’s a bad thing.” But, he says, if we can create artificial intelligence in such a way that allows people to live life more fully, it could bring them closer to God.

The personhood debate, for Christianity and Judaism in particular, originates with the theological term imago Dei, Latin for “image of God,” which connotes humans’ relationship to their divine creator. The biblical book of Genesis reads, “God created mankind in his own image.” From this theological point of view, being made in the divine image affords uniqueness to humans. Were people to create a machine imbued with human-like qualities, or personhood, some thinkers argue, these machines would also be made in the image of God—an understanding of imago Dei that could, in theory, challenge the claim that humans are the only beings on earth with a God-given purpose.

This technological development could also infringe on acts of creation that, according to many religious traditions, should only belong to a god. “We are not God,” Garner says. “We have, potentially, inherently within us, a vocation to create”—including, he says, by utilizing technology. Human creation, however, is necessarily limited. It’s the difference between a higher power creating out of nothing, and humans creating with the resources that are on earth.

Russell Bjork, a professor of computer science at Gordon College and graduate of Gordon-Conwell Theological Seminary and MIT, worries that creating a machine with strong artificial intelligence could quickly allow it to become an outlet for idolatry. It would be idolatrous, he says, to utilize strong AI as a method to defeat death and save the human race—predictions he feels scientists and futurists are wont to make. “To place one’s trust in anything other than God the creator is idolatry,” he says. “At that point it moves way beyond the realm of mirroring God’s creativity.”

Noreen Herzfeld, professor of theology and computer science at St. John’s University, further explained these issues in her paper, “Creating in Our Own Image: Artificial Intelligence and the Image of God.” She writes, “If we hope to find in AI that other with whom we can share our being and our responsibilities, then we will have created a stand-in for God in our own image.”

At this point, artificial intelligence is simply a tool for improving human experience. It can help us build cars, diagnose illnesses, and make financial decisions. It is easy to imagine a world in which our technology slowly becomes more and more intelligent, more and more self-aware. As weak AI evolves into strong AI, says James F. McGrath, author of “Robots, Rights and Religion” and a New Testament professor at Butler University, humanity will have grown accustomed to treating it like an object. Strong AI, by definition though, is human-like in intelligence and ability. Its development, he says, would force humans to reconsider how to appropriately interact with this technology—what rights the machines should be afforded, for instance, if their intelligence affords them a designation beyond that of mere tools. “Are we going to be generous in our granting of rights in the absence of clear answers to these questions, or are we going to be stingy?” McGrath says. “Do we risk enslaving a sentient, self-aware entity, or do we say, ‘We’re going to do whatever it takes to make sure that that doesn’t happen even by accident’?”

The debate around this issue has, in both pop culture and the scientific community, produced significant anxiety. The concept of the singularity, popularized by Raymond Kurzweil in his book The Singularity is Near, is an example of how taking the wrong path can lead the evolution of AI awry: It is, at its most basic, a fear that if we enlist machines to perform all of our tasks, transferring our knowledge to them, they will eventually become much more intelligent than humans—and possibly decide to dominate us. Those in the world of computer science who believe this fear has legitimacy have created an organization, the Machine Intelligence Research Institute, bent on preventing it.

But beyond speculation, there are ethical questions that need answering now, says J. Nathan Matias, a visiting scholar at the MIT Media Lab. Matias is co-author of a forthcoming paper on the intersection of AI and religion. “AI systems are already being used today to determine who police are going to investigate,” he says. “They’re used today to do sting operations of people who are imagined as potential future domestic abusers or sexual predators. They’re being used to decide who is going to get [financial] credit or not, based upon anticipated future solvency.” Religious communities should participate in conversations regarding these dilemmas, he says, and should involve themselves in the application of the AI that exists today.

Matias also points to Facebook’s algorithms that recommend content to users—a form of weak AI. In this way, AI can help make a post go viral. When a heartbreaking story is popular online, it directly influences the flow of prayer and charity. “We already have these attention algorithms as a clear example of what are shaping the contours of things like prayer or charitable donations or the theological priorities of a community,” he says. Such algorithms, like that employed by Facebook, dictate the political news—true or not—that people see. Religious groups, then, have a keen interest in the development of artificial intelligence and its ethical implications.

The ties between religious thinkers and artificial intelligence developers should be made stronger, according to Lydia Manikonda, a PhD student at Arizona State University who is working, along with several other researchers, on the paper with Matias about religion and artificial intelligence. She says, “These systems are made by us. How are we going to teach these systems what is right and what is wrong?” Addressing the morality of machines in advance of the development of strong artificial intelligence would help prevent the kind of cataclysmic robot-dictatorship that abounds in science fiction. And because artificial intelligence, by definition, builds on itself, embedding ethical principles in code now is imperative to developing an ethical machine in the future.

Machines in possession of strong artificial intelligence would likely rattle the basic understanding of the role of religion. “Just as the printing press had a significant impact on religious scholarship, both positive and negative, so the internet and then finally AI—those too will have a significant impact on both the institutions of religion and the way religions understand themselves,” says Daniel Araya, a technological innovation researcher and policy analyst. “AI is now speculated about in the way people used to speculate on the nature of God. Could it replace religion on a whole?”

Randall Reed, an associate professor of religion at Appalachian State University, says imbuing a machine with the ability to be omniscient, omnipotent, and omnipresent, would automatically create parallels to, and tensions with, monotheistic religions. “In the Christian tradition, we ascribe the big ‘omnis,’” he says, to God. “At least two, and maybe even three of those, become definitional of a superintelligent artificial intelligence.” With this type of AI, he says, “you have something that, through the internet, can be everywhere, can know everything, and has the ability to solve all the problems and understand them in ways that humans have never been able to do.”

Araya speculates that machines with strong artificial intelligence could become objects of worship in and of themselves: “There’d be religious movements that worship AI.” If a machine possesses cures for long-existing fatal diseases, knew how to improve education, and brought order to society, would humans idolize it?

The machines could, according to McGrath, develop their own sects or entirely new religions. A machine, he says, could think religion “doesn’t compute.” Or, if programmed to prioritize ethical concerns “might have a very different perspective. I can certainly imagine there being denominations that the AI develops.”

As a thought experiment, Reed raises the possibility that some branches of Christianity will try to convert machines with strong artificial intelligence to follow their God. And some Christian scientists, in the development of this new technology, may try to go beyond imbuing it with general rules of ethics, instead coding it to work within a clearly defined set of Christian values.

Regardless, the overwhelming reaction to the development of a machine with strong AI is likely to be fear. “If you’re in a religious community that is incredibly suspicious of existing technologies or past technologies and their implications, then a technology like artificial intelligence would be incredibly disturbing—to some extent, seeing it as another Tower of Babel, another [instance of] humanity attempting to usurp God’s position in the world,” says Garner. According to Heidi A. Campbell, an associate professor of communication at Texas A&M University and Garner’s co-author for Networked Theology: Negotiating Faith in Digital Culture, Christian churches have typically been slow to adapt to new technologies, having held vigorous debate regarding the televising of sermons and the use of the internet in the recent past.

The resistance should give religious communities pause. As Christopher J. Benek, a pastor and Christian transhumanist, puts it, “We are quick to assume that AI will be so different from us. My experience with technology is that it usually is heightening who we are currently.” What communities should do now, in preparation for the eventual creation of a machine with strong AI, he says, is think about how the technology created reflects their values. For Benek, those values stem from emulating Jesus. How can technology advance those principles? Artificial intelligence may change rapidly, but religious and scientific communities already have tools to explore its ethical and moral limits. “Part of this is working on ourselves formationally,” Benek says, “to work on the technology we have right now.”

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“Human plus machine isn’t the future, it’s the present,” Garry Kasparov said in a recent TED talk.

And this “present” is transforming the world of education at a rapid pace. With children increasingly using tablets and coding becoming part of national curricula around the world, technology is becoming an integral part of classrooms, just like chalk and blackboards.

We have already witnessed the rise and impact of education technology especially through a multitude of adaptive learning platforms such as Khan Academy and Coursera that allow learners to strengthen their skills and knowledge.

And now virtual reality (VR) and artificial intelligence (AI) are gaining traction. A recent report by Pearson deciphers how artificial intelligence will positively transform education in the coming years. Per the report’s authors, “The future offers the potential of even greater tools and supports. Imagine lifelong learning companions powered by AI that can accompany and support individual learners throughout their studies – in and beyond school – or new forms of assessment that measure learning while it is taking place, shaping the learning experience in real time.”

Indeed, high costs remain a challenge but the day is not far when AI and VR tools will be as accessible as smartphones and desktop computers.

Intelligent machines are playing a major role in delivering customized relevant knowledge to learners, where and when needed. For instance, Content Technologies Inc., a U.S.-based artificial intelligence research and development company is leveraging deep learning to deliver customized books. The company launched Cram101 and JustFact101 to turn decades-old text books into smart and relevant learning guides, making study time efficient.

Moreover, learning is now turning into a truly immersive experience inside and outside the classroom. As a conference curator, I design immersive experiential activities to offer participants a memorable experience, leaving them with a strong desire to return the following year.

And as an educator, I believe the same strategy has the power to spur creativity, engagement and stronger learning outcomes among my students. But for decades, experiential learning was confined to science experiments in the school’s archaic laboratory or to summer holiday assignments. But with VR and AI, experiential or hands-on learning has an all new meaning.

A variety of artificial reality tools including Microsoft’s HoloLens, Oculus Rift, or Google Expedition are translating traditional lessons into meaningful real-world experiences.

Imagine a room full of students exploring the wreck of the Titanic, watching dinosaurs walk around them, discovering the Amazon or simply landing on the moon as astronauts — what a giant leap in education?

“We are moving away from simply ‘learning’ a subject or topic to ‘feeling’ the content. This is not simply an engagement tool or a gimmick, it allows a student to explore, to experience or to be involved in something, as if they are actually present in that environment or place,” Graeme Lawrie, Director of Innovation and Outreach at the U.K.-based Sevenoaks School wrote recently.

And students aren’t the only beneficiaries.

Intelligent tutoring systems such as Carnegie Learning or Third Space Learning are helping teachers break free from the “one size fits all” approach. These one-to-one tutoring platforms leverage Big Data and learning analytics to provide tutors with real-time feedback about their students’ performances, strengths and weaknesses. The feedback helps teachers determine exact learning needs and skills gap of each student and provide supplemental guidance.

I’ve often heard experts say “technology makes bad teachers worse. So there is no doubt that we need to continue investing in their training and professional development. No machine can replace human teachers but it can save them from crumbling under pressure. Remember Georgia Tech professor Ashok Goel’s AI teaching assistant Jill Watson? It is an illustration of how smart machines will help teachers transition from the sage-on-stage to mentors and facilitators.

Per Thomas Arnett, author at the Christensen Institute, “Rather than seeing technological progress as a threat, teachers and education leaders should take advantage of the many ways technology can enhance their work.”

Arnett believes automation will help simplify basic teaching tasks and help school leaders address key challenges to quality instruction — namely variations in teacher quality, wide- ranging student needs, and added expectations placed on teachers.

“Innovations that commoditize some elements of teacher expertise also supply the tools to raise the effectiveness of both non-experts and expert teachers to new heights and to adapt to the new priorities of a 21st-century work force and education system”, writes Arnett in his report Teaching in the Machine Age

In this report, Arnett also elaborates AI’s potential to recognize and develop high-potential prospective teachers. “Researchers can pinpoint high-quality teachers ex post facto based on teacher observations, student survey responses, and student test scores but they are far less successful at identifying the characteristics of effective teachers or illuminating a clear path for preparing and developing them.”

And most importantly, in addition to content mastery, teachers will be able to help their students develop the much needed 21st century non-cognitive skills such as confidence and creativity.

The picture that I project in this article may seem overly optimistic to many.

Indeed, AI and ed-tech are not a panacea for systemic challenges. AI may not be end up being the next giant leap in education and they will of course bring their own set of problems and disadvantages.

But let’s not ignore their inherent strengths that could help address the glaring gaps in teaching and learning, that we have been struggling to fill for decades.

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Artificial intelligence is fast changing the world. The premise that intelligent machines will perform tasks more efficiently and at a lower cost than human beings is by no means far-fetched. The challenges facing the workers of the future are multiplying before our very eyes.

Some of the most vulnerable jobs in the transition to automation, robotics and artificial intelligence are related to transport, mechanical work in factories and customer service. But no sector, be it health, finance or even the military, is excluded.

In the study When Will AI Exceed Human Performance? Evidence from AI Experts, conducted by researcher Katja Grace from the Future of Humanity Institute at Oxford University, 350 artificial intelligence experts predict that AI will outperform human beings within the next ten years in activities such as translating languages (in the year 2024), essay writing at secondary school level (in 2026) and truck driving (in 2027). Writing a bestselling book or replacing a surgeon will come a little later (in 2049 and 2053), but it will come.

Global challenges, unequal risks

The potential conflicts vary considerably according to the level of economic development. “In developed countries, there is a concern that new forms of artificial intelligence will compete with humans for jobs, given their increased comparative advantage in areas of cognitive ability. Whereas in emerging and developing countries, concerns around automation are principally associated with the risk that it will replace manufacturing jobs – which have been central to past growth strategies. The central theme, of course, in both instances is the risk that jobs will be replaced by technology,” senior economist at the ILO, Steven Tobin, tells Equal Times.

Tobin emphasises that, in the past, technological innovation did not lead to the “technological unemployment” so widely feared. “In this sense, the future of work is not pre-determined. It is up to us, particularly the governments and social partners, to forge the kind of future we want. Our task is to manage technological innovation in an effort to seek the best labour market and social outcomes,” he adds.

“To some extent, automation almost intrinsically means progress, in the sense that it gives human beings greater freedom from the sacrifices that work demands of us. The problem is that the advantages or profits derived from the increased productivity resulting from automation do not necessarily benefit all social groups in equal measure. It depends on the negotiating capacity, on the power held by each social group,” warns Juan Torres López, professor of applied economics at the University of Seville.

In addition, the global rise of non-standard forms of employment, such as temporary or part-time employment, agency work, subcontracting, dependent self-employment or ambiguous employment relationships, could generate even greater insecurity when combined with technological innovation. “Such non-standard forms of employment are often linked to greater insecurity for workers. In this sense, better regulation is needed that ensures equal treatment for workers regardless of their contractual arrangement,” underlines the ILO.

Another key factor, in addition to effective social protection for workers, is broader and better access to training, to develop their skills. “We need to ensure that individuals have access to the right education and skills to take up the new jobs, and that effective social protection measures are there to provide minimum guarantees,” explains Tobin.

“As with automation, many people rush to make a judgment with respect to robots and the risk that they will take away jobs,” adds Tobin “The reality is that we don’t have a clear answer and further debate and research is required.”

For the ILO economist, Germany and Japan, which have managed to introduce robots within companies without compromising jobs, are positive examples. “Robots are now able to undertake tasks that are hazardous and dangerous for humans,” he points out. The challenge lies in stimulating innovation and cutting costs without compromising the fair redistribution of income, regardless of the worker’s contractual arrangement.

Pilot social policies, a response to the new challenges

Barcelona is to launch a programme in September that will run for 24 months, to trial four minimum income schemes in 1,000 households in the Besòs district. It is a pilot project with a budget of 13 million euros. “The aim is to study what can be done to ensure that all the people residing in the city of Barcelona have access to the minimum level of income needed to live a decent life. It is based on the certitude that the current welfare benefit system is inadequate and too complex to achieve this objective,” explains the social rights section of Barcelona city council.

“The 1000 households involved will be divided into four subgroups to see how their income is reduced, or not, when they receive supplementary or unexpected income, as well as the impact of being obliged, or not, to take part in specific socio-labour projects.”

As the city council points out: “Despite the wealth of literature on the subject, there are not many practical studies, to date, that examine, in detail, the best way for this type of income to meet its ultimate goal, which is to reduce inequalities and ensure genuine equality of opportunity. Similar studies are currently underway in the province of Ontario (Canada), the city of Utrecht (Netherlands) and Finland.”

At the end of the two-year trial, an assessment will be made of how these policies impact the social protection and the reduction of inequalities. “Our rationale is based on the fact that current policies, often too ’assistentialist’ or paternalistic, have not helped to curb the rise in poverty and inequality, which is why we believe it would be good to explore basic income in greater depth. It could also contribute to condensing exiting benefits and reducing the amount of bureaucracy,” says the city council.

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