Geospatial data and analytics company Fraym announced a Series B financing to further scale their AI/ML software for mapping humanity.

Fraym is the preeminent global provider of geospatial data for understanding population dynamics. Dozens of data-driven organizations like Mastercard, the World Bank, Department of Defense, and USAID rely on Fraym’s foundational data to drive impact and mission success. Over the past 5 years, the company has:

• Mapped hundreds of distinct population characteristics covering over 3.2 billion people and 2 billion square kilometers — enough to cover the entire globe nearly 5 times over.
• Informed over $35 billion in programmatic and operational missions, spanning the design, implementation, and monitoring of strategic activities.

“Fraym has executed on ambitious product and customer success goals year after year. This raise will further accelerate our mission of mapping humanity and deliver a future where solutions around the world are built on hyper-local, spatially standardized data,”  said Fraym CEO and Co-Founder, Ben Leo.

This $7 million in additional funding, largely from Fraym’s existing investors, will support further capital-efficient development of cutting-edge product and delivery solutions. All of which trailblaze a new frontier in location-based data about people—one that protects individual privacy.

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Founder and CEO, Analytics Insight, providing organizations with strategic insights on disruptive technologies. 

Artificial intelligence (AI) is considered one of the most revolutionary developments in human history, and the world has already witnessed its transformative capabilities. Not surprisingly, AI-based innovations are powering some of the most cutting-edge solutions we use in our daily lives.

Today, AI empowers organizations, governments and communities to build a high-performing ecosystem to serve the entire world. Its profound impact on human lives is solving some of the most critical challenges faced by society. Here are a few innovations for social causes that I find most notable. 

Developing New Drugs: The healthcare industry is ripe with disruptive applications of AI, including the discovery and development of new drugs. AI and machine learning have been used to identify potential molecules by leveraging a large volume of data. Pharmaceutical companies use predictive analytics to discover these molecule candidates and optimize them with several rounds of iteration to select the best one for drug manufacturing.

Reporting Sexual Harassment: Artificial intelligence offers new ways of reporting gender-based violence, child sex abuse and more. AI programs are being designed to monitor internal communications, such as corporate documents, emails and chat, for inappropriate content. Various applications and platforms have been developed to help victims share their experiences of sexual harassment and abuse along with the time and location these events took place.

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When some people hear the term ‘artificial intelligence’ their initial reaction is to imagine a dystopian future where robots have risen up and overthrown humanity. The truth is, application of AI technology in our day-to-day lives is a lot less sinister. It might not be long before these technologies become common in our everyday lives.

It’s currently assisting with medical diagnosis, the creation of autonomous cars and to help improve businesses by analysing data and creating accurate forecasts of client or market behaviour. The application of AI is becoming more and more popular in businesses worldwide, with the potential to improve our lives in unexpected ways.

A Helping Hand

You may not have realised it, but AI technology could already be playing a role in your life. If you happen to use one of the various virtual assistants currently available on the market, like Amazon’s Alexa, Apple’s Siri or Google Assistant, you are directly engaging with AI. These assistants are able to process data fed to them by their users, and use machine learning to tailor responses that fit their owner’s needs.

In 2019, OpenAI trained a pair of neural networks to solve a Rubik’s Cube with a human-like robot hand. This was achieved by teaching the AI through reinforcement learning, exposing it to a series of randomised simulations. On the surface, solving a Rubik’s Cube may seem like a weird application of AI, but the development and results from this technology can help with the creation of robots that have human-level dexterity.

According to IBM Developer Advocate Steve Coochin, AI systems – such as IBM’s Watson – have the potential to be applied to “virtually any scenario, industry or organisation to streamline processes, increase effectiveness, and accelerate progress.”

“One example is Prometeo, from our Call for Code hackathon,” Coochin explains, “an AI solution which uses machine learning to monitor and support firefighter health and safety in real-time while they are putting out fires.”

“Using Watson Machine Learning predicative model, the technology can reply in real time with a green, yellow, or red firefighter status to the fire station.”

AI-Assisted Agriculture

Artificial intelligence technology is currently being used to help keep Australia’s bee industry alive through biosecurity. Bega’s recent Purple Hive Project is designed to help stop entire hives from being wiped out by using AI technology to detect whether bees are carrying the Varroa mite. This tiny parasite attaches itself to unsuspecting bees, feeding on their blood and can spread viruses that can devastate entire colonies.

These bright purple hives are equipped with 360-degree cameras that scan each bee that enters. Using AI technology, it can detect whether or not a bee is carrying the Varroa mite. If a bee is a confirmed carrier, the hive will send an automatic alert to the beekeepers so they can quarantine the hive.

By making sure Australia’s bee population remains healthy, this AI technology is also helping to keep our local agriculture industry alive as, according to the CSIRO, “one in every three mouthfuls of food that we consume comes to us through the aid of pollination by honeybees.”

AI has the great potential to help improve pre-existing software and information technologies, but there’s also the possibility of it being used for entertainment purposes, too. One of the more popular, recent examples of this would be AI Dungeon. It’s a free text-based adventure game that creates unique stories by auto-generating responses based on what the player types.

AI Dungeon uses a language model known as Generative Pre-trained Transformer (GPT-3), which allows for deep learning to produce human-like text. Depending on which genre setting you choose at the start of the game, AI Dungeon will procedurally generate a story based on previous learnings and your inputs, which, for the most part, will read as a coherent story.

One of the stranger applications of it is the website DeepArt, which creates AI-assisted art. This platform uses an algorithm to pull stylistic elements from a chosen image and apply it to another. For example, you can upload a normal photo of your bedroom and use DeepArt’s algorithm to make it look like Vincent van Gogh’s ‘The Starry Night’ or Paul Cézanne’s ‘The Large Bathers’.

Get Involved in the Future of AI

These various applications of AI technology may sound interesting, but how can you become a part of this expanding frontier? Enrolling in one of Billy Blue College of Design at Torrens University Australia’s software engineering or digital transformation-based courses, such as a Bachelor Of Software Engineering (Artificial Intelligence) or Graduate Certificate of Digital Transformation and Creative Intelligence, will let you begin your adventure into creative technology, opening you up to the world of AI development.

To make sure you get the most from these courses, they’ve been developed in collaboration with IBM, who are currently leading the pack when it comes to AI. According to the IDC Market Share, IBM has been ranked the market share leader for the third year running.

IBM have become the frontrunners in the world of artificial intelligence for a few reasons. Firstly, the sturdy information architecture of their Cloud Pak for Data helps businesses by using automated AI to collect, organise and analyse data, making it easy to manage and access. They’ve also aimed for transparency when it comes to the development of AI technologies. Their Watson OpenScale platform allows business’ to measure and track the deployment of AI technology to meet set outcomes, allowing for a clearer explanation of how they work.

Billy Blue will teach you important skills used in AI development, such as design thinking, creative intelligence and human centred design, as well as giving you the tools to learn about topics like computer vision, natural language processing and machine learning. Through their collaboration with IBM, they hope to put this technology into your hands. With these tools — along with your imagination — you’ll be able to discover the vast possibilities within the field of AI technology.

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Every year I travel the world as part of my job to discover, discuss and share the future with people from all walks of life. And what I found is this: the future is likely to be better than we think – but we need to design and govern it wisely!

Just two decades in, the twenty-first century has already presented us with a massive economic crash, geopolitical quagmires and worrisome swings towards popularism. This may not be the optimal context for heralding a New Renaissance – but then again, the original renaissance wasn’t born in idyllic circumstances either. Rather, it was a literal rebirth of human culture.

I believe the exact same process is happening again today, but not for the same reasons. Let me explain.

Technology is the new religion

Technology has replaced the once-mighty church and currently dominates our personal as well as professional lives. A few global behemoths – the churches of dataism – now control how we communicate and connect, search, buy and sell, entertain and learn. What was once used to connect us (so-called social media) is now dividing and manipulating us, catapulting us towards an algorithmic society.

But we are also witnessing the rebirth of humanity just as it once reawakened in Italy, and we may already have reached ‘Peak Tech Worship’ in 2019. Silicon Valley CEOs are dragged in for questioning before the U.S. Congress and the EU Commission, and #digitalethics is now a global theme (a meme I presented back in 2017 in my book Technology vs. Humanity). The debates about ‘digital pollution’, data sovereignty, abusive data-mining, social media’s manipulation of the democratic process, and algorithmic bias are growing louder every day.

‘Business as usual’ will kill us

In addition to the wicked problem of technological domination and ‘too much of a good thing’, climate change is now – finally – recognised as a real emergency that only the crudest naysayers continue to deny, further forcing us to face ‘the end of business as usual’. The bottom line is that both the way we (ab)use our environment cannot continue, and the way we have put technology (and its financial rewards) above humanity cannot continue. These are the two externalities of exponential progress that we must now confront – because they are existential.

The New Renaissance coming in 2020 will see a rebirth of humanism and the humanities on top of exponential technological progress. In economic terms, human purpose will complement ‘people, planet and prosperity’ for a new, quadruple bottom line that I call ‘People Planet Purpose and Prosperity’, riffing off the UN’s SDGs. Maybe the recent Business Roundtable declaration on moving from shareholder primacy to stakeholder value can be viewed in this context? Personally, I think we are going to see a new stock market emerge in the next 5-7 years, dedicated to companies that adhere to these 4Ps – a kind of NASDAQ for sustainable capitalism.

Our world is going to change more in the next 20 years than in the previous 300 years

… and it could be heaven or it could be hell. How will we reassert our humanity and maintain our human values in a world that is changing exponentially? Leonardo Da Vinci’s ‘Vitruvian Man’ depicted the ideal proportions of the human body – maybe now we need a ‘neoluvian man’ depicting the future relationship of humans and technology?

The first Renaissance replaced religious dogma with human curiosity and creativity. The second renaissance will replace technological dogmas such as connectivity, efficiency, speed, optimization and productivity with human relevance, purpose, engagement, relationships and self-realisation.

Transhumanists may keep pining to ‘transcend human limitations’, while Elon Musk tells us we must become cyborgs to keep up with AIs – but don’t be mistaken: The new Renaissance that is now upon us is a very human one. After all, it will be those that keep thinking, acting and learning like robots who will be unemployed and become ‘useless humans’.

Today, technology has been enshrined and even deified, and data is indeed the new oil. Yet most technology will soon become an abundant commodity, and humanness will be a sought-after scarcity. These are the human-only traits and characteristics I call the ‘androrithms’ – the opposite of algorithms, the not-data, not-binary, non-computable attributes that actually make us human: intuition, imagination, empathy, compassion and emotional intelligence. Androrithms are the connective tissue of our civilisation, and they will never be replicable in silicon.

Our future is to be more human, not less.

The future is often presented in two flavours: Silicon Valley sells us Utopia (super-humanity), and Hollywood + Netflix et al sells us Dystopia (fear). Yet the real future is neither ideal nor infernal. Apple’s CEO Tim Cook – a rare example of a humanist running a technology company – really nailed this in his 2017 MIT commencement speech: “Technology can do great things, but it does not want to do great things – it doesn’t want anything”. The want has to come from us – and the future is something we create every day, by action or by inaction.

In order for this new Renaissance to take hold, education urgently needs to leave behind its industrial-era obsession with efficiency and productivity, and focus on enabling and empowering human-only skills – because the bottom line is that ‘the robots’ are coming to handle the donkey work, the chores and the commodity tasks – and if you are clever you will let them!

Perhaps in the industrial age and even in the so-called information society we’ve been pretending to be inhuman all along, to be ‘better machines’ – and now it’s time to give up the act: Our ultimate job is to be human.

As the third decade of the twenty-first century kicks off, let’s transcend our love-affair with ‘digital transformation’ and ‘exponential technologies’ and rediscover what it means to be human.

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Most discussions about artificial intelligence are characterised by hyperbole and hysteria. Though some of the world’s most prominent and successful thinkers regularly forecast that AI will either solve all our problems or destroy us or our society, and the press frequently reports on how AI will threaten jobs and raise inequality, there’s actually very little evidence to support these ideas. What’s more, this could actually end up turning people against AI research, bringing significant progress in the technology to a halt.

The hyperbole around AI largely stems from its promotion by tech-evangelists and self-interested investors. Google CEO Sundar Pichaideclared AI to be “probably the most important thing humanity has ever worked on”. Given the importance of AI to Google’s business model, he would say that.

Some even argue that AI is a solution to humanity’s fundamental problems, including death, and that we will eventually merge with machines to become an unstoppable force. The inventor and writer Ray Kurzweil has famously argued this “Singularity” will occur by as soon as 2045.

The hysteria around AI comes from similar sources. The likes of physicist Stephen Hawking and billionaire tech entrepreneur Elon Musk warned that AI poses an existential threat to humanity. If AI doesn’t destroy us, the doomsayers argue, then it may at least cause mass unemployment through job automation.

The reality of AI is currently very different, particularly when you look at the threat of automation. Back in 2013, researchers estimated that, in the following ten to 20 years, 47% of jobs in the US could be automated. Six years later, instead of a trend towards mass joblessness, we’re in fact seeing US unemployment at a historic low.

Even more job losses have been threatened for the EU. But past evidenceindicates otherwise, given that between 1999 and 2010, automation created 1.5 million more jobs than it destroyed in Europe.

AI is not even making advanced economies more productive. For example, in the ten years following the financial crisis, labour productivity in the UK grew at its slowest average rate since 1761. Evidence shows that even global superstar firms, including firms who are among the top investors in AI and whose business models depend on it – such as Google, Facebook and Amazon – have not become more productive. This contradicts claims that AI will inevitably enhance productivity.

So why are the society-transforming effects of AI not materialising? There are at least four reasons. First, AI diffuses through the economy much slower than most people think. This is because most current AI is based on learning from large amounts of data and it is especially difficult for most firms to generate enough data to make the algorithms efficient or simply to afford to hire data analysts. A manifestation of the slow diffusion of AI is the growing use of “pseudo-AI” where a firm appears to use an online AI bot to interact with customers but which is in fact a human operating behind the scenes.

The second reason is AI innovation is getting harder. Machine learning techniques that have driven recent advances may have already producedtheir most easily reached achievements and now seem to be experiencing diminishing returns. The exponentially increasing power of computer hardware, as described by Moore’s Law, may also be coming to an end.

Related to this is the fact that most AI applications just aren’t that innovative, with AI mostly used to fine-tune and disrupt existing products rather than introduce radically new products. For example, Carlsberg is investing in AI to help it improve the quality of its beer. But it is still beer. Heka is a US company producing a bed with in-built AI to help people sleep better. But it is still a bed.

Third, the slow growth of consumer demand in most Western countries makes it unprofitable for most businesses to invest in AI. Yet this kind of limit to demand is almost never considered when the impacts of AI are discussed, partly because academic models of how automation will affect the economy are focused on the labour market and/or the supply side of the economy.

Fourth, AI is essentially not really being developed for general application. AI innovation is overwhelmingly in visual systems, ultimately aimed for use in driverless cars. Yet such cars are most notable for their absence from our roads, and technical limits mean they are likely to remain so for a long time.

New thinking needed

Of course, AI’s small impact in the recent past doesn’t rule out larger impacts in the future. Unexpected progress in AI could still lead to a so-called robocalypse. But it will have to come from a different kind of AI. What we currently call artificial intelligence – big data and machine learning – is not really intelligent. It is essentially correlation analysis, looking for patterns in data. Machine learning generates predictions, not explanations. In contrast, human brains are storytelling devices generating explanations.

As a result of the hype and hysteria, many governments are scrambling to produce national artificial intelligence strategies. International organisations are rushing to be seen to take action, holding conferencesand publishing flagship reports on the future of work. For example, the United Nations University Centre for Policy Research claims that AI is “transforming the geopolitical order” and, even more incredibly, that “a shift in the balance of power between intelligent machines and humans is already visible”.

This unhinged debate about the current and near-future state of AI threatens both an AI arms race and stifling regulations. This could lead to inappropriate controls and moreover loss of public trust in AI research. It could even hasten another AI-winter – as occurred in the 1980s – in which interest and funding disappear for years or even decades after a period of disappointment. All at a time when the world needs more, not less, technological innovation.

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Many fear about the future of artificial intelligence and robotics. There are multiple factors supporting the claim that AI is in fact not a threat to humankind, but rather an advantage. One factor is that humans thrives off of social interaction and human communication, which robots evidently can’t provide. While online chatbots are a useful and efficient form of artificial intelligence, robots lack the necessary emotional connection to humans. 

In addition, while AI can replace certain human occupations, it also has the potential to increase job opportunities for people in the technology field. Lastly, as seen at Walmart, AI can improve the efficiency of employees without necessarily replacing them. Artificial intelligence is an amazing technological advancement and it isn’t a threat to humankind.

Most humans partake in social interaction countless times per day. Whether it’s speaking with family members, meeting with colleagues or ordering food and drink at a restaurant, social interaction keeps humankind moving forward. A study published in 1997 by Lisa F. Berkman and S. Leonard Syme, discovered that “people who lacked social and community ties were more likely to die in the follow-up period than those with more extensive contacts,” emphasizing the need for social interaction. 

People need social interaction to live long, healthy lives — and artificial intelligence can limit this. While AI can easily replace humans in various customer service jobs, the potential for AI to replace humans in the business world and other occupations based on social interaction is much more limited.

In addition to limiting social interaction, some fear that AI will replace many human jobs. Keith Block, author for The World Economic Forum, explains that advancements in the field of technology have historically created jobs. 

His claim is supported by various examples, such as “the advent of diesel, the internal combustion engine and electricity caused societal disruptions as workers moved from farms to cities, yet these innovations brought us Ford’s Model T, refrigeration, mechanised agriculture and an age of mass production that produced a new global middle class.” 

Keith suggests that while the structure of the job market may change, new jobs surrounding artificial intelligence will likely develop, as has happened in the past.

While AI can pose a targeted threat to white collar jobs, it will eventually spark a new wave of job opportunities once the initiatives are in full swing. Box is an “enterprise content management platform” meaning they deal with “sharing and accessing files,” as well as “data retention and governance.” Due to the relevance of AI in that field, their chief product officer Jeetu Patel discussed artificial intelligence in an interview for Forbes, saying it will “enable workforces to spend more energy on deep thinking versus completing low value tasks like data entry. With work that can be automated, enterprises can redistribute talent resources and gain cost savings.” 

Overall, artificial intelligence will benefit humankind greatly without posing a threat to our society. AI will replace some tedious forms of labor will be replaced in the workplace, developing our society to be higher functioning and more successful. While there are many pros and cons to the integration of AI in the workplace, it will benefit humanity more than it will harm it. 

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There is perhaps one word in today’s techno-vocabulary that drives both interest and concern.  And that’s the four-letter word, data.  It comes in all sizes and shapes and is as ubiquitous as life itself. Whether you know it or not, we manufacture data as a type of human exhaust that creates a physiologic portrait offering rich insights into wellness and disease.

Today, we live at a unique point in human history where data are becoming the new currencies.  Beyond oil, dollars, and social status, our human data are emerging as one of the most powerful and consequential currencies around the globe.  Technology, computer processing, cloud storage, and artificial intelligence are empowering these data to transform zeroes and ones into insightful and even profound realizations that can drive disease detection and longevity.

We all remember the idea of six degrees of separation. Basically, this idea suggests that we are all “friends of friends” with a direct, personal connection to everyone by six or fewer people. Add to that the novelty of “six degrees of Kevin Bacon” and you have a powerful idea that goes viral. Interestingly, that same construct applies to health data—in reverse!  Data, passive data acquisition, and advanced analytics combine to allow us to find the “six degrees of connectivity.”  What once was a disparate set of data points will become surrogates to focused insights on subtle aspects of biochemistry to the social manifestations of behaviors such as addiction.  Connecting just the right dots will reveal levels of connectivity that will impact almost every aspect of humanity—and medicine sits at the forefront of this new reality.

This ability to connect data points—many of which will be easily obtained—results in new data that were once difficult, expensive, or even unobtainable.  For example, the combination of daily steps, heart rate variability during sleep, and the number of times you open and close your refrigerator door could potentially be correlated with the likelihood of becoming obese or diabetic. Our DNA will also provide a vast data set for examination and correlation with physiologic and non-physiologic data to help guide a wide variety of decisions from drug selection to lifestyle modifications.  Similarly, subtle aspects of personal gestures will be analyzed with a simple activity tracker, similar to what’s worn today.  The results will move us far beyond the typical 10,000 steps a day goal to recognize real-time activity such as eating and even smoking. And then, appropriate, time-sensitive interventions can be implemented. What’s really interesting is that insights can be acquired with fewer and fewer data points.  And this allows us to potentially use readily available data to make impactful health-related decisions.  It’s 6, 5, 4, 3 and even 2 degrees of connectivity!

Just as the telescope and microscope revealed blasphemous and transformative perspectives, big data will emerge as the third window into humanity and establish key insights into health.  As data reveal its bold scientific conclusions, one glaring aspect of it all is the shift from reactive medicine to proactive, preventative tactics. From daily steps to DNA, the final truth to the emergence of big data may be less a window to peer into and much more of a mirror that allows us to get a richer and more informed sense of ourselves and our neighbors, and around the world.  Driven by this reality, our contributions to society will expand from the old school perspective of donating time, blood and organs to the exchange of information.  We will become data donors. And it’s this data-driven reality that will become integral to our everyday experience and fundamentally shift the trajectory of human health and wellness.

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Human activity will almost certainly push global temperatures more than 2 degrees beyond pre-industrial levels. Even with aggressive action, some climate scientists are already suggesting it may be too late to reverse course. While there’s plenty of uncertainty in climate science, there’s no good reason to assume anything other than the worst possible outcome. And there’s a lot more certainty in human behavior. We’re short-sighted, fight-or-flight–driven animals. The threat of climate change is too slow, too distant, for the human brain to meaningfully react to it in the here and now.

Climate scientists will keep running studies and modeling solutions that could reduce carbon dioxide levels more aggressively. And we should do that. But even with the most optimistic science out there, we will likely end up with catastrophic consequences on the ground, including widespread war, famine and an onslaught of disease. We need a backup plan like never before.

It’s time for humanity to get serious about getting out of Dodge. Colonization was traditionally a journey of discovery. Today it’s a journey for survival. Of course, the path between our science fiction novels and a serious colonization mission is rife with challenges. One of the most important and pressing today is our need for massive advancements in artificial intelligence. Without AI, humanity’s colonization hopes do not pass “Go.”

Sadly, the essential role that AI plays in our long-term survival is obfuscated by a roaring debate about automation killing jobs in the next five years. The benefits of aggressive investment in AI so dramatically outweigh the costs that the only rational chess move is to triple-down on AI and all of its enabling technologies.

The Chinese government seems to understand this better than the rest of the world. Its AI plan is so bold, so ambitious and so well-funded that most experts acknowledge it has the potential to reshape the geopolitical landscape for generations. Perhaps they understand what many do not: AI won’t just save humanity in the future; it’s doing it now, and it has been doing it for a while.

 HUMANITY’S UNSUNG HERO

NASA is clear that AI is the future of space exploration. The reasons are fairly obvious: Wherever our probes go, they either need to be controlled from Earth, or have some sort of intelligence to guide even the most rudimentary decisions.

Even small decisions that the average person wouldn’t think about, like choosing which areas of a planet are most interesting for taking pictures, are now made by artificial intelligence. The AEGIS system on the Mars rover Curiosity is just one current example, but AI has been playing a role since the early 2000s, when the Spirit and Opportunity rovers used the AutoNav system.

Last year, Google’s machine learning discovered a new planet using NASA’s archived Kepler data. Consider that we’ve been sitting on this data for years, but a neural network was able to discover a planet in mere minutes. Yet right after the announcement of this remarkable achievement, Google felt the need to reassure astronomers worldwide that their jobs were safe: “What we’ve developed here is a tool to help astronomers have more impact,” Chris Shallue said on a conference call about the news. “It’s a way to increase the productivity of astronomers. It certainly won’t replace them at all.”

Imagine that — AI had just massively reduced the time it takes to discover planets, to unravel the mysteries of the universe around us and light a path to a potential future home for our species, and somehow we’re worried about jobs. Even if you count only discoveries made without leaving our planet, we’re in the golden age of space exploration, a time when human knowledge is multiplying, all thanks to basic AI.

AN AI AT EVERY FRONTIER

Many climate scientists have already made the claim that climate change is now a big data problem. AI, of course, is the best technology we have for processing and analyzing massive amounts of data. If you’re holding out hope that we can turn things around on Earth, the answer is pretty simple: We need more, and better, AI.

In 2017, for the first time ever, federal scientists requested funds to accelerate research into climate engineering. They specifically cited two areas of research: removing carbon dioxide from our atmosphere and increasing Earth’s ability to reflect sunlight. This is the stuff of science-fiction novels, and the data analysis and modeling tasks alone are massive and prohibitive, but AI makes it possible to embark on these new paths to scientific discovery.

Environmental science is seeing a similar lift thanks to AI. A recent report from the World Economic Forum cited opportunities to use AI for everything from smart grids to weather modeling and prediction, to biodiversity, agriculture, conservation and ocean health.

If you’re less optimistic about Earth’s prospects, AI is already playing a role in microbiome research, which might hold answers to the most daunting block to long-term human space travel: human physiology. That our immune systems change in space isn’t just an interesting phenomenon — it could mean disaster for a 200- or 300-year colonization mission. NASA has active research projects in this area, and they learned a lot from astronaut Scott Kelly’s year on the International Space Station, such as the power required to safely send and land a heavy craft carrying three years’ worth of supplies for a mission to Mars. But it’s going to come down to AI to accelerate this research.

Consider long-distance space travel and the delays in communication with Houston as spacecraft get farther away from Earth. The farther we want to go, the more dependent our missions are on AI that can make accurate, autonomous decisions in the face of unexpected conditions.

It’s increasingly evident: Whether on Earth or in space, any solution to climate change, fight or flight, begins with AI.

JOBS ARE NOT TOO HIGH A PRICE

Humanity is indeed making a grand bargain with our own technological creations. We surrender to the machines some of our jobs. In exchange, we are given a second chance to make better decisions for future generations.

If you believe the future of the human race depends on our ability to colonize somewhere other than Earth, then you agree that AI will save humanity. If you believe that we can engineer our way out of the climate crisis here on Earth, then you agree that AI will save humanity.

And when you think about what’s at stake, do you really care who or what makes your hamburger?

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Artificial intelligence (AI) is a bigger threat to national security than terrorism, the newly appointed president of one of the world’s oldest science institutions has warned.

Jim Al-Khalili, the incoming president of the British Science Association and professor of physics and public engagement at the University of Surrey, U.K., told The Telegraph the looming dangers of AI trump those posed even by climate change, antibiotic resistance, world poverty, the threat of pandemics or terrorism.

Citing Russian cyber hackers meddling in the 2016 U.S. election, he argued little would stop “cyber terrorists” from forcing their way into AI-controlled infrastructure, such as power grids, transport networks, and military installations.

“I am certain the most important conversation we should be having is about the future of AI,” he said. “It will dominate what happens with all of these other issues for better or for worse.”

Fears that the rise of automation and AI, known as Fourth Industrial Revolution, will endanger jobs is also warranted, he said. His concerns are mirrored by a November 2017 report by the management consulting firm McKinsey, which estimated 50 percent of current work could be automated as soon as 2030.

Al-Khalili is the latest expert to warn against the unregulated rise of AI. In April, a report by the research organization Rand Corporation concluded advances in technology and AI could see humanity speeding towards an international nuclear war.

This rise of such technology could create a dangerous cycle where governments feel obliged to update their nuclear arsenal, while trusting advice from AI machinery which could be flawed or tampered with.

“The fear that computers, by mistake or malice, might lead humanity to the brink of nuclear annihilation has haunted imaginations since the earliest days of the Cold War,” the report read.

“The danger might soon be more science than fiction. Stunning advances in AI have created machines that can learn and think, provoking a new arms race among the world’s major nuclear powers. It’s not the killer robots of Hollywood blockbusters that we need to worry about; it’s how computers might challenge the basic rules of nuclear deterrence and lead humans into making devastating decisions.”

Similarly, venerated physicist Stephen Hawking cautioned AI could destroy civilization before he passed away earlier this year.

“Computers can, in theory, emulate human intelligence, and exceed it,” he said. “Success in creating effective AI, could be the biggest event in the history of our civilization. Or the worst. We just don’t know. So we cannot know if we will be infinitely helped by AI, or ignored by it and side-lined, or conceivably destroyed by it.”

But Subramanian Ramamoorthy, reader in the school of informatics at the University of Edinburgh, disagrees that AI is the biggest threat facing humanity.

He told Newsweek while the popular discourse around AI is heavily driven by major concerns, the technology could also provide benefits that will improve our day-to-day lives.

“Some obviously good applications range from prosthetic and assistive robotic devices that restore the capabilities of the disabled, to predictive models that stabilize and reduce congestion in energy and traffic networks,” he said.

“Closer to home for me, technologies like self-driving cars have the potential to fundamentally change how our cities look and feel for most of us—positively influencing congestion, accessibility and affordability of mobility. Such machines are powered by AI.”

“That said,” he continued, “AI has indeed enabled new forms of issues.

“However, I am not yet convinced that these problems can’t be overcome through careful thinking at the policy level, for which reason I do not yet consider AI to be ‘the biggest challenge facing humanity.’ There are much bigger issues, having to do with people quite independent of technology enabling them.”

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Applying big data analysis to mineralogy offers a way to predict minerals missing from those known to science, where to find them, and where to find new deposits of valuable minerals such as gold and copper, according to a groundbreaking study.

In a paper published by American Mineralogist, scientists report the first application to mineralogy of network theory (best known for analysis of e.g. the spread of disease, terrorist networks, or Facebook connections).

The results, they say, pioneer a way to reveal mineral diversity and distribution worldwide, mineral evolution through deep time, new trends, and new deposits.

Led by Shaunna Morrison of the Deep Carbon Observatory and DCO Executive Director Robert Hazen (both at the Carnegie Institution for Science in Washington, D.C.), the paper’s 12 authors include DCO colleagues Peter Fox and Ahmed Eleish at the Keck Foundation sponsored Deep-Time Data Infrastructure Data Science Teams at Rensselaer Polytechnic Institute, Troy NY.

“The quest for new mineral deposits is incessant, but until recently mineral discovery has been more a matter of luck than scientific prediction,” says Dr. Morrison. “All that may change thanks to big data.”

Humans have collected a vast amount of information on Earth’s more than 5,200 known mineral species (each of which has a unique combination of chemical composition and atomic structure).

Millions of mineral specimens from hundreds of thousands of localities around the world have been described and catalogued. Databases containing details of where each mineral was discovered, all of its known occurrences, and the ages of those deposits are large and growing by the week.

Databases also record essential information on chemical compositions and a host of physical properties, including hardness, color, atomic structure, and more.

Coupled with data on the surrounding geography, the geological setting, and coexisting minerals, Earth scientists now have access to “big data” resources ripe for analysis.

Until recently, scientists didn’t have the necessary modelling and visualization tools to capitalize on these giant stockpiles of information.

Network analysis offers new insight into minerals, just as complex data sets offer important understanding of social media connections, city traffic patterns, and metabolic pathways, to name a few examples.

“Big data is a big thing,” says Dr. Hazen. “You hear about it in all kinds of fields—medicine, commerce; even the US National Security Agency uses it to analyze phone records—but until recently no one had applied big data methods to mineralogy and petrology.”

The network analysis technique enables Earth scientists to represent data from multiple variables on thousands of minerals sampled from hundreds of thousands of locations within a single graph.

These visualizations can reveal patterns of occurrence and distribution that might otherwise be hidden within a spreadsheet.

In other words, big data provides an intimate picture of which minerals coexist with each other, as well as what geological, physical, chemical, and (perhaps most surprising) biological characteristics are necessary for their appearance.

From those insights it’s a relatively simple step to predict what minerals are missing from scientific lists, as well as where to go to find new deposits.

Says Dr. Hazen: “Network analysis can provide visual clues to mineralogists regarding where to go and what to look for. This is a brand new idea in the paper and I think it will open up an entirely new direction in mineralogy.”

Already the technique has been used to predict 145 missing carbon-bearing minerals and where to find them, leading to creation of the Deep Carbon Observatory’s Carbon Mineral Challenge. Ten have been found so far.

The estimate came from a statistical analysis of carbon-bearing minerals known today, then extrapolating how many scientists should be looking for.

Predicted before they were found

“We have used the same kinds of techniques to predict that at least 1,500 minerals of all kinds are ‘missing,’ to predict what some of them are, and where to find them,” Dr. Hazen says.

Says Dr. Morrison: “These new approaches to data-driven discovery allow us to predict both minerals unknown to science today and the location of new deposits.

Additionally, understanding how minerals have changed through geologic time, coupled with our knowledge of biology, is leading to new insights regarding the co-evolution of the geosphere and biosphere. ”

In a test case, the researchers explored minerals containing copper, which plays critical roles in modern society (e.g., pipes, wires), as well as essential roles in biological evolution. The element is extremely sensitive to oxygen, so the nature of copper in a mineral offers a clue to the level of oxygen in the atmosphere at the time the mineral formed.

The investigators also performed an analysis of common minerals in igneous rocks-those formed from a hot molten state. The mineral networks of igneous rocks revealed through big data recreated “Bowen’s reaction series” (based on Norman L. Bowen’s painstaking lab experiments in the early 1900s), which shows how a sequence of characteristic minerals appears as the magma cools.

The analysis showed the exact same sequence of minerals embedded in the mineral networks.

The researchers hope that these techniques will lead to an understanding and appreciation of previously unrecognized mineral relationships in varied mineral deposits.

Mineral networks will also serve as effective visual tools for learning about mineralogy and petrology – the branches of science concerned with the origin, composition, structure, properties, and classification of rocks and minerals.

Network analysis has numerous potential applications in geology, both for research and mineral exploration.

Mining companies could use the technology to predict the locations of unknown mineral deposits based on existing data.

Researchers could use these tools to explain how Earth’s minerals have changed over time and incorporate data from biomarker molecules to show how cells and minerals interact.

And ore geologists hope to use mineral network analysis to lead to valuable new deposits.

Dr. Morrison also hopes to use network analysis to reveal the geologic history of other planets. She is a member of the NASA Mars Curiosity Rover team identifying Martian minerals through X-ray diffraction data sent back to Earth. By applying these tools to analyze sedimentary environments on Earth, she believes scientists may also start answering similar questions about Mars.

“Minerals provide the basis for all our material wealth,” she notes, “not just precious gold and brilliant gemstones, but in the brick and steel of every home and office, in cars and planes, in bottles and cans, and in every high-tech gadget from laptops to iPhones.”

“Minerals form the soils in which we grow our crops, they provide the gravel with which we pave our roads, and they filter the water we drink.”

“This new tool for understanding minerals represents an important advance in a scientific field of vital interest.”

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