Category Archives: Artificial Intelligence

Meet Botlr, a towel-delivering assistant thats already being experimented with at Aloft Hotels. Photograph: Savioke

In the battle for the 21st century workplace, computers are winning. And the odds of us puny humans making a comeback are not very good.

A January 2017 report from the McKinsey Global Institute estimated that roughly half of todays work activities could be automated by 2055, give or take 20 years. (McKinsey helpfully offers a search portal to find out how likely youll be given the boot by a bot.)

Bottom line is robots want our jobs. And no one is going to build a wall around them or tariff them out of existence.

In a way this is nothing new. Technology has been replacing human labor since the invention of the wheel. Typically, though, machines have stepped in to perform relatively low-skill, low-wage, highly repetitive work. The least digitizable jobs have belonged to recreational therapists, members of the medical profession, social workers, teachers, and managers. The reason: computers are not yet as good as humans at things like personal interaction and off-the-cuff decision making.

But thats changing.

Thanks to advances in artificial intelligence, natural language processing, and inexpensive computing power, jobs that once werent considered good candidates for automation suddenly are.

For example, a decade ago researchers thought the complexity of navigating an automobile around obstacles and through traffic was beyond the reach of silicon. Now virtually every auto maker (as well as companies like Apple) is working on a driverless car.

The number and types of jobs that computers can do has expanded enormously in just a few years, ranging from the predictable to the absurd.

The tasks least likely to be replaced by a computer, according to a widely cited 2013 Oxford study on job digitization, are those requiring the highest degrees of social and creative intelligence. But even there the digitized writing is on the LCD wall.

For years, computers have been creating art, music and literature just usually not very good art, music and literature. Robot poetry and computer-generated music have become genres unto themselves, but so far theyve failed to have much impact on the already dismal employment prospects for human poets and musicians. Last February, the first algorithmically authored musical, Beyond the Fence, debuted in Londons West End though to less than stellar reviews.

Still, there are glimmers of a future where algorithms and artists compete head to head. The winner of the 2016 RobotArt competition, National Taiwan Universitys TAIDA, creates pointillist-style compositions that would not look out of place hanging next to a Seurat.

Last April, a computer-generated novel titled, appropriately enough, The Day a Computer Writes a Novel, was in the running for Japans Hoshi Shinichi Literary Award. The judges were unaware the book was produced via AI.

Kulitta, music composition software written by Yale computer science lecturer Donya Quick, has fooled musical sophisticates into thinking its original phrases were composed by Johann Sebastian Bach, according to a report in Yale News.

Are all of these people capable of acquiring new skills? And even if they are, do they want to do it?

But for the time being or at least until algorithms learn how to suffer for their art humans will continue to have the upper hand when it comes to creativity.

Highly creative jobs are probably pretty safe for a while, says Tom Davenport, co-author of Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. There have been a few attempts to have computers write screenplays and TV scripts, and they have been uniformly horrible thus far.

There are other hopeful signs.

Instead of being replaced wholesale, most people in high-skill positions will likely find themselves working alongside their inanimate colleagues, not unlike the way we use computers instead of typewriters and calculators. McKinsey estimates that 60% of todays occupations have at least some portion that can be automated.

This is already happening in fields such as medicine, law and banking. When not writing cookbooks or kicking ass at Jeopardy, for example, IBM Watson is helping doctors diagnose medical conditions and analyze MRIs. Electronic discovery platforms such as Symantecs eDiscovery and Kroll Ontrack help attorneys sift through thousands of documents in a few hours. And AI-driven services such as FutureAdvisor or Wealthfront help consumers make investment decisions, freeing up human financial advisers to work on more high-net-worth accounts.

Davenport says there are five paths for surviving in a workplace dominated by robots. You can move up in the organizational chain to monitor the computers work or make high-level decisions about what to computerize. You can focus on parts of your job computers arent good at, or find a new career where computers are less likely to dominate. Finally, he says, you can choose to work on creating the technology that will automate the 21st century.

Michael Jones, assistant professor of economics at the University of Cincinnati, believes the problem of displaced workers can be overcome with education and training though what positions workers should be trained to fill is not entirely clear. No one knows what new jobs will look like in 10 or 20 years, just as no one anticipated the position of drone repair technician in the 1990s.

Automation can not only create advantages for society as a whole but also for individual workers, if they can retool their skills and use technology to complement their job, not replace it, Jones says. But are all of these people capable of acquiring new skills? And even if they are, do they want to do it?

Jones adds that traditional vocations like plumbers, electricians, and carpenters are likely to be less affected by digital disruption. And while easily automated jobs will be increasingly rare, they probably wont go away entirely, says JP Gownder, vice-president and principal analyst for Forrester.

I believe for the most part people value the human touch, but it may become a bit of a luxury good, he says. Imagine a world 15 or 20 years from now where most people get their manicures from robots. Rich people might still want to get one from a real person.

And if you happen to be one of the unlucky millions who lose their job to an algorithm? A robot recruiter such as Entelo or Gild might be able to help you find a new one.

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Actors, teachers, therapists think your job is safe from artificial intelligence? Think again - The Guardian

In June last year a fascinating aerial battle took place.It didnt take place in the actual skybut rather in the virtual one, which was appropriate considering it was a battle of man against machine.

The man in question wasnt an ordinary pilotbut a retired US Airforce pilot, Gene Lee, with combat experience in Iraq and a graduate of the US Fighter Weapons School.The machine he was battling was a simulated aircraft controlled by an artificial intelligence (AI).

What was surprising about the outcome was that the artifical AI emerged as the victor.What was more surprising was that the computer running the software wasnt a multimillion dollar supercomputerbut one that used about $35 worth of computing power.

Welcome to the fast-moving world of AI.

Its an area that has attracted significant media focus, and justifiably so.Experts in the field see the deployment of AI as the dawn of a new age.Andrew Ng, chief scientist at Baidu Research, is one of the gurus in the field.

AI is the new electricity, he says. Just as 100 years ago electricity transformed industry after industry, AI will now do the same.

Most of the current applications of AI focus on recognising patterns.Software is "trained"with vast amounts of information, usually with help from people who have manually tagged the data.In this way, an AI may start with images that have been labelled as cars, then, through trial and error guided by programmers, eventually recognise images of cars without any intervention.

Extraordinary breakthroughs This simple explanation of AI belies the extraordinary breakthroughs achieved with this approachand is illustrated by an experiment conducted by an English company called DeepMind.

In 2015,DeepMind revealed that its AI had learned how to play 1980s-era computer games without any instruction. Once it had learned the games, it could outperform any human player by astonishing margins.

This feat is a stark contrast to the battle waged almost two decades ago when an IBM computer beat Russian grandmaster Gary Kasparov at chess in the mid-1990s. To beat him,the computer relied on a virtual encyclopaedia of pre-programmed information about known moves. At no point did the machine learn how to play chess.

Winning simple computer games clearly wasnt enough to prove the abilities of DeepMind, so a more challenging option was found in the game called Go.Its an incredibly complex Asian board game with more possible moves than the total number of atoms in the visible universe.

To learn Go, the AI played itself more than a million times. To put this in perspective, if a person played 10games a day every day for 60years, they would only manage to play around 180,000 games.

Despite the bold predictions of expert Go players, when the tournament ended in 2015, it was the DeepMind AI that had beaten one of the worlds best players.

The ability to "learn"can be easily leveraged into the real world.While gaming applications may excite hard-core geeks, DeepMinds power was unleashed on a more useful challenge last year increasing energy efficiency in data centres.

By looking at the information about power consumption such as temperature, server demand and cooling pump speeds the AI reduced electricity requirements for a Google data centre by an astonishing 40%. This may seem esotericbut around the world data centres already use as much electricity as the entire UK.

Potential implications Once you start to consider the power of AI, the feeling of astonishment evaporates and is replaced with an unsettling feeling about the potential implications.For example, at the end of last year a Japanese insurance company laid off a third of one of its departments when it announced plans to replace people with an IBM AI. In this example, only 34 people were made redundantbut this trend is likely to accelerate.

At this stage, its useful to put this development in contextand consider what jobs might be replaced by AI.Andrew Ng has a useful rule of thumb If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.

Whats important about this quote is the term near future. Once you extend the timeline out longer, researchers have theorised that the implications of AI on the workforce are significant. One study published in 2015 estimated that across the OECD an average of 57% of jobs were at risk from automation.

This number has been disputed heavily since it was publishedbut it doesnt really matter what the exact percentage will be.What is important to keep in mind is that AI will change the nature of jobs forever, and its highly likely that work in the future will feature people working alongside machines. This will result in a more efficient workforce, which will in turn likely to lead to job losses.

However, its not just the workforce that could change.The potential for this technology dwarfs anything humans have ever invented, and, just like the splitting of the atom, the jury is out on how things will develop.

One of the worlds experts on existential threats to humanityNick Bostrom at Oxford University surveyed the top 100 AI researchers. He asked them about the potential threat that AI poses to humanity, and responses were startling. More than half of them responded that they believed there is a substantial chance that the development of an artificial intelligence that matches the human mind wont end up well for one of the groups involved. You dont need to work alongside an AI to figure out which group.

The thesis is simple Darwinian theory applied to the biological world leads to the dominance of one species over another. If humans create a machine intelligence, probably the first thing it would do is re-programme itself become smarter. In the blink of an evolutionary eye, people could become subservient to machines with intelligence levels that were impossible to comprehend.

The exact timeframe for this scenario is hotly debated, but the same experts polled by Bostrom thought that there was a high chance of machines having human-level intelligence this century perhaps as early as 2050.

To paraphrase a well-worn clich, we will live in interesting times.

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Keeping an eye on artificial intelligence - The National Business Review

Your Alpha Doggs editor is Bob Brown, Network World Online Executive Editor, News.

Network World | Feb 8, 2017 2:03 PM PT

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Activity on the tech labs front is happening faster than we can get to it these days, so here are a few "in case you missed it" items...

The state of Ohio, JobsOhio and the Ohio State University are putting $45 million into an expansion of the Transportation Research Center's (TRC) 540-acre Smart Mobility Advanced Research and Test (SMART) Centerin the Columbus area. Research will focus both on connected and driverless vehicles within this section of the 4,500-acre TRC expanse.

This first phase of SMART expansion will include the industry's largest high-speed intersection, an urban network of intersections (i.e., roundabouts, or what we in the Northeast call rotaries), a rural network that includes wooded roads and a neighborhood network for slower speeds.

MORE: 10 cool connected car features

TRC provides the largest independent vehicle testing facility in North America, according to TRC CEO Mark-Tami Hotta.

Research at TRC goes hand-in-hand with research elsewhere in Ohio, including along a Smart Mobility Corridor between the TRC and Columbus that has been primed with fiber-optic cabling and sensors that were enabled through previous funding. New tech can be tested in real-life traffic situations there, according to JobsOhio, which notes two additional smart highway projects are now being funded, too.

These labs are going to have quite the name to live up to. Lexalytics, a Boston-based text analytics software and services provider, has established what it's calling Magic Machines AI Labs with the University of Massachusetts Amherst's Center for Data Science and Northwestern University's Medill School of Journalism, Media and Integrated Marketing Communications.

At UMass (which counts Lexalytics CEO Jeff Catlin among its grads), Lexalytics will work with faculty and students in areas such as analyzing, visualizing and exploiting data, and overall, making the AI building process easier. Lexaytics has specialized in handling unstructured data, but is no slouch on the structured side either.

At Northwestern, Lexalytics will look to identify and test real-world applications for Magic Machines AI technologies. Perhaps frighteningly, they'll be looking to advance ways marketers can use AI in their jobs.

Research at the labs will fall into categories such as swarm intelligence/emergent behavior, adaptive AI, transfer learning and meta-learning (see fuller explanations at the Magic Machines AI Labs website).

Speaking of UMass Amherst, the school is boasting of its new cluster of 400 graphics processing units (GPUs), which it says should attract a slew of Ph.D. students and researchers in areas such as AI, computer vision and natural language processing.

The cluster, which will process huge data sets via neural network algorithms, is housed at the Masachusetts Green High Performance Computing Center in Holyoke, Mass., and was enabled by a five-year $5M grant from the state and the Massachusetts Technology Collaborative last year. That grant represents a one-third match to $15M in funds from the MassMutual Foundation for data science and cybersecurity research.

The "Gypsum" cluster of GPUs is installed on 100 computer nodes, with storage and backup systems, and will be used for deep learning research on a variety of applications.

MORE: Open-source oriented RISELab emerges at UC Berkeley to make apps smarter & more secure

Bob Brown is a news editor for Network World, blogs about network research, and works most closely with our staff's wireless/mobile reporters. Email me at bbrown@nww.com with story tips or comments on this post. No need to follow up on PR pitches via email or phone (I read my emails and will be in touch if interested, thanks)

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In the Labs: Connected vehicles in Ohio, artificial intelligence in Illinois and Massachusetts - Network World

Tech giant rolls out new software which crams its virtual assistant inside the LG Watch Style and Watch Sport

Google has unveiled the second generation of its smartwatch software, which will place artificial intelligence (AI) in the companys wearables for the first time.

Android Wear 2.0, which will begin rolling out to all current Android Wear smartwatch users in the coming weeks as an update, will include Google Assistant, the tech giants AI virtual helper which responds to voice commands.

PA:Press Association

Google also revealed the first two new devices that would run the software the LG Watch Style and Watch Sport as the tech giant looks to take on the Apple Watch.

While traditional watches tell the time, Android Wear watches make the most of your time, Android Wears engineering chief David Singleton said.

In an instant, you can check when and where youre meeting a friend, whether youll need an umbrella tonight, or how many minutes youve been active today-all without reaching for your phone.

Today, were launching Android Wear 2.0 to give you watch faces that do more, better ways to work out, more ways to stay in touch, new ways to use apps, and on-the-go help from Google Assistant.

As part of the Google Assistant integration, users will be able to add items to their shopping lists, set reminders and make restaurant reservations directly from their watches.

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Google Android Wear 2.0 update puts artificial intelligence inside your wristwatch - The Sun

It has become common practice for attackers to use Artificial Intelligence (AI) and Machine Learning (ML) to link tools together so that they can be run in parallel when conducting an attack.

Attackers use AI and ML to take the results from one tool and then allow the other tools to "learn" about the finding and use it against other systems. As an example, if a one tool finds a password, that tool can feed the information to another tool or bot that may conduct the exploitation of one or many systems using the discovered password.

AI and ML allows for an attacker to program a toolset or bot to act like a "real" attacker. As an example, the tool or bot may launch a phishing attack against an organization and then take the results of the phishing tool and conduct other types of attacks just as a human would.

Attackers are building toolsets and bots that use AI and ML techniques to evade detection and blocking the methods already in place within most organizations. Many of these tools (typically open source) can be easily obtained from the Internet. This gives anyone the ability to run the tools against target organizations.

In an article in Wired President Obama expressed his concerns about AI-enabled bots attacking nuclear weapon silos and causing a launch. This intimates that the threat of AI and ML enhanced attacks are a major concern even at the highest level of government.

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How criminals use Artificial Intelligence and Machine Learning - BetaNews

Baidu, the largest search engine in China, has confirmed it will dissolve its healthcare department to focus on introducing artificial intelligence (AI) into this area, Sina Technology reported on Thursday.

Two programs will be added to its AI arm Thumb Doctor andIntelligent Little e. Thumb Doctor is an online platform where real experts answer peoples questions about medical symptoms, while Intelligent Little e is a chatbot project that helps provide instant diagnoses.

The content production team will move into the search engine department. While the rest of the business in the former healthcare department will be shut down, according to a company announcement released on Thursday at noon.

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Axing the department doesnt mean Baidu will stop exploring the field of medical care, Li Yanhong, the CEO of Baidu, said during a Q&A session at the China Entrepreneurs Forum that opened on Wednesday night, officially acknowledge the change. Baidu is aiming to participate in more upstream areas, like gene detection and new drugs R&D.

With big potential in the medical care market on the horizon, Baidus shift into more upstream areas depends on artificial intelligence, says Li.

Li shared his understanding of how AI technology could combine with medical care at the 3rd World Internet Conference in November last year.

According to Li, the first level of this combination is the O2O (or online to offline) intelligent queuing system. This means people make a hospital appointment online, which eliminates the need to queue for hours to register with a doctor. The second level is an intelligent diagnostic system, which allows a chatbot to analyze symptoms to help doctors make better diagnoses.

Baidu Doctor, an app developed by the company in 2015, already offers appointment bookings and self-diagnosis. It seems the company is already heading toward the third and fourth level, which, as Li said, is precision medicine based on gene analysis and new drugs R&D.

Li thinks artificial intelligence will play an important role in analysing the result of gene sequencing, so as to help identify rare and common diseases in advance. The technology is also expected to simulate the efficacy of new drugs, so as to lower the cost and period of R&D.

However, medical care has been a sensitive sector for the search engine giant since the death of Wei Zexi in April 2016.

Wei was a 21-year-old college student who died after receiving experimental treatment for a rare form of cancer (synovial sarcoma) at a hospital he learned about from a promoted search result on Baidu.

The company has since been criticized for its pay-for-placement results that had influenced Weis medical choices and delayed proper treatment.

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Baidu cut its healthcare business to concentrate on artificial intelligence - Asia Times

Artificial intelligence is already well-established in the world of targeted advertising and recommendations. But AIis also rapidly evolving on social media as a way to help brands quickly and efficiently discover, engage with, and learn from their followers.

Although there is no one definition for it, we can summarize social artificial intelligence as a form of collecting and sifting through customer history, user-generated content, and data from social media channels to generate more relevant content and, as a result, a more meaningful experience for followers.

Social AI has the ability to provide a better social experience overall. For an example of what social AI can do, we just have to look at Facebook. The social network has already incorporated artificial intelligence as part of the platform in many innovative ways. From automatic face tagging to the stories that appear in News Feeds, Facebook has been at the forefront of what AI can do for social media by incorporating a variety of AI technologies that help continuously improve the Facebook user experience.

Were now seeing more and more social networks investing in social AI technologies, and although the technology is still relatively young, many remarkable new ways to surface content to audiences have emerged. Yet despite the groundbreaking opportunities social AI presents, many brands have yet to turn to social AI to help engage their audiences, target new customers, and analyze the enormous volumes of social data that is now accessible.

So to help uncover what social artificial intelligence can do, heres a look at some of the exciting opportunities it brings to the table for those in the social media marketing world and how marketers can keep an eye on this trend.

Rather than viewing social AI as a potential threat to the jobs of social media marketers everywhere, John Hagel of Deloitte suggests the new wave of technology could actually be an exciting opportunity for brands to free up their time for more real, creative work. If we allow machines to take care of all of the picayune, everyday tasks that machines can take care of (such as recommendations and customer support), then marketers can have more time to focus on the creative side of their campaigns.

The technology that seems so threatening now may actually become our ally, amplifying our performance improvement by freeing us from the tasks that today keep us tightly locked into the routines of the past and providing us with the data we need to spark even more imagination and creativity, says John Hagel, co-chairman for Deloittes Center for the Edge.

For brands publishing multiple new stories or posts per day, automating a significant portion of those messages can free up time for creating more substantial content and monitoring responses. The New York Times did just this with achatbot that automates some of the 300 messages it posts to its social media pages daily.

The intelligent bot helps predict how stories will perform on social media, as well as suggests which stories editors should boost or promote. An analysis of the campaign found that the posts generated by the chatbot received almost 380 percent more clicks. For marketers seeking to keep engagement levels up while keeping the numbers of hours spent creating content down, this can be a good way to do so.

There are a number of facial recognition technologies, but Facebook took its algorithm to the next level with AI. With its enormous database of images,Facebooks algorithm is constantly improving through machine learning. Every time someone tags a photo, it is added to a huge, user-driven wealth of knowledge that helps advance the entire facial recognition algorithm. According to Facebook, it is able to accurately identify a person 98 percentof the time.

Such facial recognition on a wider scale could have many applications for a brands social strategy. Andy Pringle, head of performance media at digital marketing agencyPerformics, points out just how brands will be able to target followers with facial recognition technology:

You can imagine brands asking people to give permission to be recognised in return for offers while theyre out and about. Say, theres a guy waiting for a bus for ages in front of digital screen running a beer campaign. If that person likes that brand on Facebook you can foresee either the screen saying hi and giving him or her a voucher code for a free beer or triggering a voucher to be delivered to their Facebook inbox.

Its highly unlikely that AI will ever replace all engagements on social media after all, the point of social media is human interaction. But it does give brands the ability to automatically surface the most valuable, important conversations to respond to or engage with.

According to Eli Israel, the founder of Meshfire, a platform that uses AI to assist with social media, the workloads of social media managers have hit an all-time high. Social media teams have been assigned an overwhelming number of tasks that go beyond simple content creation they are required to perform a certain level of customer service as well. Unfortunately, customer support has become a major time suck. He suggests a number of ways social AI can help social media teams alleviate the pressures of providing instant support in order to spend their time much more effectively, including:

Increased investments and resources are being allocated to the advancement of social AI technology to revolutionize social media and a brands role in it. The intersection of social media and AI also presents many new opportunities for social media marketers to shine. To prepare for this new age, Forrester discussed a number of recommendations on how marketers can adapt. And while they mostly refer to the surge in chatbots, the advice can also be applied to adapting to social AI.

As Forresterput it, being human, helpful, and handy is key. The traditional marketer role of pushing content must be readjusted to focusing more on two-way conversations. AI will guide the conversations in the beginning, but humans must step in for the actual engagements.

Marketers must also accept that they will need to serve customers in real time. Instant responses are now expected on social media, and these expectations will only solidify over the next year. Making sure your team is set up internally to handle rapid turnarounds on social media, and implementing automated response technology if needed, will ensure your brand is prepared to deal with these customer expectations in both the short and long term.

There are a number of ethical dilemmas that surround artificial intelligence. Questionable trending algorithms and fake news are just two examples of the side effects weve seen so far. Even though these have created problems more for publishers than for actual brands on social media, its still important to follow these stories as artificial intelligence applications carry over into the marketing world.

The amount of research being put out is still limited, so following the top AI thought leaders who are discussing the intersection of AI and social media is a good way to stay on top of this trend. IBM omnichannel marketer Amber Armstrong, speaker and brand consultant Tamara McCleary, and Marshall Kirkpatrick are just a few people social discovery platformLittle Bird identifies as the best social media thought leaders to follow in this space.

Social AI will constantly change as it further develops, but keeping a close eye on this trend is a good place for marketers to start. There wont ever be a complete substitute for human engagement, but social AI definitely has the potential to be a means to the end goal of social media marketing, which is to truly understand your followers.

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What 'social artificial intelligence' means for marketers - VentureBeat

Forbes

Actress Kristen Stewart's Research Paper On Artificial Intelligence: A Critical Evaluation Forbes There are perhaps two different questions to answer here: (1) What do we think of the paper? (2) What do we think of the headlines that the paper generated? Let me address the second question first, because I think that is the root of the (possible ...

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Actress Kristen Stewart's Research Paper On Artificial Intelligence: A Critical Evaluation - Forbes

Forbes

Artificial Intelligence-Driven Robots: More Brains Than Brawn Forbes Automation and robots for manufacturing have come a long way since Unimate was introduced in the 1960's. The machines that manufacturers are using today are smaller, safer and able to perform more than a single task without expensive programming.

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Artificial Intelligence-Driven Robots: More Brains Than Brawn - Forbes

"The acceptance of AI in the business is going to involve an evolution."

There's plenty of excitement around artificial intelligence: analyst Gartner places it at the top of its top 10 strategic technology trends for 2017. The analyst says the technology has reached a tipping point and AI is beginning to extend its tentacles into every service, thing, or application, and that it will become the primary battleground for technology vendors looking to make money through 2020.

Interim CIO Christian McMahon, who is managing director at transformation specialist three25, acknowledges interest in AI has exploded recently, but he also voices a word of caution.

AI and the Future of Business

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of them.

"All the major corporates, accelerators and venture capitalists are desperate to find a foothold," he says. "However, I don't think the current AI market is at a stage where breakthrough technologies are about to be unveiled. Rather, it's a vibrant market which seems more conceptual than one of tangible substance."

It is a sentiment that chimes with Omid Shiraji, interim CIO at Camden Council. His organisation holds a huge amount of data and aims to use its knowledge to help people with complex needs. AI could provide a breakthrough in data insight, yet Shiraji says CIOs must focus on value creation.

"The business case for these projects is not easy -- you can take a step into the unknown," says Shiraji. "You sometimes have to rely on intuition rather than ROI to place your investments in these types of projects."

Gartner suggests executives who take a risk on AI projects will be rewarded and should consider experiments in one or two high-impact scenarios. So how will pioneering organisations build a business case for AI? Two IT leaders -- one each from the private and public sectors -- give us their take.

Sizing up the opportunity

Matt Peers, CIO of global law firm Linklaters, draws a parallel between the use of big data and the growing importance of AI. Peers says success in big data is all about being able to make the best use of the information you possess -- and Linklaters, a 175-year-old firm, is a business with more knowledge than most.

Peers says his organisation should be able to turn its history into a competitive advantage. Lawyers need knowledge about legal precedent, previous projects, and internal skills specialisms. He believes advances in AI will help his firm to create more sophisticated approaches to search.

"The key to success is getting the right information to people quickly," he says. "Some of the tools that are being developed for AI will help us search big data. Most of the technologies on the market today are good at clustering and reading contracts, and enabling you to search vast volumes of data for legal themes."

He expects the ability to digitise and search contracts for key legal themes to become commonplace very quickly. Linklaters has already created an AI working group to help analyse services in the marketplace and to work out how these technologies might impact the business.

"Firms in some key sectors are already making a move," says Peers. "We've spent a lot of time in the past 18 months sizing up the opportunities by talking to people, seeing demonstrations, and running proof of concept studies."

Peers recognises AI could also help change the way lawyers work, yet he also expects a cultural challenge. Senior partners trust their associates to spend hours considering the details of legal documents. Trusting computers to undertake the same task in seconds presents a different form of dependence.

"It's a big shift because the reputation of that lawyer and firm is on the line," he says. "The acceptance of AI in the business is going to involve an evolution. It's important to remember that there are many matters in the legal world where AI is not going to be useful for quite a long time. It's going to take a while for computers to provide trusted advice and opinion."

Using data to save lives

Toby Clarke, interim head of IT at Moorfields Eye Hospital NHS Foundation Trust, says AI will have a huge impact on the work of publicly-funded organisations. Moorfields has been working closely with DeepMind Research, a project that involves the Trust sharing a set of one million anonymised eye scans.

The project between Moorfields and DeepMind relies on historic scans, meaning that while the results of the research might be used to improve future care, they will not affect patients today. However, the hope is that discoveries through the initiative will lead to earlier detection and help reduce preventable eye disease.

"What they're doing with that information is truly amazing," says Clarke, referring to the DeepMind project. "It's cutting edge and will make a significant difference."

He says the key to long-term change through AI is being able to use information to inform patient care. And that use presents challenges, particularly in terms of data security and confidentiality. "The real value will come from using non-anonymised data," he says.

"If you have a large repository of information, and you can add big data from demographics, you can start to take make predictions about patient healthcare. You could potentially say when people should be coming in for tests in terms of early warnings."

The current project uses anonymous data. "It has to be that way," says Clarke. "In terms of healthcare, there will always be issues around how you commercialise data, and how you deliver value back to the host organisation and its patients."

Clarke, however, is keen to point out that similar projects could sponsor significant change. "It's difficult for humans to understand the impact of AI right now but the potential is huge," he says. "The technology self-learns and I find it exceptionally exciting. AI is different and new, and it's something everyone involved in IT should be investigating."

In contrast to reports that automation simply leads to job cuts, Clarke says AI - particularly in the role of predictive medicine - could lead to a whole new range of data science roles. "It's not about removing jobs but it is potentially about saving lives," he says.

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Artificial intelligence: How to build the business case - ZDNet