Daily Archives: February 15, 2017

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What impact will artificial intelligence (AI) have on the workforce? Will smart machines really replace a large number of people in a variety of jobs?

10 types of enterprise deployments

As businesses continue to experiment with the Internet of Things, interesting use cases are emerging. Here are some of the most common ways IoT is deployed in the enterprise.

These questions have been on the minds of a lot of people of late -- especially as AI becomes even more advanced. Clearly the technology will take away the need for some functions that are now performed by humans. But there's good reason to believe that AI will actually create a lot of new jobs as well -- at least in some areas of the economy.

"For information workers, the near-term opportunity is to leverage machine learning and natural language processing to make sense of a disconnected and cacophonic set of information sources, so people can focus on what matters most to them," said David Lavenda, vice president of product strategy at mobile-enterprise collaboration company Harmon.ie, who does academic research on information overload in organizations.

AI automation now is best geared toward specific, highly-contextual tasks, Lavenda said. "In the consumer world, we are seeing things like customer service bots," he said. "But information workers typically operate in a broad range of tasks and responsibilities. Without a definite context, AI will struggle to make decisions independently."

For example, IBM is focusing Watson's AI capabilities on highly-contextual business cases such as evaluating health studies and helping doctors make decisions.

Still, organizations and individuals need to prepare for the growing role of AI in the workplace.

"The trick is to make it easier for workers to consume the increasing amount of disconnected information, not make them learn new skills," Lavenda said. "People want to focus on the business, not on learning new technology. If anything, the promise of AI is that people won't have to know more IT skills to be effective."

The focus on AI in the enterprise should be on making workers' lives simpler, not more difficult, Lavenda said. "People are already inundated by continuous new software and gadgets," he said. "They just can't keep up. The future lies in hiding complexity, not introducing new complexity."

Some industries are feeling the impact of AI sooner than others. For instance, healthcare is already seeing an impact from IBM's AI-based Watson technology, Lavenda said. "Since AI is a horizontal technology, it will appear first in industries where suppliers identify key use cases," he said.

One promising use case Lavenda cites is helping salespeople close more business by connecting disconnected information from sources such as Salesforce, Zendesk, SharePoint, email, Yammer, and Chatter into one coherent picture of what's happening with their business. "Without having to learn any new skills or install new apps, AI-based solutions can present this information in a coherent fashion right within email or within a document window, so that salespeople can focus on closing business, not using technology," he said.

Long term, there is no doubt that AI will impact jobs. "Like in the past, all new technology displaces professions," Lavenda said. "We don't have many telegraph or telephone operators today, to say nothing of keypunch data entry clerks. Yet new technologies bring new opportunities, and at least so far the new technologies increase the number of job opportunities, not lessen them."

How artificial intelligence is changing the data center:

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Artificial intelligence doesn't have to be a job killer - ZDNet

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Artificial Intelligence Is Becoming A Major Disruptive Force In Banks' Finance Departments Forbes A combination of elements including massive distributed computing power, the decreasing cost of data storage, and the rise of open source frameworks is helping to accelerate the application of artificial intelligence (AI). Our own research indicates ... Will Big Data Influence Artificial Intelligence as a Major Disruption?insideBIGDATA These Companies Are Banking on AI to Raise ProductivityEntrepreneur all 3 news articles »

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Artificial Intelligence Is Becoming A Major Disruptive Force In Banks' Finance Departments - Forbes

Predicting earthquakes is the holy grail of seismology. After all, quakes are deadly precisely because theyre erraticstriking without warning, triggering fires and tsunamis, and sometimes killing hundreds of thousands of people. If scientists could warn the public weeks or months in advance that a large temblor is coming, evacuation and other preparations could save countless lives.

So far, no one has found a reliable way to forecast earthquakes, even though many scientists have tried. Some experts consider it a hopeless endeavor. Youre viewed as a nutcase if you say you think youre going to make progress on predicting earthquakes, says Paul Johnson, a geophysicist at Los Alamos National Laboratory. But he is trying anyway, using a powerful tool he thinks could potentially solve this impossible puzzle: artificial intelligence.

Researchers around the world have spent decades studying various phenomena they thought might reliably predict earthquakes: foreshocks, electromagnetic disturbances, changes in groundwater chemistryeven unusual animal behavior. But none of these has consistently worked. Mathematicians and physicists even tried applying machine learning to quake prediction in the 1980s and 90s, to no avail. The whole topic is kind of in limbo, says Chris Scholz, a seismologist at Columbia Universitys LamontDoherty Earth Observatory.

But advances in technologyimproved machine-learning algorithms and supercomputers as well as the ability to store and work with vastly greater amounts of datamay now give Johnsons team a new edge in using artificial intelligence. If we had tried this 10 years ago, we would not have been able to do it, says Johnson, who is collaborating with researchers from several institutions. Along with more sophisticated computing, he and his team are trying something in the lab no one else has done before: They are feeding machinesraw datamassive sets of measurements taken continuously before, during and after lab-simulated earthquake events. They then allow the algorithm to sift through the data to look for patterns that reliably signal when an artificial quake will happen. In addition to lab simulations, the team has also begun doing the same type of machine-learning analysis using raw seismic data from real temblors.

This is different from how scientists have attempted quake prediction in the pastthey typically used processed seismic data, called earthquake catalogues, to look for predictive clues. These data sets contain only earthquake magnitudes, locations and times, and leave out the rest of the information. By using raw data instead, Johnsons machine algorithm may be able to pick up on important predictive markers.

Johnson and collaborator Chris Marone, a geophysicist at The Pennsylvania State University, have already run lab experiments using the schools earthquake simulator. The simulator produces quakes randomly and generates data for an open-source machine-learning algorithmand the system has achieved some surprising results. The researchers found the computer algorithm picked up on a reliable signal in acoustical datacreaking and grinding noises that continuously occur as the lab-simulated tectonic plates move over time. The algorithm revealed these noises change in a very specific way as the artificial tectonic system gets closer to a simulated earthquakewhich means Johnson can look at this acoustical signal at any point in time, and put tight bounds on when a quake might strike.

For example, if an artificial quake was going to hit in 20 seconds, the researchers could analyze the signal to accurately predict the event to within a second. Not only could the algorithm tell us when an event might take place within very fine time boundsit actually told us about physics of the system that we were not paying attention to, Johnson explains. In retrospect it was obvious, but we had managed to overlook it for years because we were focused on the processed data. In their lab experiments the team looked at the acoustic signals and predicted quake events retroactively. But Johnson says the forecasting should work in real time as well.

Of course natural temblors are far more complex than lab-generated ones, so what works in the lab may not hold true in the real world. For instance, seismologists have not yet observed in natural seismic systems the creaking and grinding noises the algorithm detected throughout the lab simulations (although Johnson thinks the sounds may exist, and his team is looking into this). Unsurprisingly, many seismologists are skeptical that machine learning will provide a breakthroughperhaps in part because they have been burned by so many failed past attempts. Its exciting research, and I think well learn a lot of physics from [Johnsons] work, but there are a lot of problems in implementing this with real earthquakes, Scholz says.

Johnson is also cautiousso much so that he hesitates to call what he is doing earthquake prediction. We recognize that you have to be careful about credibility if you claim something that no one believes you can do, he says. Johnson also notes he is currently only pursuing a method for estimating the timing of temblors, not the magnitudehe says predicting the size of a quake is an even tougher problem.

But Scholz and other experts not affiliated with this research still think Johnson should continue exploring this approach. Theres a possibility it could be really great, explains David Lockner, a research geophysicist at the U.S. Geological Survey. The power of machine learning is that you can throw everything in the pot, and the useful parameters naturally fall out of it. So even if the noise signals from Johnsons lab experiments do not pan out, he and other scientists may still be able to apply machine learning to natural earthquake data and shake out other signals that do work.

Johnson has already started to apply his technique to real-world datathe machine-learning algorithm will be analyzing earthquake measurements gathered by scientists in France, at Lawrence Berkeley National Laboratory and from other sources. If this method succeeds, he thinks it is possible experts could predict quakes months or even years ahead of time. This is just the beginning, he says. I predict, within the next five to 10 years machine learning will transform the way we do science.

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Can Artificial Intelligence Predict Earthquakes? - Scientific American

As organizations plan their customer strategies they foresee an onslaught of customer interactions coming their way. The fallacy of believing that adding self-service options will decrease customer requests is now known. When your organization opens channels for customer to interact with you, even with self-service options, customers will interact with you more. This engagement is a good thing. But the only way to handle all of your volume in an effective manner without adding more staff is by leveraging Artificial Intelligence.

Listening to John Pisarek of Interactionsat Call Center Week Winterthe scenario of about projecting more customer interaction volume and not getting additional staff to handle it is a common reality for many contact center leaders.

And its a worry and issue across the industry. In the 2016 Global Contact Center Benchmark Report by Dimension Data67.8% of contact center leaders project an increase in overall interaction volume. How many of those 67.8% do you think have been provided an increase in staffing in order to handle that increased volume?

Even though a lot of that increased volume is coming via digital channels, an increase in staffing levels in often needed to handle customer interactions that opt into different channels whether its another digital channel or voice channel.

This is where Artificial Intelligence (AI) could greatly assist in this common dilemma. But not all AI is built alike. Learning and understanding your needs is the best way to determine the solution you seek.

Watch John Pisarek of Interactions talk Artificial Intelligence at Call Center Week Winter with Jim Rembach Click to Tweet

Interactions is a leading provider of speech and natural language technology that enables businesses and consumers to engage in productive conversations. With flexible products and solutions designed to meet the growing demand for unified, multichannel customer care, Interactions is delivering significant cost savings and unprecedented customer experience for some of the largest brands in the world. Founded in 2004, Interactions is headquartered in Franklin, Massachusetts with additional offices in Indiana, Texas, New Jersey and New York. Source: http://www.interactions.com.

Total disruption and massive job losses are headed for the contact center industry. The robo agent will take over customer service and the call center agent will be a relic from the past just like rotary dial telephone.

Thats a bunch of foolishness, dont fall victim to that type of hysteria. What will happen as we continue with advances in AI and natural language capabilities is a shifting in the work conducted by agents.

As the lower level requests are handled by better technology the more complex requests will make their way to the live agent queue. A Frost & Sullivan study claims that by 2022 the number of high-skilled outsourcing jobs could almost double. You can probably expect the same for non-outsourced agent jobs.

The global economy continues to grow. As economies grow there is most often and increase in the need for jobs. Global growth in in 2017 is projected to rise to 2.7 percent according to World Bank. And the world population is on the rise. More people more (customer) service required.

As we see this shift in the work of the contact center agent, we should also see a shift in the work of quality assurance. What types of channels do you support?:

What else? Are you measuring quality in each of these channels? We know that customers may opt out into your agent assisted channel from another channel. But you cant just measure the quality of the voice interaction and expect improvements in the customer experience.

Its actually an unjust burden to put on agents to only quality monitor their interactions. Agent assisted or not, the quality in each channel is vital to understand your risk of losing a customer and controlling your costs.

Visibility into the quality of your Artificial Intelligence solutions (as well as your other channels) must be part of your strategic planning process. If its not your expected savings in staffing wont be real either.

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JimRembach

Call Center Coach | Fast Leader Show

Jim Rembach is a twenty-year contact center veteran, SVP forCustomer Relationship Metrics, Principal forBeyond Moraleand Board Chair for Call Center Coach. His past experience in operations builds the credibility that follows. Jim is a Certified Emotional Intelligence Practitioner, Certified Contact Center Auditor, and is a CX Expert Emeritus for the Customer Experience Professionals Association (CXPA).

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John Pisarek Talks Artificial Intelligence - Customer Think

News One

Artificial Intelligence Enters The Classroom News One For example, in flipped classrooms, teachers assign students homework that utilizes artificial intelligence technology. The software can send the instructor a detailed analysis of students' comprehension of the assignment. That can enable the teacher ...

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Artificial Intelligence Enters The Classroom - News One

Google's DeepMind is one of the most famous examples of artificial intelligence.

Last year it famously defeated the world's best Go player at the tricky Chinese board game. It's also being used at Moorfields Eye Hospital to recognise eye diseases from scans.

But new research shows that DeepMind reacts to social situations in a similar way to a human. Notably, it started to act in an "aggressive manner" when put under pressure.

Google's computer scientists ran 40 million different turns of Gathering a fruit-gathering video game that asked two different DeepMind participants to compete against each other to collect the most apples.

When there were enough apples to share, the two computer combatants were fine - efficiently collecting the virtual fruit. But as soon as the resources became scarce, the two agents became aggressive and tried to knock each other out of the game and steal the apples.

The video below shows the process - with the DeepMind "gamers" represented in red and blue while the apples are green. The laser beams are yellow - and while the combatants don't get any reward for a hit, it does knock the opponent out of the game for a set period of time.

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"We characterize how learned behavior in each domain changes as a function of environmental factors including resource abundance," the team wrote in a paper explaining their results.

"Our experiments show how conflict can emerge from competition over shared resources and shed light on how the sequential nature of real world social dilemmas affects cooperation.

"We noted that the policies learned in environments with low abundance or high conflict-cost were highly aggressive while the policies learned with high abundance or low conflict cost were less aggressive. That is, the Gathering game predicts that conflict may emerge from competition for scarce resources, but is less likely to emerge when resources are plentiful."

The results are interesting in that they show computers are able to adapt to situations and modify their behaviour accordingly.

Many experts have warned of the dangers of true artificial intelligence in machines. Elon Musk singled out DeepMind in particular as one to keep an eye on.

"The pace of progress in artificial intelligence (I'm not referring to narrow AI) is incredibly fast. Unless you have direct exposure to groups like DeepMind, you have no idea how fast it is growing at a pace close to exponential," he wrote in 2014.

"I am not alone in thinking we should be worried."

"The leading AI companies have taken great steps to ensure safety. They recognize the danger, but believe that they can shape and control the digital superintelligences and prevent bad ones from escaping into the Internet. That remains to be seen..."

So while Google's super-smart computers may be content to beat each other up in a race to collect virtual apples, the prospects for the future could be worrying. Especially if your name's Sarah Connor.

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Google's DeepMind artificial intelligence becomes 'highly aggressive' when stressed. Skynet, anyone? - Mirror.co.uk

Artificial intelligence expert and RPI professor Selmer Bringsjord will lecture Wednesday on the concepts behind the HBO series Westworld.

Artificial intelligence expert and RPI professor Selmer Bringsjord will lecture Wednesday on the concepts behind the HBO series Westworld.

RPI artificial intelligence expert looks at Westworld

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Fans of the innovative HBO series "Westworld" a futuristic tale of life-like robots mixing with guests of a Wild West-styled adult theme park can hear Wednesday about how close such technology is from a Rensselaer Polytechnic Institute professor involved in artificial intelligence research for the U.S. military.

"'Westworld' is an HBO series that deals with the 'big questions' of artificial intelligence (AI) in an undeniably vivid and timely way," said Selmer Bringsjord, director of the RPI Artificial Intelligence and Reasoning Lab. "The real world will ineluctably move toward giving experiences to humans in environments that are at once immersive and populated with sophisticated AIs and robots."

Currently, Bringsjord is working on a multi-million dollar AI development project with support from the U.S. Office of Naval Research, which wants to advance military robotics for logistics and other missions. His work focuses on how to program a form of moral sense into AI, so that a robot not under continuous human control can make appropriate choices such as not harming innocent humans or causing unnecessary damage when faced with unexpected circumstances.

In "Westworld," robots are residents (called "hosts") of a corporate-owned Wild West theme park where they meet paying human guests who seek adventures including violence and sex, all while overseen by human staff. The first season was the highest-rated for an initial season in the history of HBO and the schedule for the second season has yet to be announced.

While all the technology necessary for such robotics does not exist today, much of it is rapidly developing, said Bringsjord, who also heads the RPI Department of Cognitive Science. His lecture: Is "Westworld" Our (Near) Future? is set for noon Wednesday on campus in Room 4101 of the Russell Sage Building on campus.

His research relies on the development of increasing levels of AI in computer systems, and then using that computing power to contain and employ concepts of morality, expressed as algorithms in programming language. What humans can choose through free will, and have developed through experience, philosophy and religious strictures, machines will have to grasp through mathematics and logic.

While the physical aspects and appearance of lifelike robots are now very possible, one of the biggest challenges facing AI today is creating a robot that can react, empathize and improvise when dealing with humans and its other surroundings.

The challenge is how to write computer code that can make "story-based entertainment and, for that matter, art engaging, and at the same time new and improvisational," said Bringsjord. "'Macbeth' is great, yes; but the witches give us the same ghoulish deal in every run, and Lady Macbeth has her way with her man in every run as well."

Such a repetitive, static experience at a robotic theme park would soon become tiresome to a human guest. "'Westworld' is based on the dream of allowing humans to enter stories in immersive environments in which new narrative is created on the fly by AIs themselves, drawing humans in," he said.

Currently, there is no known method to impart such improvisational ability to AI, as is possessed by human actors and authors. Some theme parks with robotic attractions have tried to work around this issue by also deploying human actors, so that some characters' reactions to visitors can be spontaneous, he said.

bnearing@timesunion.com 518-454-5094 @Bnearing10

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RPI artificial intelligence expert looks at Westworld - Albany Times Union