Finding The Humanity In Data: IBM Watson’s CTO Rob High Defines The Emerging Era Of Cognitive Computing [PODCAST]

Hessie Jones

It’s increasingly clear that we, as humans, continuously upload our identities every day. Those needs and propensities become quantified and contextualized. For companies like IBM Watson, understanding the human condition is important so technology can increasingly define patterns, learn, and potentially predict outcomes that benefit both business and industry.

We were pleased to host Rob High, IBM Fellow, vice president and chief technology officer, Watson Solutions, IBM Software Group. In this episode, Rob talks about:

  • The definition of cognitive computing
  • How Watson is aiding the advancement of health care
  • Chef Watson and recommendation on recipes
  • Advanced cognitive systems and how they’re applied across different mediums
  • The future of AI – Should humans be fearful?

You can listen to the podcast here or catch the episode here on Libsyn.

What is cognitive computing?

  • Ultimately, cognitive computing has the greatest benefit for people. By definition, it is the interpretation of the human condition that includes all those things that we take in every day: the information, our communication. It deciphers the intent we derive from them that is meaningful and used in the way we make decisions in our everyday lives.
  • Cognitive computing augments our own human cognition and gives us the insight and inspiration to those specific things we need to know to do our job better.

Classical computing methods have been unable to understand the underlying intent in how we, as humans, have communicated with each other, through voice and text, audible or written.

Cognitive computing does not replace human thinking. It does the research for you so you can do your thinking better.

How is Watson making strides in healthcare?

Watson can operate only in digital form, aggregating the information and looking at discreet elements to explicitly understand the various treatment options to better inform decision making.  Massive amounts of data will uncover trends across the population and yield certain correlations that may help interpret and predict patient response to various treatments.

Through Watson’s work with MD Anderson Cancer Centre, the Oncology Expert Advisor (OEA) was launched.

By pulling together and analyzing vast amounts of information from patient and research databases, the OEA is expected to help our care teams identify and fine-tune the best possible cancer treatments for our patients, while also alerting them to problems that arise during a patient’s care.

In accessing millions of patient records, Watson can aid in identifying a micro-segmentation of the population that have common traits; i.e., exposure to environmental impacts, genetics, heritage, and symptoms. These will aid in surfacing the opportunities to apply the knowledge and understanding to determine how well someone with the same exposure will respond to certain treatments.

While health information across the world has been fragmented, Watson can aid in processing massive quantities of information (not humanly possible) to create implications in a meaningful way, and in a short period of time. Now doctors and patient caregivers who have documented success can share that information with other medical practitioners across the globe to accelerate diagnosis and treatment.

Chef Watson: “Ready to do some cognitive cooking?”

This was for me the most fascinating part of the segment: Chef Watson enables people to make decisions about menus, identifying and helping us discover new recipes based on our unique preferences.

At IBMchefwatson.com,Watson partnered with Bon Appetit, which provided 9000 recipes for Watson to ingest and learn about the different types and styles of recipes. For a computer which innately has no sense of palette or smell, Watson learned about the taste makeup and flavors and the feeling that results when you consume a particular dish. It also learns about the science of taste chemistry and the chemical compounds that give the recipes their specific tastes. From this perspective, it has the ability to begin to imitate the human senses. As per Rob:

Watson starts from scratch, dealing with many – potentially up to a quintillion– combinations of ingredients when it comes up with its unique recommendation every time.

It’s getting at the root of what makes people who they are – the things we experience are interpretable.

As an example, if you wanted a Belgian flavor for a given recipe, Watson will evaluate the different combinations of ingredients that pair well and produce a Belgian flavor, and may come up with different variations.

Starting out as a fun and interesting project, this has occurred as a result of the cognitive ability and has allowed Watson to venture into the art of the possible.

Patterns and the evolution of interpretations

Similar to the learnings with MD Anderson, there are trends or patterns within the data where we can derive the greatest understanding or intention. Overlay contextual history which informs more of the human understanding. Collectively these allow us to extract meaning. Cognitive systems draw meaning that can bring the right set of information to humans and attention to just the right thing(s) to shape the decision-making process.

Pervasive technology has been able to to process 20% of the world’s information until now. The other 80% of that data is the human condition: the spoken word, written word, music, visual representations – all interpretations of our interests and needs. This is the heart of understanding. As Rob points out:

Multi-modal is how we communicate with each other: Not only what you’re hearing, but the intonation in the voice reflects the substance of that expression that’s being conveyed. Add the cadence that punctuates these points and now we know how humans understand each other. The computer needs to understand that as well.

Cognitive systems are not based on the same mathematical models as traditional computers. Attempting to interpret the human condition is doing so in the presence of idiosyncrasies and nuances carried through conversations and other communications.

Our words, our expressions are ambiguous…

Are these models reliable?

There is “no absolute level of correctness necessary;” these results are being applied in the eyes of the beholder. The computer will need to be exposed to enough examples that it will begin to surface patterns of meaning that will allow it to work well in that context. Be prepared for the outcomes to vary by environment or time period or when new variables are introduced.

What is the future of AI? Should we, as humans, be fearful?

The potential of cognitive is vast and in the near future, the amazing strides that are introduced are evidence of the inherent benefit to our human strength and potential.

Technology will continue to progress and there will always be a risk that people and organizations will use it in nefarious ways.

Technology should not be feared. With increased understanding comes progress. It also means humans should be responsible and use it for the purposes for which it was intended.

As this information becomes for common, technology companies need to ensure safeguards are put in place to mitigate abuse to our privacy.

Rob High is an IBM Fellow, vice president and chief technology officer, Watson Solutions, IBM Software Group. He has overall responsibility to drive Watson Solutions technical strategy and thought leadership. As a key member of the Watson Solutions Leadership team, Rob works collaboratively with the Watson engineering, research, and development teams across IBM.

Want more on future tech and its effect on business? See Bring Your Robot To Work.

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Answers To Two Burning Questions About Conversational AI

Warren Miller

Fire: one of civilization’s earliest and most groundbreaking technological advancements.

Two million years ago, when the first homo erectus shared his newfound discovery with his hominid peers, they likely ran for the hills. But once they realized everything they could achieve with fire—from seeing in the dark and keeping warm to cooking food and fashioning tools—they quickly came around.

People have always feared the unknown. Even today, innovative technology initially intimidates most people. But if a tool proves sound and benefits individuals in some tangible way, they’ll eagerly embrace it.

One technology that people are currently on the fence about—particularly in the enterprise space—is conversational artificial intelligence (AI).

While voice-activated digital assistants powered by conversational AI have been a mainstay in the home for the past several years, organizations are just beginning to bring them into the workplace. Many companies remain skeptical, however. They wonder whether these digital assistants can truly help them simplify the lives of their customers and employees. They wonder if they can leverage the technology to save time, cut costs, and increase productivity.

But most of all, they wonder if they can rely on these digital assistants to support people around the globe who speak different languages, and if this technology can securely protect their most sensitive data and proprietary information.

Here are two burning questions companies have about adopting conversational AI tools—and reasons they can finally put their reservations to rest.

1. Does conversational AI support my native language?

Multilingualism is an impressive characteristic, and the ability to fluently speak multiple languages opens up whole new worlds.

What if you could speak 21 different languages? Imagine what you could achieve. Imagine how much you could help others.

Apple’s Siri can do just that. In fact, the company’s digital assistant is way ahead of its conversational AI competitors when it comes to the number of languages it supports. Comparatively, Microsoft’s Cortana supports eight languages, Google Assistant supports four, and Amazon Alexa supports two.

The important thing to note here, however, is that because conversational AI is a branch of machine learning, it has the ability to support any native tongue—eventually.

First, your digital assistant needs a strong knowledge base in each language, be it one widely spoken around the globe, like English, or one used in a specific area of the world, like Shanghainese.

It then requires deep learning algorithms that help your device process structured and unstructured language data in the form of e-mails, online chat logs, or phone transcripts. By studying this data, digital assistants can iron out complex communication issues and improve how they interact with users, no matter the language.

Rather than using a linguistic, rules-based approach—where the device would have to identify nouns, verbs, and adjectives—machine learning is a more scalable solution that enables digital assistants to figure out how words are connected and what phrases do or don’t make sense. In other words, no one has to continue defining specific syntactical rules for the device. It learns them on its own.

If a voice-activated digital assistant doesn’t currently support your native language, rest assured—it can and it will.

2. Will digital assistants threaten the security of my company’s data and proprietary information?

Security is a major concern for companies in today’s digital age—and understandably so.

Cybercrime affected nearly one-third of all organizations in 2016, according to a PwC survey. And Vanson Bourne research found that 87% of CIOs believe their companies lack the security controls necessary to adequately protect their businesses in the future.

While security breaches are certainly something to worry about, sharing your data with digital assistants is more helpful than harmful. And the more data your digital assistants collect, the more their conversational AI capabilities improve, and the better they can assist you.

So, the solution to protecting your data isn’t to stop communicating and sharing your data with digital assistants. Instead, your security depends on taking the proper safety precautions. These include:

  • Muting your device: Although digital assistants wait to hear a trigger word or phrase before helping you, their microphones are always listening—unless you mute them, of course. Find the mute button on your device, and only unmute your digital assistant when you’re actively using it.
  • Sharing only what’s necessary: Giving your digital assistant access to your calendar is one thing. Sharing confidential financial information is something else altogether. Exercise caution in what details you provide your digital assistant.
  • Deleting old recordings: Digital assistants retain audio files of the questions you ask them for months or even years. You do, however, have the option to erase these recordings, and you don’t need to be a magician to make these files disappear; simply visit a website and hit the delete button.

There are also steps that technology companies and developers can take to protect your data. For example, they can ensure that your information is inaccessible to unauthorized users. Today, digital assistants cannot tell the difference between voices. But in the future, with greater conversational AI capabilities, these devices will come equipped with biometric-based authentication such as voice recognition technology—so if your digital assistant is hacked or stolen, an unauthorized user will be unable to control your device and access your data.

Technology companies could also impose severe restrictions around the use and sharing of your company’s proprietary information. If an organization develops a digital assistant for both you and an industry competitor, it can keep your trade secrets private. Your knowledge base will be reserved for your business only. That means no other company can benefit from the questions your employees ask your digital assistant.

By taking the proper precautions with your device—and trusting that the enterprises developing them will do the same—you can rest easy that your company’s data and propriety information will remain safe.

Hesitate to adopt a digital assistant and you’re playing with fire

Two million years ago, our ancestors took a revolutionary step when they discovered how to control fire. But they also learned that if you play with fire, you’re bound to get burned.

Today, if you fear emerging technologies like conversational AI and hesitate to adopt a digital assistant in the workplace, you risk the painful sting of missed opportunities.

Interested in learning more about conversational AI and how digital assistants can empower your enterprise to thrive? Join Juergen Mueller’s strategy talk at SAP TechEd in Las Vegas, September 25-29, or sign up to attend an upcoming SAP TechEd event in Bangalore on October 25-27, or Barcelona on November 14–16 to hear from inspiring industry thought leaders and see innovative technology solutions in action.

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AI, Blockchain, And Cloud Fuel Banking’s Evolution

John Bertrand

Artificial intelligence (AI), blockchain, and cloud technologies are increasingly appearing on the horizon. This could be exactly what the banker ordered, given the legal mandates for open banking and General Data Protection Regulation for 2018. These three key technologies can fuel the financial services industry’s evolution into the digital age.

Artificial intelligence

AI is a collection of machine learning, natural language processing, and cognitive computing designed for scale. It is this scalability that is exciting, as it can create exponential growth and deliver today’s required personalized communications. For example, in July 2017 UK payments processed 21 million payments per business day. If 0.5% of the daily volume needed additional review, 105,000 items would need to be checked, often manually and with rules-based, tick-the-box solutions. AI would significantly increase productivity by matching payment behavior and pattern recognition, and simply asking the question, “does this look right?” AI-powered chatbots could help business users and consumers answer inquiries and enhance the customer experience.

Blockchain

Blockchain is also a mix of technologies that enables us to trust someone we do not know and protects us from cybercriminals. The block contains vital information about a party, and the chain is the sequence of third-party, verified events that have taken place over the history of the transaction. Blockchain is fully encrypted and can be permissioned for private and public groups. Given the manual, paper-based state of the supply chain, it is not surprising that we’re seeing many new proofs of concepts and pilots using blockchain.

Cloud

Cloud computing gives improved security, scale, and agility to respond to market demands and can decrease banks’ cost bases. The advances in cloud technologies permit software applications to move seamlessly between legacy, private cloud, and public cloud solutions. One such technology, containers, allows the applications to flow safely across the end-to-end processes regardless of the underlying technologies, much like how shipping containers transformed the inefficient, non-scalable 20th century transportation industry to the one today.

Finance’s digital evolution

These technologies are could be the savior of financial services industry. Financial services are rapidly becoming a technology-driven sector, evidenced by the increasing amount of money being spent in this area.

  • Financial services is now one of the largest buyers of software
  • IDC expects this figure to grow more than five percent over 2016’s spending
  • The forecast of $2.7 trillion in worldwide IT spending by 2020 is led by the financial services industry

Legacy banks and financial services firms can either build the technology themselves or work with fintechs to do so; either way it has to be done. Eminent evolutionary biologist Charles Darwin could have been discussing this new banking environment when he noted:

It is not the strongest of the species that survive, nor the most intelligent, but the one most responsive to change. 

Potential impacts of financial services’ digital evolution include:

  • Low-cost centers using AI to increase straight-through processing (STP) to 100%, thus removing cost, increasing customer satisfaction, and reducing liabilities from errors
  • Administration of trade finance through blockchain to reduce costs and increase certainty of ownership at any point in time
  • Spare computer capacity created by using the cloud, enabling banks to meet peak-day requirements and increase cybersecurity

Security is now a bottom-line concern. See The Future of Cybersecurity: Trust as Competitive Advantage.

This article was originally published on Finextra.

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Diving Deep Into Digital Experiences

Kai Goerlich

 

Google Cardboard VR goggles cost US$8
By 2019, immersive solutions
will be adopted in 20% of enterprise businesses
By 2025, the market for immersive hardware and software technology could be $182 billion
In 2017, Lowe’s launched
Holoroom How To VR DIY clinics

From Dipping a Toe to Fully Immersed

The first wave of virtual reality (VR) and augmented reality (AR) is here,

using smartphones, glasses, and goggles to place us in the middle of 360-degree digital environments or overlay digital artifacts on the physical world. Prototypes, pilot projects, and first movers have already emerged:

  • Guiding warehouse pickers, cargo loaders, and truck drivers with AR
  • Overlaying constantly updated blueprints, measurements, and other construction data on building sites in real time with AR
  • Building 3D machine prototypes in VR for virtual testing and maintenance planning
  • Exhibiting new appliances and fixtures in a VR mockup of the customer’s home
  • Teaching medicine with AR tools that overlay diagnostics and instructions on patients’ bodies

A Vast Sea of Possibilities

Immersive technologies leapt forward in spring 2017 with the introduction of three new products:

  • Nvidia’s Project Holodeck, which generates shared photorealistic VR environments
  • A cloud-based platform for industrial AR from Lenovo New Vision AR and Wikitude
  • A workspace and headset from Meta that lets users use their hands to interact with AR artifacts

The Truly Digital Workplace

New immersive experiences won’t simply be new tools for existing tasks. They promise to create entirely new ways of working.

VR avatars that look and sound like their owners will soon be able to meet in realistic virtual meeting spaces without requiring users to leave their desks or even their homes. With enough computing power and a smart-enough AI, we could soon let VR avatars act as our proxies while we’re doing other things—and (theoretically) do it well enough that no one can tell the difference.

We’ll need a way to signal when an avatar is being human driven in real time, when it’s on autopilot, and when it’s owned by a bot.


What Is Immersion?

A completely immersive experience that’s indistinguishable from real life is impossible given the current constraints on power, throughput, and battery life.

To make current digital experiences more convincing, we’ll need interactive sensors in objects and materials, more powerful infrastructure to create realistic images, and smarter interfaces to interpret and interact with data.

When everything around us is intelligent and interactive, every environment could have an AR overlay or VR presence, with use cases ranging from gaming to firefighting.

We could see a backlash touting the superiority of the unmediated physical world—but multisensory immersive experiences that we can navigate in 360-degree space will change what we consider “real.”


Download the executive brief Diving Deep Into Digital Experiences.


Read the full article Swimming in the Immersive Digital Experience.

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Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation. Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

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Jenny Dearborn: Soft Skills Will Be Essential for Future Careers

Jenny Dearborn

The Japanese culture has always shown a special reverence for its elderly. That’s why, in 1963, the government began a tradition of giving a silver dish, called a sakazuki, to each citizen who reached the age of 100 by Keiro no Hi (Respect for the Elders Day), which is celebrated on the third Monday of each September.

That first year, there were 153 recipients, according to The Japan Times. By 2016, the number had swelled to more than 65,000, and the dishes cost the already cash-strapped government more than US$2 million, Business Insider reports. Despite the country’s continued devotion to its seniors, the article continues, the government felt obliged to downgrade the finish of the dishes to silver plating to save money.

What tends to get lost in discussions about automation taking over jobs and Millennials taking over the workplace is the impact of increased longevity. In the future, people will need to be in the workforce much longer than they are today. Half of the people born in Japan today, for example, are predicted to live to 107, making their ancestors seem fragile, according to Lynda Gratton and Andrew Scott, professors at the London Business School and authors of The 100-Year Life: Living and Working in an Age of Longevity.

The End of the Three-Stage Career

Assuming that advances in healthcare continue, future generations in wealthier societies could be looking at careers lasting 65 or more years, rather than at the roughly 40 years for today’s 70-year-olds, write Gratton and Scott. The three-stage model of employment that dominates the global economy today—education, work, and retirement—will be blown out of the water.

It will be replaced by a new model in which people continually learn new skills and shed old ones. Consider that today’s most in-demand occupations and specialties did not exist 10 years ago, according to The Future of Jobs, a report from the World Economic Forum.

And the pace of change is only going to accelerate. Sixty-five percent of children entering primary school today will ultimately end up working in jobs that don’t yet exist, the report notes.

Our current educational systems are not equipped to cope with this degree of change. For example, roughly half of the subject knowledge acquired during the first year of a four-year technical degree, such as computer science, is outdated by the time students graduate, the report continues.

Skills That Transcend the Job Market

Instead of treating post-secondary education as a jumping-off point for a specific career path, we may see a switch to a shorter school career that focuses more on skills that transcend a constantly shifting job market. Today, some of these skills, such as complex problem solving and critical thinking, are taught mostly in the context of broader disciplines, such as math or the humanities.

Other competencies that will become critically important in the future are currently treated as if they come naturally or over time with maturity or experience. We receive little, if any, formal training, for example, in creativity and innovation, empathy, emotional intelligence, cross-cultural awareness, persuasion, active listening, and acceptance of change. (No wonder the self-help marketplace continues to thrive!)

The three-stage model of employment that dominates the global economy today—education, work, and retirement—will be blown out of the water.

These skills, which today are heaped together under the dismissive “soft” rubric, are going to harden up to become indispensable. They will become more important, thanks to artificial intelligence and machine learning, which will usher in an era of infinite information, rendering the concept of an expert in most of today’s job disciplines a quaint relic. As our ability to know more than those around us decreases, our need to be able to collaborate well (with both humans and machines) will help define our success in the future.

Individuals and organizations alike will have to learn how to become more flexible and ready to give up set-in-stone ideas about how businesses and careers are supposed to operate. Given the rapid advances in knowledge and attendant skills that the future will bring, we must be willing to say, repeatedly, that whatever we’ve learned to that point doesn’t apply anymore.

Careers will become more like life itself: a series of unpredictable, fluid experiences rather than a tightly scripted narrative. We need to think about the way forward and be more willing to accept change at the individual and organizational levels.

Rethink Employee Training

One way that organizations can help employees manage this shift is by rethinking training. Today, overworked and overwhelmed employees devote just 1% of their workweek to learning, according to a study by consultancy Bersin by Deloitte. Meanwhile, top business leaders such as Bill Gates and Nike founder Phil Knight spend about five hours a week reading, thinking, and experimenting, according to an article in Inc. magazine.

If organizations are to avoid high turnover costs in a world where the need for new skills is shifting constantly, they must give employees more time for learning and make training courses more relevant to the future needs of organizations and individuals, not just to their current needs.

The amount of learning required will vary by role. That’s why at SAP we’re creating learning personas for specific roles in the company and determining how many hours will be required for each. We’re also dividing up training hours into distinct topics:

  • Law: 10%. This is training required by law, such as training to prevent sexual harassment in the workplace.

  • Company: 20%. Company training includes internal policies and systems.

  • Business: 30%. Employees learn skills required for their current roles in their business units.

  • Future: 40%. This is internal, external, and employee-driven training to close critical skill gaps for jobs of the future.

In the future, we will always need to learn, grow, read, seek out knowledge and truth, and better ourselves with new skills. With the support of employers and educators, we will transform our hardwired fear of change into excitement for change.

We must be able to say to ourselves, “I’m excited to learn something new that I never thought I could do or that never seemed possible before.” D!

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