Business AI

MARCH 2019 | FUTUREOFBUSINESSANDTECH.COM |

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Before we hand over all decisions to artificial intelligence, we need to understand what we want AI to do for us — and what we don’t want it to do.

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or all the hype, it’s clear that artificial intelligence (AI) certainly will be at the forefront of the information evolution. That’s why now, not later, we must ask the bigger and bolder societal questions around the full scale of the disruption brought about by AI in business.

Slowly but steadily, the issue of “responsible AI” is making its way to front-of-the-boardrooms discussions about the technology. The debate is on about the best way to build fairness, transparency, data

privacy and security into brand-new, untested AI-powered systems and business practices.

We know that AI can discriminate. There’s a male-dominated global community of AI developers — and few of those responsible for engineering AI systems are miniorities. This lack of diversity and inclusivity may lead to algorithms that exclusively mirror their creators and their worldview.

Transparency is also critical, and businesses need to know what data

AI uses, as well as why the data is being used.

Law of the land There’s no legal framework that covers who’s responsible when AI systems make mistakes. Questions of jurisdiction and liability need to be addressed prior to a wide-ranging use of AI systems, particularly in public-facing projects.

The law is catching up when it comes to data privacy and security. The European Union has introduced perhaps the tightest laws globally in the possession, analysis and use of personal data. GDPR is changing the nature of the conversation around the speed with which AI can be implemented.

But the world has yet to welcome any kind of comprehensive legal framework on AI. The industry is, so far, self-regulating, while governments are only starting to figure out what is and isn’t acceptable through the use of AI. The world will need some kind of mechanism to monitor and audit AI systems when they are implemented across organizations will become essential in the continuous evolution of the technology.

The socio-economic impact of AI is also a significant item in the discussion around responsible AI, including how society evolves with the disruptions caused by unemployment this new technology will surely bring.

Time to act The time to address these issues is now. Business leaders cannot wait until after AI is embedded into the functional fabric of their organizations. For AI to help create a world of enhanced human productivity, the right foundations need to be set now with a responsible approach. n

Publisher Mitchell Gross Business Developer Abraham Freedberg Managing Director Luciana Olson Designers Tiffany Pryor, Keziah Makoundou Copy Editor Jeremy Binckes Director of Sales Shannon Ruggiero Director of Business Development Jourdan Snyder Director of Product Faye Godfrey Lead Editor Mina Fanous Production Manager Josh Rosman Content Strategist Vanessa Rodriguez Cover Photo NASA/JPL-Caltech All photos are credited to Getty Images unless otherwise specified. This section was created by Mediaplanet and did not involve The San Francisco Chronicle.

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How AI Is Changing the MarketerCustomer Relationship Artificial intelligence will allow companies to better understand their customers, says 4A’s chief digital officer Chick Foxgrover. That means they can reach them better and create a more meaningful connection.

How can artificial intelligence create more personalized messaging and connections with consumers?

Where we want the most personalization is in the context of an existing relationship, especially in customer service situations. But that can also include recommendations and the awareness of new products.

Artificial intelligence (AI) algorithms can more easily uncover patterns in our use, derive insights from other sources of data, derive a general sense of the consumer’s sentiment and intentions through language and visual signals when available. It can then map that to our customer profiles.

We’re starting to see principles of anticipatory design in action. For example, on iOS and Android, we see that reminders and suggested actions are constructed from calendars or travel time estimates are created. These hold a lot of promise for certain brands to add a whole new dimension to what we call marketing.

How is AI helping to fill a gap or challenge in the marketing world?

AI technology is gradually being introduced to improve by marketers to find audiences that will likely positively receive their messages. AI algorithms are helping marketers create defined custom audiences. They’re grouping common individual properties, such as demographics and past purchases with contextual properties like the weather, a media channel or video or an article. The targeted people can be reached on certain websites and soon on TV through cable and subscription streaming devices.

Visual recognition advances have been one of the major signals that a key component of the quest for AI is moving quickly. Marketers are using visual recognition and visual search to match user-supplied photos with product catalogs or find similar items. It also enables marketers to find instances of their logos and products in social photo streams and add deeper understanding

of prevalence and consumer sentiment or identification with a brand.

I know you’ve mentioned facial recognition and emotion tracking as interesting uses of AI. What other uses do you see?

It’s going to be exciting and unsettling to see how AI technology can work to create a new piece of creative communication. But for certain contexts, it’s very much on its way. Natural language generation is used to write articles and ad copy-use cases are emerging, along with layout and image selection algorithms to create digital ads variations on the fly. It’s in its infancy now, but we’re seeing this increasingly used in China.

What advice would you give to businesses looking to improve their marketing processes?

Marketing today has become very complex. There is a dizzying array of media formats, channels and contexts. Brand building increasingly requires the com-

bined talents of many disciplines that have not traditionally worked together in the compressed time frame of a consumer-driven marketplace. So agencies need to find ways to build teams of the right skills for the right business challenge and fight the desire to work only through traditional workflows.

What has AI in conversational commerce done to the way businesses interact with consumers?

We know there is a demand for AI-driven conversational customer service utilities.

These will save money for companies, all of whom will be wondering how they will deal with voice-driven shopping.

We’re seeing the emergence of chatbased ad formats that can be delivered in mobile apps or online in browsers.

Altogether, businesses are just beginning to interact through AI with human ovesight. With new learnings and improvement, and when automation becomes reliable across many situations, the operational savings will propel adoption. n

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Closing the Customer Experience Loop With Artificial Intelligence — and a Human Touch Artificial intelligence is transforming brand messaging, but human oversight remains key to the future of satisfactory customer relations.

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rtificial intelligence (AI), once the province of scary science fiction stories, is quickly becoming a standard business tool. In fact, people are interacting with AI more than they realize as businesses seek the scaling and speed that AI can bring to their brand messaging — in fact, a recent Gartner report predicted that by 2020 at least one-fourth of all customer service interactions will involve AI to some degree — a startling increase from just 2 percent in 2017.

But growing pains are showing, and there’s mounting evidence that while AI’s benefits are very real, the ideal scenario isn’t handing over your branding and messaging solely to thinking machines, but including some degree of human oversight.

Problem solving

More than chatbots

“AI is more than just chatbots,” says Manlio Carrelli, executive vice president of enterprise business at LivePerson, a leading messaging platform for brands.

“AI can be designed to handle almost any type of inquiry a customer might have.”

Carrelli is blunt about what separates LivePerson from competitors. “We’re the only one that works,” he says. “One crucial difference is that we have figured out that the crucial thing to getting these technologies to work is having them supervised by human beings, and the best supervisors are the agents in a big business’ contact center.

Agents know how to engage with customers, they’re trained on the brand’s voice, and they intuitively understand how to best solve a customer’s inquiry — even complicated ones.”

The human touch

One thing that human oversight helps AI overcome is the unpredictable nature of customer service interactions. “Humans are weird and unpredictable in the ways that they talk to technology

and use technology,” he notes.

“If you’re an airline, a lot of your inbound volume is related to things that are happening with the weather. If you are a retailer, a lot of your inbound inquiries have to do with everyday product promotions, that sort of thing.

So having that human in the loop is really critical to ensuring that the customer experience is awesome.

“With LivePerson technology, agents are able to monitor the

conversations between customers and bots,” Carrelli notes. “If the bot is struggling or the customer is getting frustrated, the agent can intervene and immediately take over the conversation. For example, our recently-launched Conversation Builder allows agents to update a bot to improve its performance. Even non-technical staff — like agents but also designers or business managers — are able to use it to create and update bots.”

From Carrelli’s perspective, the problem isn’t automation — it’s an over-reliance on automation. “I don’t think just spitting out some automation works — that’s a bill of goods that people have tried to sell for years. People who just think this is an engineering problem are wrong; it’s about humans working with technology. It’s a design and engineering problem — not only how do we teach computers to be able to have conversations with people, but what are the design principles that are necessary to make those conversations effective for the consumer and effective for the business? One of the key ways of solving that as we develop applications for the human and AI to work together.”

It’s not just about technology — it’s about the bottom line.

“The companies we work with often see customer satisfaction scores increase 20 percent or more,” Carrelli points out. “Agent efficiency increases 2-3 times because our technology uses AI to help agents manage up to 40 conversations at once, and turnover among call center jobs dramatically decreases with conversational commerce — up to 50 percent or higher — because agents also enjoy messaging more.”

When it comes to brand messaging, the machine revolution is already happening — but the disruption is transforming, rather than eliminating, the human presence. n Jeff Somers

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Separating Hype From Reality in Voice Technology Tom Hebner, the head of product innovation, voice technology and AI at Nuance Communications, explains why voice technolgy proponents need to find out first what problems need to be solved.

Voice assistants like Alexa have become ubiquitous.

What’s the state of conversational artificial intelligence (AI) today?

Although today we can accomplish simpler tasks that help solve immediate consumer needs — such as requesting a song through a smart speaker or telling your car where to take you via GPS — that’s not a true dialogue. We still have a ways to go before we can really, truly engage intelligently with the systems around us.

What’s holding us back?

The most-used voice device in the home is the remote control.

Being able to just ask for the channel you want or to bring the guide up — these kinds of things are really using voice to solve a problem.

While these virtual assistants

all have strengths and specialties, today they rarely communicate with each other or work together across devices, ultimately building barriers between intelligent systems.

How do we break down those barriers?

The key is in brands understanding the opportunity and owning it. These barriers can be broken down by enabling these systems to essentially speak the same language through the use of cognitive arbitration functions that seamlessly connect and integrate disparate virtual assistants, third-party services and content via a single interface.

Are biometrics being used with conversational AI? Combining the two can be a game-changer. Voice biometrics allows intelligent systems to

know exactly who’s speaking to them. This simplicity of engagement means from the moment a person says “hello,” their assistant is ready to help them with a highly personalized experience.

What is different about how you’re working with AI? We start with finding the problems we’re trying to solve. Anyone today can build their own machine learning model. Anyone

today can build their own chatbot. But will it have value? Will it solve a problem? That’s really where we live.

What’s next in voice technology?

The hype around AI is significant.

What’s important is the data and understanding what to do with the data. AI should make lives easier, whether it be interacting with banks and airlines, improving the quality of communication

when folks go to the doctor, or making the lives of doctors easier by taking a lot of the manual work they have to do out of their hands and doing it automatically.

We have researchers that are taking the latest algorithms and developing new products, like our own Pathfinder, a breakthrough technology that uses machine learning and to increase the conversational intelligence of virtual assistants. That’s why we exist, and why we are making a difference in the world. ■

MEDIAPLANET | 7

Things to Come From the Future of Artificial Intelligence An AI visionary offers a glimpse of what’s to come, and it’s conversational, ambient — and smarter than you think.

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rtificial intelligence (AI) is everywhere — in our phones, in our homes, and in our customer service. It’s estimated that by 2023 there will be 8 billion voice assistants in use, and that’s just the beginning.

“The hype around AI is significant,” says Tom Hebner, head of product innovation, voice technology and AI, at Nuance Communications. “We’ve lived through the pain of the marketing bot. They make a splash but people don’t use them because they don’t actually solve a problem.”

The smart future

Hebner has spent decades on the cutting edge of AI and voice

user interface design, thinking about how close we are — or aren’t — to a “smart” future.

“The whole thing with conversational technology is, what makes things easier?” Hebner says. “Why isn’t it everywhere?

Because it’s still hard. You still have to buy those certain pieces of technology. You have to integrate them yourself and tinker with them. Until all of that is in one ecosystem, you’re still going to have some of those challenges.”

All about the data

Hebner and Nuance are at the forefront of breaking down those barriers in the name of improving both customer experiences; a recent study by Frost and Sullivan found that 77 percent of customers were moved to switch service after one frustrating interaction.

“We use AI technology to make lives easier,” he says. “Making interactions easier when people are interacting with banks and

airlines, or improving the quality of communication when folks go to the doctor — and also making the lives of doctors easier by taking a lot of the manual work they have to do out of their hands and doing it automatically.”

The road to making lives easier is paved with data — and the knowledge of how to use it. “Natural language understanding performance has improved significantly over the last decade, but the NLU technology itself wasn’t what changed” Hebner notes.

“The reason the performance got so much better was access to data — knowing what data to use and what data not to use.”

Blazing a trail

Hebner and Nuance turn that expertise in leveraging data into products that improve experiences — and thus return on investment (ROI). “We recently announced an innovation called Project Pathfinder,” he says, “leveraging unsupervised

machine learning to ingest conversations (whether they are voice or text-based) and automatically create conversation paths. For example, everyone that’s contacting a bank about activating a new card, we can see every conversation graphically, and see that your best agents have the conversation this way, while your newest agents have it this way. Supervisors can use that to craft training — here’s how I can make my humans better. Even without that supervisor, we can recognize that this pattern is the most efficient, this is the least efficient, let’s alert the newer agent in real time and give them the next best action so they can perform like the best agent. Our vision here is that we will make every agent your best agent.”

When it comes to fraud prevention, the ROI is easier to see but no less important. “With our biometric-based conversational AI technology, we can recog-

nize people’s voiceprints and behaviors — from how they talk to how they tap, type and text.

That technology is almost magic these days because it’s allowing organizations to authenticate customers in a whole new way and in the meantime halt fraudsters trying to perpetrate attacks.

By implementing biometrics, organizations not only improve the customer experience but save millions of dollars in fraud.

That’s a perfect example of how we’re taking the potential of AI and applying it to a real problem and ultimately, when implemented, it drives impactful ROI for our customers.”

For Hebner, the future of AI and customer engagement goes hand-in-hand with making lives better. “The question is, are you making something they’re doing easier?” he says. “Will it have value? Will it solve a problem?

That’s really where we live.” n Jeff Somers

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PHOTO: STEVE CHIEN

to study plant stress and the Orbiting Carbon Observatory 3 (OCO-3) mission to measure carbon dioxide in the Earth’s atmosphere.

Machine learning is also in widespread use to solve problems such as classification of imager y to track science phenomena such as plant growth, weather, burn scar mapping, cryosphere and others. Many companies are using machine learning to develop business intelligence from this orbital imagery.

Why NASA Needs AI Space exploration brings a set of challenges that requires a need for autonomous decision-making. Without humans, it’s up to AI to fill the void.

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umans are explorers, always seeking to expand the reach of humanity and knowledge. Space is a natural frontier for humanity, telling us how Earth, our solar system and the universe formed, and if we have neighbors somewhere. The incredible distances involved in space require operations without humans in the loop.

When you can’t call home The New Horizons spacecraft flyby of Ultima Thule in January 2019 was over 4 billion miles from Earth. Its radio signals took over 6 hours to reach us.

Because of limited communications stations, we have only intermittent contact. By compar-

ison, we talk to the Mars rovers two or three times per Martian day, and Earth orbiters perhaps six times per day. In order to best use these valuable assets, spacecrafts need to be able to make decisions on their own.

Artificial Intelligence (AI) has been used to support scheduling space missions for decades, going all the way back to the SPIKE system used to schedule the Hubble Space Telescope and the GPSS system used to schedule Space Shuttle preparation for reflight operations in the 1990s. Automated AI scheduling has parallels in the commercial world in AI and operations research for a wide range of fields: logistics, supply

chain management, production management and pharmaceuticals, just to name a few. AI is also used to enable the Curiosity rover to select its own science targets based on scientist-selected criteria.

Sorting the stars For any given assignment, we need to examine massive quantities of data. Machine learning techniques can triage these large data sets so that scientists can quickly examine the most interesting or novel data. AI can search these data sets to understand irregularities, common patterns and other key characteristics that lead to scientific discoveries.

In the 1990s, this SKICAT system used a machine learning technique called decision trees to classify stars and galaxies in data from the 2nd Mount Palomar Sky Survey (POSS-2).

Using machine learning to deal with enormous datasets can translate directly to business problems.

Seeing Earth in a new way AI is being used in many ways to increase our understanding of Earth’s ecosystems. AI was used to intelligently network space and ground sensors to monitor volcanoes and flooding.

AI scheduling is being used to operate Earth Observing space missions such as ECOSTRESS

Finding friends AI is a key component of the search for extraterrestrial life.

To go to extreme environments such as the sub-ice oceans of Europa (a moon of Jupiter), a robotic explorer needs to travel vast distances through high radiation and ice sheets into an unexplored ocean. It must do this with little guidance from Earth. Such a robot would only be able to contact Earth every few weeks or even months. In the absence of detailed guidance from the Earth, it must navigate out and back from a base station, avoid hazards and study instrument data for minute signals of life. When a potential signature is found, it must balance the risks of further exploration against dangers to itself. Finding life is of no value if the data is not returned to Earth. Ideally it would return the key data then return to the site for further exploration.

This would be a large step for current AI technology.

An interstellar mission represents an even greater challenge for AI. Proxima Centauri and the Trappist system require a voyage of decades, fully independent from the Earth.

When arriving, the probe must operate autonomously, deciding observations to take, what data to return and how to survive — a true challenge for AI. n Steve Chien, Senior Research Scientist, Jet Propulsion Laboratory, California Institute of Technology

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PHOTOS: TERRELL LLOYD

How AI Is Keeping 49ers Fans in the Game

AI has the power to analyze fan behaviors, and give them indvidualized experiences — even in the National Football League.

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rtificial intelligence (AI) is one of the most exciting technological innovations of the modern age. It’s therefore unsurprising that whenever a company announces they’re using AI, the news just about guarantees a headline or two.

Because of AI’s potential to improve business, the hype may be worthy in some cases. But AI is also novel, and not every busi-

ness may be prepared to incorporate it into their strategy, says Moon Javaid, the head of strategy and analytics for the San Francisco 49ers.

When AI might make sense for a business The 49ers are one of first teams in the NFL to employ AI, Javaid says, but it wasn’t done just to generate media buzz. Instead, the 49ers added the technology, supplied by Satisfi Labs, to help their customers.

For at least 10 games a year, the team needs to employ an extra 3,000 workers to address customer questions, such as where to find

a hot dog, bathroom or ATM within the stadium.

Fans can also use a virtual assistant and chatbot to get immediate answers on their phones. “Customers want a timely answer. They don’t necessarily care if they have a dedicated [representative],” Javid says. “Our goal is to get people timely issue resolution, and if our virtual assistant is successful, that would be our best use case for why and where AI makes sense.”

Preparing for AI Not every company has the data and infrastructure to successfully implement AI into their business strategy, Javaid says. “The majority

of sports teams don’t have the infrastructure in place from a technology perspective, nor do they have the bandwidth to analyze it and assess it in a smart fashion,” he says, adding that will change in the next few years.

One of the first steps the team took was gathering fan data, such as purchase and demographic information. Javid says that other teams don’t have that capability just yet, but should get them soon.

AI doesn’t make sense for everything, however. “I would not push for AI just to generate a headline or get a buzz because we have a ton of priorities and limited bandwidth,” Javaid says. “I want to focus on the

changes that will affect the masses — so the changes that will affect 60,000 fans, not a couple hundred fans. I like to focus on areas that can generate a good return on investment for us.”

With AI advancing at the speed of light, there’s no definitive answer as to what’s next for the team.

“Think about the first iPhone.

Think about the first Tesla. Think about the first iteration of anything,” Javaid says. “If I talk to you five years from now on AI, my opinion might be different because of the advances that have been made.” n Melinda Carter

10 | FUTUREOFBUSINESSANDTECH.COM

New Tech, Old Roads, and Big Rigs

Giant robot trucks just aren’t a practical solution. Why not make better use of the tech we already have?

Every day, Maverick USA’s trucks travel 650,000 miles. As the company’s owner, Steve Williams, likes to say, that’s “to the moon and back, and then to the moon again.”

His trucks use technologies that make them run cleaner and more safely. And that’s for a reason.

“We operate within 3 feet of the American citizens at all times. There’s a lot of stress associated with that,” Williams says. “Collision avoidance systems in that environment reduced our rear-end accidents to only three last year.”

That doesn’t mean Williams is going to be considering driverless trucks anytime soon. “We want drivers in our trucks and we want pilots in our airplanes,” says Williams. “If autonomous trucks to people mean there’s not going to be any driver in it and it’s going to be operating on a smart highway, and it’s just out there like a robot — that isn’t happening.”

The problem is the state of our highways. Autonomous technology largely relies on cameras reading lane striping and other markings on roadways. Faded paint, patched asphalt, potholes and other damage make it hard for cameras to process the input. Until our roads are consistently maintained and upgraded, truly autonomous vehicles just aren’t practical.

But well-placed cameras could finally eliminate the blind spots that plague tractor-trailers. Williams’ company has been involved in some beta testing to eliminate a truck’s huge side mirrors while improving visibility around the truck. He’s also installed software that allows his company to monitor changes to drivers’ safe-driving patterns.

Marijane Miller, Producer and Co-Director, “Be Prepared to Stop”

Are You Ready for the AI Revolution?

Hubert Wassner, chief data scientist at AB Tasty, says that companies need to be aware of the changes that are coming to the business world thanks to AI development.

ously different from one consumer or consumer segment to another. That may may cause customers to feel singled out or believe that others are getting special treatment.

What would you tell a business owner or developer looking to AI to optimize their business?

Be sure that the AI you are willing to use has reached maturity and is stable and functional. Be sure you have the right expert to accompany you. And be sure you are correctly handling AI errors. Those errors aren’t ones that can be forgiven as an understandable human error and may damage a brand’s image.

What is one possible challenge to adoption?

The general public will barely see that AI powers services, so the adoption problem is more a technical challenge for businesses.

Identifying business cases where AI can improve things or cut costs is the more pressing challenge. It’s a tricky issue, because to tackle the adoption challenge, one needs both business prowess and AI skills to be able to accurately measure risks vs. opportunity. The problem is these skills are rarely found in the same person.

How will continued developments in AI change the way we do business?

and even wages are being disrupted by cloud services, 24-hour business models and unimaginable margins.

AI isn’t just chaning how we do business. It’s changing what we sell.

When computers were introduced into the world of commerce in the 1980s and 1990s, they automated manual tasks like word processing, creating spreadsheets and general business intelligence. But it wasn’t about what was being produced, it was just about how they were being produced.

Today, the product of AI-designed work is valuable. Human labor and services are being replaced by machine intelligence. That means that everything from HR services to office hours

What changes will consumers see?

Consumers adapt surprisingly quickly to evolutions to the customer experience. Many have already come to expect personalization as a given part of the shopping experience, for example.

But because most of the work is behind the scenes, many changes — such as better targeting of advertising campaigns in social media feeds — won’t be noticed by consumers.

Brands shouldn’t make personalized experiences that are too obvi-

What are some developments coming down the pipeline right now that will help to create these improvements?

Video is the field currently experiencing the most impressive improvement. The analytical capabilities of AI programs are up to human-level accuracy, and that’s great. But the most impressive incoming improvements are related to image production, which will revolutionize image and special effects production.

Natural Language Processing has also recently made startling advances.

Since there are currently wide-ranging applications for NLP in a myriad of industries — chatbots, spam filtering, email classification, insurance document analysis, CV analysis and job recruiting — the progress being made in academia will have a rapid and powerful impact in the business world. n

12 | FUTUREOFBUSINESSANDTECH.COM

Finding the Human Element in AI

Why is it so important to add the human element into all artificial intelligence (AI)?

The human world is complex and nuanced, and AI is still extremely reliant on the human element. Problem definition, data annotation and output validation all incorporate human skill and subtlety. Humans also need to be involved with the ethics of AI, and that means a diverse set of people need to be involved.

What should businesses do before implementing AI? Evaluate where you have access to plentiful, diverse and relevant data. The better and more plentiful the data, the more likely you are to succeed at the problem you select.

Why should humans be in the loop?

Human truth is used to train AI. Multiple diverse human viewpoints can create an information-rich environment for the AI. Humans can also look at edge cases where the AI is not very sure of its output.

Dispel a common myth about AI in customer experience and business.

People believe that AI will eliminate the need for people, but AI and skilled people will need to work together. Tech-enabled services and human expertise will both be needed.

Radha Basu, Founder and CEO, iMerit

The Advantages and Dangers of AI Futurist Martin Ford says that artificial intelligence can bring many advances in humanity — but can easily be weaponized if we’re not careful.

Robots won’t be taking over the world anytime soon, but the technology that fuels them may be coming for your job, threatening your data security, and increasing inequality.

That’s the messaging of futurist and artificial intelligence (AI) expert Martin Ford, whose expertise has earned him numerous speaking engagement and book deals.

Ford, the author of 2015’s “The Rise of the Robots” and 2018’s “Architects of Intelligence,” wants more people to start talking about the implications — good and bad — of AI and robotics. “I think it’s going to be hugely disruptive across the board,” he says. “It’s going to have positive aspects, but there are also going to be some things we need to worry about.”

Understanding AI and its impact While numerous definitions abound, the Brookings Institute defines AI as “machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention.”

That doesn’t mean AI will lead to a

“Terminator”-like world, or one where our computers turn against us, even though much of our technology already is assuming human-like qualities and capabilities. “Right now, it’s the beginning of it from the consumer side and on the daily life side,” Ford says. “We’re already beginning to see Alexa and with smartphones. But so far, I think a lot of it is marginal.”

Immediate areas of concern are when systems that rely on AI begin to wipe out human employment. “Everyone thinks AI is going to hit blue-collar jobs, and that’s really not necessarily true,” Ford says. “There’s going to be a major impact on the kind of people who have a college degree,” like those whose work involves sitting in front of a computer doing relatively routine tasks.

“I think it’s clearly going to have a huge impact on the finance industry,” Ford says. “You already see automated trading and you see CEOs of banks talking about as many as half of the jobs disappearing over time.”

Preparing for a future of competition with AI Competing with robots for jobs might sound scary, but Ford compares AI to electricity, an invention that many people would argue has improved daily life across the board. “In the same way you would never ask, ‘What industry is most dependent on electricity?’ That’s

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kind of a dumb question, right? Everything relies on electricity. I think the same will be true of AI,” says Ford, who projects that AI will become universal in this way not next week or even next year, but in 10 or 20 years.

To reap the potential benefits of AI — including solving big problems such as climate change — preparation and more public discourse will be key, Ford argues.

“AI is going to be the main thing in our toolbox to solve these kinds of challenges,” he says. “So the last thing we want is for it to be overregulated or for there to be some sort of public backlash against the technology. That tends to slow things down. I think that would be really unfortunate because I think it’s going to be the main force that takes us forward.”

In the near future, AI’s effect on privacy and security is a serious concern to Ford. The technology could reasonably be weaponized by terrorists or leveraged by hackers. Ford doesn’t dismiss the idea of AI posing a direct threat regarding robots harming humans, but urges the public to focus on those more immediate dangers. “I think this is going to be one of the biggest challenges we’re going to face,” he says. “For that reason, I think it’s really important that we have a discussion about what all of this means for the future.” n Melinda Carter

MEDIAPLANET | 13

Technology Helps Retailers Shake Up Status Quo From taco trucks to Fortune 500 companies, retail technology is transforming the nature of how we’ll be doing business in the future.

To some, the idea of disruption in retail might not sound like a positive thing. But when a new technology disrupts a product or a business, it often replaces old inefficiencies and makes things better and stronger than they were before.

Artificial intelligence and virtual reality might not be taking over completely, but they are sta r ting to emerg e. We a re at the point where consumer expectations are rising and influencing how retailers who want to stay on top must interact with their customers.

One of consumers’ biggest demands is a seamless shopping experience, regardless of whether they are standing in a retailer’s store, sitting at a computer or holding a mobile device.

That means the technology behind a brand’s physical stores, websites and apps needs to work in perfect sync.

If the web says an item is in stock at a store, it needs to be there when the customer shows up. If something bought online doesn’t work, the customer wants to be able to return it at the store. If next-day shipping isn’t soon enough, picking up in-store should be an option. If the mobile app says the store is open, it had better be open.

For smarter shoppers Retailers must be able to answer consumers’ questions about the products they sell, and one of the ways technology helps with that is through chat bots. These are computer programs that use a form of artificial intelligence to give the customer a human-sounding conversation, either through spoken-word audio or via text.

TV shopping, a predecessor to online shopping, is being reborn with fully shoppable

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programs, where everything seen is available for purchase with the click of a mouse or a tap on a touchscreen. Similarly, social media is increasingly full of opportunities to buy.

In-store, retailers are using technology such as “Li-Fi,” which transmits data via LED lightbulbs rather than radiobased Wi-Fi. Mobile payments are becoming more popular, along with mobile point-of-sale terminals on tablets or smartphones that let sales associates go to the customer and avoid the need to stand in long checkout lines.

New retail jobs With retail using all this technology, the world of retail jobs is changing as well. Retailers don’t just buy gadgets off the shelf and use them. Retailers today operate their own innovation labs to come up with the latest in cutting edge technology.

That means they are hiring engineers, software designers and social media experts.

From the days of the general store to paper catalogs to online shopping, retailers have always been constantly reinventing themselves. With technology, the pace of that reinvention has accelerated to a level that’s never been seen before.

All this means that technology isn’t just the “what” of the future, it’s the “who” of the future. n Matthew Shay, CEO, National Retail Federation

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How Today’s Mining Industry Has Changed for the Better Learn how today’s U.S. mining industry, the individuals it employs and the equipment it uses are exceptional.

The current U.S. mining industry is a far cry from the mining industry in the 1970s.

In the ‘70s, a 410-brake horsepower Caterpillar D-9 bulldozer with a 21.4 cubic yard capacity blade was considered large.

Today an 862-brake horsepower Cat D-11 bulldozer with a 57 cubic yard blade is considered common. In the ‘70s, a 50- or 100-ton mine haul truck was considered a large truck. Today a 350- to 400-ton truck is considered common, and in some mines worldwide, the truck and its loader are operated by automation.

Likewise, drilling and blasting are often automated. Surveying is often done by drones and mine-planning is computerized.

Reclamation, non-existent in 1970, is fully practiced from beginning to end of the mining process.

Industrywide changes Mineral processing plants have likewise changed over the past 50 years. Crushing plants commonly have primary crushers with capacities of several thousand tons per hour. Flotation plants use a single semi-autogenous grinding or ball mill today to grind 25-30 thousand tons of ore per day, where in the ‘70s it was common to use a series of 10-12 smaller ball mills grinding the same amount of ore. Cyanide leaching is commonly used to recover gold, where in the early ‘70s it was a new technology. Mill controls are often electronic rather than manual.

I n 1970 ou r n at io n ha d a population of 205.1 million, compared to today’s population of 325.7 million. Today, the U.S. mining industry employs 626,100 individuals, about the same as in 1970, but the gross output of the mining industry in 2016 totaled $682.7 billion versus $187.7 billion in 1970 in current U.S. dollars. That rep-

resents an increase of 3.6 times above 1970 production.

Safety and sustainability In the early 1970s, our mining industry was beginning its recovery from being the second most dangerous industry in the United States. Today, with industrial safety a key activity in mining, our industry is rated twentieth in industry severity. In the 1970s, there were few women in the workforce. Today they are common.

Likewise, social responsibility and sustainability are key items of management in today’s industry.

Today we operate all manner of mines in a safe, environmentally friendly and efficient manner nationwide. These mines provide components of almost everything we use in our everyday lives. These items include automobiles and the material used in the roads we drive them on, equipment for the electric e n e r g y w e u s e f r o m s o l a r, wind and thermally generated

sources, the components in our cell phones, the fertilizer used in growing our food, the chemicals and pipes used to purify and carry water to our homes, and components of most everything we use to maintain our way of life.

To d a y ’s m o d e r n m i n i n g industry provides the minerals and fuels that America needs to sustain its high standard of living while providing high wages for the women and men working in the industry.

A museum with a mission The National Mining Hall of Fame and Museum, located in Leadville, CO, is an organization whose mission is to tell the story of mining, its people and its importance to the American public. It is appropriate that we are in Leadville, which has a long history in mining. Silver, lead, zinc and gold are some of the mineral products for which the area is known.

The National Mining Hall of Fame and Museum has a twofold purpose. Our first focus is

to honor women and men who have made a significant impact on America’s mining industry and, through it, the U.S. economy.

On the top floor of our facility are plaques honoring 240 individuals who have influenced our industry in a significant way. A U.S. President, leaders of industry, academics, inventors, individual miners and even a few scoundrels are found in our Hall of Fame.

Each individual’s career and its impact on America is described both on plaques and digitally.

The remaining portion of our 25,000-square-foot facility describes the past, present and future of mining in the United States. and worldwide. Exhibits touch on the technical, operational and personal factors that make the mining industry capable of providing a fundamental base for America’s economic strength today.

We encourage you to visit our facility and learn about the American mining industry. n Paul Jones, Principal, Sovereign Management Group, Ltd.

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“Shark Tank” Star Explains How to Keep Your Tech Safe

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Robert Herjavec, the “Shark Tank” host and cybersecurity expert explains what the future has in store for your data.

With the increasing use of personal assistants in the home, what should customers be mindful of to protect their personal information?

You have to be vigilant, and this starts with getting back to basics, such as securing your home Wi-Fi network, which really is the virtual door into your home. Make sure you have WPA2 encryption enabled and have a strong, unique password. Then, change the default login settings, install software updates and disable features that are not needed.

It’s very easy to love convenience, especially if you can ask your home assistant to restock your pantry. But is your shopping list really as private as you think it is? Once someone gains access, it’s far more than your list exposed. Your banking information, personal data and corporate data you interact with or connect to from your home

office is all vulnerable. Never make the mistake of dropping security for convenience.

In an era of major customer data breaches, how can artificial intelligence (AI) help to predict, protect and prevent more effectively than past technologies?

The foundation of AI is logs. You have to have an input. Being able to leverage big data analytics is great, but AI is an avenue that works hand-in-hand with traditional and current technologies to drive insight and alter behavior.

Many past technologies leverage signature-based detections, which are easy for adversaries to change. AI and behavioral-based technologies focus on the patterns of attack, which are much harder to constantly change. By focusing on behavior, AI can leverage data features to determine answers

to questions such as what might happen next or what the best corrective action is for the current situation. It will be interesting to watch the intersection of AI and security operations, analytics and reporting. If AI algorithms truly begin to predict and prevent attacks, allowing them to automatically integrate with other security platforms could be huge.

What is the biggest myth behind AI cybersecurity you’d like to debunk?

The biggest myth is that AI can make sense of any data, because there has to be quality data in order for the algorithms to work correctly. AI won’t be able to solve our cybersecurity problems completely. All these advancements in AI and machine learning are not supposed to replace traditional security measures and cyber hygiene; they’re supposed to enhance what’s currently in

place. As attacks become more automated and sophisticated, defenders will need tools to match that. AI is one answer to that challenge as we grow past signature-based detection.

What do you think the next generation of cyber threats will look like?

Does AI play a role in defending against these threats?

It’s hard to say what the next generation of cyber threats will look like. The real question may be, who will be targeted? Industries that have a major influence on our economy and society, such as health care and manufacturing — and even government systems themselves — will be targets.

But cyber criminals are evolving just as much as security professionals. They’re using tools like AI, machine learning, technologies, algorithms — you name it — and defense mech-

anisms are finding it difficult to keep up.

What role do you see b loc kc h a in /di s t rib ute d ledger technology (DLT) playing in the future of asset management and cybersecurity?

There is a misconception that blockchain is a single, secure, impenetrable location like Fort Knox, but in reality, blockchain resolves the issues of lack of trust and human error while providing accuracy. If blockchain technology were integrated properly, it could help reduce the risk of a breach—assuming blockchain is used to complement the existing security infrastructure and technology.

So many organizations are still lacking in terms of how they store and protect customer data and identities, and these systems can help going forward solve the question of how data is stored and where. n

Speeding Research with ArtificialIntelligence Advanced memory and storage technologies are unleashing new possibilities in science and medicine.

Š 2019 Micron Technology, Inc. All rights reserved. Micron, the Micron logo, and Intelligence Accelerated are trademarks of Micron Technology, Inc. All other trademarks are the property of their respective owners.

micron.com/insight

18 | FUTUREOFBUSINESSANDTECH.COM

How AI Will Make Your Next Job Search Better

PandoLogic CEO Jonathan Bulkeley says that the “pay and pray” approach to job listing is ending — and a better way to find new hires is coming.

What are the main challenges in recruitment today?

Recruiters have disparate technology platforms, which traditionally have not communicated with one another and aren’t too transparent for talent acquisition partners. We need to find end-to-end solutions.

What is programmatic recruitment?

How can it change a business’ recruitment strategy?

Programmatic recruitment is effectively putting the right job opening in front of the right person at the right time for the right price.

Historically, employers have been required to “pay and pray” for job applicants online. But now, programmatic platforms allow employers to use AI to target potential applicants and only pay based on actual performance of those campaigns.

How has AI changed job advertising?

It’s giving employers, for the first time, sophisticated tools and technology platforms to spend more efficiently, target job seekers more effectively and measure ROI on advertising spend.

Ultimately, that keeps publishers like Indeed and LinkedIn accountable for delivering value to both employers and job seekers.

Why HR Needs to Stay Ahead of Automation Harness the power of automation — or risk being automated out of your HR job.

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ill automation cause the workforce of the future to be dominated by malevolent, beady-eyed robots gleefully expelling humans from their offices and cubicles to lay claim to their jobs?

Probably not. But if it takes scary robots to alert human resources (HR) professionals to the importance of tracking and responding to the rise of automation in the workplace — and the threat that automation could pose to the careers of many — the image will have served its purpose. Automation is everywhere and its impact on human resources is expanding. But many say HR professionals are only dimly aware of the trend.

There’s no doubt that a more automated future is coming. Employers predict 17 percent of work will be auto-

mated by 2020, compared to about 5 percent in 2014, according to Willis Towers Watson, a global consulting company.

For HR, automation increasingly affects workforce strategy. It vastly expands the potential of, and expectations for, HR analytics. Technology is transforming traditional HR functions such as hiring, training and benefits administration. And the execution of all this change demands a strong HR role.

The understanding and use of the power of automation may prove to be the dividing line between those who advance in the field and those who are marginalized and, eventually, automated out of their HR jobs.

Some HR operations “have woken up and are leading a higher-purpose conversation on the trajectory of auto-

mation within their organizations,” says Robert Bolton, a London-based partner with KPMG, a global consultancy.

“But far too frequently I’m seeing other business divisions raise the issue, and HR is nowhere to be seen.”

Sourcing and hiring are becoming increasingly automated. This is altering the role of HR professionals, who will have more time to focus on higher-level functions. Many organizations will be chasing the same types of tech-savvy employees, and HR will need to lead the way in finding them, competing effectively for them and facilitating speedy offers, as delays often result in losing prospects to competitors.

Increasingly, people will be working with machines that don’t need benefits, reassurance or human support — or weekends and holidays off. They will provide endless streams of data and conceal nothing.

At Lincoln Financial Group, a Pennsylvania financial services company, automation has rippled through the company in recent years, driving significant changes in such job functions as underwriters, marketers, advisors and actuaries, says Lisa Buckingham, executive vice president and chief people, place and brand officer.

Keeping humans at the top of the agenda is important in automation efforts, she says. “I believe putting people ahead of process and technology is ultimately how HR will enable an organizational transformation when it comes to automation,” Buckingham says. “Although, it’s still the case that many transformation initiatives are more focused on process and technology than on their talent strategies, it’s important to remember that people are at the heart of our organizations. n Paul Jones, Principal, Sovereign Management Group, Ltd.

MEDIAPLANET | 19

How Is Artificial Intelligence Shaping Customer Experience?

Ryan Lester Director of Customer Engagement Technologies, LogMeIn

What are the main challenges of the AI business and specifically the customer experience (CX) industry today?

Ryan Lester: Many companies struggle to understand the value they can expect from investments in AI-powered CX technology.

This problem manifests in three ways: a lack of budget, outdated technology and siloed organizations. Those that do prioritize CX face a different challenge of making their data actionable.

Sanjay Mehrotra: I think the fundamental challenge with AI is learning to trust the results when they seem counterintuitive. AI can provide huge efficiencies, but not if we don’t act on the results. AI can give you answers to questions you didn’t know you should ask.

Rob Walker: AI projects are looking for a problem to solve, or don’t meet overhyped expectations. Although AI is incredibly

and increasingly powerful, too many failed “hobby projects” may tarnish its reputation. In the CX industry, AI is often being positioned as a solution to optimize real-time conversations with customers. If done well, it delivers unprecedented customer relevance and mutual value to those conversations between the customer and organization.

What are the business benefits behind AI? RL: Automating low-level tasks cuts costs, directly impacting the business’s bottom line. AI also drives top-line revenue by increasing the number and quality of customer engagements and gives customers a way to self-serve, reducing the load on support agents and increasing customer satisfaction.

SM: What is your data trying to tell you? AI can provide answers. It’s an essential tool that can give you a better understanding of the insights hidden

Sanjay Mehrotra, President and CEO, Micron Technology

in your data and how to continually modify what you’re doing to optimize your company’s resources for peak efficiency.

RW: We’ve only just scratched the surface on how businesses can benefit from AI. It can instantly analyze and assess a large palette of potential options for each customer and then personalize a next-best action in the moment.

AI deployed in the right way and across the right departments — like marketing, risk, service and other mission-critical business functions — will only increase its value to businesses.

What’s the biggest misconception behind AI’s use-case today?

RL: The biggest misconception today is that adopting AI must be a massive and complex project, taking months to implement and see an ROI. This is far from the truth, with companies seeing a positive ROI in weeks. Compa-

Dr. Rob Walker, Vice President Decision Management and Analytics, Pegasystems

nies should prioritize speed to market when initially adopting AI. SM: AI is often seen as a magic bullet — a switch you flip for instant results. The secret of applying AI effectively starts with your data. AI thrives on data.

Where we once saw data as a cost to be managed, AI is now turning data into a new source of competitive advantage.

RW: What people don’t see is how widely it’s been adapted.

It was reported that 33 percent of consumers “think” they use technology with AI; in reality, 77 percent had already interacted with it. If you are reading this, you have likely used AI today in some capacity.

What are other businessuse cases you can tackle with AI? RL: Offering internal-facing human resources (HR) and IT chatbots helps employees clear daily hurdles so they can spend

more time being productive. In addition to making employees more efficient and productive, having employee-facing AI-powered chatbots in the workplace helps businesses hire and retain top talent.

SM: In the semiconductor business, we generate enormous quantities of data across manufacturing. We’ve found that we can prevent costly downtime of our semiconductor tools by asking the AI to analyze the sound patterns a tool makes and how they change over time to proactively schedule maintenance.

RW: Like CX, HR can stand to gain operational strides in their everyday work. AI can help automate tasks, accelerate time to hire, forecast staffing needs with accuracy and provide a number of other benefits across all industries. The opportunities are limitless when businesses understand how to create an AI deployment that is intelligent and based on quality data. n

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