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Pete Giorgio, principle with Deloitte Consulting LLP, leads Deloitte’s US Sports practice
Sports trends expected to disrupt and dominate
Like most other industries, sports are being disrupted by technology advancements and cultural changes. How can sports executives capitalize on these industry changes in 2019? Our annual report explores eight trends that could redefine the sports industry in the year ahead.
Our starting lineup for 2019
2018 was an exciting year for sports. France beat out Croatia in a goal-filled match to win the World Cup. Simone Biles took home six medals at the world championship. The Red Sox won their fourth World Series title in 15 years. And the Capitals took home the Stanley Cup for the first time in team history.
Off the field, we’ve seen athletes grow as spokespeople for causes, front offices overhauled to bring in even more analytical rigor, and streaming media options grow in prominence. What trends will we be scouting this year? Our 2019 sports industry outlook covers eight trends to watch:
Athletes as content creators
Gone are the days of sports fans needing reporters to get news about their favorite players. Over the past few years, athletes are increasingly becoming content creators in their own right—be it through Instagram, Twitter, or long-form stories on websites like The Players’ Tribune.
While the athlete’s role as an individual content creator serves as a small complement to traditional media, this trend—buoyed by stars who were raised in the digital age—could become even more impactful and important in the coming years. This platform will enable further expansion and value of personal brands while also opening the door for the next generation of athletes to build their brands before they become household names.
“The fewer barriers there are between athletes and fans, the more commercial opportunities that will materialize. The value in having fans relate to their favorite players is immeasurable.”
Brian Finkel, Deloitte Sports Research, Deloitte & Touche LLP
Augmented and virtual reality
As technology advances, the challenge of keeping fans constantly engaged has become more and more difficult. Any lull in the game leads to fans diverting their attention to their phones and consuming content from other venues.
However, the growing integration of augmented and virtual reality is transforming the customer experience by giving fans the opportunity to get “closer” to athletes while having a single platform to access a wealth of data. While there are still some kinks that need to be worked out, this is a time where prioritization of customer experience is at an all-time high.
“VR brings the best of the stadium into the home, while AR brings the best of home into the stadium.”
Allan Cook, digital reality leader, managing director, Deloitte Consulting LLP
The offensive revolution
Few ideas are as widely accepted among sports fans and players as the old adage that offense sells tickets, but defense wins games. As we watch shootout after shootout across professional sports, during the regular season and the playoffs, analysts are beginning to wonder whether times have officially changed.
While viewership numbers are up, purists question whether such a focus on offense has impacted the integrity of the games they love. This presents teams with a tough decision to make: Do they keep investing in offense and hope that’s enough? Or do they consider strategic defensive investments that will enable them to play a different game to compete in both the arena and in the market?
“While increasing offense intends to sell more tickets, leagues will have to balance offense with maintaining the value of defensive skill and the historical backdrop of their sport.”
Lee Teller, specialist leader, Deloitte Consulting LLP
Sports betting trends
What happens in Vegas no longer needs to stay in Vegas. With states now free to choose whether to legalize sports betting or not, many key stakeholders see opportunities to monetize, while others raise concerns about the impact legalized gambling could have on the integrity of the game, and federal and state governments consider their roles and legislative next steps.
Not only will betting impact the relationship between leagues, gambling institutions, data providers, and the government, it’s already changing the way fans can interact with games. The NBA recently announced an offering that allows fans to stream the fourth quarter of a game for $1.99. While convenient for the busy fan who is only able to watch part of a game, this is particularly notable for gamblers staking bets on real-time game lines who want to watch critical moments in the games they bet on.
“September 2018 marked the first month of online sports betting dominance in New Jersey. With results from recent months, this trend has and will continue to be the dominant theme for the foreseeable future.”
Jamie Poster, manager, Deloitte & Touche LLP
Tackling mental health
The past few years have seen an increasing number of high-profile athletes, storied franchises, and top programs publicly address a topic that affects both MVPs and weekend warriors: mental health. Many stars have offered a glimpse behind the curtain of endorsements and champion podiums into lives affected by symptoms of depression, anxiety, and other mental health conditions.
With one in four people worldwide affected by mental or neurological disorders during their lives, the notion that handsomely paid and highly visible athletes are willing to shed light on a topic historically burdened with a negative stigma is both a positive movement and refreshingly relatable. With each athlete that comes forward, it becomes increasingly apparent that the sports world’s investment in mental wellness is only just the beginning.
“Mental health is more than a hot-button societal issue, it has the opportunity to become a key long-term competitive advantage for the teams and countries that effectively engage, support, and work with their athletes.”
Every two years, soccer’s popularity in America spikes as fervor surrounding the World Cup spreads throughout the nation. However, recent polling points not just to cyclical interest but long-term, sustained growth. Soccer is now the second-most-played youth sport in America and more Americans between the ages of 18 and 34 name soccer as their favorite sport over baseball.
European nations have taken note of this rise and are seeking to capitalize. The English Premier League inked a deal with NBC Sports in 2015 reportedly worth a billion dollars to stream its games to American households. And investments extend to human capital as well: European clubs are increasingly looking to young Americans to fill their rosters.
“The US market provides a massive marketing, financing, and talent opportunity for European soccer—from traditional powerhouses to lower division teams looking to regain relevancy.”
Sam Ebb, senior consultant, Deloitte Consulting LLP
With the vast audiences drawn to eSports and the increasing direct ties to professional leagues, we’ve seen players, executives, and owners jumping into the arena as team owners and avid gamers, as well as a way to continue to connect with teammates and fans off the court. As leagues look to continue building and expanding their fan bases, their eSports presence will be a major part of those interactions.
Over the coming year, we expect teams and leagues will continue to embrace eSports as a part of the existing major sports leagues, including efforts to integrate eSports opportunities into the existing sports experience, from eSports lounges in Topgolf facilities to an eSports arena in the Real Madrid’s new stadium.
“The eSports landscape continues to stabilize around the maturation of teams and leagues and increasing sponsor engagement.”
Kat Harwood, senior manager, Deloitte Consulting LLP
Personalizing fan engagement
While organizations have always collected data from season ticket holders, fan loyalty programs, and other fan engagement sources, many teams house this data in disparate databases and siloed customer-relationship management systems. These organizations, though, are starting to think about the fan holistically, requiring a centralization of these touchpoints into a single source of truth that can drive deeper, more personalized fan engagement—inside and outside of the stadium.
As sports teams and leagues build on and incorporate the successes of the e-commerce revolution, they’ll be able to connect all dots of a single fan’s journey, helping to sell additional tickets while also driving personalized connections and experiences that can increase the lifetime value of fans. Over the next year, we believe organizations will adapt their marketing functions to leverage fan data and become even more nimble and automated.
“A key question for teams remains who is in each seat, but more importantly, focus is shifting to who engages with the brand inside and outside the venue?”
We believe these topics are going to impact the business of sports, both on and off the field, over the next 12 months. But invariably new stories, trends, and themes will emerge that further disrupt the industry, derail the game plan for executives, and delight us as sports fans. Please tweet #DeloitteSports to share the sports trends or opportunities that are on your mind in 2019.
Pete, a principal with Deloitte Consulting LLP, leads Deloitte’s US Sports practice, serving multiple sports clients including the United States Golf Association, NBA, United States Tennis Association… more
Even in this conservative industry, the latest technologies can make a huge impact.
By Lal Karsanbhai, Executive President, Automation Solutions, Emerson for IndustryWeek | Apr 16, 2019
As long as people have existed, we’ve needed to harness energy to live: fire to warm ourselves and cook food, gas to generate clean electricity. Energy is a traditional industry with roots that stretch as far back as human history. Yet even in this conservative industry, the latest technologies can make a huge impact.
Organizations that embrace digital transformation can see measurable benefits in critical industry focus areas: safety, reliability, production, emissions and overall performance. But there is always the underlying question: How do you get started?
The good news? The optimal digital strategy is different from company to company, meaning there is no single right path. The bad news? Digital transformation does not have one consistent playbook. This can be confusing for businesses trying to capitalize on the promise of the Industrial Internet of Things (IIoT). A recent Emerson survey of industry leaders responsible for digital transformation initiatives found that 90 percent felt that a clear and actionable roadmap was critical for success, yet only 20 percent of respondents said they had a vision and roadmap.
Even as companies work to find their way in the new digital transformation landscape, a few definitive trends are emerging:
1. Software will remain the backbone of making data actionable. It has long been an industry staple, but advanced software solutions are making it possible for companies to safely test new approaches to optimize productivity and efficiency without any risk to operations. Take power generation, for instance – a critical industry with no margin for error. Through “digital twin” technology, power companies can simulate a live plant that allows them to test proposed changes without impacting the actual operations. Software advances like digital twin have the potential to help the industry find game-changing improvements.
2. Cybersecurity is non-negotiable, but its implementation depends on its environment. Not everything needs to go to the cloud. There are many opportunities for remote monitoring of systems and other data analytics in the cloud, but knowing which applications are best suited for on-premise (or edge computing) versus the cloud will be key for businesses. Different cybersecurity protections are required for each, and understanding what makes the most sense will help guide many digital implementation programs. Secure remote monitoring has created a new business model that brings significant performance and financial benefits, through predictive analytics that detect maintenance problems in oil fields, refineries and chemical plants before they occur – leading to millions of dollars saved annually.
3. A clear business case and scalability are the name of the game. Sweeping initiatives won’t work; companies need solutions that account for where they are and where they want to go. Digital transformation programs must have a clear business case. Implementing technology and hoping for a return will not deliver the significant impact that’s possible.
4. Information technology (IT) and operational technology (OT) need to be on the same side of the table. IT and OT can too often speak different languages even as they develop and implement programs for the same company. Successful transformation will happen only when IT and OT come together with an integrated approach to technologies and work together to implement and optimize. We are seeing movement in this direction, as some companies are organizing integrated teams to drive digital transformation and encourage the collaboration of these complementary skillsets.
5. Technology should empower – not replace – the workforce of the future. The rise of automation is bringing with it trepidation that robots will eliminate manufacturing jobs. Done well, the influx of automation will instead evolve current manufacturing jobs. Yes, automation may replace repetitive tasks-related jobs, but it will also require new data analytics and interpretation skills that rely on science, technology, engineering and math (STEM) knowledge. Technology and automation are complementary job creators.
Empowering the future workforce comes down to meeting and supporting people where they are. This includes upskilling the current workforce, making the industrial sectors attractive to students planning their careers, and instilling a passion for math and science with young learners beginning their educational journey.
Digital transformation has the potential to change the energy industry for the better—and give companies that embrace it competitive advantage.
Gaggles of delivery R2D2’s scurrying down suburban streets? It sounds like a technological nightmare worse than an e-scooter infestation. But the concept of robot messengers got a major boost recently when FedEx announced plans to start testing such a service this summer, and for smart cities, it may not be such a crazy idea after all.
There are already several pilot robo-delivery projects running in the U.S.
Nuro, for example, recently announced it’s moving on from Arizona and expanding its delivery partnership with grocery giant Kroger to four Houston zip codes. Nuro’s vehicle is more of autonomous compact car than a rolling robot, but so far people seem happy to pay the roughly $6 for the self-driving silver surfer (probably because they don’t have to tip the car).
The 7,000-pound gorilla in retail, Amazon, is reportedly testing a sidewalk-crawling delivery bot in Seattle. The project looks like a more practical service for suburbs — especially compared to drones, which are restricted or outright banned in many urban areas.
Most recently, FedEx has announced that it plans to begin testing its own autonomous delivery robot in Memphis, Tennessee. And while there are other delivery bot tests underway in addition to the ones mentioned, the entrance by the preeminent delivery service in the U.S. into the self-driving space represents something of a milestone.
Hitting the streets sidewalks
FedEx isn’t talking about autonomous vans and trucks — at least not yet. And the challenges facing even mainly on-the-sidewalk robots are legion. Weather, uneven terrain, traffic, poor cellular network coverage, and humans behaving badly are just a few of the headaches facing programmers. However, FedEx’s partners and its own delivery infrastructure imply that it may be uniquely positioned to overcome those obstacles.
The delivery bots, for example, are designed in partnership with Dean Kamen’s DEKA Development & Research Corp. Kamen is best known for developing the Segway and the iBot Personal Mobility Device, a wheelchair that can climb stairs. The latter demonstrates that DEKA’s engineering skills will probably be able to help FedEx surmount some of the navigation issues for door-to-door delivery. Indeed, the fully electric FedEx SameDay Bot is based on the iBot, with some additional technology that makes it autonomous, including lidar, radar, and video cameras to assist in navigation.
According to Kamen, the SameDay bot can run at about 10 miles per hour, “which won’t disturb pedestrians.” Kamen made the remarks during a presentation to announce the new partnership. The inventor said the SameDay Bot’s speed limiter means it won’t cause the kinds of problems associated with cyclists and messengers who hop onto sidewalks — but it will still be able to handle round trips of up to eight miles relatively quickly.
The road ahead
FedEx plans to work with retailers including AutoZone, Lowe’s, Pizza Hut, Target, Walgreens, and Walmart to perform, as its robot’s name implies, same-day door-to-door deliveries. Customers can open the bot using a smartphone app, or have it opened by a remote operator. Those operators will also control the bots should the machines encounter situations they don’t recognize.
“It’s a way they could take on Amazon,” Gary Goralnick, a shopping center developer, told Digital Trends regarding self-driving technology. Goralnick said integrating online ordering and same-day delivery, for example, has helped brick and mortar retailers turn the corner and compete against Internet-only outlets.
Still, others note that such self-driving solutions beg for an infrastructure solution.
“You have to redesign the city before you layer in the technology,” Duncan Davidson, a technology investor with Bullpen Capital, told Digital Trends. Davidson pointed to examples such as e-scooters causing problems in Los Angeles and Uber cars causing additional congestion in New York City as ways in which technology can wreak havoc in cities — unless it’s supported by the right infrastructure changes.
None of these robo-delivery services will work unless consumers embrace the concept
Autonomous cars and delivery vehicles, for example, may need their own dedicated lanes. Making such changes could improve safety and help reduce traffic. And there are many ways in which same-day delivery in underserved areas could help home-bound individuals who suffer from chronic illnesses or other restrictions that prevent them from getting outside.
Indeed, Hyundai has a program called Elevate to develop an autonomous vehicle that can navigate rough terrain and even climb stairs to reach customers. And Dean Kamen’s iBot was originally designed to help people such as disabled veterans get around on their own. (The partnership with FedEx should help make the iBots more affordable for those who need them, according to Kamen.)
Ultimately, none of these robo-delivery services will work unless consumers embrace the concept. As long as they steer clear of scary robots, like Boston Dynamics’ headless Spot Mini, and focus on friendly delivery devices that look like R2D2, it may just work out.
By Matthew DeBord, Senior Correspondent, Transportation for Business Insider Mar 30, 2019
The first few decades of technology innovation have been characterized by rapid growth and quick profits based on low headcounts and low capital outlays.
The next few decades will require much larger headcounts and massively larger amounts of money.
If you have doubts, just look at Tesla and Elon Musk.
Tesla is 15 years old, and despite its considerable struggles and internal and external dramas, Elon Musk’s electric carmaker remains a Silicon Valley darling and is widely admired in the traditional auto industry.
None of that means the company is getting better at its core function, which is building cars. Tesla has improved drastically on this front, but compared to other automakers, it’s gone from what I would say is an “F” to managing a “C.”
That’s because large-scale manufacturing is difficult. Musk knows this and often points to Tesla’s aspirations to reinvent the process as the thing that will ensure the company’s legacy.
But what Elon knows is largely ignored by Tesla’s most enthusiastic supporters, and it’s now broken free and appears to be moving menacingly toward Uber and Lyft as those high-expectation startups IPO.
The basic issue is one of scale combined with speed. I’ll give you an example, drawn from a company I know pretty well. Business Insider started out with a few guys in a borrowed loading dock in New York City, hammering out blog posts on tech and the markets in 2009. Ten years later, BI is the biggest business news site in the world, with far-flung global offices. We were acquired by Axel Springer, a German media conglomerate, in 2015, for about $450 million, and since then our growth has been impressive by any measure.
But our central New York operation fits on two office floors in lower Manhattan, and while we employ a large number of journalists relative to many other digital media sites, we’re pretty far from Tesla’s headcount of around 40,000. A classic example is Instagram, which was bought by Facebook in 2012 for $1 billion, when the photo-sharing app had 13 employees.
The problem is getting worse
Uber and Lyft have some structural similarities — the tech side can be run by a relatively small number of high-value software engineers and managers — but the “on the ground” part of the business requires a staggeringly expensive army of human drivers, as well as capital investment in cars, which are a depreciating asset. If I were to transfer this model to BI, we’d all be creating the publication as we do now, writing a number of stories every day — then printing them all and distributing the results by hand. Our business plan would be worse than the one it’s replacing, daily newspapers.
I could go on. Apple is having a tough time figuring out what it’s next awesome product will be. The Apple Watch has a done OK, but it’s no iPhone. The much-discussed Apple Car project has reportedly changed from an actual car into a self-driving software project; meanwhile Alphabet’s Waymo has spent a decade on the problem and is just now getting self-driving cars on the road in a commercial application.
You get the point. The low-hanging, scale-fast-and-cheap fruit has been picked. The internet of things is evolving in herky-jerky fashion. So investors have turned to transportation, largely because everybody needs to get around and because the auto industry is worth trillions worldwide but tends to innovate rather slowly.
Tesla’s ongoing struggles with the real world
Tesla was ahead of the curve on this trend by a decade, but Silicon Valley is ignoring the carmaker’s struggles. The lesson ought to be that the best way to make (or lose) a fortune in the auto industry is to start with one (Elon Musk basically lost the millions he initially invested in Tesla after he and his partners sold PayPal to eBay, but he was able to reverse the death spiral later in 2008, and the company has grown massively since).
The basic math of the car business is that it demands a gigantic amount of capital to generate an immense level of cash flow, out of which you try to achieve profit margins that could run above 10%. Cash balances don’t rise to Apple or Google levels, but before the tech economy’s economics became the standard, people used to worry about what Ford, for instance, would do when it piled up tens of billions in cash on its balance sheet. Even now, Ford has enough cash to ride out several short, cyclical recessions.
Back to Uber and Lyft. Their balance sheets also enjoy lots of revenue coming in, but the businesses quickly convert a growing topline into a ruinous bottom line because there’s an insatiable need for more drivers. That end of the business isn’t rightsized for anything but the most robust, densely urban environments; an Uber driver outside a place like New York or San Francisco probably can’t get enough rides to think of the job as more than a short-term gig or a stopgap wage.
Driverless cars might remedy this flaw, and that’s why General Motors’ Cruise and Waymo are pushing in that direction. For Tesla, the solution is automated manufacturing, but that’s never going to eliminate 100% of the labor headcount. And thus far, the company’s efforts to roboticize its assembly lines have met the same fate as the industry’s earlier experiments. In fact, Tesla had to build a quickie assembly line under a tent last year to make its production targets — a line that wouldn’t have looked unfamiliar to Henry Ford.
Even Amazon isn’t exempt
If I’m feeling especially grumpy, the only tech company that’s using the old model (think: Facebook and Google) and looking pretty solid is the brutally competitive Amazon. This is a company that’s good at experimenting with innovations that don’t reinvent the wheel but gain traction (Echo speakers are no Sonos, but Alexa is winning) and whose buy-everything-from-us strategy has won over consumers in droves. Resistance is futile, as I discovered recently when I needed to buy a tuxedo for an eight-year-old on a few days’ notice.
That said, Amazon doesn’t have a perfect track record (remember the Fire phone?), and it’s starting to get into stuff like airplanes and electric pickup trucks (it invested in startup Rivian not too long ago), so we’ll have to see if the great aggregator of online consumption can make it in the world of large, complicated machines.
If Tesla’s experience is a guide, the ride is gonna be rough. Another example, from my own life. I’m writing this story at home at 9 a.m. on a Thursday, using a high-speed internet connection and Insider’s content-management system. I’ll file it, photos and all, entirely digitally, all from the comfort of my home. The story could be good to go in less than half an hour.
In the 1990s, before the web, when I wrote stories at home, I had to save the file to a 3.5-inch disk and take it myself to the publication that would later turn it into a print product. The writing part consumed about the same amount of time as it does now, but the logistics around delivering the end result added hours. And of course there was still a lot of work for other people to do once my job was done. You don’t even want to know what it was like when everything was written on typewriters and publications were assembled without digital tools (the appearance of a daily broadsheet, in those days, was something of a miracle).
Welcome to the Era of Slow Scaling
What Tesla has been trying and failing to do is reverse-engineering some more speed into the production of the automobile — to make the physical car more like virtual software. They have been somewhat successful at this, believe it or not (over-the-air software, updates, for example, that can fix things like braking dynamics). But attempting to crack the code of the moving assembly line has been much more difficult.
Many of the future opportunities that Silicon Valley wants to attack are like this: the so-called disruption can take hold and gain investment, but it doesn’t scale fast enough toward profitability. Tesla is exhibit A: In 15 years, the company grew dramatically, but it’s only made money in three quarters since 2010.
Two-decade timeframes aren’t going fly on Sand Hill Road. Even isolated success stories — GM bought Cruise for around $1-billion all-in when Cruise has about 15 staffers, and the company is now valued at $14.5 billion — come with staggering ongoing costs. Cruise’s future investment prospects, for example, come in part from GM’s possession of a multi-billion-dollar factory in Michigan where it builds the EVs that Cruiser operates.
How many venture capitalists want to invest in companies that require a few billion in long-term investment right out the gate?
We’re going to find out because this is what’s coming: the Era of Slow Scaling. And if anybody wants a comprehensive tutorial on how it will go down, there’s no better person to pay attention to than Elon Musk.
While no one knows what artificial intelligence’s effect on work will be, we can all agree on one thing: it’s disruptive. So far, many have cast that disruption in a negative light and projected a future in which robots take jobs from human workers.
That’s one way to look at it. Another is that automation may create more jobs than it displaces. By offering new tools for entrepreneurs, it may also create new lines of business that we can’t imagine now.
A recent study from Redwood Software and Sapio Research underscores this view. Participants in the 2017 study said they believe that 60 percent of businesses can be automated in the next five years.
On the other hand, Gartner predicts that by 2020 AI will produce more jobs than it displaces. Dennis Mortensen, CEO and founder of x.ai, maker of AI-based virtual assistant Amy, agreed. “I look at our firm and two-thirds of the jobs here didn’t exist a few years ago,” said Mortensen.
In addition to creating new jobs, AI will also help people do their jobs better — a lot better. At the World Economic Forum in Davos, Paul Daugherty, Accenture’s Chief Technology and Innovation Officer summed this idea up as, “Human plus machine equals superpowers.”
For many reasons, the optimistic view is likely the more realistic one. But AI’s ability to transform work is far from preordained. In 2018, workers are not being adequately prepared for their futures. The algorithms and data that underlie AI are also flawed and don’t reflect the diverse society it’s meant to serve.
How AI Could Grow Jobs: Inventing New Ones, Empowering Existing Ones
While AI will certainly displace some jobs, such displacement has occurred long before AI was on the scene. In the past century, we’ve seen the demise or diminishment of titles like travel agent, switchboard operator, milkman, elevator operator and bowling alley pinsetter. Meanwhile, new titles like app developer, social media director, and data scientist have emerged.
Daugherty and Jim Wilson, managing director of Information Technology and Business Research at Accenture Research have co-authored a book titled Human+Machine: Reimagining Work in the Age of AI. In their view, future (and current) jobs include trainers and explainers. Trainers will teach AI systems how to perform and mimic human behaviors. Explainers will liaise between machines and human supervisors.
Chatbots have recently emerged as a new communications conduit for brands and consumers. It’s no secret though that they have often been stiff and offered inappropriate responses. For instance, we might say “It’s raining again. Great,” and humans would recognize the sarcasm. A machine wouldn’t.
Understanding language is one component of perfecting chatbots. Another is empathy. A new wave of startups is injecting the emotional intelligence into chatbot-based communication.
Eugenia Kuyda, cofounder of Replika, said empathetic chatbots like hers rely on human trainers. “In the future I think one of the most interesting areas of knowledge will be knowing human behavior and psychology,” she said. “You have to build chatbots in a way that makes people happy and want to achieve their goals. Without a certain amount of empathy, it’s not going to happen.”
In addition, companies like Facebook and Google use humans to moderate content. Facebook currently employs around 7,500 people for this purpose. Google parent company Alphabet also recently said it planned to have 10,000 people moderating YouTube content.
Trainers bring a human element to AI systems, but “explainers” will bridge the gap between the new systems and their human managers.
C-suite executives, for instance, will be uneasy about basing decisions on “black box” algorithms. They will need explanations in plain English — delivered by a human — to ease their concerns.
Legislation is another impetus. The European Union’s General Data Protection Regulation, which goes into effect this year, includes the “right to explanation.” That means consumers can question and fight any decision made on an algorithmic base that affects them.
Such explainers will perform “autopsies” when the machines make mistakes. They will also diagnose the error and help to take steps to avoid similar mistakes in the future.
Empowering Workers, Businesses and Industries
Rather than replacing workers, AI can be a tool to help employees work better. A call center employee, for instance, can get instant intelligence about what the caller needs and do their work faster and better. That goes for businesses and industry too. In another example, in life sciences, Accenture is using deep learning and neural networks to help companies to bring treatments to market faster.
In addition to helping existing businesses, AI can create new ones. Such new business include digital-based elder care, AI-based agriculture and AI-based monitoring of sales calls.
Finally, automation can be used to fill currently unfilled jobs. As Daugherty noted recently, there is a shortage of 150,000 truck drivers in the U.S. right now. “We need automation to improve the productivity of the drivers, the lifestyle of the drivers to attract more people to the industry,” he said.
Changes We Need To Make Today
It will likely take a decade or so until some AI technologies become the norm. While that provides plenty of lead time for the transition, few companies are taking action now to train their workers. Another little-noticed problem is that the AI systems themselves are being created with data and algorithms that don’t reflect the diverse American society.
Regarding the former, Accenture research shows business leaders don’t think that their workers are ready for AI. But only 3% of those leaders were reinvesting in training. At a Davos meeting held by Accenture, Fei-Fei Li, an associate professor at Stanford University and director of the school’s AI lab, suggested using AI to retrain workers. “I think there’s a really exciting possibility that machine learning itself would help us to learn in more effective ways and to re-skill workers in more effective ways,” she said. “And I personally would like to see more investment and thought going into that aspect.”
Another issue to address in 2018 is the lack of diversity among the companies creating AI. As Li noted, this lack of diversity “is a bias itself.” Recent research from MIT has underscored this point. MIT Media Lab researcher Joy Buolamwini said she found evidence that facial recognition systems recognizing white faces better than black faces. In particular, the study found that if the photo was of a white man, the systems guessed correctly more than 99 percent of the time. But for black women, the percentage as between 20 percent and 34 percent. Such biases have implications for the use of facial recognition for law enforcement, advertising and hiring.
As such research illustrates, AI may present itself as an alien force of disruption, but it’s actually a human invention that reflects its creator’s flaws and humanity. “The effect of AI on jobs is totally, absolutely within our control,” Cathy Bessant, chief operations and chief technology officer, Bank of America, said in her Davos chat. “This isn’t what we let AI do to the workforce, it’s how we control its use to the good of the workforce.”
This story was produced by the WIRED Brand Lab for Accenture.