萝莉社官网

Photography by Lisa Predko

Artificial intelligence has dominated popular culture for years; it may soon dominate marketing. Scientists, researchers and marketers are looking for the next step to make data self-aware

“If a machine can think, it might think more intelligently than we do, and then where should we be? Even if we could keep the machines in a subservient position, for instance by turning off the power at strategic moments, we should, as a species, feel greatly humbled.鈥� 鈥�

IBM鈥檚 artificial intelligence (AI) platform, , is loquacious; it can tell jokes, answer questions and write songs. Google鈥檚 AI can now and can within hours. MIT鈥檚 AI can . Tesla鈥檚 AI powers the company鈥檚 . All seem to propel us closer to Turing鈥檚 world of machines with more intelligence than humans.

If Turing鈥檚 words now ring true, should we feel humbled or anxious? For many marketers, the anxiety and existential fear has given way to hope and excitement for a new tomorrow. 

鈥淚t鈥檚 exciting, isn鈥檛 it?鈥� says , who has been studying data鈥檚 impact on marketing for 30 years. Dome, who works as a marketing consultant and adjunct professor at University of Chicago鈥檚 Graham School, grows excited as he talks about the possibility of AI: the time it could save marketers, how it can bring companies closer to consumers and its potential to catch customers in stride, saving effort on the business and consumer side. As an integrated marketing communications professional, his excitement about the potential of AI has given way to the belief that AI will completely change branding, marketing, advertising and perhaps the world. 

鈥淛ust think about all the innovations, all the promise of technology,鈥� Dome says. 鈥淚s your life now really that much more convenient? Is it easier? I don鈥檛 know that it is. 鈥� I think in order to be able to fully benefit from a data-driven marketplace, marketers will have to take a broader perspective on problem resolution, and the tribal approaches that Pedro Domingos has articulated are the solution.鈥�

Dome is referring to , The Master Algorithm. This is the future of marketing, he believes. Dome animatedly spins his fingers around a circular chart within the book that explains the need to bring unique tribes鈥攐r philosophies鈥攐f machine learning together, each with their own algorithm.

So certain is Dome that AI is the future of marketing that he has banked his time and money on it with Core7, what he calls his 鈥渆ntrepreneurial sabbatical.鈥� Core7 is, in theory, a marketing platform that applies AI to marketing ecosystems via a 鈥渕aster algorithm.鈥� The algorithm would be licensed to brands and agencies, which he says would create a hyper-speed version of a fully integrated marketing ecosystem. However, Dome has been unable to get the company off the ground; investors have not yet been on board with the idea. It鈥檚 an ambitious goal, he admits, and when he first started pitching the idea two years ago, it was downright audacious. The Core7 team was developing the platform and algorithm and ready to go further, but thus far, Dome has been left to study AI from the outside.  

Dome still believes he鈥檚 on the path to finding marketing AI鈥檚 master algorithm. 鈥淚t may not be me, but it will be somebody like me that will ultimately develop an applicable master algorithm in marketing,鈥� he says. 鈥淚鈥檓 disheartened to some degree, but at the same time I know I am on the cutting edge of where the marketing industry is headed. I know that philosophically, I鈥檓 there.鈥�

What Is Marketing AI?

For many marketers, terms like AI, machine learning and master algorithm may seem akin to a foreign language. In Domingos鈥� words, the 鈥渕aster algorithm鈥� would work much like a key that could open every lock. A professor of computer science at University of Washington, Domingos says this is the big difference between the machine learning he writes about鈥攚hich functions as the limitless key鈥攁nd traditional programming. To keep the comparison consistent, new keys must be created for every lock in traditional programming; if marketers want to track a certain subsegment of customers, they must create a new algorithm for each. 

鈥淭he beauty of machine learning,鈥� Domingos says, 鈥渋s you don鈥檛 have to program the computer to do any of these things. The same algorithm will learn to do all of them depending on the data you give it.鈥�

Domingos describes AI as a subset of computer science, in which computers can undertake reasoning and common sense tasks鈥攕uch as vision and knowledge鈥攚hich were formerly only undertaken by humans. 

Stuart Russell, professor of computer science and Smith-Zadeh professor in engineering at University of California, Berkeley, describes AI a bit differently on his website: 鈥淚t鈥檚 the study of methods for making computers behave intelligently. Roughly speaking, a computer is intelligent to the extent that it does the right thing rather than the wrong thing. The right thing is whatever action is most likely to achieve the goal, or, in more technical terms, the action that maximizes expected utility. AI includes tasks such as learning, reasoning, planning, perception, language understanding and robotics.鈥�

is a subset of AI that allows computers to learn the same way people do, only faster, without being explicitly programmed, Domingos says. Machines can rapidly change, grow and create when new data is inputted into the system. In theory, this means a program might be able to do years of work in the span of days or even moments. It is, Domingos says, the fulcrum of AI and what gives computers potential to learn, hold conversations, seem human and potentially create their own marketing algorithms. 

鈥淎I is the goal; AI is the planet we鈥檙e headed to,鈥� says Domingos. 鈥淢achine learning is the rocket that鈥檚 going to get us there. And Big Data is the fuel.鈥�

The central idea for Domingos鈥� 鈥渕aster algorithm鈥� is to take algorithms from the five machine learning schools of thought (Bayesians, Evolutionaries, Connectionists, Symbolists and Analogizers) and meld them into one. The Core7 concept would shrink this down to an industry-specific basis, Dome says. For example, the automotive industry could have a single master algorithm, as the customer journey is essentially the same at each company. This master algorithm would, in theory, add efficiency, increase ROI and allow brands to develop a customized relationship at the consumer level that would revolutionize branding. While Dome鈥檚 dream has yet to be fulfilled, Domingos already sees an entryway within the marketing industry. He believes that in five to 10 years, machine learning will be used beyond marketing and across entire companies.

鈥淭he first can be segmentation 鈥� but then it spreads to everything else,鈥� he says. 鈥淲hen you look at companies like Amazon and Google鈥攖he most advanced in machine learning鈥攖hey use machine learning in every nook and cranny of what they do.鈥� 

In fact, Amazon has become so good at machine learning that a third of its business comes from a machine learning-powered function: recommended purchases. Similarly, Domingos says approximately three-fourths of movies watched on Netflix come from the company鈥檚 recommendation system, which also runs on machine learning. 

鈥淭he recommended system is very famous at Amazon, but it鈥檚 one of many,鈥� he says, calling this 鈥渜uintessential machine learning.鈥� 鈥淭hey鈥檝e become good enough at this that they鈥檙e starting to roll out what they call 鈥榩redictive delivery,鈥� in which they send you stuff before you even order it. They鈥檙e so confident you want it that they just put it on the truck. I鈥檝e asked them, 鈥榃hat happens if I get this and I don鈥檛 want it?鈥� They say, 鈥榃ell, we鈥檒l just let you have it for free.鈥� This is how confident they鈥檝e become in their ability.鈥�

While Domingos says Amazon has yet to pinpoint exact future purchases, the company is adept at stocking items on the delivery truck with the knowledge that someone will order that item within hours. 

This concept could solve a real challenge marketers have: hitting the customer 鈥渋n stride,鈥� not just having them come to you, but knowing when they stop and start, where they travel and what they need. Knowing their desires, more or less, and having the ability to communicate with them via AI chatbot programs or automated messages without wasting employee time. The potential of AI allows companies to use data already at their disposal to measure in real time, learn more about the customer and anticipate what happens next.

鈥淭oday is very much a race to who can develop the master algorithm first,鈥� Dome says.

---

Marketing鈥檚 Quest for Singularity 

鈥淥ur technology, our machines, are part of our humanity. We created them to extend ourselves, and that is what is unique about human beings.鈥� – Ray Kurzweil, futurist, computer scientist and inventor 

When Markus Giesler was a child, he was floored by the idea of the profoundly villainous HAL 9000, a conceptual AI from Stanley Kubrick鈥檚 鈥�2001: A Space Odyssey.鈥� He was so titillated by the idea that he and a friend tried to recreate a good-natured version of HAL in his own home. For weeks, Giesler would videotape his parents as they entered and exited rooms. He analyzed their language and noted their moods, realizing his AI would have to be tailored to his parents鈥� experiences to deliver the realism of HAL. 

鈥溌芾蛏绻偻鴗 a month or two later, we had finally established a constellation that worked: every time our parents entered the room they were able to have a one-minute conversation with a computer. Not really the most elaborate chat but enough to impress them鈥攁nd the occasional guests,鈥� . 

Giesler, who is the chair of the marketing department at York University鈥檚 Schulich School of Business and director of the Big Design Lab, researches AI concepts further down the path of his childhood creation, such as smart homes and driverless cars. However, humans were interested in AI long before his adventures with HAL, all the way back to antiquity before the Middle Ages, he says. There has always been a longing for what he calls 鈥渢echnology with a spirit.鈥� 

鈥淚t鈥檚 surprising to me that we鈥檙e only now beginning to see AI as a marketing construct and as something to look into from a marketing and customer experience design standpoint,鈥� he says. 鈥淚t makes sense for it to become more mainstream now when you consider the influx of AI algorithms, apps and mechanisms coming into everyday consumption, but artificial intelligence is not necessarily a new thing.鈥�

What has changed is the awareness of AI, particularly in marketing. This awareness seemed to begin with a bang in 2012 with the infamous story of Target accidentally figuring out a young woman was pregnant before her father did by automatically analyzing her shopping habits and sending her advertisements for baby necessities. Now, perhaps startled by the technology鈥檚 abilities, companies have convinced themselves of AI鈥檚 impact. In a June 2016 report, with 55% of CMOs expecting AI to have a 鈥済reater impact on marketing and communications than social media ever had.鈥� This change in awareness may go a long way toward marketing and other industries accepting AI. Giesler says a shift in the decision-making process takes as much change in humans as it does in technology.

鈥淚 am most fascinated with AI in marketing when it鈥檚 invisible,鈥� he says. 鈥淚t鈥檚 one thing to talk about AI as this [creation of] applications that totally immerse consumers into these extraordinary experiences. It鈥檚 another to see how AI has invisibly crept into some of the most taken-for-granted aspects of everyday consumption to shape who we are as individuals, who we are as families, how we think about safety, togetherness and all this. One level on which we see that is cellphones having become an extension of who we are.

鈥淎I is dramatically reshaping and redefining not only the market and what companies can or cannot do with customer experience, but who we are as individuals and groups,鈥� Giesler says.

Writer Robots

In a towering office building off of the Chicago River sits a notable example of AI鈥檚 current and potential capabilities. , a natural language generator, has become well-known by marketers for its ability to produce written stories within seconds based off analytics. The company鈥檚 AI can use data from Google Analytics, for example, and write sentences like: 鈥淣ew users spent 16 fewer seconds on your site than returning users did last month. This could indicate that your new users didn鈥檛 铿乶d the information they needed or came to the site expecting something else.鈥� 

Katy De Leon, vice president of marketing at Narrative Science, says she couldn鈥檛 believe the company鈥檚 claim when she first read the job ad four years ago. 鈥淚t just sounded incredulous to me,鈥� she says. 鈥淚 needed to talk to someone about it because I just couldn鈥檛 believe it.鈥�

After four years of seeing AI in action, De Leon is a believer in not just Narrative Science, but in the potential for AI in marketing. AI has come at the right time with the explosion of Big Data, she says, and her company鈥檚 capabilities are especially mind-boggling at first glance for those on the outside. Narrative Science, born at Northwestern University as a collaboration between a computer science class and a journalism class, received coverage early in its existence when journalists at were awed by a tool that could put together sentences from raw data鈥攊n this case, reports from sporting events. Now, the most lucrative customers of Narrative Science are in the government and the financial industry鈥攖hink Fortune 1,000鈥攁s well as web analysts and small to medium-sized marketers.

Eyes across the industry are on the marketing tech landscape, which even De Leon admits is getting crowded and noisy. However, with increasing access to data, it鈥檚 never been more important for organizations to make sense of the noise. AI is another tool marketers can have at their disposal with potential for saving money, increasing efficiency and improving business. 

鈥淲hen you have 20,000 customers and you want to communicate with them as if you know them very well and 鈥� communicate something relative to them鈥攕omething they care about鈥攚e can enable them to get to that level of personalization at a scale that wouldn鈥檛 be possible with people,鈥� she says.

Where is Marketing AI Going?

Marketers should expect quick changes with AI鈥檚 potential to build upon and grow itself, experts say. Businesses and marketing departments are already vigorously moving ahead with the adoption of AI technology, according to . They are eager to see its promised benefits come to fruition.

鈥淚t鈥檚 not just about automation for automation鈥檚 sake, but if we can go faster, there鈥檚 more money to be made,鈥� she says of the average company鈥檚 mentality. 

How humans view technology, especially in marketing, has progressed over the past five years, Quoirin says, and it鈥檚 likely to keep progressing at breakneck speed. There are many possibilities for AI in marketing, health, entertainment and business; the technology is just starting to bear fruit, she says. 

One possibility sure to entice across industries is what Quoirin calls 鈥渂eyond human鈥� AI, which can be used to 鈥渃heat death,鈥� as well as add human bio-enhancements, prosthetics or implants. This could work well in the medical field, of course, but she says it may also work from a customer experience perspective. Marketers could find interest in tools for performance improvements for the average person; ways to burn calories, eat well, work faster and move better, especially considering the success of gadgets such as the FitBit. 

鈥淏roadly speaking, we tend to find that as soon as people are using [technology] like this in a context where it helps them get things done faster, they adjust to that convenience very quickly,鈥� she says. 鈥淲hat we see is that it is a question of 鈥榳hen鈥� rather than 鈥榠f鈥� with AI. But it will happen bit by bit. A lot of the things we worry about will just gently recede as we get used to being better humans.鈥�

AI advancements may also change the concept of who we are and how marketers interact with humans and their technological extensions. Giesler says how consumers represent themselves online, how machines become an extension of who we are and whether marketers should market to these technologies once they gain a certain kind of sentience are all concepts he actively studies. 鈥淭hat鈥檚 wicked, right?鈥� he says with a laugh. 

Gieseler has done his own research on where humans end and where machines begin, which he says is an unbelievably fascinating and terribly scary new frontier to study. This inevitably leads to questions about how people live, how their habits are measured and how they鈥檙e watched by government-run AI technology, such as facial-recognition software鈥攁nother budding AI concept. This brings to light existential fears of society becoming a bit too similar to , causing many to demur at the thought of AI鈥檚 rapid progress. Through all of these possibilities and theories, Giesler believes marketers can take center stage in redefining and renegotiating the boundaries of where the human ends and where technology begins. It鈥檚 an onerous duty filled with opportunity. 

鈥淲e are the ones who best understand the human technological interfaces and how to design markets that are truly better than the sum of their parts when it comes to these redesigned interfaces,鈥� he says. 

Apple is the best example of this thus far, Giesler says. He鈥檚 assisted in Apple鈥檚 research and says Apple TV鈥攁 recent advancement that Steve Jobs called simply a 鈥渉obby鈥濃�攊s .  

鈥淔or a long time, Apple adopted this top-box approach where you have the Apple TV box next to other cable boxes. That probably didn鈥檛 work,鈥� Giesler says. 鈥淭he difference came when Apple recognized that consumption is really more a matrix than an individual box with a person looking at a TV screen. If you want to conquer the living room, you really need to spread all through the home.鈥�

By seeing the market as more of a matrix, he says Apple cleared the path for marketers to use interfaces that let consumers better navigate their lives. Enabled by AI, Apple and researchers made these advancements after looking through the lens of today鈥檚 technology-enabled world. 

鈥淎I leads to changes in the way we do marketing, not just in the tech space literally, but also metaphorically, in terms of how we understand brands, customers and market segments,鈥� he says. 

Will Marketing Jobs Be Safe?

Upon hearing about AI鈥檚 capabilities, many will ask, 鈥淲hat鈥檚 the catch?鈥� There are the existential fears expressed by . There are fears that AI could occupy the citizenry鈥檚 space too heavily and be seen as an invasion of privacy. Then there are palpable fears of AI taking jobs away from marketing and many other industries. After all, robots and computers don鈥檛 make a yearly salary. 

According to a June 2016 report from Forrester, AI, machine learning, robots and automation will mean a net loss of 7% of U.S. jobs by 2025. The technology will mainly eat away at office and administrative support staff. New jobs, such as content curators, data scientists and robot monitoring professionals, will be created, but the losses will be greater than the gains.

鈥淚 think there will be an impact on jobs; we call this trend de-pop in the sense that working at large is going to change,鈥� Quoirin says. 鈥淭here will be competition for jobs. Equally, the new jobs will create new demands 鈥� We do see a shift in that.鈥�

Even with fears of job loss looming in marketing and across other industries, Domingos says humans will still be necessary due to a paucity of data scientists, or those who automate the work of computer scientists and create AI algorithms. These algorithms have potential to take jobs鈥攁 factor of 1 million, when you talk about automating the jobs of computer scientists, Domingos says鈥攆rom many people, but there鈥檚 a lack of data scientist talent. 

鈥淭he war for talent is really raging,鈥� he says. 鈥淥ne reason the demand has exploded and the supply changed quickly is you need people with a Ph.D.; that takes five years. … The irony is a lot of the professors are moving to the industry level, which is good in the short term but it鈥檚 actually eating the seed corn. There are not enough people to train the students.鈥�

This may come as a breath of relief for marketers, but Quoirin says marketers should expect the necessity for a transition of skill set and talent management to more creative and conceptual endeavors, areas where humans thrive over machines.

鈥淟et鈥檚 not be too vanilla on this: If we take a sector like finance or retail baking, there will be an eye on how many tellers can be replaced,鈥� she says. 鈥淭hose numbers of cost cutting will have been done already. But let鈥檚 face it, without even a hint of what鈥檚 to come in AI, those jobs were under threat. Simple computer processing and mobile banking have already threatened those kinds of things. Artificial intelligence is much beyond that level of cost cutting. People are mostly thinking about how they can rechannel mundane jobs.鈥� Although Quoirin believes AI will be 鈥渦nstoppable,鈥� she says humans will still be needed to interpret AI鈥檚 signals and numbers. 

AI is expected to keep growing. Neuroscientist and author Sam Harris, who presented a to lose control of AI, said on his podcast 鈥淲aking Up鈥� that AI鈥檚 growth will keep advancing unless something much worse happens to society first. For this reason, Quoirin believes menial jobs will eventually be replaced by the robots, which may mean an alternate solution, such as a minimum salary for all, needs to be considered. 

鈥淭here is, of course, also the future where we just work less,鈥� she says. 鈥淎nd we get longer weekends. Wouldn鈥檛 that be fantastic?鈥�

The Way Forward: Excitement or Fear? 

鈥淪ome people worry that artificial intelligence will make us feel inferior, but then, anybody in his right mind should have an inferiority complex every time he looks at a flower.鈥� 鈥� Alan Kay, computer scientist 

AI鈥檚 marketing moment may be coming soon, if it isn鈥檛 already here. Domingos says Silicon Valley had its AI tipping point five years ago but kept it to themselves as a 鈥渟ecret sauce,鈥� of sorts, for competitive advantage. Now, the proverbial cat is out of the bag and he says CEOs of Fortune 500 companies demand AI. 鈥淚 don鈥檛 know what it is yet, but I know we need it,鈥� Domingos says, doing his best CEO impression. However, he believes adopting AI will be easier for digitally native companies鈥攕uch as Facebook and Google鈥攐r industries like marketing or finance where data has been essential from the start. 

鈥淭he companies furthest along also happen to be in sectors where they have profit margins large enough for them for afford machine learning efforts,鈥� he says. 鈥淚f you鈥檙e Google and you [essentially] print money, you can afford to spend money on machine learning and you do. If your profit margins [are 1% or 2%], then it鈥檚 harder. They can only afford to do it so much because they don鈥檛 have money to do more.鈥�

For the Doug Domes of the world, this makes AI look that much more enticing. Dome believes AI has 鈥渓imitless鈥� potential for profitability and says the positives of the technology will be immense, even if there are some ethical and moral bugs to work out. 

In Giesler鈥檚 view, the negative predictions of AI have always been around; he鈥檚 always heard that his beloved HAL 9000 would be created in real life. However, despite advancement, he thinks AI is still far away from the ability to snuff out humans. 

鈥淭here is something about being human that is unique,鈥� he says. 鈥淭here are simple mechanisms we can use to unmask the technology as what it is: a stupid series of algorithms that doesn鈥檛 really get it. That鈥檚 still pretty much the reality of everything we have around us.

鈥淎ll the beautiful things we associate with marketing, they are and will continue to be the human actors and the human participants, not so much the technology,鈥� Giesler says. 鈥淭he beauty of real technology is that it鈥檚 like a mirror: We look inside it and what we see is who we are as human beings. Markets are human. The technology helps us get closer to the beauty of that principle.鈥�