The Rise of AI in the Age Of Digital Connectivity

FUTURE TREND REPORT

the rise of ai in the age of digital connectivity NOTTINGHAM TRENT UNIVERSITY FASHION MARKETING & BRANDING Year 3 Semester 1

PREPARED BY ANASTASIIA SOROKINA N0669209

NOVEMBER 2017

The Rise of Artificial Intelligence in the Age of Digital Connectivity

Future Trend Report

Anastasiia Sorokina Tutor: Naomi Braithwaite

Nottingham Trent University School of Art & Design BA (H) Fashion Marketing & Branding Year 3 Semester 1 November 2017

Word Count: 2995

TABLE OF CONTENTS

1

INTRODUCTION

2

TREND ORIGIN & DRIVERS

6

AI IN HEALTHCARE

8

AI IN TRANSPORTATION

9

AI IN FASHION & LIFESTYLE

13

UNCERTAIN FUTURE

15

CONCLUSION

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BIBLIOGRAPHY & LIST OF ILLUSTRATIONS

Fig.1

intro In 2017 digital technology is ubiquitous - people are constantly connected to it to fulfil all kinds of their needs. Digital connectivity is what a person in many countries faces every day communicating with people, getting and sharing various types of information, knowledge, entertainment, services and products through his digital devices.

Therefore, the amounts of online data grow at inconceivable pace. For a human it is impossible to sort and analyse such abundance of digital information which called “Big Data”.

People have been using this term for two past decades to indicate the phenomenon (Lohr, 2013); however, innovative solutions and approaches to it as well as raised ethical discussions make it one of the most relevant subjects in the world right now.

Indeed, there is a limitless potential in getting Big Data systematised and optimised for an accurate detection of various patterns in society, environment, economy and, even, human health; all of which can catalyse the exponential improvement of people’s lives in every imaginable and, probably unimaginable way.

This report aims to explore how digitally connected world became a premise to the rise of artificial intelligence and machine learning, how this technological macro trend is evolving and affecting different industries as well as consumer behaviour and the future scenarios the trend may bring. The report is supported by explicit secondary research materials which included books, journal articles, latest reports, films and various credible online sources.

1

DATA IS A NEW SCIENCE. BIG DATA HOLDS THE ANSWERS Pat Gelsinger, CEO of VMware, Inc. (Forbes, 2012)

THE RISE OF AI IN THE AGE OF DIGITAL CONNECTIVITY

trend origin & drivers According to the latest Smart Insights infographic on Digital Marketing, there are more than 3 billion Internet users in the world which is around 40% of global population. Widespread digital technology changed people’s lives irrevocably in a relatively short span of time. The revolution started from introducing personal computers to the market in the late 1970s and expanded enormously with mobile phones penetration.

Fig.2 IBM Simon (on the left) and iPhone 4 (on the right)

40% OF GLOBAL POPULATION USE INTERNET Smart Insights, 2017

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One of the first smartphone prototypes, IBM Simon, was on the market already in 1994 (Fig. 2). However, Steve Jobs was the first to use a word “smartphone” while presenting first-generation iPhone in 2007. The development of smartphones has been accelerated ever since. Every year tech corporations like Apple, Google, Samsung or any other one introduce their latest innovative gadgets promising new experiences, prolonged battery life and advanced efficiency to the customers. Being digitally connected with the latest device has become as essential as refreshing a wardrobe.

The rise of social media and decreasing cost of internet access has triggered the growth of online engagement. The instant access to the web at just a few fingertips reformed the way people think and interact with each other.

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People no longer rely only on their memory and knowledge on a daily basis because they can find a relevant information from a credible source within few seconds. Which makes scientists debate on whether it weakens our own memory capacity or just changing the way we learn and remember. (Sanders, 2017).

Nevertheless, in Digital Age people have the possibility to prioritise their self-actualization instead of spending time on fulfilling their basic needs.

Uber solves the problem of catching a taxi on the sidewalk or booking taxi through the call and wondering where it is. Deliveroo connects the user to the restaurants and cafes around his location and delivers the orders within a specific timeframe. Whatever the person need is, in many cases there will be an app for that.

Fig. 3 Maslow's Hierarchy of Needs

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Focusing on the top of Maslow’s hierarchy of needs (Fig.3) people are going to enjoy their life more than those who are fulfilling only physical needs (Maslow, 1999).

Complete optimisation and acceleration of all processes that take too much time to perform for a human is the key to the realisation of his full creative potential in a significantly shorter time frame. If everyone is a creator in his field of interest, the evolution of humankind will gain unprecedented speed.

Therefore, Artificial Intelligence got a new surge of interest and this time it is very promising to change the world.

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THE ORIGINAL QUESTION IS "CAN MACHINES THINK?"

- Alan Turing, Mechanical Intelligence

Fig.4 R.U.R

Even though, the thoughts of what we call “robots” today had intrigued the minds of people long before computer development in the middle of twentieth century - it was illustrated in Greek myths (the inventions of the god Hephaestus like bronze automaton Caucasian eagle sent by Zeus to gore Prometheus every day as his punishment) as well as in Mary Shelley’s Frankenstein (1818), where a scientist becomes a creator of human being with scientific methods (Hope, 2015).

In 1920 Karel Capek wrote the play R.U.R. (Rossum’s Universal Robots), coming up with the word “robot” which derived from Czech “robota” meaning forced labour.

There he introduced the idea of human-like machines, threatening to humankind when their intelligence exceeds beyond people's understanding (S. Cook, 2016).

The term “AI” first was brought by John McCarthy on Dartmouth Summer Research Project on Artificial Intelligence, first academic conference, relevant to the subject in 1956.

Nonetheless, solid ideas of cognitive machine thinking were introduced earlier

by Vannevar Bush in his paper As We May Think (1945) and Alan Turing in his work Computing Machinery and Intelligence (1950), where he raised the question whether machines can think and deliberated about how such machines can be made and the way of measuring their intelligence which is well-known as Turing test (Anyoha, 2017).

Turing test is based on Imitation game, its purpose to determine the ability of the computer to think like a human. In the game the judge corresponds with one man and one woman, trying to distinguish one from another, the same way the judge needs to understand whether it is a machine or a human that sends him replies.

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Since then, the development of artificial intelligence had had some setbacks called AI winters. Even though the subject was heavily popularized in mass culture and scientists were very optimistic about the future of the machines - the technology excitement has been followed by the decrease of funding and interest several times due to relatively deliberate progress pace.

In 2012 Deep Learning breakthrough performed by Google and inspired by neuroscience has shown the world that machines can be smart if they learn from their mistakes gaining layers of artificial neural networks while presenting the ability of their neural network identify cats after studying 10 million images (Marr, 2017). Just like kids get the intelligence from the experiences that come from observation, evaluation and decision making, computers proved to be able to process an unstructured data (images, audio, video, text) Â based on their previous experience.

Fig.5

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ai impact on industries Healthcare

Through centuries people were trying to find a way of prolonging their lives. Ageing, physical vulnerability including the threat of unknown viruses and diseases have been the pillars on which healthcare stands.

Today biology, as well as neurology, are strongly connected to the technology world. Tracking the health of millions of people helps specialists enormously to conduct a better medical research and come up with brilliant solutions.

People’s willingness to share and track their own health through digital technology has widened the horizons for scientists and medical researchers.

However, allowing the machine to process the data on human health can lead to much faster results. AI is already starting to define “New Health� (PwC, 2017).

Firstly, it is able to significantly cut the time of drug research and discovery. It takes 10 to 15 years to develop a drug; however, less than 12% of them get approved. AI guidance has potential to fasten the process and minimise chances of fail.

BERG Health company, founded in 2006 with the mission to find better solutions and treatments to diseases like cancer and diabetes, it uses AI along with in-the-lab drug development. In 2013 the company started a research and development of pancreatic cancer treatment. In three years with the help of AI, the first phase was completed. Researchers got a deep understanding of the disease functioning model and what catalyse its progress. In 2016 company started the second phase of drug development - trials, which they aimed to complete in 18 months (Fortune, 2016).

Therefore, BERG Health has liable chances to become the first company that successfully implemented a machine cognitive thinking to the human drug development.

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Where we're Going Before even typing your report, first take the time to consider who the report is for. One good rule of thumb to remember is that the higher up the stakeholder is in the organizational ladder, the more succinct the report needs to be.

With the myriad of metrics social media marketers have access to, it’s tempting to drown your audience in numbers. While figures aren't bad per se, you do have to make sure that these are relevant to the role of those receiving the report. Strive to tell the story behind the numbers by including learnings or insights.

Fig.7 IBM Watson

Another important change that AI brings to the healthcare industry is a new approach to diagnostics.

Human factor plays a big role in medical advisers’ decisions and conclusions. People tend to misinterpret the information and make mistakes. Even though doctors have to approve their qualifications frequently to prove their proficiency, diagnostic accuracy will never reach one hundred percent.

With machine cognitive system like IBM Watson Health, it is possible to

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minimise medical errors allowing the machine to dive into the world of medical data which doubles every 3 years and turn it into knowledge (IBM, 2017).

From the research of University of North Carolina School of Medicine after analysing 1000 cancer diagnoses Watson found treatment options in 30 percent of cases where the actual doctors missed those (Galeon, 2017).

This indicates that AI potential in healthcare is huge and the industry transformation is happening now.

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Transportation

In digital fast-paced world transportation industry embraces the changes. Competition is tough and successful transportation and travel companies understand the importance of delivering value and memorable but seamless experience in whole to the customer.

Transport is one of the things that people do not want to spend too much of their own resources.

They demand it to be fast, safe and affordable.

Companies are driven to give consumers what they want and embrace the rise of sharing economy and AI. Uber, a tech company that has made usual taxi irrelevant, has its own AI lab where the researchers are working on “self-driving cars, urban aviation, optimising cities, and keeping riders safe” (Uber, 2017).

In fact, self-driving cars which are operated by AI is not a far future. In 2016 startup called nuTonomy from the US partnered with company Grab which is Singapore local rival to Uber and had done first trials of self-driving cabs. This year they announced that testing will be already available to the public in 2018 in Singapore (Reuters, 2017).

Considering more luxurious transport experience, Elon Musk, the CEO of Tesla, promises that the combination of radar and AI makes the vehicle safe and smart enough to know passenger’s destination without asking directly because of the connection to his other devices, which now called the Internet of Things. With the growth of Tesla customers, proportional rising connectivity will be enhancing the experience constantly.

Connected and smart personal and public transport is what being developed year by year. However, It is very important for transport tech companies to build trust with the customer because most people still hesitate towards self-driving cars (Goldberg, 2017).

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Fig. 8 Self-driving car

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fashion & lifestyle

Fig. 9 Burberry in Hong Kong

According to Business of Fashion report State of Fashion 2017, 29% of executives in Fashion industry see Digitalisation & E-commerce as the biggest opportunity.

website software can get insights instantly and minimise any miscommunication or inconvenience predicting what the customer would like to buy.

Digitalisation keeps growing among fashion companies on every level - from design to marketing. Implementation of AI to the business model happens at a slower pace; however, some businesses start to prepare for another tech revolution now to get an advantage in front of competitors.

Also, with the past experience of being heavily counterfeited, Burberry has the technology by Entrupy which helps to detect not authentic product right away by just photograph of product’s tiny part that shows weaving and texture (Marr, 2017).

One of the major examples is Burberry which uses Big Data for sales and increase of customer satisfaction. They encourage customers to share their purchasing history and information so the shop assistant in a brick-and-mortar store or

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Artificial Intelligence is changing all processes within fashion industry from design and manufacturing to retail experience and marketing.

THE RISE OF AI IN THE AGE OF DIGITAL CONNECTIVITY

Artificial Fashion Design

Fig. 10 Chanel SS'17

Amazon research centre Lab125 presented a concept of AI fashion designer. Through learning styles by looking at lots of examples software consisting of deep neural networks can generate a design of similar clothes (Knight, 2017). It does not specifically mean that it will replace all fashion design jobs straight away but rather will be a tool in hands of senior designers that cannot keep up with the pace that fashion trends change today.

Even the most talented man has the limitations to his creativity, designing collections like a conveyor is exhausting.

However, human designers could focus on their best ideas and give directions to the software for designing more commercialised designs for sales so they could concentrate on creating something exceptional.

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Sewing Robots Startup Sewbo from U.S. has developed a machine that has a potential in sewing full garments and which is already able to sew a whole T-shirt. Zornow, the founder, realised that it is easier to manipulate fabric to make it a hard material so the robot could work with it.

Liquid polymers that he used for that easily wash out with water leaving a quality sewed piece of clothing (Fast Company, 2017).

Fig. 11 Sewbo, sewing robot

The company is only one year old but the invention rises a lot of questions about future of manufacturing.

Currently, most of the fashion manufacturing is happening in Asia, often in less developed countries like Bangladesh or Cambodia.

Bringing manufacturing back to the developed world would definitely bring a lot of bonuses and advantages to the country of origin; however, millions of factory workers in Asia will lose their jobs.

Further automation of manufacturing is inevitable and it is going to change the whole retail business model.

Enhanced Customer Experience Improving efficiency in retail stores is another important tendency in the fashion industry.

According to the forecast of The Future of Jobs 2015 report, 76 percent of different sales tasks will be performed by robots in store by 2022 (Abnett, 2016).

In 2017, 45 percent of retailers said they plan to “utilise artificial intelligence within three years to enhance the customer experience” (Wilson, 2017). Moreover, some of the brands already do it.

American department store, Neiman Marcus embraces image recognition technology offering their customers the feature Snap.

Find. Shop - so the customers can take the picture of what they would like to find (it does not matter if it is not the product of the store).

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The software shows you similar products that Neiman Marcus has and gives you different options.

Also, interaction with chatbots become more common. IBM claims that 65 percent of millennials prefer interacting with bots rather than have a phone conversation with agents (Young, 2016). One of the first popular brands that experimented with it was Tommy Hilfiger in 2016 when collaboration with Gigi Hadid was introduced. -forbes That collection sold out very well and social media were excited about the whole experience the brand built through the events and tech innovations.

AI is shaping a new customer service model which is more efficient but human interaction is still important, so the formula of impeccable customer service is combining both.

Fig. 11 Sewbo, sewing robot

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Fig. 12

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uncertain future The future of AI in a digitalised connected world is certain only in a sense that it is an irreversible process of getting machines more intelligent.

However, the opinions of famous researchers, scientists and entrepreneurs differ.

Living in a connected world of smart devices and smart cities will allow more people to work on selfactualization but most importantly AI can make people live longer. It has the ability to turn us into Superhumans with endless access to global knowledge and devices embedded in our bodies.

Despite that, after being exposed to Hollywood dystopian realities where machines are rather destroying the human world than enhancing it (like Terminator) it is not hard to imagine such scenario. Nonetheless, theoretically technological singularity when machines outweigh human brain is possible. At some point, the machine intelligence will not be understood and in that case, it will be a threat to human existence because people are afraid of what they can not understand by their nature.Â

To avoid the worst scenarios, people will probably have to think on the ethical use of machines and how to put those ethics to the machine itself.

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The more obvious negative consequence is unemployability. Many jobs in service, banking and manufacturing will be taken away by intelligent machines and it is not clear whether new vacancies will be open for those people.

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Fig.15 Elon Musk

AI IS THE BIGGEST RISK WE FACE AS A CIVILISATION

Elon Musk (Telegraph, 2017)

Fig.16 Mark Zuckerberg

EVERY TIME WE IMPROVE OUR AI METHODS, ALL OF THE SYSTEMS GET BETTER. I’M EXCITED ABOUT ALL THE PROGRESS HERE AND IT’S POTENTIAL TO MAKE THE WORLD BETTER

Mark Zuckerberg (CNBC, 2017)

AI WILL BE EITHER THE BEST OR THE WORST THING, EVER TO HAPPEN TO HUMANITY

Stephen Hawking (The Guardian, 2016)

Fig.17 Stephen Hawking

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conclusion To summarise, it must be said that the trend of machine learning is not new; however, it has a huge potential to evolve now, when with existing technological level society is ready for a big but gradual change. That change will affect all of the industries and, therefore, companies should consider starting adapting early before all market gaps are closed.

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THE RISE OF AI IN THE AGE OF DIGITAL CONNECTIVITY

List of illustrations Fig. 1 Cover. Neurons. (2017). [image] Available at: https://www.pinterest.co.uk/pin/366269382181634644/ [Accessed 8 Nov. 2017].

Fig. 2 IBM Simon. (2017). [image] Available at: http://time.com/3137005/first-smartphone-ibm-simon/ [Accessed 8 Nov. 2017].

Fig. 3 Maslow Hierarchy. (2017). [image] Available at: https://www.simplypsychology.org/maslow.html [Accessed 8 Nov. 2017].

Fig. 4 R.U.R. (2017). [image] Available at: http://paleofutur.gobelins.fr/2014/g2/ [Accessed 8 Nov. 2017].

Fig. 5 Hands. (2017). [image] Available at: https://yourstory.com/2015/05/buysmaart-com-artificial-intelligence/ [Accessed 8 Nov. 2017].

Fig. 6 Doctor. (2017). [image] Available at: https://www.verdict.co.uk/ibm-startup-docdok-health/ [Accessed 8 Nov. 2017].

Fig. 7 IBM Watson. (2017). [image] Available at: https://technical.ly/baltimore/2015/10/05/best-maryland-healthcare-startups-emocha-avhana-sisuvasoptic/ [Accessed 8 Nov. 2017].

Fig. 8 Self-driving Car. (2017). [image] Available at: https://www.digitaltrends.com/cars/self-driving-car-moral-decisions/ [Accessed 8 Nov. 2017].

Fig. 9 Burberry HK. (2017). [image] Available at: http://www.borseline.com/index&manufacturers_id=4.html [Accessed 9 Nov. 2017].

Fig. 10 Chanel SS17. (2017). [image] Available at: https://qz.com/1062257/amazons-new-ai-algorithm-designs-clothes-without-human-designers/ [Accessed 8 Nov. 2017].

Fig. 11 Sewbo. (2017). [image] Available at: https://www.youtube.com/watch?v=sjjzo3c7b_8 [Accessed 8 Nov. 2017].

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Fig. 13 Terminator. (2017). [image] Available at: http://cdn2-www.superherohype.com/assets/uploads/gallery/terminator-genisys/terminatorgenisys-018.jpg [Accessed 8 Nov. 2017].

Fig. 14 Tech Singularity. (2017). [image] Available at: http://www.historyextra.com/article/ancient-greece/7-phases-history-artificial-intelligence [Accessed 8 Nov. 2017].

Fig. 15 Elon Musk. (2017). [image] Available at: https://en.wikipedia.org/wiki/Elon_Musk [Accessed 8 Nov. 2017].

Fig. 16 Mark Zuckerberg. (2017). [image] Available at: https://imanila.ph/2015/10/12/5-things-about-mark-zuckerberg-that-will-give-you-themotivation-you-need/ [Accessed 8 Nov. 2017].

Fig. 17 Stephen Hawking. (2017). [image] Available at: https://www.youtube.com/channel/UCPyd4mR0p8zHd8Z0HvHc0fw [Accessed 8 Nov. 2017].

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