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The US election of Donald Trump, used the digital canvassing. Election advertising played a great role. The objective is to reach the maximum number of people and influence them. Several demographic components are addressed, e.g. salaried class, businessmen, farmers etc. These days advertising goes beyond this. It takes into account the temperament of the voters. A firm called Cambridge Analytica exactly did this. It concentrated on the 17 states of the US. They collected maximum data of the people in these states. To illustrate, what cars they have used and are using, their economic condition, their purchase behaviour, their methods of entertainment. Such data is available through some companies. Another source was to get the data from Facebook. A researcher from Cambridge Analytica has developed an app to assess personalities on Facebook. This researcher was Alexander Kogan. You have to answer questions like — whether you lose temper early, whether you like to interact with people. Depending on your answers, a judgement can be made about your personality. It is called psychometry. Psychometry measured individuals on Facebook against five dimensions — openness, conscientiousness, extroversion, agreeableness and neuroticism. It is called OCEAN model. You can predict the likes, dislikes, fears, intellect based on this. It can predict the decision making of an individual under certain circumstances.

Rogan’s information collected from Facebook facilitated the design of the model by Cambridge Analytica, which was used in the elections. It was inferred who are likely to vote Trump and who are not likely to vote him. It paved the path to reach the prospective voters and the customised message which would generate a response.

To illustrate, there is one issue in all the elections, whether to have fire arm. Republicans are for it, and Democrats against it. According to OCEAN models, those with high O and N are practical and would love to have gun to protect against thieves. Those who have less O and more A, can be appealed emotionally by saying having a gun is a part of family honour, culture and traditions. Such customised messages are more effective. Trumps canvassing was based on such analysis. The information was used to influence the voters. Can technology be used like this? Is it legal? Is it moral? It was later revealed that information from social media was collected unauthorisedly. There is an issue of credibility of Facebook. Cambridge Analytica was in vortex of controversy and wound up business in 2018.

How Data Is Abused

Jamie Bartlett has written Secrets of Silicon Valley. CA allegedly mined data of 87 million Facebook users, including half a million Indians, for election campaign. His new book is The People vs Tech. Here Bartlett proposes that relentless march of technology could chip away at the pillars of democracy. At present, he is the Director, Centre for the Analysis of Social Media, London.

Michal Konsinki is a psychologist, who is one of the pioneers of psychographics. This is the technique that CA has allegedly used. He is the professor at the Stanford Graduate School of Business. He has developed an algorithm which registers Facebook likes and compares them to other people who have taken the personality test. Then it gives the output — what it considers your personality. It poses a risk in the wrong hands.

Psychographics is powerful and dangerous. It has the potential to manipulate people. It is powerful in close elections where relatively small margins could swing the entire election. Enough key people can be moved one way or the other. The more the data we share about ourselves, the better the technique is going to be.

Election advertising has been there but big data and micro targeting is different. Here politicians are able to send customised, personalised messages. It is like a direct talk. In propaganda, the visible party can be held accountable. Here as the message is personalised, it is difficult to fix accountability. Politics so far used to address a broad collection of people. Here an individual’s concerns and prejudices are addressed. It is divisive politics, and it is emotionally driven.

Alexander Nix, the former CEO of CA denies having used psychographics. He feels targeting and psychographics are the techniques of future.

Theresa Hong, the member of the digital arm of Trump’s presidential campaign contends that Facebook did make a difference. It is due to Facebook that Trump won. Without Facebook, they would not have reached the right people at the right place. Facebook was more important than CA to Trump campaign.

Facebook admits 87 millions users were affected by CA. Most public profiles have their data scraped. Which other companies do this? Europe wants to implement General Data Protection Regulation (GDPR).

What is a meme? It is difficult to explain. The earliest example in advertising is that of an Amul girl with topical, at times satirical and punny, lines on current affairs. The focus is on a twist to a recent event.

Perhaps, the copywriters of Amul had an understanding of how the world would consume information in future — in small, easily palatable bites. Memes do exactly this. They add a twist to the story.

Memes have become a sine qua non of today’s digital discourse. The word has its genesis in The Selfish Gene by Richard Dawkins (1976). In this book memes represented ideas, behaviours and styles that go viral. These memes are counterparts of a gene that gets transmitted from person to person. Virtual memes mimic this.

Reddit as a website made gaming and anime popular among teenagers. Memes came into picture since then. They are the smallest units of internet culture. Memes are politically incorrect. Best memes enter the mainstream social media sites after being in the chat rooms.

Memes are exploited by political parties, social media influencers, marketers and government agencies. Memes enagage users, as they are funny, clever or irreverent. They have the capacity to build a brand.

Memes encourage active participation from anyone and everyone on the Internet. They are shared, liked and commented on. This adds to their virality. They are malleable too.

Meme requires creative thinking, social thinking and brand thinking at the same time. Digital agencies may not have such talents. Advertising agencies do not understand digital. Meme marketing is thus sporadic. Memes are pithy — one or two lines of text. Such creation requires wit, humour and knowledge of what is making news. It has to be made instantly as soon as the event happens. Later the story is too old to be effective.

Lot of misinformation is likely to be converted into memes. Memes need scrutiny and are to be consumed with a pinch of salt.

Messages can be encrypted at the user level or at the server level. WhatsApp messages are encrypted at the user level, and WeChat messages at the server level. SMS messages are at the un-encrypted level. Encryption is for security. Modern encryptions use algorithms to convert message text into random characters and symbols. It can be decoded only using a key.

Symmetric encryption is one of the oldest methods. Ceaser cipher moves each letter by three. This can be used in combination with a symmetric encryption. Symmetric keys can be decipherable over time. That has led to a concept of public keys. These are asymmetric. Suppose you log in to WhatsApp. It generates a public key and a private key. The public key is visible to all. Private key is the real decoder or has encoding value. A message is sent over a public key lands up in another users system where it is decoded using private key. This is called end-to-end encryption. WhatsApp, Telegram, Signal and other message services use this. It used a mechanism called RSA (Rivest-Shamir-Adleman), along with other systems. iMessage has been doing it what WhatsApp is doing now. Signal has a better standard than WhatsApp. It is the gold standard of messaging services.

WhatsApp generates metadata, and though messages calls, bites, photos and videos are encrypted, but not the metadata, and can show who you are talking to.

Telegram offers end-to-end encryption once the service is activated. And such convesations are in secret chat where messages are deleted after a specific time. Telegram, however, leaks more metadata than WhatsApp does.

Signal too has an additional feature called disappearing messages. It deleted within a few minutes or hours or days whatever is on server.

People keep back up of their chats on Google. This means that chats can be decipherable on Google server. Disappearing messages ensure that nothing gets saved on any of the servers.

Despite this, the messaging apps are not completely safe. With malware, nothing is safe. Someone can mask your private key and your public id.

Indian advertising in the beginning of the 20th century was directed to the elite in the British India. Organised advertising started in India in 1905 by B. Dultaram & co,. In 1929, J Walter Thomson ( JWT ) introduced professionalism in advertising. In those days, Hollywood actresses and celestrial models appeared in soap ads. Leela Chitnis pioneered an Indian’s endorsements of Lux beauty soap. In 1946, Bobby Kooka Air India’s commercial directory and Umesh Rao artist with JWT created a mascot-Air India’s Maharaja. The decade is 1950s marked the Indian contribution to advertising as prior to that many creatives were imported from London’s Fleet Street. R K Laxman created Gatta, a mascot for Asian Paints.

In the 1960s, Zodiac advertising by Ogilvy caught attention. Lintas created Lifebuoy ad on health platform. Wills Filter Cigarettes made for each other series was initiated. In 1966, Sylvester da Cunha, Eustaco Fernandes and Usha Katrak created ‘utterly butterly’ Amul campaign. Amul girl was created for topical punchlines.

Air India flight attendant Karen Lunel appreared in waterfall ad in 1975 and again in 1985. In 1976, Gabbar of Sholay was used to sell Britannia biscuit.

In the wake of Asian Games in 1982, colour TV was introduced in India. Epic serials Ramayana and Mahabharata were telecast. Nirma girl was used for detergents’ advertising on TV screens. Surf was sold as’ Lalita’s samajdhari’. Pan Parag’s ad with Shammi Kapoor and Ashok Kumar appeared. Mudra produced ‘ I love you, Rasna’ and ‘ Only Vimal’. Complan ad featured complan boy and girl, ie. Shahid Kapoor and Ayesha Takia.

Zakir endorsed Taj Mahal tea’ Onida devil was created in 1982. Gold Spot was the zing thing. Prestige cooker ads for ” biwi ka pyar’ and Bajaj Electrical’s ‘ jab main chhota bachcha tha made an impression. Vick’s lozenge, Maggie’s two-minute noodles and ‘Give Me Red’ were remarkable campaigns. The two-wheeler ads of Bajaj, Hero Honda and Kinetic were noticeable. Social Service advertising of ‘Mile Sur Mera Tumhara’ too appeared. Cola Wars were fought backed by advertising. Kamsutra condom ad and Tuff shoes ad of Milind Soman and Madhu Supre too appeared Raymond’s complete Man was created. Cadbury resorted ‘asli swad zindagika’. Thums up bungee Jump ad was exciting. Coke was official sponsor of 1996 cricket world Cup. Pepsi used the line ‘nothing official about it’.

Ericcson One Black Coffee ad to indicate compact product and the famous Fevicol ads too were highly popular.

In the new millennium, Asian’s paints Har Ghar Kuch Kehta Hai was one of the iconic campaigns. Coca cola started Thanda Matlab Coca Cola, Maruti Suzuki emphasised its fuel efficiency (petrol khatam ni hunda). Center shock barbar commercial and ‘Dimag ki batti jalade’ for Metos appeared. Happydent featured bright teeth turning into light bulbs. Amitabh appeared in social service advertising for polio vaccination-Do boond zindagi ke. Indian tourism was promoted by an incredible India campaign. Hutchinson Essar initiated famous pug and boy campaign, later followed by Vodafone. Zoozoos the alian like Creatured appeared in 2009. Idea started ‘What an idea, Sirji’ campaign.

Surf Excel’s ‘ daag achehe hai’ campaign and HDFCStandard Life’s ‘Sar utha ke jiya’ stirred the emotional pitch, Nike featured a man playing a game in a traffic jam.

After 2010, there were many story-telling campaigns-Har ek friend zaroori hota hai for Airtel, prisonbreak by Tata Sky, Google’s story of separated friends reunited thanks to internet search.

Many think AI will create destructive humanoid robots. Actually, this is not the real danger. The real danger are the cognitive biases which can be programmed into AI unknowingly by the scientists who created them.

A cognitive bias is a systematic error in how we think. To illustrate, if a person in Britain is asked what is likely to kill him — a terrorist attack or having a bath. Cognitive bias may make you opt for a terrorist attack but statistics prove more people die by drowning in a bath.

Then there is systemic bias called the availability heuristic. Information about terrorist attack is flashed in media and is more available to the mind. Drowning in bath-tubs do not make headlines. Such cognitive biases could be unknowingly programmed into AI computer programmes which run the robots.

Meat can be made outside of the animal. Such meat could come from vats and plants rather than slaughtered animals. There is research going on for plant-based alternatives to meat and milk. There are attempts to grow cell-based chicken in vats.

The first ever prototype of cultured meat in the form of a hamburger was very expensive. They have also produced the first cell-based meatball, and cell-based shrimp, crab and lobster. There are cell-grown beef steak. The toughest challenge is to get the alternative taste like the real thing.

Scientists of synthetic biology and tissue culture work in this field. There are experiments to produce sheep and goat meat.

To produce cultured meat muscle stem cells are isolated from the animal without killing it. They are introduced in liquid medium. They are allowed to mature until there is enough density of cells to make a solid mass. They are fed a combination of nutrients including vitamins, amino acids and fatty acids. Researchers would like to mimic scaffolds that will hold the cells together. The culture medium used is serum drawn from foetal calves or horses. They would like to replace this by a plant-based culture medium.

There is a need for cellular agriculture. It requires lesser water.

It is to be seen how the lab model could be scaled up. It is to be seen how the lab model could be scaled up. It may require large bio-reactors and not vats and flasks.

Face recognition systems have been spreading owing to advances in AI. It relies on machine learning ( a subfield of AI ) in which computers teach themselves to do tasks that their programmers are unable to explain to them explicitly. They are rewarded when they correctly identify a face, and penalised when they do not. Thus it can be taught to recognise images that contains faces from those that do not. Once it has an idea of what a face consists of, it begins to distinguish one face from the other. The specifics vary depending on the algorithm. Usually, it involves mathematical representation of a number of crucial anatomical points, such as the location of a nose relative to the other facial features, or the distance between the eyes. In lab tests, such systems could be very accurate.

There are many weaknesses in computer vision which is nothing like human vision.

CV Dazzle

Make up can, fool face recognisers. Bright colours, high contrast, graded shading and asymmetric stylings confound an algorithm’s assumptions of what a face looks like.

Hyperface aims to hide faces from dozens of fakes. The idea is to disguise the real thing.

Baseball cap fitted with tiny light-emitting diodes that project infra-red dots onto the wearer’s face could be used.

FaceNet

It is a face recognition system developed by Google. The researchers find that the right amount of infra-red illumination prevent a computer from recognising that it was looking at a face at all.

More sophisticated attacks are possible by searching for faces that are mathematically similar.

Adversial Machine Learning

Training one algorithm to fool another is known as adversial ML. Images are created to mislead CV. Innocuous looking abstract patterns printed on paper and stuck onto the frame of a pair of glasses could convince a CV system that a male research worker is a female actress.

Thus all these systems have constraints.

The Chinese researchers are developing an autonomous bicycle which navigates with the help of a neuromorphic chip, modelled after human brain. It highlights the effort to achieve new levels of AI with novel kinds of chips. China is investing heavily in the idea of ‘ AI chip .’

Existing robots can learn to open a door or toss a ping-pong ball into a plastic bin, but the training takes hours to days of trial and error. Even then, the skills are viable only in very particular situations. With help from neuromorphic chips and other new processors, machines could learn more complex tasks more efficiently, and be more adaptable in executing them.

AI is being developed through neural networks. These are complex mathematical systems that can learn tasks by analysing vast amounts of data. A neural network can learn to recognise a cat by metabolising thousands of cat photos. This technology is Face recognition technology. Many smart phones use this. It facilitates the development of autonomous robots and self-driving cars.

A neural network does not learn on the fly. Engineers train a neural network for a particular task before deploying it in the real world. It learns after absorbing enormous number of examples.

Researchers are developing the neuromorphic processore including chips which imitate the network of neurons in the brain. These systems include faux neurons. Instead of confining to processing of 0s and Os, these neurons operate by trading tiny bursts of electrical signals. It is called firing or spiking when input signals reach critical thresholds. This is what biological neurons do. It is unifying computer science and neuro science.

By mimicing the brain, AI systems are helped to learn skills and executive tasks more efficiently.

Faux neurons fire on demand rather than continuously. Neuromorphic chips thus consume lesser energy than traditional processors. As information is processed in short bursts, it could lead to systems that learn on the fly, from much smaller amounts of data.

Google, Facebook and Amazon attract large chunk of ad spend, and the rest of the industry shrinks. It is because of a walled garden approach. It is a closed eco-system in which all operations are controlled by the eco-system operator, e.g. Apple controls the whole iOS ecosystem. In digital marketing, such operators force the clients to use their whole marketing stack to run their campaigns.

DMP targets audience on their data. DSP pushes ads on selected inventory. DCO handles ad personalisation or ad hosting.

The walled garden directs user’s navigation within particular areas, to allow access to a selection of material or prevent access to other material. Thus it is a closed platform or eco-system. In open platform consumers have unrestricted access to applications and content.

With GDPR and other upcoming privacy laws, the walled gardens are definitely under more scrutiny. Independent players, however, will always have a significant portion of digital ad spend.

Rewarded video ads are popular both with the advertisers and publishers. They are more popular in the mobile games sector. Rewarded video integrates ads into the app. Consumers can choose to watch it in exchange for points, lives or virtual goods. Publishers are able to monetise easily with rewarded video. Advertisers can communicate brand message effectively. Users can continue their game. this video does not lead to false clicks. Rewarded video ads cannot be skipped once the user has opted in. Rewarded videos have become one of the top video formats.

Rewarded videos cost up to 86% lesser than the other video ads. Apart from games, other verticals are also realising its benefits. Retail and media brands use this format.