Social & Innovation

What it is and why it matters

INTRODUCTION TO

AI

The term “artificial intelligence” was created in 1956, based on academic research that explored topics like problem solving. In the ‘60s, focus shifted to training computers to mimic basic human reasoning. Today, the term has come to be applied to machines, computers or software that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving.

Enabled by better, cheaper processing and massive data sets, Deep Learning – an AI sub-field – is driving the current AI-boom. When people talk about the potential of AI, they’re often referring to Deep Learning, which uses “neural networks” to derive meaning, insight or application.

What is ai?A brief history

AI’s impact on society is predicted (by some) to be akin to that of electricity or the internet. Broadly speaking, AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms that allow software to learn automatically from patterns in the data. A few AI subfields are particularly important – and exciting – today:

hoW doesai WoRK?

Machine Learning:the science of getting computers to learn and act like humans do, improving their learning over time autonomously, by feeding them data and information in the form of observations and real-world interactions.

Neural Network:a type of machine learning that processes information by responding to external inputs, relaying information between each unit, similar to neurons firing in the human brain.

Deep Learning:uses huge neural networks with many layers of processing units, only possible because of computing power improvements and improved training techniques. Used for image and speech recognition.

Cognitive Computing:a sub-field that strives for a natural, human-like interaction with machines. The goal is for a machine to simulate human processes through the ability to interpret images and speech, and then speak back in response.

Computer Vision:recognizing what’s in a picture or video through pattern recognition and deep learning. Machines capture images or videos in real time and interpret their surroundings. 

Natural Language Processing:the ability of computers to analyze, understand and generate human language, including speech. 

1 2 3 4 5 6

AI will touch every industry and every field in the coming years because it can do so much:• Automate repetitive learning and discovery

through data• Add intelligence• Adapt through progressive learning

algorithms• Analyze more and deeper data• Achieve incredible accuracy• Get the most out of data

In other words, it will fundamentally changewhat and how we do and get things.

Why is ai iMPoRtaNt?

• Autonomous, driverless vehicles• Content such as newspaper articles, music,

websites and movie trailers• Things that move or fly themselves• Understanding people and objects and their

relationships in the real world • The optimization of complex systems,

such as driving patterns or electricity consumption in data centers

• People’s understanding of software and each other

What caN ai eNaBLeSome possibilities

Health CareAI applications provide personalized medicine and X-ray readings. Through the use analysis of massive

patient data sets, AI-based technologies can help identify broken bones and even spot diseases or

cancer before they’re visible.

Consumer GoodsAI provides virtual shopping capabilities that

offer personalized recommendations and discuss purchase options with the consumer. Stock

management and site layout tech is improved by AI.

Food and AgricultureFarmers use AI to increase yields, spot

diseased crops and analyze conditions to make recommendations sooner and quicker than

humans. Autonomous drones and tractors survey and maintain fields while connected to irrigation

systems to maximize output and efficiency.

ManufacturingAI can analyze factory data as it streams from

connected equipment to forecast expected load and demand using a specific type of deep learning network used with sequence data. AI is built into

vehicles, tools, and machines to make them smarter or even autonomous.

Four key industry sectorsaPPLyiNG ai

The world’s largest tech firms – especially those based in China and the U.S. – are driving AI forward, thanks to their massive data sets, engineering capital and dedicated resources.

A large and ever-growing ecosystem of startups are launching almost daily, often with specific specialties. Among those specialties are enterprise intelligence (visual, audio, internal data, market), enterprise functions (customer support, sales, marketing), agents (personal, professional), industries and technology stack solutions.

Tech giants and startups

Key ai PLayeRs

AI has already made its way into social and public relations functions today, a trend that will only accelerate in the years to come. Social news feeds already rely on Machine Learning (ML) algorithms under-the-hood, but there are a couple notable developments – and new capabilities – that AI is currently enabling.

Artificial Intelligence

iN PRactice

ChatbotsFound in messaging apps like FB Messenger or voice apps like Alexa, Chatbots imitate human conversation and are called AI “agents.” They typically use a combination of Natural Language Processing to analyze and respond with human-like cadences, and ML algorithms to analyze, learn and produce smarter interactions.

Companies are using chatbots for customer care, as a first line of defense in reputation management.

Image RecognitionSocial measurement and analytics tools are incorporating ML-based image recognition to their offerings. Brands and agencies are now able to extend social listening beyond mere text, and look for logos and particular features within an image.

On mobile devices, cameras now function as platforms themselves, with image sensors and AI technology that allow a screen to display layers of information about the world in real-time.

NewsroomsFact-based news stories, like a recap of a baseball game, can be automated and published immediately thanks to AI-based software. AI-driven tools can scan a press release and instantly develop an accompanying video, complete with graphics and visual assets.

And AI lets companies automate the generation of press releases and distribution materials for financial or earnings announcements.

Today’s

CHALLENGES IN AI ApplicationGiven the current AI hype, organizations are scrambling to implement “AI,” broadly speaking. Rather than AI for AI’s sake, brands should be identifying problems first, and then deciding if there is an AI-based solution.

LaborJobs that require repetitive tasks, like manufacturing, are likely to be taken over by AI-based robots or machines capable of performing those tasks faster, and more efficiently and reliably. Questions of how companies or governments should help or retrain the growing labor force taken over by AI – if at all – remain unanswered and promise to grow in importance.

Emotional IntelligenceCompanies and brands wanting to employ AI technology need to understand the limits of the emotional intelligence AI can display, while working on development of higher cognitive capabilities within its human workforce.

TalentOrganizations are still under-resourced when it comes to talent with technical and core skills needed for AI development. Even AI-leading large tech firms are in an arms race to attract the small pool of able developers and data scientists.

DataData is the lifeblood of AI – the more data you have, the better your results may be. Data quality is paramount. The output will only be as good as what’s put in it. Key privacy issues to consider include what personally identifiable information will be used (and how), alongside inherent security risks that accompany massive data exchanges.

EthicsAI practitioners must be aware of the data fed into algorithms – including its existing biases and intended outcomes – while promoting transparency. This also extends to how AI results are communicated: data scientists will increasingly be called upon to explain how the “black box” of algorithms and machine learning works, along with AI’s role in society, as a whole.