These days, I am quite overwhelmed and intrigued; a tad intimidated too as I come to terms with the realisation that how every online activity of mine, be it on the web or on social media, is meticulously being tracked and analysed in the background to decode my distinct search behaviour. I am equally amazed at how my deep-seated needs and preferences are being uncovered to extract personalised and deeper insights, which are then being harnessed to gain a holistic understanding of what all makes me tick and what is my characteristic buying behaviour.
Thus, every time I explore some new content, browse through a certain website, like a page, click on a particular ad, make comments on posts and images (especially those that surface as promotional campaigns) or check-in to a particular place using the Facebook app, invariably I get to see targeted ads popping up on my Facebook timeline in the form of suggested posts - ones that are being run by the companies and communities that I have looked up in the past or those that Facebook believes are relevant to me and attuned to my distinct likes and dislikes.
What astonishes me the most in this entire exercise is that how, most of the time, Facebook gets it just right in figuring what’s useful for me and what motivates me. This is excluding those occasional misses when it interprets my impromptu web searches and page/website visits incorrectly and floods my timeline with irrelevant suggestions of what it thinks will pique my interest and curiosity or what will be beneficial for me when the matter of fact is that such events were a mere outcome of my work-related research or referencing or simple chance events that occurred during my search for something more meaningful or contextual.
Keeping such sporadic inconsistencies aside, many like me wonder how social medial channels or any other business or marketing firm for that matter is able to make such near-accurate predictions of what kind of brands, products and services would attract and appeal to us - their target consumers. The answer lies in their deployment of deep analytics and cutting-edge research tools that embed Artificial Intelligence (AI) and Machine Learning (ML) within their core to examine and unveil trends and patterns related to consumer behaviour through establishment of a correlation between their consumers’ diverse personal attributes, such as their thinking, attitudes, motivations, interests and inclinations.
Natural Intelligence vs. Artificial Intelligence
As humans, we are all too familiar with the concept of natural intelligence (NI) that is innate to us and that enables us to think, comprehend, demonstrate awareness, learn, solve problems and take decisions in a logical manner.
Then, what is Artificial Intelligence all about? Also known as MI (Machine Intelligence), AI is the intelligence demonstrated by one of humankind’s most ingenious creations - man-made machines. Going beyond the standard abilities of machines that aim to reduce manual efforts by automating mundane and repetitive tasks, AI aims to further expand the outreach of machines in context to their impact on the various aspects of our lives through use of high-end capabilities that include heightened natural language processing, speech/facial/audio/image recognition, superior visual perception, complex data interpretation, strategic decision-making, object manipulation and seamless translation of languages among others.
Predominantly used in reference to advanced computer systems that make use of programming software to mimic the cognitive abilities of humans, the concept of AI can be traced back to the era of the noted philosopher and logician, Ramon Llull, when he envisioned the idea of constructing a machine to produce knowledge through logical reasoning. In fact, it is said that the most primitive form of AI dates back to the ancient times when storytelling devices made use of artificial beings that were empowered with the ability to think on their own.
Machine Learning - What is it and How Does it Work?
A field of computer science, Machine Learning is a typical illustration of how AI can be exploited to free up systems from their dependency on explicit programming in order to be able to learn and improvise on their own, based on their experiences instead of a set of static program instructions.
Machine learning works on the premise that instead of teaching computer systems and machines everything about the world and its related activities, it is more practical and worthwhile to invest efforts in making machines more self-reliant by giving them access to all the data that they need to deduce meaningful patterns and correlations which can be further utilized to make data-driven predictions or conclusions that mirror the decision-making and data classification abilities of the human brain.
The field promotes the unsupervised and self-learning of machines through the design and study of complex models and algorithms that can learn from input data and make acceptable predictions on it by leveraging the subfields and methods of pattern recognition, statistical analysis and mathematical optimization.
Real-World Applications of Artificial Intelligence and Machine Learning
While the last couple of decades have witnessed telltale advancements being made in the area of Artificial Intelligence, the discipline is largely considered to be in its nascent stages, even in the 21st century. This is primarily owing to the fact that our definition of AI’s scope has changed manifold over the years and also because of the reality that majority of AI’s present-day applications make use of Weak AI or Narrow AI that applies limited intelligence to solve a specific type of problem as opposed to a Strong or Generalized AI-equipped machine that has the sentience, self-awareness, creativity and intelligence to handle any type of problem. The emergence of ML and development of ML-dependent NLP (Natural Language Processing), deep learning and neural networks are concerted efforts that have been made in this regards to bridge the wide gap between Weak and Strong AI.
Despite the obvious limitation of AI in terms of its competence in imitating the human mind to the T and its ability to humanize actions and decisions in an indisputable way, there is no denying the fact that transformative technologies like AI and ML have permeated almost every aspect of our lives and are transforming our lives for the better in many ways.
Here are few game-changing applications of AI and ML that have literally changed the way we have been managing our businesses and daily lives till such time these useful functionalities appeared on the scene and led to what is rightfully being dubbed as the initiation of the ‘AI revolution’.
Development of in-built, machine-learning embedded intelligent personal assistants - As if the highly intuitive and feature-rich smartphones did not make our lives seamless enough, the technology giants came up with the novel idea of empowering their mobile phone users with natural language processing capability-enabled virtual personal assistants that made it surprisingly easy for the users to operate their mobile phones and its plethora of apps and functionalities with the use of voice-based commands, thus relieving them of the need to use keyboards to type elaborate and time-consuming queries.
So, whether you are the proud owner of an iPhone or the holder of an exclusive Pixel/android device or a Windows Phone, you can trust a Siri, Google Assistant or Cortana to scour the Internet and retrieve the information that you are looking for, engage in two-way conversations with you and make recommendations to you about local attractions and restaurants while supporting a host of ancillary activities such as setting reminders for you, managing your calendar, scheduling your appointments, opening apps on your phone and even forewarning you of a probable storm or traffic congestion while you are en route to work!
Catapulting UX to new heights with artificial intelligence-aided chatbots
Designed to automate and optimise the customer support side of businesses without making the former lose its characteristic human touch and personalised approach, chatbots are one of the most powerful applications of AI that are transforming the way companies have been interacting with their consumers till now. Providing real-time, 24/7 customer service has been a long-standing challenge for many businesses - one that entails additional resources and significant operational costs. Advanced machine learning-enabled chatbots address this need by making use of computer programs to conduct auditory or textual method-based conversations with users that retain their humanized flavour while providing the users with prompt, efficient and round-the-clock service.
Considering the cost benefits, seamless user experience and operational efficiency that chatbots bring to the table and the rising popularity of messenger apps within the social media population, chatbots are increasingly being deployed across numerous industries and business sectors to manage large volumes of repetitive user queries in a swift, interactive and cost-effective manner. Case in point are Facebook and Insurance major Allstate that deployed these conversational bots in 2016 or the recent AI-fuelled chatbot debut of TripAdvisor this year that allows tourists to check on the best vacation deals and/or seek helpful reviews and recommendations of hotels, restaurants, flights and local attractions in the form of a dialogue facilitated via TripAdvisor’s chatbot on Facebook Messenger.
Optimizing marketing efforts by channelizing them in a focused manner
Effective marketing strategies are critical for the successful launch of any new product or service. Instead of taking the conventional marketing route of bringing new offerings out into the market for the attention of all and sundry, ML-empowered strategies help marketers to reduce marketing waste by directing their campaigns towards a specific demographic i.e. people who have an actual need for their distinct line of product and who have searched for them online or whose viewing activity and behavioural data tend to indicate their preference for this type of service or offering. For example, it is common practice these days for companies to run focused retargeting ads on Facebook in order to generate business from their existing customers. Such ads target a custom audience that comprises people who have been site visitors at some point in time, thereby increasing one’s chances of accomplishing successful conversions through their ads.
Another important contribution of AI and ML in the field of marketing is their employment to analyse enormous volumes of data on the go in order to extract powerful and actionable insights that can give competitive advantage and impetus to businesses. ML is also being used to create powerful algorithms that can help businesses make accurate demand forecasting, provide relevant deal and service-related recommendations to their target consumers, improve search ranking of their offerings and proactively identify possible fraud through timely detection of inconsistent patterns and trends in the given data set.
Versatile use across industries and sectors
As disruptive technologies like AI and ML continue to evolve and mature, their all-pervading influence in our lives is nothing short of awe-inspiring and inspirational. Take the case of the automobile industry that is harnessing AI and ML to manufacture self-operated autonomous cars that can drive on their own using advanced sensors in order to eliminate the probability of accidents that are triggered by human failure. Close to home, the booming e-commerce industry is making extensive use of these technologies to convert online shopping into a hassle-free and enjoyable experience for its consumers by indulging them with filtered product suggestions that are customised based on their past purchase history and with the intent to ease their decision-making processes by helping them make swift and informed choices.
Even the education, banking and healthcare sectors have not been aloof from the far-reaching impact of AI and ML. Thus, you now have free language course apps that are proficient in gauging and correcting a learner’s pronunciation, automated banking processes that aid companies in lowering costs and assuring their customers of a faster turnaround time and a revamped healthcare industry that is using AI and ML to digitize its cumbersome paper-based operations, make rapid advancements in life-saving fields such as personal genetics that concerns the study of the human genome, expedite the elaborate drug discovery processes and make disease diagnosis and management more precise and robust through accurate reading and analysis of digital scans and images and recommendations of viable treatment options based on study of past clinical cases.
Considering all of the above, there is no doubt that technologies, such as AI and ML have surely come of age in the last couple of decades even as they continue to make rapid progress in multifarious fields and application areas that impact the longevity and quality of our lives. Despite certain naysayers voicing their concerns about how these life-transforming technologies can eventually make humans redundant or even surpass human intelligence some day, one cannot overlook the fact that these revolutionary technologies hold promise of exciting and innovative possibilities in the years to come - possibilities that one hopes to be deployed in a safe and responsible manner and in a way that benefits the human race and the environment in general.