AI and Machine Learning
August 16, 2021
Once upon a time, the world was divided into two calendars- BC and AD. But in the last decade itself, that calendar has changed again. It is called after-digitalization or the new AD. Now, we live in an era dotted with digital powers and of all stripes possible.
Our banks run on algorithms, our factories are controlled via IoT, bots handle our customer grievances, virtual assistants answer our queries, autonomous cars leverage deep learning, our museums use AR, drones deliver our books, our tools are made through 3D. Computers man even our electricity grids. This shows disruption is all around us impacting businesses and lives, to the deepest level possible. The question is – are we ready to survive it? and make the most of these emerging technologies?
Recall the last time you watched a movie, booked a cab, or ordered a burger.
But how do they make you feel so special? and how do they serve you so fast and precisely the way you want?
Well, the genie that makes it all happen is packed in a bottle called AI (artificial intelligence). AI is a salient emerging technology that is redefining a lot of fields. It is injecting intelligence, precision, and proactive action in a lot of business models. With AI, businesses and customers alike have hopped on to a new paradigm. It’s the landscape of intelligent machines, helping humans get better, faster, and smarter – in every way.
This growth and depth are being reflected in impressive numbers – on all kinds of calculators. Whether it is IDC that reckons worldwide revenues for the AI market to grow to 2021 to $327.5 billion and touch $554.3 billion by 2024 or it is Gartner that tells from a 2020 survey that 24 percent organizations have upped their AI investments since COVID-19 – AI is getting deep into the skin of almost every breed of business. As the post-pandemic reset takes a solid shape, 75 percent of organizations will continue or start new AI initiatives as they move into the Renew phase. Of course, Cloud and IoT are also gaining a lot of traction in enterprise usage. Still, AI is at the forefront of technologies that businesses use for automation, augmentation, and customer-centricity.
AI is hot and has been nascent for a long time – that’s a beautiful contradiction that it lives. AI technology has a lot of promise for many areas – like transportation, education, health, manufacturing, retail, arts, medicine, etc. Leaders realize both the advantages and dangers of using AI as a weapon in the new landscape.
Do you know that in 2021, AI augmentation would have created $2.9 trillion of business value and 6.2 billion hours of worker productivity globally? If we look at a McKinsey Global Survey on AI, we will prove how organizations are using AI to generate value. And this value is being manifested as revenues. People from various industries attributed 20 percent or more of their organizations’ earnings before interest and taxes (EBIT) to AI. No wonder these companies plan to invest even more in AI in response to the COVID-19 pandemic. The crisis has pumped up the acceleration lever of all things digital. As a result, AI is steaming with possibility. And that’s why it should be handled smartly and carefully.
There are endless areas where AI can be put to profitable use. From demand forecasting in retail to real-time behavioral and intelligence in customer service to many services powered by hyper-personalization and customer experience improvement, so many use scenarios where AI alone can deliver results. AI has gained this muscle because of the convergence of a lot of forces. From increased processing power that helps handle complex tasks to progress in cloud computing and the outsourcing of data storage – which allows it to chew data at speed – AI has leveraged many tools and advancements very well. And it has transformed them into plug-and-play applications.
As we get closer and closer to a sophisticated understanding of how the human brain works, we enhance our ability to embed brain-like elements into computers. That’s why we are getting so much better at applications around voice and pattern recognition, natural language learning, and machine learning. Within the next three to five years, an exponential increase in the number of commercial AI-based applications is expected. A Deloitte study titled ‘Cognitive technologies: The real opportunities for business’ outlines that AI applications fall into three broad categories: Product, Process, and Insight Applications. Yes, we can embed AI in a product or service to provide end-customer benefits. Or we could inject AI into an organization’s workflow to either automate processes or start augmenting worker effectiveness. Then we can harness advanced analytical capabilities such as machine learning to uncover insights. These can be applied for operational and strategic decisions across an organization. That’s what makes AI so amenable for vehicle automation, marketing personalization, and robotics for a wide range of applications.
By now, you must have realized that AI is not a smooth tap on the shoulder. It is seismic. It disrupts the industry it touches. In McKinsey’s latest survey findings, we can see that a minority of companies recognize many of the risks of AI use, and fewer are working to reduce the risks. Cybersecurity and risks related to AI explainability are still on top of many lists. AI high performers, however, remain more likely than others to recognize and mitigate most risks. Those at high performers are 2.6 times more likely than others to say their organizations are managing equity and fairness risks such as unwanted bias in AI-driven decisions.
The task is challenging, but it has to be done. We have to balance the positive side of AI’s disruption with the flip side. We have to leverage AI’s gains, improvise and manage internal processes efficiently, and make sure that we minimize the risks associated with it. People and organizations who rise to this disruption will gain. Those failing to cope with these areas will find AI overwhelming and disturbing, reminds McKinsey.
AI has a lot of advantages when it is used for its positive potential. But when used the wrong way, it can also bring in many risks, data issues, privacy concerns, bias, discrimination, inaccuracy, and misapplication of information. Unfortunately, the world has seen many such fiascos already. Whether AI ends up as turbulence or a much-needed disruption depends on the people, skills, and approaches used to apply it.
While some industries are retrenching—such as energy, oil, gas, and mining—a few markets, like healthcare, are speeding up AI adoption- according to Omdia’s latest diagnosis. As we speak, convolutional neural networks and other deep learning technologies are presently being used primarily for image, voice, and unstructured text processing. However, they are slated to evolve to be applied in a wide variety of applications. They are turning into a standard approach for processing some incredibly large, and complex data streams. As to the Covid-effect, despite the economic challenges that pandemic-mitigation measures have caused for many companies, the ones who are witnessing the most value from AI are doubling down on the technology. The respondents at high performers said their organizations had increased investment in AI in each primary business function in response to the pandemic. It was noticed that automotive and assembly and in healthcare services and pharmaceuticals and medical products are the most likely to say their companies have increased investment.
The future is still being written. As AI moves into the cerebral workspace, it will augment and empower many tasks by humans so far. The pandemic has stressed its role. With digital transformation turning into a mainstream priority for many enterprises, AI will stay to play its vital role here.
AI has only been growing to new heights since it hit the business application space. AI market is pegged to rise by $76.44 billion, progressing at a CAGR of 21 percent between 2021 and 2025, as per Technavio. In addition, Gartner, Inc. has predicted that by 2025, 70 percent of organizations will shift their focus from big to small and wide data, providing more context for AI and making it less data-hungry.
As per Omdia, the global market for AI software will grow to $98.8 billion by 2025. However, what is also happening is that disruptions such as the COVID-19 pandemic are pushing historical data that reflects past conditions into obsolescence. This is breaking many production AI and machine learning models.
The global AI market size has been slated to touch $169,411.8 million in 2025, as per Allied Market Research. AI, and has been slotted as one of the fastest-growing technologies in recent years. What makes it even more powerful is that AI is positioned at the core of the next-gen software technologies. AI would be the primary architect for a lot of emerging technologies and tools ahead. A business that has not invested in AI will fall short on both AI value and many upcoming and competitive technologies.
So what happens when AI makes the jobs of humans faster, easier, and more intelligent? Will it hurt their jobs too?
In some advanced economies, additional investments would be required to reduce the risk of job shortages. A recent Forrester report, ‘Future of Work,’ showed that automation is not a singular trend. We cannot say clearly how future scenarios are influenced. There will be many trends like the gig economy, the destruction of industry boundaries, and the increasing desire for privacy and transparency. Automation can open the doors to new, previously unthinkable business opportunities. Forrester recommends that as much as companies must become learning institutions, so must employees become learners. It is vital now that people learn core skills, adapt to new working models, and understand what it means to be ready for the future. This is about maximizing their Robotics Quotient. Forrester predicted job losses of 29 percent by 2030 with 13 percent job creation to compensate.
As per ‘The Future of Jobs Report 2020’ by World Economic Forum, ‘We find ourselves at a defining moment: the decisions and choices we make today will determine the course of entire generations’ lives and livelihoods. We have the tools at our disposal. The bounty of technological innovation which defines our current era can be leveraged to unleash human potential. We have the means to reskill and upskill individuals in unprecedented numbers, to deploy precision safety nets that protect displaced workers from destitution, and to create bespoke maps which orient displaced workers towards the jobs of tomorrow where they will thrive.’
It has been estimated that around 40 percent of workers will require reskilling for six months or fewer, and 94 percent of business leaders expect employees to pick up new skills on the job. Almost 84 percent of employers will digitalize working processes rapidly. Employers expect that by 2025, increasingly redundant roles will decline from 15.4 percent of the workforce to nine percent while emerging professions will grow from 7.8 percent to 13.5 percent. So by 2025, 85 million jobs may be displaced by a shift in the division of labor between humans and machines, but 97 million new roles may emerge. These would be aligned to the new division of labor between humans, machines, and algorithms.
The WEF report underlines that apart from the current disruption from the pandemic-induced lockdowns and economic contraction, technological adoption by companies will transform tasks, jobs, and skills by 2025. Just notice that 43 percent of businesses indicate they will reduce their workforce because of technology integration, 41 percent plan to expand their use of contractors for task-specialized work, and 34 percent plan to expand their workforce because of technology integration. By 2025, the time spent on current tasks at work by humans and machines will be equal, as the WEF report said. So think of the top skills and skill groups that employers see as rising in prominence in the lead-up to 2025 – these include critical thinking and analysis, problem-solving, and skills in self-management such as active learning, resilience, stress tolerance, and flexibility.
AI will not make humans less relevant. It will make them more relevant because someone has to use all the time and data that AI is churning out. Someone has to make sure that ethical issues and data integrity imperatives are not thrown out of the window while wielding the power of AI. So should we not start getting ready for these new roles and skills?
AI has percolated into almost every function, requiring respective professionals to prepare themselves adequately and adapt to a radical change of work functions. The roles spawned by AI go beyond tech experts. Professionals across different layers of an organization, irrespective of their job roles, need to know AI and how they can integrate it within their domain. That means almost everyone – 1. CXOs, 2. Project Managers, 3. Product Leaders, 4. Research Analysts and 5. Developers- everyone will have to adapt and get reborn. Yes, unless AI is understood well by a business leader, unless the data aspect is handled well by analysts, unless project managers create the right models and applications – the entire exercise for AI can go pointless. AI’s role and relevance, hence, straddles across many functions and roles in an enterprise.
As the world adapts and rises to this AI era, it is time for tech professionals to enrich their knowledge, skills, and the core mindset of AI. We need expertise across many frontiers, like:
AI expertise is becoming the clincher for many tech professionals as they aspire to reach smart technology. Everything else can be automated or converted into an algorithm. But the human-in-the-loop aspect of AI and the Black Box conundrum help make a professional eye even more vital for the proper usage of AI. From data integrity, quality, modeling approach, application-angle, and governance, AI’s expertise has to cover a wide range of areas where only a human brain would stay dominant.
It all begins with understanding the 5Ws of building AI expertise. Before you get into the course or skill training, find out where, what, why, when and who – everything about AI’s imperatives. Then, educate yourself well. With multiple online and offline options available, it is now easy for you to build a promising career in AI. The trick is to stay ahead of the game. You need to upgrade capabilities to remain competitive in the industry constantly. This can be done by exploring platforms that not only bring expertise and tools to the table; but are also well-tuned into the realities and challenges of AI. The training should make you well-equipped to enable others in the proper application of AI. It should make you agile and open enough to a vast range of possibilities. It should also make you aware and capable of the risks, constraints, and dead-ends of AI in the business world. Finally, the expertise you gain should have a long shelf life too. Do not focus on learning a short-term skill, but invest your time towards a long-sight approach and capability for AI.
The best way to do so is to find a learning avenue where deep academic collaborations form the foundation of the course. This is important because AI is unlike a programming language or a gaming tool. Much knowledge is still lurking in deep research projects and documents that academic teams are privy to. A lot of exploration, experimentation, and research in the domain of AI is still happening in universities and academic labs. Also, these technologies, by their innate nature, are radical. They need a fresh approach to learning. AI is also wrestling with a lot of ethical, pragmatic, and governance issues. These are some prominent reasons you should choose programs from top academic institutions.
Start early. Start right. And fix your date with the AD calendar soon.
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Why is AI the hottest buzzword in the Tech World?
AI today is a topic of conversation, a subject for corporate presentations, a space for technological debates; in general, a term uttered by many who are familiar with a machine. AI is a concept that is being adopted by many sectors; indeed the latest and hottest buzz word in the world of technology.
However, the fact is Artificial Intelligence has remained in the nascent stage of development for quite a while. When one hears the word `artificial intelligence’ the visuals of different characters from science fiction come to mind. What was a mythical concept of time travel or spacecraft with extra-terrestrial creatures is not considered a futuristic science anymore? Though still primitive in form, AI can solve unique business problems, provided one knows and decides how to leverage the technology to its potential.
James Goodnight, Co-Founder and CEO of SAS says: `AI is certainly being hyped as another buzzword, and there are many companies rushing to jump on the AI bandwagon’. Despite the hype, AI is a significant emerging technology that will continue to grow in importance. Years ago the term `cloning’ became very popular; and in course of time, was included in the general context and usage, where anything which is replicated was described as `cloned’. Dolly, the sheep (the first mammal cloned from an adult somatic cell) became a widely talked about subject. Along the same lines, people have started using AI to describe any analytics problem, be it faulty equipment or credit card fraud. The catchword now is AI, and Sophia, the Robot has replaced Dolly sheep. With everyone using the buzzword AI, one needs to see whether reality aligns with this hype.
There is so much information on the internet stored in the last few years. Wall Street Journal recently stated that the internet is filling up with good morning messages, and largely by Indians, many of whom are yet new users of the internet! On a more serious note, there are huge quantities of data collected and stored in the recent times. Almost all information is online and accessible to net browsers. A tool to statistically filter, analyze and process large data sets, not merely as a process but with intelligence, is the primary need of industries, investors, for that matter, any establishment across sectors and geographies. A growing technology like AI can unlock the value of data, and eventually help transform businesses, industries, and above all, people’s experiences. It is no surprise that AI being such a powerful concept has become not just a household term, but a word across the technology world.
Though the research in Artificial Intelligence dates back to the 1940s, it is only around the 1980s that AI progressed from research to application. In recent years, however, interest in the field of artificial intelligence has sky-rocketed as evidenced by the amount of funding invested in researching and adopting it.
To go back to sci-fi, we have seen in many robots featuring stories about how the machine ultimately overpowers the man to the point of bringing about total annihilation. This threat could be as real as the creation of artificially intelligent robots. Well, known personalities like physicist Stephen Hawking and Tesla CEO Elon Musk have been stressing on the importance of regulating artificial intelligence.
There is merit in the thought that AI technology will help society in a range of areas like transportation, education, health, manufacturing, retail, arts, medicine and so on. It can be a danger though if used to build weaponry. Leaders across the world have found this worrisome, even terrifying.
One has to admit, turning a buzzword into business is exciting, but like communications specialist Lindsay Kwan says: The danger of artificial intelligence is that we can both overestimate its power today and underestimate its capabilities tomorrow.
Which, between the two, is riskier, is a matter of conjecture.
AI has come to stay high
In the mid-eighties, Small Wonder, a sci-fi TV series entertained adult and child alike. The story revolved around an android in the form of a 10-year-old girl. Looking back, the series was indeed very amateurish and loosely structured. The point is it introduced for the first time, the machine made man to the lay person. Thirty odd years later we hear of Saudi Arabia’s decision to grant citizenship to a robot. Endowed with artificial intelligence, visual data processing and facial recognition, the robot, Sophia is designed to get smarter over time.
The citizenship as such is of hardly any consequence; what it signifies is that Artificial Intelligence (AI) has come of age. Critics have spoken at length about the absurdity of awarding citizenship and an array of rights to a robot, while Saudi ironically is yet highly restrictive about women’s rights. However, many see this as a positive move towards making the country tech savvy and progressive.
In the computing history, man and machine interfaces have only improved and enhanced over a period of time – hence both are not mutually exclusive. Satya Nadella, CEO of Microsoft, said AI, mixed reality, and quantum computing will shape the world in the coming years. The crux of the matter is that the technology world will have a blend of the real and virtual. While current technology enables in us the ability to collect data, Nadella referring to AI says, what is more important is to reason over the data to create intelligence. This is most critical as a differentiator between mechanical equipment and an AI enabled robot. In the mid-fifties the term GIGO (Garbage In Garbage Out) became a descriptive term for computers, primarily because the machines lacked the ability to think for themselves. Whatever output emerged was only as accurate as the information entered. Deep down, computers still are improvised calculators. Recent development in AI comes under the aegis of `machine learning’ and involves programming computers to learn from example data or past experiences and process information based on that.
So how does machine learning impact tasks and get independent of human influence (in terms of execution of task)? Let’s take an example: Automatic transmission in cars has been prevalent for quite some time and in India, they are getting popular by the day. With increasing traffic bottlenecks people are finding it more convenient to drive a car which does not require changing gears. The driver needs to navigate by keeping the steering in control. With AI, autonomous driving, a wide step ahead of automatic transmission, the technology required for a car to accelerate, turn, and brake on real time roads without human intervention is not anymore impossible or far into the future. The recognition that autonomous driving was a prediction problem solvable with machine learning meant that autonomous vehicles could start to become a reality in the marketplace years earlier than has been anticipated.
By breaking down tasks into components, we can begin to see how AI will affect the workplace. AI is usually framed in terms of machines versus humans, but gradually we see it more in terms of understanding the level of judgment necessary to pursue actions. In cases where whole decisions can be clearly defined with an algorithm (for example, image recognition and autonomous driving), we expect to see computers replace humans. This will take longer in areas where judgment cannot be easily described – where there is high level of ambiguity in arriving at decisions or solutions. In other words, where the task is not a mere process with anticipated outcome and the pros and cons fail to fall into previous experience; AI may not accomplish the same without human intervention.
Product companies are all uniformly using AI during their product launches. This has caused excitement as well as anxiety amongst the people. Will AI assist and enable humans to perform better and with ease, or will AI replace humans to the point of redundancy?
With AI moving into the cerebral workspace, it cannot be denied that it will soon take over many tasks hitherto performed by humans. Just as the advent of machines had a significant impact on how people performed physical labor and dispensed with many jobs handled by humans, AI is soon to be responsible for transitioning many of the tasks performed by humans to robot responsibilities.
In the medical field, AI can help improve diagnostics to a very high level, treatment and care will still require human attention and action. Online shopping has rendered many counter sales jobs redundant; but, at the same time courier and door delivery jobs have increased. Apart from these examples, AI is already playing a large role in the areas of music, architecture, education, manufacturing, gaming and just about any sector or industry. In the corporate world (as a quick example) AI has gotten into recruitment – a very important task in any company. Automatic process was only used before to sort resumes based on keywords. Now, many organizations like Ola or Accenture are using bots to streamline their recruitment processes.
As Artificial Intelligence systems evolve and become more and more sophisticated, job displacement is bound to happen. However, interestingly, many new jobs very different from the ones that are currently in existence will be created. Jobs that involve creativity and those that require advanced degrees and highly specialized skill sets will be available alongside the continuous technology transformation.
AI and its Impact on Jobs
The world, at the moment, is awash with speculations, opinions, and fears about artificial intelligence and its perceived `threat’ to human held jobs. Many researchers and scientists are still of the conviction that AI cannot, in actuality, replace human intelligence. They still maintain that AI can assist and augment but never take the place of humans at the workplace.
AI has been an area of passion and pursuit for a long time. However, it is in the recent years that it has come to stay, moving from the research desk to active field. AI is now dominant, taking on an exponential role, influencing particularly the fields of gaming, natural language processing, speech and handwriting recognition and robotics.
Since artificial intelligence is poised to take on many tasks that the human has so far been performing, is there a threat of unemployment across the globe? How is AI going to impact the job scene world over?
Leading research and advisory firm, Gartner comforts job holders in its statement: Robots are not here to take away our jobs; they’re here to give us a promotion. Instead of replacing the human at work, artificial intelligence may increase the number of job opportunities, especially in healthcare, public sector, education, to name a few. As the gig economy is gaining popularity, retail, manufacturing and transportation could possibly be the first to adopt AI for work. Industry heads are not as optimistic as Gartner. Leading personalities Elon Musk and Stephen Hawking feel AI may go beyond taking away people’s jobs. AI could eventually become a real threat to human beings. For now, it is helpful and comforting to go with Gartner’s report which states by 2020, AI will generate 2.3 million jobs, exceeding the 1.8 million that it will remove.
When one of the Big Four consulting firms, Deloitte delved into UK census data for the last 140 plus years only to discover that technology has very steadily taken over many jobs that were being handled by humans. Deloitte also quickly pointed out that jobs in the professional sector have increased multifold.
This pattern of generating new jobs as and when a machine takes over current jobs will continue in this era of AI. Emerging technologies will allow for emerging new jobs, not only for people working with new technologies but also for the enablers who need to manage the increasing requirements of content development and training to bring people up to speed.
The fact is, AI is contributing in a major way to the evolving landscape of work. Going back to the gig economy, the concept is gaining prominent space as it provides scope for professional work within a time-bound period. The big gig companies differ from traditional firms not only in conducting business online but also in allowing and encouraging individuals to freelance and engage `just in time’. As TED CEO Richard Saul Wurman sums up the online marketplace platform: For the first time in human history, individuals can design a life around the pursuit of interesting work.
AI is going definitely going to define the way work happens. How much humans will be involved in `working’ is a subject of speculation for anyone who is familiar with AI. But if we have to think about the next decade, we need to remember though AI is enabling a machine to be independent of man, it is dependent on data. The more data AI consumes the smarter it gets. But to sift data and feed AI and obtain output is a process as laborious as the creation of AI.
Google AI chief John Giannandrea explained this concept of AI’s need to be fed data by using an example involving his 4-year-old daughter. She was able to identify a 19th-century “penny-farthing” bicycle anywhere once he had told her what it was. But computers, need to be shown 100,000 penny-farthings before identifying one. Once they’d seen 100,000, they’d probably be better at identifying them than humans are.
Companies may talk at length about AI and secretly look forward to right-sizing their employee base by bringing in machines. However, they would need to clean up messy databases, work on file management and in overall make their data algorithm-friendly, before any machine can really take over a man’s job. How long will this take? Well, time will tell.
