AI and Machine Learning
September 24, 2021
Will AI replace jobs? Can we swap AI and ML? Can we deploy AI without a plan? Let’s find out.
Artificial intelligence (AI) is creating more myths, fears, and skepticism in many minds than what is corroborated by actual events and facts. So, shall we swim deep into these waters and face our fears in the eye? To do that, we have to deconstruct some myths.
Is AI going to make human labor obsolete? That’s a plausible apprehension. After all, AI is supposed to remove the need for human labor with smart intelligence and clever automation? But wait. This is only for labor that is unnecessarily time-intensive and resource-depleting. AI is designed to augment humans. It is aimed to help them not only do their jobs better but also to do better jobs. It will liberate their time and brainpower for innovative leaps. Recall how the Internet created millions of jobs and, at the last count, was comprising 10 percent of the US GDP. In a PwC Annual Global CEO Survey, it was seen that 63 percent of CEOs believe AI will have a more significant impact than the Internet. By 2030, AI can lead to an estimated $15.7 trillion, or a 26 percent jump in global GDP – as per PwC’s Global AI Study.
It was observed here that any job losses from automation are likely to be broadly offset in the long run by new jobs which would be created because of the larger and wealthier economy made possible by these new technologies. For example, the World Economic Forum’s ‘Future of Jobs Report’ 2020 has estimated that 85 million jobs will be displaced, but 97 million new jobs will be created across 26 countries by 2025.
They are all part of the same species, but they are different creatures. AI is about creating and using intelligence that is as close as possible to human cognitive powers. In machine learning (ML) technologies, computers are trained to analyze data, identify hidden patterns, make classifications, and predict future outcomes. As for deep learning (DL), it is a subset of machine learning based upon a conceptual model of the human brain. It works on neural networks, which have multiple layers that interconnect. If we talk about natural language processing or NLP, it represents extracting or generating meaning and intent from text. This text is in a readable, stylistically natural, and grammatically correct form. This umbrella also houses computer vision as a technology segment. This is where the extraction of meaning and intent from visual elements happens. These can be as characters (document digitization) or images as faces, objects, scenes, and activities.
Enterprises have been using these segments for various purposes and at multiple levels. In a Deloitte survey, it has been spotted that 67 percent of respondents are using machine learning (ML) today, and 97 percent are using or planning to use it in the next year. As to deep learning (DL), 54 percent said they use deep learning (DL), and 95 percent are using or planning to use it next year. About 58 percent of global respondents adopted natural language processing or NLP, and 94 percent are using or planning to use it next year. On computer vision, 56 percent said they use it and 94 percent are using or planning to use it next year.
AI is supposed to transcend human intelligence and get to the level of singularity. But that level of explosive growth and power is not to be seen for many decades yet. Many efforts and projects have been raised to the level of AI to strong AI instead of the present and imminent weak AI level. But general AI is not the same as the initial AI efforts hint at. We would need a lot of research and progress to ever come to a level where AI surpasses human intelligence. The question, for now, is – how much can it empower humans?
If we look at Deloitte’s ‘State of AI in the Enterprise’ survey, we see that seasoned (26 percent) is setting the pace in terms of AI adoption maturity. These are companies that have undertaken many AI production deployments and have developed a high level of AI expertise across the board. They are selecting AI technologies and suppliers, identifying use cases, building and managing AI solutions, integrating AI into their IT environment and business processes, and hiring and managing AI technical staff. Look at the category of skilled (47 percent) adopters, and they seem to have launched multiple AI production systems but are not yet as AI-mature as the seasoned organizations. They show many gaps – on their number of AI implementations, their level of AI expertise, or both.
As to starters (27 percent), well, they are just dipping their toes into AI adoption. They have not shown solid proficiency in building, integrating, and managing AI solutions. AI adoption needs a careful strategy around many areas like- implementation, financial investment, competitive advantage, and expected transformative impact.
An enterprise cannot simply wake up one morning and start investing in AI. It has to know exactly what applications, goals, and differences it is aiming for. It has to chart a proper path for it. AI needs strategic mapping – and at continuous levels.
Interestingly, ninety percent of seasoned adopters in the survey believe AI is “very” or “critically” important to their business today. They are the ones embracing machine learning (ML), deep learning (DL), computer vision, and natural language processing or NLP at a high rate. Adopters are investing significantly, with 53 percent spending more than $20 million on AI-related technology and talent over the past year. Seventy-one percent of adopters expect to increase their investment in the next fiscal year by an average of 26 percent. Seasoned adopters typically achieve payback on their investments in a shorter amount of time. Almost 81 percent reported their payback period is less than two years.
AI is here to stay. And grow. IDC has also forecasted that spending on AI technologies will grow to $97.9 billion in 2023—over two-and-a-half times the spending level of 2019. That’s just one estimate. A lot of predictions hint at disruptions of massive proportions for many industries. Now is the time to look beyond AI myths and do some reality checks. And to gain from AI. This is the right time for professionals to build relevant capabilities in this space and shape their careers.
TalentSprint
TalentSprint is a leading deep-tech education company. It partners with esteemed academic institutions and global corporations to offer advanced learning programs in deep-tech, management, and emerging technologies. Known for its high-impact programs co-created with think tanks and experts, TalentSprint blends academic expertise with practical industry experience.
Advance your career with the right program
Related articles
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.
