Is AI already here or are we decades away from true AI?

Written by Shrisha Sapkota
Written by Shrisha Sapkota


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If you have followed the world of pop culture or tech for some time now, then you know that advances in artificial intelligence are heating up.[1] When most people hear the term artificial intelligence, the first thing they usually think of is robots, which is because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth.[2] With so many articles and content proliferating the media space on how humans are at the cusp of full AI (artificial intelligence), it’s no wonder that we believe that the future — which is full of robots and drones and self-driven vehicles, as well as diminishing human control over these machines — is right on our doorstep.[3] But how true is that?

What is AI?


Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.[4] It is the intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans.[5] It is the science and engineering of making intelligent machines, especially intelligent computer programs, and is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to biologically observable methods.[6]


The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalise, or learn from experience.[7] Some popular accounts use the term “artificial intelligence” to describe machines that mimic “cognitive” functions that humans associate with the human mind, such as “learning” and “problem-solving”, however, this definition is rejected by major AI researchers.[8]


In its simplest form, artificial intelligence is a field, which combines computer science and robust datasets, to enable problem-solving which also encompasses sub-fields of machine learning and deep learning, that are frequently mentioned in conjunction with artificial intelligence.[9] The ideal characteristic of artificial intelligence is its ability to rationalise and take actions that have the best chance of achieving a specific goal and a subset of artificial intelligence is machine learning, which refers to the concept that computer programs can automatically learn from and adapt to new data without being assisted by humans.[10]


How does AI work?


AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data.[11] Each time an AI system runs a round of data processing, it tests and measures its performance and develops additional expertise.[12]


The computer has to learn how to respond to certain actions, so it uses algorithms and historical data to create something called a propensity model that will then start making predictions (like scoring leads or something).[13] The trick to understanding how AI truly works is understanding the idea that AI isn’t just a single computer program or application, but an entire discipline, or a science.[14] The main goal of artificial intelligence includes mimicking human cognitive activity.[15] To understand How Artificial Intelligence works, one needs to deep dive into the various sub-domains of Artificial Intelligence and understand how those domains could be applied to the various fields of the industry.[16] Some of the major ones are:


Machine Learning

A specific application of AI that lets computer systems, programs, or applications learn automatically and develop better results based on experience, all without being programmed to do so.[17]


Deep Learning

Deep learning uses huge neural networks with many layers of processing units, taking advantage of advances in computing power and improved training techniques to learn complex patterns in large amounts of data.[18]


Neural Networks

Neural networks work on similar principles to human neural cells in that they are a series of algorithms that captures the relationship between various underlying variables and processes the data as a human brain does.[19]


Cognitive Computing

Another important component of AI systems is designed to imitate the interactions between humans and machines, allowing computer models to mimic the way that a human brain works when performing a complex task, like analysing text, speech, or images.[20]


Applications of Artificial Intelligence


The applications for artificial intelligence are endless as the technology can be applied to many different sectors and industries.[21] To fully get how AI works, it’s important to understand where and how it’s being applied.[22] Some of them are:

  • AI is being used when searching for data, and optimising the search to give the most relevant results.[23]
  • AI systems are being consulted to design more effective store layouts, handle stock management, and provide shopping suggestions, like via Amazon’s “You May Also Like” recommendations.[24]
  • AI makes virtual shopping assistants and chatbots possible which helps improve the user experience while shopping online.[25]
  • AI tutors allow students to get one-on-one help and they can reduce anxiety and stress for students stemming from tutor labs or human tutors.[26]
  • AI has made it possible to develop face recognition tools that may be used for surveillance and security purposes.[27]
  • By considering the usage patterns, AI can also help reduce the possibility of credit card fraud and fake reviews.[28] Similarly, banks use AI to organise operations, bookkeeping, invest in stocks, and manage properties because AI can react to changes when business is not taking place.[29]
  • AI technology has been trained to provide personalised medicine, including giving reminders about when patients need to take their medicine and suggestions for specific exercises they should perform to improve their recovery from injuries.[30]
  • Social media sites like Facebook and Instagram use AI to customise content for the Explore Tab, write ads, and help marketers to analyse and track their steps among other things.[31]
  • Automobile manufacturing companies like Toyota, Audi, Volvo, and Tesla use AI to train computers to think and evolve like humans when it comes to driving in any environment and object detection to avoid accidents.[32]
  • AI facial recognition systems are used for mass surveillance, notably in China. Various countries are deploying AI military applications to enhance command and control, communications, sensors, integration, and interoperability.[33]
  • AI intelligence is actively applied to review complex data sets that are useful in testing new medicines, helping life science organisations get effective medicines to market faster.[34]

Is AI Already Here?

The modern project of creating human-like artificial intelligence (AI) started after World War II when it was discovered that electronic computers are not just number-crunching machines, but can also manipulate symbols.[35] AI has been a stable component of contemporary culture for multiple generations now – from time-travelling machines hell-bent on destroying humanity to friendly and lovable robots adventuring through space, we’ve anthropomorphized machines in preparation for what we all know is coming.[36] It’s fitting that the industry of predicting when we’d have human-level intelligent AI was born at around the same time as the AI industry itself – in fact, it goes back to Alan Turing’s first paper on “thinking machines,” where he predicted that the Turing Test—machines that could convince humans they were human—would be passed in 50 years, by 2000.[37]

With what we have as AI now – that seems like an impossibly optimistic prediction by Turning. Only, what if it’s already here? What if ‘true’ artificial intelligence has already been created?[38] It’s not hard to have that impression with the likes of Elon Musk, Stephen Hawking, leading university departments and research centres around the world, and more being highly concerned with the potential risks brought about by AI and taking action now to avoid a doomsday scenario soon – they are still predicting that by the year 2030 machines will develop consciousness through the application of human intelligence.[39]

The reality is we’re still some way from AI being able to convincingly mimic a human being.

Technically, AIs can understand or learn intellectual tasks to the aptitude that humans can but most AIs today are highly specialised.[41] For instance, there’s AI that can beat the world chess champion in chess, but that’s the only thing it does.[42] Computer programs capable of playing chess at Grand-Master levels are incapable of playing checkers, which is a much simpler game, and for the same computer to play checkers, a different, independent program must be designed and executed.[43] AI doesn’t have the adaptability – like humans – to switch gears like this yet.

Some of the biggest advancements in AI today have been artificial neural networks, which are technologists’ way of mimicking the way that human brains work with code but defining what exactly makes something intelligent is hard as humans have multiple forms of intelligence, and we likely need to take a closer look at just what it means to be “intelligent” if we want to determine how close artificial general intelligence is to reality. Even when scientists have built neural networks that mimic the intricate layers of how the brain understands, analyses information, and builds concepts, they don’t know what exactly is going on in there, and why neural networks are interpreting things in a certain way.
Current AI technologies are not just far from general intelligence; they are not even that good at things that are second nature to humans — such as facial recognition, language comprehension, and problem-solving.


Probably not anytime soon. The creativity, relatability, and general understanding of the world required for the former, and the emotion and impulsiveness required for the latter remain with humans alone for now.

It may be that we don’t yet have the mechanism for human-level intelligence, but it’s also true that we don’t know how far we can go with the current generation of algorithms.[48] Also, we don’t have to model our AI systems after the human brain; however, if we aim for AI that is smarter than humans, then it is implied that it will at least have to surpass the human brain in one capacity or another but most importantly, the brain is also the best benchmark we have available.[49]



Artificial Intelligence and Law


Artificial intelligence (AI) is just beginning to come into its own in terms of its use by lawyers and within the legal industry[50] – especially in the legal tech section. The growing interest in applying AI in the legal sector is slowly transforming the profession and closing in on the work of paralegals, legal researchers, and litigators.[51]



AI is already being used to review legal documents, as well as assist in research before or during a case – particularly when cases have large amounts of paperwork that would take a significant amount of time to sift through, AI helps make sure documents with certain keywords get pushed to the top of the stack.[52] Similarly, AI is also being used for contract drafting which can be a very tedious, time-consuming, and expensive process. AI tools for lawyers allow identification, extraction, and analysis of business information contained in large volumes of contract data which is used to create contract summary charts for M&A due diligence.[53] Moreover, the tool can be set up as “self-service” for clients, i.e., the client can log onto the system, select the type of contract they need, enter in a few variables, and the system will produce a standard form agreement ready to go.[54]


Through legal data analytics of past cases, AI can provide insights into future outcomes through predictive analytics.[55] Data analytics in the legal industry allows lawyers to identify potential risks earlier, advise clients wisely about their exposure, and head off legal problems before they even occur.[56] As AI can access more of the relevant data, it can be better than lawyers at predicting the outcomes of legal disputes and proceedings, thus helping clients make decisions.[57]


While some in-house legal departments are still using paper invoices, most are moving to simple legal billing software.[58] The use of AI for the bill review process allows legal departments to review cost and expense data in the pre-billing stages of a matter.[59] It has led also to a variety of new fee structures, driven largely by client expectations like fixed fees, contingent fees, task-based billing, percentage fees, and retrospective fees.[60] The use of billing and accounting software for law firms also strengthens the professional relationship between clients and lawyers or law firms by providing accurate billing information that reduces potential conflicts between the two parties, allows the law firm to provide more than just basic billing data, and can assist in discussions about alternative charging models.[61]


AI shines when it comes to increasing efficiency which can be seen in scheduling, planning, data management, and other tasks that typically require the dedication of large amounts of time.[62]


These are just a few examples of the uses of AI in the legal profession. From all this, we can see that AI has undoubtedly made inroads into the legal industry but in doing so, the technology is empowering lawyers to concentrate on what’s most important: practising law.[63]


It is better to be at the forefront of this new frontier than try and keep up once AI has increased the speed and efficiency of competing law firms.[64] Firms that fail to take advantage of Artificial Intelligence in the legal sector and the efficiencies it provides may lag in competing with those who do and lawyers who understand the technology and educate themselves about the latest legal tech developments. maybe of increasing value to their firms.[65] The legal field is a great example of how AI and humans can work together to improve the quality, cost, and timeliness of legal delivery as instead of wasted man-hours, AI takes care of mundane jobs like crawling through reams of jurisprudence, drafting contracts, and scouring petabytes of legal data to find answers – an impossible task for even an army of associates to complete.[66]





































































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